How best to diagnose in-home mould exposure: The validity and accuracy of self-reported measures

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Understanding the prevalence and scope of the exposure largely relies on resident self-diagnosis; yet there is little guidance on how to optimise self-reported measures of mould in homes to achieve more accurate diagnosis of exposure. We compared the predictive performance of a range of self-reported measures that varied by their vernacular, framing, reference period, and severity of mould to be identified, against measures of mould taken from dust samples in 100 homes and analyzed using the quantitative polymerase chain reaction (qPCR) tests. Kappa and areas under the receiver operating characteristic curve (AUC) statistics were used to test the validity and accuracy of self-diagnosis of domestic mould. We find moderate agreement between self-reported and lab tested mould measures. Occupants tended to overestimate the presence of mould when asked about visible mould and suspicion of mould and to underestimate the presence of mould when asked about mould size, odour, dampness, and water damage. Identification of visible mould had the highest sensitivity while identification of mould larger than an A4 sheet of paper had the highest specificity. Combining self-reported visible mould and mould size achieved the best accuracy. When using self-rated mould severity (no, mild, moderate, or severe mould), grouping mild, moderate, and severe mould best detected actual mould presence. Prediction accuracy also varies by occupant sociodemographic and residential factors, with older age, lower household income, and major plumbing problems associated with better accuracy of self-diagnosed mould. Earth and environmental sciences/Environmental sciences Earth and environmental sciences/Environmental social sciences Figures Figure 1 Figure 2 Introduction Mould growth is indicative of unhealthy indoor environments and poses potential health risk to occupants across building typologies [1, 2]. Dampness, mould and dampness-related agents in homes are found to be associated with increased risks of asthma, respiratory infections and symptoms, hypersensitivity pneumonitis, allergic alveolitis, and immunological reactions, posing a significant treat to vulnerable demographics [1, 3, 4]. The World Health Organisation (WHO) recommends that no exposure can be considered safe for health and that dampness and mould should be prevented, or remediated early, to avoid hazardous exposure [1, 3]. Climate change and increased frequency and duration of weather-related events such as storms and heavy rain are likely to aggravate exposure [3, 5]. The impacts of dampness and mould are unequal across populations, with higher prevalence in substandard housing for low-income people [1] and private rental and social housing that are in poor states of repair [6]. Despite increasing evidence on the adverse health and health inequality impact of indoor dampness and mould and widely reported experiences of biotoxin-related illness [6], the prevalence and scope of the exposure in our homes are not well quantified [6, 7]. Epidemiological studies largely rely on self-reported measures of dampness and mould - often estimating prevalence through self-reported questionnaires. However, these data are subject to measurement bias and estimates vary widely depending on the questions used [3]. Reliance on self-reports can risk mis- or under-diagnosis and threaten the validity of study results [8]. While external inspection allows objective and standardised measures of mould, it is costly and often limited to a single timepoint. Therefore, it is crucial to understand the consistency between self-reported and objective indicators of mould to build a basis for exposure assessment at scale, which allows establishment of longitudinal exposure information and databases for monitoring. The validity and accuracy of subjective measures of mould remain under-examined. The few studies comparing agreement between self-reports and inspection by trained surveyors suggest poor consistency between occupants’ and inspectors’ observations of odour, visible mould, and visible damp [9-13], with some studies describing an overestimation by occupants [14] and others an underestimation [15]. There is also a dearth of evidence on the consistency between occupants’ self-reports and laboratory tests and how the framing of self-assessment questions affects the accuracy of self-reporting. To address these knowledge gaps, we investigated the validity and accuracy of self-reported measures of indoor mould exposure against laboratory testing of samples collected from homes. We considered a range of self-reported measures that varied by their vernacular, framing, timeframe, and severity of target to be identified. Alongside self-reported measures, we collected dust samples from households to provide an objective comparator so as to determine the optimal design of survey questions that yield the most accurate mould reporting in population-wide surveys. Methods Data Participants were recruited through an online survey disseminated in June 2022 via the Centre of Research Excellence in Healthy Housing website, university and faculty newsletters, social media postings on Facebook, LinkedIn, and X (then Twitter), posters within the University of Melbourne campus, and mail drops. The first one-hundred people indicating either mould presence or absence at home who completed the online survey and consented to testing were invited to enrol to this validation study. Home visits for dust sample collection were conducted between 13 August 2022 and 13 May 2023, during which the mould samples from 100 participants were collected and tested. All participants provided online and written informed consent and completed on-site questionnaires on mould measures. Self-reported mould measures During home visits, participants were asked to complete questions compiled from questions commonly asked in mould surveys (see Appendix A for full list). These included whether they noticed visible mould, mould in any part of the dwelling that was larger than an A4 sheet of paper, mould odour, dampness, and water damage, in the last 12 months, in the last 3 months, or at present, with responses including yes, no, or not available (e.g., if they recently moved into the house). In addition, participants were asked to rate mould severity at their dwelling as severe, moderate, mild, no mould, or not available, and, through the online survey, report if they suspected any humidity/mould problems inside the floor, walls or ceiling of the home that were not visible. Lab-tested mould measures The researcher collected floor dust samples using a vacuum cleaner connected to a dust collector (manufactured by Zefon International Inc., USA) for at least 5 minutes in each of two primary rooms (living room and main bedroom) before removing the dust collector from the vacuum hose and placing the capped dust collectors into a re-closeable bag. Dust samples were collected from a 1 metre x 2 metre rectangular sampling area on the floors from the living room and main bedroom each. If the sample location could not accommodate these dimensions, the researcher adjusted them to sample a total of 2 square metres[1]. Samples were sent to the NSJ Enviro Sciences Lab using express mail (next day delivery) and once in the laboratory remained frozen until the Health Effects Roster of Type-Specific Formers of Mycotoxins and Inflammagens – 2 nd version (HERTSMI-2) analysis using the quantitative polymerase chain reaction (qPCR) technique. Developed by the United States Environmental Protection Agency, the qPCR technique is a DNA-based approach to exposure assessment of microorganisms and their components [16], which are shown to yield the highest sensitivity and precision of fungal contamination of dust and reduce the variability associated with culture-based approaches in determining mould contamination [17-19]. The application of mould specific quantitative polymerase chain reaction (MSQPCR) techniques resulted in the development of the Environmental Relative Mouldiness Index (ERMI) and HERTSMI-2 [20]. While both tests are used to inform objectively if water damaged building conditions exist and if a given building is safe for occupancy by people previously sickened by water-damaged buildings [21], HERTSMI-2 is a more streamlined test that analyses the 5 major mould species (including aspergillus penicilloides, aspergillus versicolor, chaetomium globosum, stachybotrys chartarum, and wallemia sebi) and becomes the standard exposure tool for assessing adverse health effects of exposure to water-damaged buildings and safety for re-entry into the building after remediation [22]. HERTSMI-2 testing uses a weighted scale applied to the concentration in spore equivalents/mg of each target mould’s DNA [21]. The samples were tested and analysed by the NSJ Enviro Sciences Lab. Covariates Through the online questionnaire (delivered through Qualtrics), participants were asked about their sociodemographic status (age, gender, education, employment, household income, and housing tenure), dwelling condition (major structural problems including major cracks in walls/floors, sinking/moving foundations, wood rot/termite damage, major plumbing problems, walls/windows not level, and major roof defect; dwelling insulation; and dwelling type), and health conditions (allergy and asthma conditions). Each factor is related to housing circumstances and indoor air quality [3, 5, 23, 24]. Statistical analysis For each self-reported question asked in the survey, summary statistics describing their diagnostic performance including sensitivity, specificity, positive predictive value, and negative predictive value were estimated using the lab-tested measures as validation. The overall classification accuracy of self-reported mould was described by the Cohen’s Kappa statistics [25] which measure the agreement between occupants reporting and lab tests. The Kappa coefficients range from -1 to +1, with a higher value indicating better agreement. To capture the trade-off between true positives and false positives, the receiver operating characteristic (ROC) curve and the area under the ROC curve (AUC) [26] were also used as a quantitative measure of classification accuracy. A greater AUC value indicates better diagnostic performance. Parametric analyses of the ROC curve with covariate adjustment for sociodemographic, dwelling, and health conditions were performed to test covariate effects on the discriminatory accuracy. Bootstrap of 1,000 replications using bias-corrected methods [27] were applied to obtain confidence intervals. Ethics Ethics approval was obtained from the University of Melbourne Human Ethics Committee (Reference Number: 2022-24051-28012-4). [1] Details on the vacuum dust sampling procedures are available on the NSJ Enviro Sciences Lab website. https://nsjenviro.com.au/product/hertsmi-2-analysis-and-vacuum-sampling-kit/ Results Sample statistics All respondents lived in one of the two most populated states in Australia: Victoria (65%) or New South Whales (35%) [28]. Table 1 shows sociodemographic and residential characteristics of 100 participants grouped by their lab test results as being exposed to minimal mould (HERTSMI2 score ≤10), moderate mould (HERTSMI2 score 11-15, and severe mould (HERTSMI2 score >15). Data were collected across a wide range of age groups (40.0% aged 18-34, 34.0% aged 35-44, 11.0% aged 45-54, and 15.0% aged ≥55) and genders (30.0% identified as males, 65.0% as females, and 5.0% as others). The majority of the participants were employed (80%) and had a bachelor’s degree or higher (86%), and about half of them were renters (54.0%) and half were homeowners (46.0%). Regarding residential conditions, 61% of the participants resided in houses (compared to 39.0% in flats, units, or apartments); 28% reported major cracks in walls/floors, 25% walls/windows not level, 19% sinking/moving foundations, 15% wood rot/termite damage, 13% major roof defect, and 6% major plumbing problems; and 61.0% reported their homes being poorly insulated. Noticeably, HERTSMI-2 scores were higher for older people, lower income households, dwellings with major plumbing problems, and poorly insulated dwellings. TABLE 1 HERE Presence of mould The distribution of self-reported mould measures across lab tested results shows that in general more participants reported the presence of mould at home as the lab HERTSMI2 scores increased, and this pattern is more pronounced for self-reported visibility and odour relative to other self-reported measures (Table 1). More than half of the participants reported noticing visible mould (61%) or suspicion of invisible mould (61%) at home, more than one third reported noticing a mouldy or musty odour (39%) and excess dampness (32%) at home, and less than one third reported seeing mould in parts of the dwelling that in total was larger than an A4 sheet of paper (21%) or noticing water damage (27%) at home. Apart from visible mould and suspicion of invisible mould, other self-reported measures underestimated the presence of actual mould. Agreement between self-reported and lab tested mould Table 2 presents the diagnostic summary statistics of self-reported mould measures in classifying lab-tested mould status and the Kappa statistics on the agreement between self-reported and lab-tested mould measures. In identifying the presence of mould, identification of visible mould had the highest sensitivity (correctly reporting mould when mould is present), positive predictive value (probability of mould being present when it is reported by occupants), and negative predictive value (probability mould being absent when it is reported by occupants). Self-reported measures of mould size had the highest specificity (correctly reporting the absence of mould when mould is absent). TABLE 2 HERE In terms of the agreement with lab-tested moderate or severe mould, identification of visible mould and suspicion of invisible mould yielded the highest Kappa values (0.24 for each), with resident self-reports and lab results agreeing for 62% of dwellings (Table 2 panel (a)). In terms of the agreement with lab-tests for severe mould, visible mould exhibited the highest Kappa value (0.17) (Table 2 panel (b)). These results indicate a fair level of agreement between self-reported and lab-tested mould measures for cases of moderate to severe mould in homes [29]. Tables 3 and 4 present the estimates of the AUC that quantify the accuracy of individual and combined measures of self-reported mould in classifying the presence of moderate or severe mould (Table 3) and severe mould (Table 4), respectively, tested through mould samples. Overall, there was a moderate level of agreement between self-reported and lab-tested mould measures, based on the interpretation of the AUC values [30]. TABLE 3 AND TABLE 4 HERE Of the range of self-reported mould measures used to identify moderate or severe mould in homes (Table 3), visible mould and suspicion of invisible mould had the largest AUC value (0.622 for each), followed by identification of mould severity (no, mild, moderate, or severe mould) (AUC=0.591), mould odour (AUC=0.538), water damage (AUC=0.535), dampness (AUC=0.526), and mould size greater than A4 sheet of paper (AUC=0.494). When considering the use of more than one measure, the combination of mould visibility and size produced the highest AUC value (0.647). When combining three measures, mould visibility, mould size, and dampness produced the highest AUC value (0.647) and when combining four measures, mould visibility, mould size, dampness, and water damage yielded the highest AUC value (0.649). Five self-reported mould measures yielded an AUC value of 0.638 – lower or similar success than is generated from combinations of fewer variables. Results for tests of equality of ROC areas in classifying moderate or severe mould (Table 3) reveal that, among single self-reported measures, mould visibility performs significantly better than mould size at the 5% level of significance and better than dampness and water damage at the 10% level of significance. There are no significant differences in classification abilities amongst reports of mould odour, suspicion of invisible mould, and mould severity. A combination of two self-reported measures predicts mould better than a single self-reported measure (including mould size, mould odour, dampness, and water damage). A combination of 3-5 self-reported measures performed better than a single-reported measure of either mould size, dampness, or water damage, but not significantly better than two measures. The differences among combined measures were not statistically significant at the 5% level. Self-reported identification of visible mould also performed the best at predicting cases of severe mould (AUC=0.602) (Table 4). When considering combinations of two self-reported measures, mould visibility and mould size performed best (AUC=0.638). When considering three combined measures, mould visibility, mould size, and water damage performed best (AUC=0.649), and of four combined self-reported mould measures, mould visibility, mould size, mould odour, and water damage were the best predictors (AUC=0.653). Five self-reported mould measures altogether gave an AUC value of 0.652 – achieving no greater accuracy than for four measures. In testing equality of ROC areas in classifying severe mould (Table 4), mould visibility performed better than mould size and water damage at the 5% level of significance, with no difference in predictability compared to mould odour, dampness, suspicion of mould, and mould severity. Using more than one measure performed better than using a single measure (including mould size, mould odour, dampness, or water damage) at the 5% or 10% significance level. The differences among combined measures were not statistically significant at the 5% level. Variation in diagnostic performance of self-reported mould by household characteristics Tables 5 and 6 shows the estimated covariate effects of individual sociodemographic, health, and dwelling characteristics on the diagnostic performance of self-reported mould measures in the identification of moderate or severe mould (Table 5) and severe mould (Table 6) respectively. TABLE 5 AND TABLE 6 HERE Age, household income, employment status, and major dwelling structural problem had a more consistent influence on diagnostic performance of self-reported measures at the 5% significance level. Specifically, older people, lower household income, unemployment, and major plumbing problems were associated with better accuracy of self-diagnosed mould. Having allergic and respiratory conditions were also associated with better accuracy in reporting mould (although this varied by measure). Variation in diagnostic performance of self-reported mould by timeframe Accuracy in prediction varied by the timeframe people were asked to consider – at present, the past 3 months, or the past 12 months. Figure 1 shows the timeframe of the mould exposure asked of participants for the best diagnostic self-reported measures of moderate or severe mould (panel (a)) and severe mould (panel (b)). In predicting objective moderate or severe mould, the predictability of self-reported mould visibility, dampness, and water damage were higher when using past 3 months as the reference period, while the predictability of mould size, mould severity, and mould odour were higher when using past 12 months as the reference period. This was similar for objective severe mould, except for mould size and severity for which current mould status was associated with the largest AUC values. FIGURE 1 HERE Threshold of self-reported mould severity in predicting lab tested mould Figure 2 shows the cut-offs of self-reported mould severity (no mould, mild mould, moderate mould, and severe mould) to best identify the presence of objective moderate or severe mould (panel (a)) and severe mould (panel (b)). In predicting both moderate or severe mould and severe mould, self-reports of at least mild mould (i.e., mild, moderate, or severe mould) performed the best in classifying the presence of actual mould (AUC=0.614), compared to other thresholds across gradients of mould severity. This suggests that self-reporting at least mild mould vs no mould performed best at classifying the actual presence of mould. FIGURE 2 HERE Discussion We provide comprehensive guidance on how to optimise self-reported mould measures to assess mould exposure. This is the first study that systematically summarises the diagnostic performance of varied construction of self-reported measures, through analyses of the consistency between self-reported and lab-tested (using qPCR) assessment. We consider single and combinations of self-reported measures varied by wording, framing, time periods to be referenced, severity of target to be identified, and household characteristics that are associated with the validity and accuracy of self-diagnosed mould. Overall, we find that there was moderate agreement between self-reported and lab tested mould measures based on Kappa and AUC statistics. Occupants tended to overestimate the presence of mould when asked about visible mould and suspicion of mould and to underestimate the presence of mould when asked about mould size, odour, dampness, and water damage. Identification of visible mould had the highest sensitivity, positive predictive value, and negative predictive value, while identification of mould larger than an A4 sheet of paper (as is used in the New Zealand Census) had the highest specificity. Findings suggest that when considering a single measure, reporting of visible mould yielded the most accurate diagnosis. Combining self-reported visible mould and mould size increased accuracy, noting that no substantial improvements in prediction are achieved by adding more than two self-reported measures. When using self-rated mould severity (no, mild, moderate, or severe mould), grouping mild, moderate, and severe mould best detected actual mould presence. More accurate assessment of moderate or severe mould in past 3 months is elicited from questions on visible mould, dampness, and water damage, while for the past 12 months, mould size, odour, and severity were associated with better diagnostic accuracy. Analyses also reveal that the severity of mould exposure is patterned by age, income, and plumbing problems and prediction accuracy varies by occupant sociodemographic and residential factors. There were significant differences by age, household income, and major plumbing problems on the diagnostic performance of self-reported mould, with better discriminatory accuracy among occupants who were older, had lower household incomes, or major plumbing problems. These groups had higher HERTSMI2 scores, which may explain their better diagnostic performance of self-reported indoor mould, as more severe the mould in homes, higher the accuracy of reporting. These groups may also have more experience with mould or dwelling structural problems within the building and therefore heightened awareness of recuring mould exposure. This has a policy implication underscoring the need for building event records in place for potential buyers and renters to identify mould risk. This study fills an important gap in our understanding of how to assess domestic mould contamination. Population-based studies have largely relied on self-report measures [ 2 , 7 , 31 ]. Yet the lack of evidence on the validity of self-reported exposure assessment contributes a degree of uncertainty around estimates. By focussing on improving self-report – the tool of large-scale studies – we bridge the gap between mould assessment at the individual level and population metrics relevant to estimating prevalence and attributable disease burden whilst paving the way to consolidating longitudinal studies and databases. Our study has a few limitations. First, while the sample size of 100 homes is not uncommon in studies that employ microbiological measurement for identification of dampness and mould [ 32 ], the study sample is not representative of sociodemographic and geographic distribution of the population at the national level. Second, mould samples were collected from floors of the two main living spaces where people spend most of their indoor time, missing other locations in the home. 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Adams, Does evidence support measuring spore counts to identify dampness or mold in buildings? A literature review. Journal of Exposure Science & Environmental Epidemiology, 2022. 32 (2): p. 177-187. Tables Table 1. Sample summary statistics Full sample (n=100) Lab test no/mild mould (n=51) Lab test moderate mould (n=14) Lab test severe mould (n=35) HERTSMI2 HERTSMI2≤10 11≤HERTSMI2≤15 HERTSMI2>15 % n Mean % n % n % n Age 18-34 40.0 40 11.2 41.2 21 35.7 5 40.0 14 35-44 34.0 34 11.9 29.4 15 50.0 7 34.3 12 45-54 11.0 11 8.0 17.7 9 7.1 1 2.9 1 >=55 15.0 15 13.6 11.8 6 7.1 1 22.9 8 Gender Male 30.0 30 11.7 31.4 16 28.6 4 28.6 10 Female 65.0 65 11.0 64.7 33 64.3 9 65.7 23 Other 5.0 5 14.8 3.9 2 7.1 1 5.7 2 Education Below degree 14.0 14 11.9 11.8 6 14.3 2 17.1 6 Degree or higher 86.0 86 11.4 88.2 45 85.7 12 82.9 29 Employment Unemployed 20.0 20 10.9 23.5 12 7.1 1 20.0 7 Employed 80.0 80 11.6 76.5 39 92.9 13 80.0 28 Annual household income Under $52,000 16.7 14 13.4 9.5 4 33.3 4 20.0 6 $52,001-$104,000 32.1 27 10.7 35.7 15 25.0 3 30.0 9 Over $104,001 51.2 43 11.5 54.8 23 41.7 5 50.0 15 Housing tenure Renter 54.0 54 11.3 54.9 28 64.3 9 48.6 17 Owner 46.0 46 11.6 45.1 23 35.7 5 51.4 18 Major structural issues Major cracks in walls/floors 28.0 28 13.6 23.5 12 35.7 5 31.4 11 Sinking/moving foundations 19.0 19 13.4 13.7 7 21.4 3 25.7 9 Wood rot/termite damage 15.0 15 12.9 9.8 5 21.4 3 20.0 7 Major plumbing problems 6.0 6 17.0 2.0 1 14.3 2 8.6 3 Walls/windows not level 25.0 25 11.8 19.6 10 35.7 5 28.6 10 Major roof defect 13.0 13 13.7 9.8 5 14.3 2 17.1 6 Insulation Poorly insulated 73.0 61 12.8 69.0 29 72.7 8 77.4 24 Well insulated 27.0 23 9.8 31.0 13 27.3 3 22.6 7 Dwelling type Flat/unit/apartment 39.0 39 9.4 45.1 23 57.1 8 22.9 8 House 61.0 61 12.8 54.9 28 42.9 6 77.1 27 Allergies No 50.0 50 10.1 54.9 28 57.1 8 40.0 14 Yes 50.0 50 12.8 45.1 23 42.9 6 60.0 21 Asthma No 77.0 77 12.0 72.6 37 71.4 10 85.7 30 Yes 23.0 23 9.5 27.5 14 28.6 4 14.3 5 Residential location VIC 65.0 65 9.1 80.4 41 71.4 10 40.0 14 NSW 35.0 35 15.8 19.6 10 28.6 4 60.0 21 Self-report mould measures Mould visibility 61.0 61 13.7 49.0 25 71.4 10 74.3 26 Mould size 21.0 21 11.9 21.6 11 28.6 4 17.1 6 Mould odour 39.0 39 11.7 35.3 18 42.9 6 42.9 15 Dampness 32.0 32 12.3 29.4 15 35.7 5 34.3 12 Water damage 27.0 27 13.0 23.5 12 42.9 6 25.7 9 Suspicion of invisible mould 61.0 61 12.9 49.0 25 78.6 11 71.4 25 Mould severity No mould 32.0 32 7.7 43.1 22 28.6 4 17.1 6 Mild mould 45.0 45 13.7 33.3 17 50.0 7 60.0 21 Moderate Mould 20.0 20 11.0 23.5 12 14.3 2 17.1 6 Severe mould 3.0 3 20.0 0.0 0 7.1 1 5.7 2 Table 2. Results on self-reported diagnoses of mould compared to lab tested mould status (a) Abilities of self-reported mould measures to identify moderate/severe mould Prevalence Sensitivity Specificity Positive predictive value Negative predictive value Agreement Kappa stats Kappa P-value Lab tested moderate/severe mould (HERTSMI2 Score≥11) 49.0% Self-reported visibility 61.0% 73.5% 51.0% 59.0% 66.7% 62.00% 0.24 0.01 Self-reported size 21.0% 20.4% 78.4% 47.6% 50.6% 50.00% -0.01 0.56 Self-reported odour 39.0% 42.9% 64.7% 53.8% 54.1% 54.00% 0.08 0.22 Self-reported dampness 32.0% 34.7% 70.6% 53.1% 52.9% 53.00% 0.05 0.29 Self-reported water damage 27.0% 30.6% 76.5% 55.6% 53.4% 54.00% 0.07 0.21 Self-reported suspicion of invisible mould 61.0% 73.5% 51.0% 59.0% 66.7% 62.00% 0.24 0.01 (b) Abilities of self-reported mould measures to identify severe mould Prevalence Sensitivity Specificity Positive predictive value Negative predictive value Agreement Kappa stats Kappa P-value Lab tested severe mould (HERTSMI2 Score>15) 35.0% Self-reported visibility 61.0% 74.30% 46.20% 42.60% 76.90% 56.00% 0.17 0.02 Self-reported size 21.0% 17.10% 76.90% 28.60% 63.30% 56.00% -0.07 0.76 Self-reported odour 39.0% 42.90% 63.10% 38.50% 67.20% 56.00% 0.06 0.28 Self-reported dampness 32.0% 34.30% 69.20% 37.50% 66.20% 57.00% 0.04 0.36 Self-reported water damage 27.0% 25.70% 72.30% 33.30% 64.40% 56.00% -0.02 0.58 Self-reported suspicion of invisible mould 61.0% 71.40% 44.60% 41.0% 74.40% 54.00% 0.14 0.06 Table 3. Results on the performance of combination of self-reported mould measures in predicting lab tested moderate/severe mould AUC 95% CI Test on equality of AUC (P-value) Single self-reported measure Visibility 0.622 0.529 0.716 Baseline 0.280 0.368 0.347 0.590 Size 0.494 0.414 0.575 0.010 0.025 0.028 0.027 0.042 Odour 0.538 0.441 0.634 0.132 0.076 0.109 0.106 0.101 Dampness 0.526 0.434 0.619 0.072 0.046 0.092 0.089 0.105 Water damage 0.535 0.448 0.623 0.090 0.064 0.087 0.069 0.082 Suspicion of invisible mould 0.622 0.529 0.716 1.000 0.734 0.741 0.725 0.827 Severity scale (no, mild, moderate, or severe mould) 0.591 0.485 0.697 0.393 0.266 0.319 0.303 0.379 Two self-reported measures Visibility + Size 0.647 0.546 0.748 0.280 Baseline 0.979 0.894 0.645 Visibility + Odour 0.632 0.526 0.738 0.704 0.652 0.628 0.590 0.882 Visibility + Dampness 0.636 0.531 0.740 0.594 0.708 0.575 0.535 0.928 Visibility + Water damage 0.624 0.521 0.728 0.926 0.407 0.408 0.443 0.710 Size + Odour 0.539 0.434 0.644 0.201 0.090 0.125 0.121 0.116 Size + Dampness 0.525 0.423 0.627 0.121 0.052 0.101 0.097 0.113 Size + Water damage 0.547 0.451 0.644 0.209 0.108 0.138 0.114 0.131 Odour + Dampness 0.539 0.436 0.643 0.136 0.084 0.133 0.129 0.130 Odour + Water damage 0.553 0.449 0.658 0.195 0.128 0.171 0.151 0.149 Dampness + Water damage 0.546 0.446 0.647 0.145 0.101 0.154 0.136 0.157 Three self-reported measures Visibility + Size + Dampness 0.647 0.541 0.753 0.368 0.979 Baseline 0.769 0.589 Visibility + Size + Odour 0.644 0.537 0.752 0.445 0.880 0.863 0.787 0.831 Visibility + Size + Water damage 0.647 0.542 0.751 0.350 1.000 0.986 0.916 0.645 Visibility + Odour + Dampness 0.634 0.526 0.741 0.696 0.684 0.573 0.542 0.860 Visibility + Odour + Water damage 0.624 0.516 0.732 0.949 0.455 0.405 0.430 0.729 Visibility + Dampness + Water damage 0.633 0.526 0.739 0.702 0.632 0.484 0.498 0.860 Size + Odour + Dampness 0.541 0.433 0.650 0.214 0.095 0.143 0.138 0.137 Size + Odour + Water damage 0.569 0.462 0.676 0.382 0.206 0.256 0.229 0.236 Size + Dampness + Water damage 0.567 0.463 0.671 0.358 0.195 0.258 0.232 0.266 Odour + Dampness + Water damage 0.558 0.452 0.665 0.251 0.163 0.196 0.173 0.174 Four self-reported measures Visibility + Size + Dampness + Water damage 0.649 0.542 0.756 0.347 0.894 0.769 Baseline 0.447 Visibility + Size + Odour + Dampness 0.648 0.540 0.755 0.391 0.966 0.968 0.909 0.484 Visibility + Size + Odour + Water damage 0.641 0.532 0.750 0.526 0.767 0.804 0.715 0.905 Visibility + Odour + Dampness + Water damage 0.636 0.527 0.745 0.641 0.739 0.643 0.626 0.940 Size + Odour + Dampness + Water damage 0.569 0.461 0.677 0.389 0.214 0.254 0.226 0.231 Five self-reported measures Visibility + Size + Odour + Dampness + Water damage 0.638 0.530 0.747 0.590 0.645 0.589 0.447 Baseline Table 4. Results on the performance of combination of self-reported mould measures in predicting lab-tested severe mould AUC 95% CI Test on equality of AUC (P-value) Single self-reported measure Visibility 0.602 0.507 0.698 Baseline 0.139 0.177 0.090 0.117 Size 0.470 0.389 0.552 0.012 0.020 0.022 0.012 0.013 Odour 0.530 0.428 0.632 0.262 0.126 0.154 0.081 0.057 Dampness 0.518 0.420 0.615 0.155 0.077 0.122 0.041 0.045 Water damage 0.490 0.398 0.582 0.035 0.021 0.031 0.025 0.026 Suspicion of invisible mould 0.420 0.322 0.517 0.753 0.443 0.434 0.332 0.322 Severity scale (no, mild, moderate, or severe mould) 0.592 0.487 0.697 0.803 0.404 0.412 0.296 0.305 Two self-reported measures Visibility + Size 0.638 0.532 0.744 0.139 Baseline 0.751 0.429 0.530 Visibility + Odour 0.617 0.500 0.734 0.621 0.562 0.424 0.398 0.478 Visibility + Dampness 0.619 0.506 0.731 0.552 0.556 0.260 0.398 0.424 Visibility + Water damage 0.628 0.521 0.736 0.308 0.735 0.602 0.277 0.356 Size + Odour 0.564 0.454 0.674 0.633 0.296 0.307 0.207 0.180 Size + Dampness 0.544 0.439 0.648 0.447 0.161 0.199 0.096 0.100 Size + Water damage 0.529 0.429 0.628 0.319 0.085 0.095 0.076 0.076 Odour + Dampness 0.529 0.419 0.639 0.260 0.132 0.174 0.081 0.066 Odour + Water damage 0.542 0.433 0.650 0.401 0.204 0.224 0.122 0.091 Dampness + Water damage 0.529 0.424 0.634 0.272 0.137 0.186 0.067 0.073 Three self-reported measures Visibility + Size + Dampness 0.644 0.529 0.759 0.177 0.751 Baseline 0.762 0.798 Visibility + Size + Odour 0.639 0.531 0.747 0.230 0.957 0.891 0.571 0.492 Visibility + Size + Water damage 0.649 0.540 0.758 0.093 0.431 0.769 0.775 0.877 Visibility + Odour + Dampness 0.616 0.503 0.729 0.656 0.535 0.298 0.388 0.365 Visibility + Odour + Water damage 0.630 0.522 0.737 0.383 0.803 0.719 0.347 0.259 Visibility + Dampness + Water damage 0.628 0.520 0.736 0.382 0.761 0.697 0.229 0.320 Size + Odour + Dampness 0.561 0.447 0.674 0.603 0.273 0.299 0.183 0.163 Size + Odour + Water damage 0.571 0.458 0.684 0.706 0.367 0.368 0.252 0.223 Size + Dampness + Water damage 0.541 0.432 0.650 0.450 0.179 0.214 0.099 0.104 Odour + Dampness + Water damage 0.529 0.417 0.641 0.327 0.162 0.190 0.080 0.062 Four self-reported measures Visibility + Size + Dampness + Water damage 0.653 0.544 0.761 0.090 0.429 0.762 Baseline 0.943 Visibility + Size + Odour + Dampness 0.645 0.531 0.759 0.187 0.746 0.925 0.802 0.807 Visibility + Size + Odour + Water damage 0.653 0.546 0.761 0.103 0.475 0.745 0.962 0.705 Visibility + Odour + Dampness + Water damage 0.633 0.525 0.742 0.323 0.893 0.784 0.464 0.380 Size + Odour + Dampness + Water damage 0.558 0.443 0.672 0.582 0.271 0.299 0.172 0.152 Five self-reported measures Visibility + Size + Odour + Dampness + Water damage 0.652 0.544 0.760 0.117 0.530 0.798 0.943 Baseline Table 5. Effects of the covariate on the ROC curve for moderate/severe mould Sociodemographic status Health condition Older age Male vs female Higher education Employed Lower household income Owner occupancy Allergy conditions Asthma conditions Visibility 1.325 -0.266 0.240 -2.825 2.778 1.549 1.951 1.388 -0.918 2.476 -1.101 2.308 -1.737 1.710 -4.933 0.000 1.999 3.800 -0.432 3.238 -0.321 4.094 -1.075 2.977 Size 1.223 -1.420 -1.937 0.199 1.855 -1.104 -0.384 1.643 0.416 2.214 -2.277 -0.725 -2.976 0.000 -0.722 1.116 0.973 2.737 -2.593 1.130 -1.399 2.310 0.000 2.710 Odour 1.067 -1.125 -1.214 -1.716 1.750 0.383 0.930 0.892 0.324 1.797 -2.285 -0.413 -2.052 0.754 -3.050 -0.013 0.027 2.785 -1.702 1.170 -1.070 1.795 -1.413 1.706 Dampness 0.843 1.065 -0.998 -0.404 1.707 1.147 -0.443 1.546 0.163 1.571 -0.904 2.028 -1.996 0.000 -1.992 0.844 -0.030 2.917 -0.350 2.474 -1.745 0.953 0.643 2.434 Water damage 0.894 1.280 -1.400 0.110 1.783 0.708 2.683 1.255 -1.246 1.975 -0.719 2.148 -2.049 -0.789 -1.580 1.383 0.430 2.443 0.059 1.641 1.998 3.393 -1.040 1.953 Suspicion of invisible mould 1.745 -0.920 1.236 0.086 -0.041 1.050 1.116 -0.589 0.844 3.523 -2.308 1.310 -1.239 2.848 -2.249 1.577 -1.265 2.346 -0.591 2.598 -0.450 2.158 -1.997 1.374 Severity 0.881 -0.218 -1.030 -2.259 1.611 0.689 0.175 0.767 -0.278 1.546 -1.179 1.186 -2.268 0.367 -3.387 -1.083 0.844 3.129 -0.169 1.944 -0.715 1.743 -0.440 2.099 Dwelling condition Major cracks in walls/floors Sinking/moving foundations Wood rot/termite damage Major plumbing problems Walls/windows not level Major roof defect Well-insulated dwelling (Semi)Detached house Visibility -0.458 -0.008 -0.109 . 1.950 -0.240 2.212 -0.742 -1.395 0.230 -0.949 2.351 -1.003 0.858 . . 0.000 3.895 -1.194 1.595 0.000 3.964 -1.526 0.344 Size -0.157 0.440 1.879 2.687 1.857 1.737 1.330 -0.914 -1.579 2.015 -0.933 1.659 -0.265 2.945 0.907 4.466 -0.291 3.319 -0.194 2.955 -0.727 2.385 -1.840 -0.300 Odour 0.105 0.440 -0.381 2.285 0.137 0.496 0.442 -1.020 -0.928 1.848 -0.629 2.232 -1.360 1.589 0.154 4.416 -0.804 1.894 -0.287 2.462 -0.814 1.059 -1.906 1.022 Dampness -0.030 0.093 0.034 2.636 0.275 0.285 0.895 -1.507 -1.374 1.709 -0.987 1.965 -1.257 1.738 2.179 3.255 -0.838 1.800 -0.705 1.929 -0.936 1.784 -2.399 0.139 Water damage -0.059 0.265 -0.020 2.743 0.022 0.452 1.191 -0.967 -1.134 1.851 -0.592 1.755 -1.179 1.919 2.310 3.560 -1.093 1.666 -0.527 2.112 -0.910 2.076 -1.855 1.018 Suspicion of invisible mould 0.107 -0.008 -0.109 0.696 0.122 0.394 1.139 -1.423 -0.716 2.503 -0.735 2.566 -0.977 1.224 0.254 1.032 -0.617 3.029 0.000 1.024 -0.463 2.875 -2.911 1.116 Severity 0.113 0.747 0.175 3.089 0.428 0.675 0.870 0.004 -1.216 0.817 -1.014 1.698 -1.230 1.059 2.608 4.141 -0.776 1.593 -0.663 2.945 -0.531 1.733 -0.618 1.314 Notes: Coefficients and 95%CI are reported. Table 6. Effects of the covariate on the ROC curve for severe mould Sociodemographic status Health condition Older age Male vs female Higher education Employed Lower household income Owner occupancy Allergy conditions Asthma conditions Visibility 0.781 -0.477 0.202 -2.851 0.007 1.549 -0.318 1.803 -2.207 1.949 -1.370 1.714 -3.100 1.128 -5.025 0.000 -1.027 2.858 -0.432 3.238 -1.644 2.509 -1.045 3.862 Size 0.863 . 0.361 -0.069 1.991 -1.104 -0.202 1.891 -1.634 1.918 . . 0.000 0.830 -2.099 0.729 0.331 3.651 -2.593 1.130 -1.631 0.328 0.059 3.722 Odour 0.825 -1.715 . 0.000 0.167 0.383 1.322 1.270 -0.711 1.728 -2.812 0.000 . . -1.522 1.609 -1.620 1.826 -1.702 1.170 -0.312 2.576 0.000 2.456 Dampness 0.775 -1.718 -1.004 -0.306 -0.352 1.147 -0.447 1.447 0.127 1.632 -2.501 -1.314 -1.754 0.000 -1.957 0.910 -1.519 0.299 -0.350 2.474 -1.562 0.798 0.000 2.509 Water damage 0.850 1.224 -1.242 -2.034 -0.779 0.708 0.035 1.317 -1.069 2.327 -0.728 2.437 -2.370 -0.115 -3.295 -0.746 -2.505 0.946 0.059 1.641 -0.390 0.955 0.000 2.526 Suspicion of invisible mould 1.504 -1.113 -1.495 -2.562 2.436 1.050 1.447 -0.625 -0.805 4.196 -2.540 1.304 -3.260 -0.881 -6.706 -0.197 0.680 4.761 -0.591 2.598 0.731 2.720 -2.230 0.199 Severity 0.363 -0.506 -0.617 -2.519 1.234 0.689 0.320 1.263 -1.301 1.399 -1.537 1.079 -2.121 0.751 -4.779 -1.128 -0.362 2.831 -0.169 1.944 -0.627 2.093 0.000 3.166 Dwelling condition Major cracks in walls/floors Sinking/moving foundations Wood rot/termite damage Major plumbing problems Walls/windows not level Major roof defect Well-insulated dwelling (Semi)Detached house Visibility 0.095 -0.185 0.015 0.669 1.438 0.244 3.636 -0.795 -0.842 3.694 -1.210 2.633 -0.920 2.446 0.168 1.036 -0.895 3.572 -0.385 4.118 2.804 7.976 -1.997 0.770 Size -0.897 0.299 -0.483 0.539 -0.821 . 1.616 -0.814 -1.690 0.000 -0.823 1.825 -2.521 1.554 0.000 2.738 -1.679 0.000 . . 0.000 2.842 -1.711 0.000 Odour 0.129 0.301 -0.153 0.348 0.131 0.413 0.659 -1.503 -1.364 1.578 -0.875 1.563 -1.479 1.357 -0.655 1.709 -0.991 1.801 -0.559 1.365 -0.516 1.417 -2.757 0.219 Dampness 1.931 2.079 0.126 1.586 0.484 0.302 1.070 0.499 0.377 3.483 0.580 3.303 -0.954 1.864 0.000 2.440 -0.724 2.125 -0.828 1.807 -0.063 1.921 -1.155 1.824 Water damage 0.032 0.168 -0.008 0.883 -0.297 0.603 1.051 -1.143 -1.132 2.072 -0.722 1.652 -1.239 1.475 -0.128 2.219 -1.358 0.618 -0.487 2.093 -0.978 2.058 -2.581 -0.342 Suspicion of invisible mould -0.255 -0.133 0.027 0.282 -0.083 0.359 1.265 -1.680 -1.335 0.284 -1.320 0.344 -1.002 2.193 -0.593 0.705 -1.243 1.922 -0.397 0.854 -0.186 3.694 -4.285 -0.532 Severity 0.316 0.628 0.340 1.645 0.232 0.827 1.221 -0.282 -0.647 1.501 -1.298 1.708 -0.572 1.874 0.000 4.154 -1.327 1.179 -0.729 3.359 0.000 2.095 -1.427 0.998 Notes: Coefficients and 95%CI are reported. 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Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-4162197","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Article","associatedPublications":[],"authors":[{"id":283972607,"identity":"5e6ae41e-d544-42ba-b560-13954871557b","order_by":0,"name":"Ang Li","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAA80lEQVRIie3RMQrCMBSA4VccXKpdK0i9whNXwatEBLNU6CSOglgX3RUvUW8Q6SriGDFDXTI5OCqomFbBRUNHh/xDaEg/XkoBTKZ/LcGHB2ANAQKmtiQHIcgaL4K5CbD2MHvKQ5zlZAckEDQ6jMbRGQU4RR/hGv4mrtgE6mKyF4l1uJ+jhMr0hNZMQ4D7RJFCL+Lt8GBjDMjVlJKG1N6EYkpuirQUse4agpwyRWKSEUinuD4WdFPq3AdGsFtfKLKforTdjQzi6vY38Tg9Judbs1bmVPLLQHjOpLM6nvqazwc7+xefbbqwby9+Kib6c5PJZDI9AV0yXSu0AHe3AAAAAElFTkSuQmCC","orcid":"https://orcid.org/0000-0002-6269-6432","institution":"The University of Melbourne","correspondingAuthor":true,"prefix":"","firstName":"Ang","middleName":"","lastName":"Li","suffix":""},{"id":283972608,"identity":"065c5b50-76de-4495-80b5-ab00bdd2cbfc","order_by":1,"name":"Mathew Toll","email":"","orcid":"","institution":"The University of Melbourne","correspondingAuthor":false,"prefix":"","firstName":"Mathew","middleName":"","lastName":"Toll","suffix":""},{"id":283972609,"identity":"4f45ea6b-0e06-4fbc-a610-30f15bc1290c","order_by":2,"name":"Christhina Candido","email":"","orcid":"","institution":"The University of Melbourne","correspondingAuthor":false,"prefix":"","firstName":"Christhina","middleName":"","lastName":"Candido","suffix":""},{"id":283972610,"identity":"f0167add-404a-460c-93d9-dcd3dc7d8d2c","order_by":3,"name":"Rebecca Bentley","email":"","orcid":"","institution":"The University of Melbourne","correspondingAuthor":false,"prefix":"","firstName":"Rebecca","middleName":"","lastName":"Bentley","suffix":""}],"badges":[],"createdAt":"2024-03-25 09:30:47","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-4162197/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-4162197/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":53556590,"identity":"b11898cf-3c74-47e9-a72e-c4e067ee5282","added_by":"auto","created_at":"2024-03-27 12:41:43","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":306452,"visible":true,"origin":"","legend":"\u003cp\u003eDiagnostic performance of self-reported mould measures by observation timeframe\u003c/p\u003e","description":"","filename":"1.png","url":"https://assets-eu.researchsquare.com/files/rs-4162197/v1/84c18857de5a53e640718742.png"},{"id":53556321,"identity":"be041045-75c1-419f-9f1a-95d5780cfd1d","added_by":"auto","created_at":"2024-03-27 12:33:43","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":130299,"visible":true,"origin":"","legend":"\u003cp\u003eCut-off of self-reported severity of mould in identifying mould presence\u003c/p\u003e","description":"","filename":"2.png","url":"https://assets-eu.researchsquare.com/files/rs-4162197/v1/ac0cb4afb3f6f739c99408cb.png"},{"id":54048573,"identity":"b74e328f-6edf-4717-abb7-ff716b131b0b","added_by":"auto","created_at":"2024-04-03 20:29:21","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":778051,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-4162197/v1/811f098a-f74b-4547-a4df-b15c58bb774e.pdf"},{"id":53556323,"identity":"3ecebf4e-9a53-4166-83c0-634525d49ff2","added_by":"auto","created_at":"2024-03-27 12:33:43","extension":"docx","order_by":1,"title":"","display":"","copyAsset":false,"role":"supplement","size":21371,"visible":true,"origin":"","legend":"","description":"","filename":"AppendixA.docx","url":"https://assets-eu.researchsquare.com/files/rs-4162197/v1/724d8b4af5a7fa74c2468dd3.docx"}],"financialInterests":"There is \u003cb\u003eNO\u003c/b\u003e Competing Interest.","formattedTitle":"How best to diagnose in-home mould exposure: The validity and accuracy of self-reported measures","fulltext":[{"header":"Introduction","content":"\u003cp\u003eMould growth is indicative of unhealthy indoor environments and poses potential health risk to occupants across building typologies\u0026nbsp;[1, 2]. Dampness, mould and dampness-related agents in homes are found to be associated with increased risks of asthma, respiratory infections and symptoms, hypersensitivity pneumonitis, allergic alveolitis, and immunological reactions, posing a significant treat to vulnerable demographics\u0026nbsp;[1, 3, 4]. The World Health Organisation (WHO) recommends that no exposure can be considered safe for health and that dampness and mould should be prevented, or remediated early, to avoid hazardous exposure\u0026nbsp;[1, 3]. Climate change and increased frequency and duration of weather-related events such as storms and heavy rain are likely to aggravate exposure\u0026nbsp;[3, 5]. The impacts of dampness and mould are unequal across populations, with higher prevalence in substandard housing for low-income people\u0026nbsp;[1]\u0026nbsp;and private rental and social housing that are in poor states of repair\u0026nbsp;[6].\u003c/p\u003e\n\u003cp\u003eDespite increasing evidence on the adverse health and health inequality impact of indoor dampness and mould and widely reported experiences of biotoxin-related illness\u0026nbsp;[6], the prevalence and scope of the exposure in our homes are not well quantified\u0026nbsp;[6, 7]. Epidemiological studies largely rely on self-reported measures of dampness and mould - often estimating prevalence through self-reported questionnaires. However, these data are subject to measurement bias and estimates vary widely depending on the questions used\u0026nbsp;[3]. Reliance on self-reports can risk mis- or under-diagnosis and threaten the validity of study results\u0026nbsp;[8]. While external inspection allows objective and standardised measures of mould, it is costly and often limited to a single timepoint. Therefore, it is crucial to understand the consistency between self-reported and objective indicators of mould to build a basis for exposure assessment at scale, which allows establishment of longitudinal exposure information and databases for monitoring.\u003c/p\u003e\n\u003cp\u003eThe validity and accuracy of subjective measures of mould remain under-examined. The few studies comparing agreement between self-reports and inspection by trained surveyors suggest poor consistency between occupants’ and inspectors’ observations of odour, visible mould, and visible damp\u0026nbsp;[9-13], with some studies describing an overestimation by occupants\u0026nbsp;[14]\u0026nbsp;and others an underestimation\u0026nbsp;[15]. There is also a dearth of evidence on the consistency between occupants’ self-reports and laboratory tests and how the framing of self-assessment questions affects the accuracy of self-reporting.\u003c/p\u003e\n\u003cp\u003eTo address these knowledge gaps, we investigated the validity and accuracy of self-reported measures of indoor mould exposure against laboratory testing of samples collected from homes. We considered a range of self-reported measures that varied by their vernacular, framing, timeframe, and severity of target to be identified. Alongside self-reported measures, we collected dust samples from households to provide an objective comparator so as to determine the optimal design of survey questions that yield the most accurate mould reporting in population-wide surveys.\u003c/p\u003e"},{"header":"Methods","content":"\u003cp\u003e\u003cem\u003eData\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003eParticipants were recruited through an online survey disseminated in June 2022 via the Centre of Research Excellence in Healthy Housing website, university and faculty newsletters, social media postings on Facebook, LinkedIn, and X (then Twitter), posters within the University of Melbourne campus, and mail drops. The first one-hundred people indicating either mould presence or absence at home who completed the online survey and consented to testing were invited to enrol to this validation study. Home visits for dust sample collection were conducted between 13 August 2022 and 13 May 2023, during which the mould samples from 100 participants were collected and tested. All participants provided online and written informed consent and completed on-site questionnaires on mould measures.\u003c/p\u003e\n\u003cp\u003e\u003cem\u003eSelf-reported mould measures\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003eDuring home visits, participants were asked to complete questions compiled from questions commonly asked in mould surveys (see Appendix A for full list). These included whether they noticed visible mould, mould in any part of the dwelling that was larger than an A4 sheet of paper, mould odour, dampness, and water damage, in the last 12 months, in the last 3 months, or at present, with responses including yes, no, or not available (e.g., if they recently moved into the house). In addition, participants were asked to rate mould severity at their dwelling as severe, moderate, mild, no mould, or not available, and, through the online survey, report if they suspected any humidity/mould problems inside the floor, walls or ceiling of the home that were not visible.\u003c/p\u003e\n\u003cp\u003e\u003cem\u003eLab-tested mould measures\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003eThe researcher collected floor dust samples using a vacuum cleaner connected to a dust collector (manufactured by Zefon International Inc., USA) for at least 5 minutes in each of two primary rooms (living room and main bedroom) before removing the dust collector from the vacuum hose and placing the capped dust collectors into a re-closeable bag. Dust samples were collected from a 1 metre x 2 metre rectangular sampling area on the floors from the living room and main bedroom each. If the sample location could not accommodate these dimensions, the researcher adjusted them to sample a total of 2 square metres[1]. Samples were sent to the NSJ Enviro Sciences Lab using express mail (next day delivery) and once in the laboratory remained frozen until the Health Effects Roster of Type-Specific Formers of Mycotoxins and Inflammagens \u0026ndash; 2\u003csup\u003end\u003c/sup\u003e version (HERTSMI-2) analysis using the quantitative polymerase chain reaction (qPCR) technique.\u003c/p\u003e\n\u003cp\u003eDeveloped by the United States Environmental Protection Agency, the qPCR technique is a DNA-based approach to exposure assessment of microorganisms and their components\u0026nbsp;[16], which are shown to yield the highest sensitivity and precision of fungal contamination of dust and reduce the variability associated with culture-based approaches in determining mould contamination\u0026nbsp;[17-19]. The application of mould specific quantitative polymerase chain reaction (MSQPCR) techniques resulted in the development of the Environmental Relative Mouldiness Index (ERMI) and HERTSMI-2\u0026nbsp;[20]. While both tests are used to inform objectively if water damaged building conditions exist and if a given building is safe for occupancy by people previously sickened by water-damaged buildings\u0026nbsp;[21], HERTSMI-2 is a more streamlined test that analyses the 5 major mould species (including aspergillus penicilloides, aspergillus versicolor, chaetomium globosum, stachybotrys chartarum, and wallemia sebi) and becomes the standard exposure tool for assessing adverse health effects of exposure to water-damaged buildings and safety for re-entry into the building after remediation\u0026nbsp;[22]. HERTSMI-2 testing uses a weighted scale applied to the concentration in spore equivalents/mg of each target mould\u0026rsquo;s DNA\u0026nbsp;[21]. The samples were tested and analysed by the NSJ Enviro Sciences Lab.\u003c/p\u003e\n\u003cp\u003e\u003cem\u003eCovariates\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003eThrough the online questionnaire (delivered through Qualtrics), participants were asked about their sociodemographic status (age, gender, education, employment, household income, and housing tenure), dwelling condition (major structural problems including major cracks in walls/floors, sinking/moving foundations, wood rot/termite damage, major plumbing problems, walls/windows not level, and major roof defect; dwelling insulation; and dwelling type), and health conditions (allergy and asthma conditions). Each factor is related to housing circumstances and indoor air quality\u0026nbsp;[3, 5, 23, 24].\u003c/p\u003e\n\u003cp\u003e\u003cem\u003eStatistical analysis\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003eFor each self-reported question asked in the survey, summary statistics describing their diagnostic performance including sensitivity, specificity, positive predictive value, and negative predictive value were estimated using the lab-tested measures as validation. The overall classification accuracy of self-reported mould was described by the Cohen\u0026rsquo;s Kappa statistics\u0026nbsp;[25]\u0026nbsp;which measure the agreement between occupants reporting and lab tests. The Kappa coefficients range from -1 to +1, with a higher value indicating better agreement. To capture the trade-off between true positives and false positives, the receiver operating characteristic (ROC) curve and the area under the ROC curve (AUC)\u0026nbsp;[26]\u0026nbsp;were also used as a quantitative measure of classification accuracy. A greater AUC value indicates better diagnostic performance. Parametric analyses of the ROC curve with covariate adjustment for sociodemographic, dwelling, and health conditions were performed to test covariate effects on the discriminatory accuracy. Bootstrap of 1,000 replications using bias-corrected methods\u0026nbsp;[27]\u0026nbsp;were applied to obtain confidence intervals.\u003c/p\u003e\n\u003cp\u003e\u003cem\u003eEthics\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003eEthics approval was obtained from the University of Melbourne Human Ethics Committee (Reference Number: 2022-24051-28012-4).\u003c/p\u003e\n\u003cdiv id=\"ftn1\"\u003e\n \u003cp\u003e[1] Details on the vacuum dust sampling procedures are available on the NSJ Enviro Sciences Lab website. https://nsjenviro.com.au/product/hertsmi-2-analysis-and-vacuum-sampling-kit/\u003c/p\u003e\n\u003c/div\u003e"},{"header":"Results","content":"\u003cp\u003e\u003cem\u003eSample statistics\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003eAll respondents lived in one of the two most populated states in Australia: Victoria (65%) or New South Whales (35%)\u0026nbsp;[28]. Table 1 shows sociodemographic and residential characteristics of 100 participants grouped by their lab test results as being exposed to minimal mould (HERTSMI2 score ≤10), moderate mould (HERTSMI2 score 11-15, and severe mould (HERTSMI2 score \u0026gt;15). Data were collected across a wide range of age groups (40.0% aged 18-34, 34.0% aged 35-44, 11.0% aged 45-54, and 15.0% aged ≥55) and genders (30.0% identified as males, 65.0% as females, and 5.0% as others). The majority of the participants were employed (80%) and had a bachelor’s degree or higher (86%), and about half of them were renters (54.0%) and half were homeowners (46.0%). Regarding residential conditions, 61% of the participants resided in houses (compared to 39.0% in flats, units, or apartments); 28% reported major cracks in walls/floors, 25% walls/windows not level, 19% sinking/moving foundations, 15% wood rot/termite damage, 13% major roof defect, and 6% major plumbing problems; and 61.0% reported their homes being poorly insulated. Noticeably, HERTSMI-2 scores were higher for older people, lower income households, dwellings with major plumbing problems, and poorly insulated dwellings.\u003c/p\u003e\n\u003cp\u003eTABLE 1 HERE\u003c/p\u003e\n\u003cp\u003e\u003cem\u003ePresence of mould\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003eThe distribution of self-reported mould measures across lab tested results shows that in general more participants reported the presence of mould at home as the lab HERTSMI2 scores increased, and this pattern is more pronounced for self-reported visibility and odour relative to other self-reported measures (Table 1). More than half of the participants reported noticing visible mould (61%) or suspicion of invisible mould (61%) at home, more than one third reported noticing a mouldy or musty odour (39%) and excess dampness (32%) at home, and less than one third reported seeing mould in parts of the dwelling that in total was larger than an A4 sheet of paper (21%) or noticing water damage (27%) at home. Apart from visible mould and suspicion of invisible mould, other self-reported measures underestimated the presence of actual mould.\u003c/p\u003e\n\u003cp\u003e\u003cem\u003eAgreement between self-reported and lab tested mould\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003eTable 2 presents the diagnostic summary statistics of self-reported mould measures in classifying lab-tested mould status and the Kappa statistics on the agreement between self-reported and lab-tested mould measures. In identifying the presence of mould, identification of visible mould had the highest sensitivity (correctly reporting mould when mould is present), positive predictive value (probability of mould being present when it is reported by occupants), and negative predictive value (probability mould being absent when it is reported by occupants). Self-reported measures of mould size had the highest specificity (correctly reporting the absence of mould when mould is absent).\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eTABLE 2 HERE\u003c/p\u003e\n\u003cp\u003eIn terms of the agreement with lab-tested moderate or severe mould, identification of visible mould and suspicion of invisible mould yielded the highest Kappa values (0.24 for each), with resident self-reports and lab results agreeing for 62% of dwellings (Table 2 panel (a)). In terms of the agreement with lab-tests for severe mould, visible mould exhibited the highest Kappa value (0.17) (Table 2 panel (b)). These results indicate a fair level of agreement between self-reported and lab-tested mould measures for cases of moderate to severe mould in homes\u0026nbsp;[29].\u003c/p\u003e\n\u003cp\u003eTables 3 and 4 present the estimates of the AUC that quantify the accuracy of individual and combined measures of self-reported mould in classifying the presence of moderate or severe mould (Table 3) and severe mould (Table 4), respectively, tested through mould samples. Overall, there was a moderate level of agreement between self-reported and lab-tested mould measures, based on the interpretation of the AUC values\u0026nbsp;[30].\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eTABLE 3 AND TABLE 4 HERE\u003c/p\u003e\n\u003cp\u003eOf the range of self-reported mould measures used to identify moderate or severe mould in homes (Table 3), visible mould and suspicion of invisible mould had the largest AUC value (0.622 for each), followed by identification of mould severity (no, mild, moderate, or severe mould) (AUC=0.591), mould odour (AUC=0.538), water damage (AUC=0.535), dampness (AUC=0.526), and mould size greater than A4 sheet of paper (AUC=0.494). When considering the use of more than one measure, the combination of mould visibility and size produced the highest AUC value (0.647). When combining three measures, mould visibility, mould size, and dampness produced the highest AUC value (0.647) and when combining four measures, mould visibility, mould size, dampness, and water damage yielded the highest AUC value (0.649). Five self-reported mould measures yielded an AUC value of 0.638 – lower or similar success than is generated from combinations of fewer variables.\u003c/p\u003e\n\u003cp\u003eResults for tests of equality of ROC areas in classifying moderate or severe mould (Table 3) reveal that, among single self-reported measures, mould visibility performs significantly better than mould size at the 5% level of significance and better than dampness and water damage at the 10% level of significance. There are no significant differences in classification abilities amongst reports of mould odour, suspicion of invisible mould, and mould severity. A combination of two self-reported measures predicts mould better than a single self-reported measure (including mould size, mould odour, dampness, and water damage). A combination of 3-5 self-reported measures performed better than a single-reported measure of either mould size, dampness, or water damage, but not significantly better than two measures. The differences among combined measures were not statistically significant at the 5% level.\u003c/p\u003e\n\u003cp\u003eSelf-reported identification of visible mould also performed the best at predicting cases of severe mould (AUC=0.602) (Table 4). When considering combinations of two self-reported measures, mould visibility and mould size performed best (AUC=0.638). When considering three combined measures, mould visibility, mould size, and water damage performed best (AUC=0.649), and of four combined self-reported mould measures, mould visibility, mould size, mould odour, and water damage were the best predictors (AUC=0.653). Five self-reported mould measures altogether gave an AUC value of 0.652 – achieving no greater accuracy than for four measures.\u003c/p\u003e\n\u003cp\u003eIn testing equality of ROC areas in classifying severe mould (Table 4), mould visibility performed better than mould size and water damage at the 5% level of significance, with no difference in predictability compared to mould odour, dampness, suspicion of mould, and mould severity. Using more than one measure performed better than using a single measure (including mould size, mould odour, dampness, or water damage) at the 5% or 10% significance level. The differences among combined measures were not statistically significant at the 5% level.\u003c/p\u003e\n\u003cp\u003e\u003cem\u003eVariation in diagnostic performance of self-reported mould by household characteristics\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003eTables 5 and 6 shows the estimated covariate effects of individual sociodemographic, health, and dwelling characteristics on the diagnostic performance of self-reported mould measures in the identification of moderate or severe mould (Table 5) and severe mould (Table 6) respectively.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eTABLE 5 AND TABLE 6 HERE\u003c/p\u003e\n\u003cp\u003eAge, household income, employment status, and major dwelling structural problem had a more consistent influence on diagnostic performance of self-reported measures at the 5% significance level. Specifically, older people, lower household income, unemployment, and major plumbing problems were associated with better accuracy of self-diagnosed mould. Having allergic and respiratory conditions were also associated with better accuracy in reporting mould (although this varied by measure).\u003c/p\u003e\n\u003cp\u003e\u003cem\u003eVariation in diagnostic performance of self-reported mould by timeframe\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003eAccuracy in prediction varied by the timeframe people were asked to consider – at present, the past 3 months, or the past 12 months. Figure 1 shows the timeframe of the mould exposure asked of participants for the best diagnostic self-reported measures of moderate or severe mould (panel (a)) and severe mould (panel (b)). In predicting objective moderate or severe mould, the predictability of self-reported mould visibility, dampness, and water damage were higher when using past 3 months as the reference period, while the predictability of mould size, mould severity, and mould odour were higher when using past 12 months as the reference period. This was similar for objective severe mould, except for mould size and severity for which current mould status was associated with the largest AUC values.\u003c/p\u003e\n\u003cp\u003eFIGURE 1 HERE\u003c/p\u003e\n\u003cp\u003e\u003cem\u003eThreshold of self-reported mould severity in predicting lab tested mould\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003eFigure 2 shows the cut-offs of self-reported mould severity (no mould, mild mould, moderate mould, and severe mould) to best identify the presence of objective moderate or severe mould (panel (a)) and severe mould (panel (b)). In predicting both moderate or severe mould and severe mould, self-reports of at least mild mould (i.e., mild, moderate, or severe mould) performed the best in classifying the presence of actual mould (AUC=0.614), compared to other thresholds across gradients of mould severity. This suggests that self-reporting at least mild mould vs no mould performed best at classifying the actual presence of mould.\u003c/p\u003e\n\u003cp\u003eFIGURE 2 HERE\u003c/p\u003e"},{"header":"Discussion","content":"\u003cp\u003eWe provide comprehensive guidance on how to optimise self-reported mould measures to assess mould exposure. This is the first study that systematically summarises the diagnostic performance of varied construction of self-reported measures, through analyses of the consistency between self-reported and lab-tested (using qPCR) assessment. We consider single and combinations of self-reported measures varied by wording, framing, time periods to be referenced, severity of target to be identified, and household characteristics that are associated with the validity and accuracy of self-diagnosed mould. Overall, we find that there was moderate agreement between self-reported and lab tested mould measures based on Kappa and AUC statistics. Occupants tended to overestimate the presence of mould when asked about visible mould and suspicion of mould and to underestimate the presence of mould when asked about mould size, odour, dampness, and water damage. Identification of visible mould had the highest sensitivity, positive predictive value, and negative predictive value, while identification of mould larger than an A4 sheet of paper (as is used in the New Zealand Census) had the highest specificity.\u003c/p\u003e \u003cp\u003eFindings suggest that when considering a single measure, reporting of visible mould yielded the most accurate diagnosis. Combining self-reported visible mould and mould size increased accuracy, noting that no substantial improvements in prediction are achieved by adding more than two self-reported measures. When using self-rated mould severity (no, mild, moderate, or severe mould), grouping mild, moderate, and severe mould best detected actual mould presence. More accurate assessment of moderate or severe mould in past 3 months is elicited from questions on visible mould, dampness, and water damage, while for the past 12 months, mould size, odour, and severity were associated with better diagnostic accuracy.\u003c/p\u003e \u003cp\u003eAnalyses also reveal that the severity of mould exposure is patterned by age, income, and plumbing problems and prediction accuracy varies by occupant sociodemographic and residential factors. There were significant differences by age, household income, and major plumbing problems on the diagnostic performance of self-reported mould, with better discriminatory accuracy among occupants who were older, had lower household incomes, or major plumbing problems. These groups had higher HERTSMI2 scores, which may explain their better diagnostic performance of self-reported indoor mould, as more severe the mould in homes, higher the accuracy of reporting. These groups may also have more experience with mould or dwelling structural problems within the building and therefore heightened awareness of recuring mould exposure. This has a policy implication underscoring the need for building event records in place for potential buyers and renters to identify mould risk.\u003c/p\u003e \u003cp\u003eThis study fills an important gap in our understanding of how to assess domestic mould contamination. Population-based studies have largely relied on self-report measures [\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e, \u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e, \u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e31\u003c/span\u003e]. Yet the lack of evidence on the validity of self-reported exposure assessment contributes a degree of uncertainty around estimates. By focussing on improving self-report \u0026ndash; the tool of large-scale studies \u0026ndash; we bridge the gap between mould assessment at the individual level and population metrics relevant to estimating prevalence and attributable disease burden whilst paving the way to consolidating longitudinal studies and databases.\u003c/p\u003e \u003cp\u003eOur study has a few limitations. First, while the sample size of 100 homes is not uncommon in studies that employ microbiological measurement for identification of dampness and mould [\u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e32\u003c/span\u003e], the study sample is not representative of sociodemographic and geographic distribution of the population at the national level. Second, mould samples were collected from floors of the two main living spaces where people spend most of their indoor time, missing other locations in the home. Nevertheless, with a focus on the diagnostic performance of self-reported mould measures, this study can guide on how best to use self-assessed measures of domestic mould, provide basis for quantitative bias analyses, and inform the design of exposure measures for large epidemiological and prevalence studies.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n \u003cli\u003eWorld Health Organization, \u003cem\u003eWHO housing and health guidelines.\u003c/em\u003e 2018.\u003c/li\u003e\n \u003cli\u003eCaillaud, D., et al., \u003cem\u003eIndoor mould exposure, asthma and rhinitis: findings from systematic reviews and recent longitudinal studies.\u003c/em\u003e European Respiratory Review, 2018. \u003cstrong\u003e27\u003c/strong\u003e(148).\u003c/li\u003e\n \u003cli\u003eHeseltine, E. and J. Rosen, \u003cem\u003eWHO guidelines for indoor air quality: dampness and mould.\u003c/em\u003e 2009.\u003c/li\u003e\n \u003cli\u003eRatnaseelan, A.M., I. Tsilioni, and T.C. 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Sundell, \u003cem\u003eHow valid are parents\u0026apos; questionnaire responses regarding building characteristics, mouldy odour, and signs of moisture problems in Swedish homes?\u003c/em\u003e Scandinavian journal of public health, 2007. \u003cstrong\u003e35\u003c/strong\u003e(2): p. 125-132.\u003c/li\u003e\n \u003cli\u003eSun, Y., J. Sundell, and Y. Zhang, \u003cem\u003eValidity of building characteristics and dorm dampness obtained in a self-administrated questionnaire.\u003c/em\u003e Science of the Total Environment, 2007. \u003cstrong\u003e387\u003c/strong\u003e(1-3): p. 276-282.\u003c/li\u003e\n \u003cli\u003eCai, J., et al., \u003cem\u003eValidity of subjective questionnaire in evaluating dwelling characteristics, home dampness, and indoor odors in Shanghai, China: Cross-sectional survey and on-site inspection.\u003c/em\u003e Energy and Buildings, 2016. \u003cstrong\u003e127\u003c/strong\u003e: p. 1019-1027.\u003c/li\u003e\n \u003cli\u003eMarasinghe, S.A., et al., \u003cem\u003eValidity of questionnaire survey in evaluating residence\u0026rsquo;s characteristics and dampness in contemporary human dwellings in Tianjin, China.\u003c/em\u003e Science and Technology for the Built Environment, 2023. \u003cstrong\u003e29\u003c/strong\u003e(2): p. 241-249.\u003c/li\u003e\n \u003cli\u003eBornehag, C.-G., et al., \u003cem\u003eDampness in buildings and health. Nordic interdisciplinary review of the scientific evidence on associations between exposure to\u0026quot; dampness\u0026quot; in buildings and health effects (NORDDAMP).\u003c/em\u003e Indoor air, 2001. \u003cstrong\u003e11\u003c/strong\u003e(2): p. 72-86.\u003c/li\u003e\n \u003cli\u003eNevalainen, A., et al., \u003cem\u003ePrevalence of moisture problems in Finnish houses.\u003c/em\u003e Indoor Air, 1998. \u003cstrong\u003e8\u003c/strong\u003e(S4): p. 45-49.\u003c/li\u003e\n \u003cli\u003eHaugland, R. and S. Vesper, \u003cem\u003eMethod of identifying and quantifying specific fungi and bacteria\u003c/em\u003e. 2002, Google Patents.\u003c/li\u003e\n \u003cli\u003eBiyeyeme Bi Mve, M.-J., et al., \u003cem\u003eComparison of methods to evaluate the fungal biomass in heating, ventilation, and air-conditioning (HVAC) dust.\u003c/em\u003e Environmental monitoring and assessment, 2017. \u003cstrong\u003e189\u003c/strong\u003e: p. 1-10.\u003c/li\u003e\n \u003cli\u003eShorter, C., et al., \u003cem\u003eObjective assessment of domestic mold contamination using quantitative PCR.\u003c/em\u003e Journal of Allergy and Clinical Immunology, 2016. \u003cstrong\u003e137\u003c/strong\u003e(2): p. 622-624.\u003c/li\u003e\n \u003cli\u003eCox, J., et al., \u003cem\u003eComparison of indoor air sampling and dust collection methods for fungal exposure assessment using quantitative PCR.\u003c/em\u003e Environmental Science: Processes \u0026amp; Impacts, 2017. \u003cstrong\u003e19\u003c/strong\u003e(10): p. 1312-1319.\u003c/li\u003e\n \u003cli\u003eEPA, \u003cem\u003eThe Environmental Relative Moldiness Index (ERMI).\u003c/em\u003e United States Environmental Protection Agency, 2021.\u003c/li\u003e\n \u003cli\u003eShoemaker, R.C. and D. Lark, \u003cem\u003eHERTSMI-2 and ERMI:\u0026ldquo;Correlating Human Health Risk with Mold Specific qPCR in Water-Damaged Buildings\u0026rdquo;,# 658 in Proceedings of the 14th International Conference on Indoor Air Quality and Climate.\u003c/em\u003e International Society for Indoor Air Quality and Climate, Ghent, Belgium, 2016.\u003c/li\u003e\n \u003cli\u003eShoemaker, R., et al., \u003cem\u003eNewer Molecular Methods Bring New Insights into Human-And Building-Health Risk Assessments from Water-Damaged Buildings: Defining Exposure and Reactivity, the Two Sides of Causation of CIRS-WDB Illness.\u003c/em\u003e Medical Research Archives, 2021. \u003cstrong\u003e9\u003c/strong\u003e(3).\u003c/li\u003e\n \u003cli\u003eSuzuki, N., et al., \u003cem\u003eRisk factors for the onset of sick building syndrome: A cross-sectional survey of housing and health in Japan.\u003c/em\u003e Building and Environment, 2021. \u003cstrong\u003e202\u003c/strong\u003e: p. 107976.\u003c/li\u003e\n \u003cli\u003eDHARMAGE, et al., \u003cem\u003eResidential characteristics influence Der p 1 levels in homes in Melbourne, Australia.\u003c/em\u003e Clinical \u0026amp; Experimental Allergy, 1999. \u003cstrong\u003e29\u003c/strong\u003e(4): p. 461-469.\u003c/li\u003e\n \u003cli\u003eCohen, J., \u003cem\u003eA coefficient of agreement for nominal scales.\u003c/em\u003e Educational and psychological measurement, 1960. \u003cstrong\u003e20\u003c/strong\u003e(1): p. 37-46.\u003c/li\u003e\n \u003cli\u003eBen-David, A., \u003cem\u003eAbout the relationship between ROC curves and Cohen\u0026apos;s kappa.\u003c/em\u003e Engineering Applications of Artificial Intelligence, 2008. \u003cstrong\u003e21\u003c/strong\u003e(6): p. 874-882.\u003c/li\u003e\n \u003cli\u003eStata, \u003cem\u003eReceiver operating characteristic (ROC) regression.\u003c/em\u003e 2023.\u003c/li\u003e\n \u003cli\u003eAustralian Bureau of Statistics, \u003cem\u003eNational, state and territory population.\u003c/em\u003e ABS, 2023.\u003c/li\u003e\n \u003cli\u003eLandis, J.R. and G.G. Koch, \u003cem\u003eThe measurement of observer agreement for categorical data.\u003c/em\u003e biometrics, 1977: p. 159-174.\u003c/li\u003e\n \u003cli\u003ede Hond, A.A., E.W. Steyerberg, and B. van Calster, \u003cem\u003eInterpreting area under the receiver operating characteristic curve.\u003c/em\u003e The Lancet Digital Health, 2022. \u003cstrong\u003e4\u003c/strong\u003e(12): p. e853-e855.\u003c/li\u003e\n \u003cli\u003eHaverinen-Shaughnessy, U., \u003cem\u003ePrevalence of dampness and mold in European housing stock.\u003c/em\u003e Journal of Exposure Science \u0026amp; Environmental Epidemiology, 2012. \u003cstrong\u003e22\u003c/strong\u003e(5): p. 461-467.\u003c/li\u003e\n \u003cli\u003eMendell, M.J. and R.I. Adams, \u003cem\u003eDoes evidence support measuring spore counts to identify dampness or mold in buildings? A literature review.\u003c/em\u003e Journal of Exposure Science \u0026amp; Environmental Epidemiology, 2022. \u003cstrong\u003e32\u003c/strong\u003e(2): p. 177-187.\u003cstrong\u003e\u003cbr\u003e\u003c/strong\u003e\u003c/li\u003e\n\u003c/ol\u003e"},{"header":"Tables","content":"\u003cp\u003eTable 1. Sample summary statistics\u003c/p\u003e\n\u003ctable border=\"0\" cellspacing=\"0\" cellpadding=\"0\" width=\"695\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd width=\"23.132183908045977%\" valign=\"bottom\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"20.689655172413794%\" colspan=\"3\" valign=\"bottom\"\u003e\n \u003cp\u003eFull sample\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e(n=100)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.39080459770115%\" colspan=\"4\" valign=\"bottom\"\u003e\n \u003cp\u003eLab test no/mild mould (n=51)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"20.54597701149425%\" colspan=\"4\" valign=\"bottom\"\u003e\n \u003cp\u003eLab test moderate mould (n=14)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.24137931034483%\" colspan=\"4\" valign=\"bottom\"\u003e\n \u003cp\u003eLab test severe mould (n=35)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"23.09899569583931%\" valign=\"bottom\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.604017216642755%\" valign=\"bottom\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"4.017216642754663%\" valign=\"bottom\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.190817790530847%\" colspan=\"2\" valign=\"bottom\"\u003e\n \u003cp\u003eHERTSMI2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.916786226685796%\" colspan=\"2\" valign=\"bottom\"\u003e\n \u003cp\u003eHERTSMI2\u0026le;10\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"20.37302725968436%\" colspan=\"4\" valign=\"bottom\"\u003e\n \u003cp\u003e11\u0026le;HERTSMI2\u0026le;15\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.938307030129124%\" colspan=\"4\" valign=\"bottom\"\u003e\n \u003cp\u003eHERTSMI2\u0026gt;15\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"0.860832137733142%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"23.165467625899282%\" valign=\"bottom\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"7.625899280575539%\" valign=\"bottom\"\u003e\n \u003cp\u003e%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"4.028776978417266%\" valign=\"bottom\"\u003e\n \u003cp\u003en\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.223021582733812%\" colspan=\"2\" valign=\"bottom\"\u003e\n \u003cp\u003eMean\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.338129496402877%\" valign=\"bottom\"\u003e\n \u003cp\u003e%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.618705035971223%\" valign=\"bottom\"\u003e\n \u003cp\u003en\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.647482014388489%\" colspan=\"2\" valign=\"bottom\"\u003e\n \u003cp\u003e%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.906474820143885%\" valign=\"bottom\"\u003e\n \u003cp\u003en\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.964028776978417%\" colspan=\"3\" valign=\"bottom\"\u003e\n \u003cp\u003e%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.330935251798561%\" valign=\"bottom\"\u003e\n \u003cp\u003en\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"1.1510791366906474%\" colspan=\"2\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"23.165467625899282%\" valign=\"bottom\"\u003e\n \u003cp\u003e\u003cstrong\u003eAge\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.625899280575539%\" valign=\"bottom\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"4.028776978417266%\" valign=\"bottom\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"11.223021582733812%\" colspan=\"2\" valign=\"bottom\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"7.338129496402877%\" valign=\"bottom\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"6.618705035971223%\" valign=\"bottom\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"10.647482014388489%\" colspan=\"2\" valign=\"bottom\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"6.906474820143885%\" valign=\"bottom\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"14.964028776978417%\" colspan=\"3\" valign=\"bottom\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"6.330935251798561%\" valign=\"bottom\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"1.1510791366906474%\" colspan=\"2\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"23.165467625899282%\" valign=\"bottom\"\u003e\n \u003cp\u003e18-34\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.625899280575539%\" valign=\"bottom\"\u003e\n \u003cp\u003e40.0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"4.028776978417266%\" valign=\"bottom\"\u003e\n \u003cp\u003e40\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.223021582733812%\" colspan=\"2\" valign=\"bottom\"\u003e\n \u003cp\u003e11.2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.338129496402877%\" valign=\"bottom\"\u003e\n \u003cp\u003e41.2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.618705035971223%\" valign=\"bottom\"\u003e\n \u003cp\u003e21\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.647482014388489%\" colspan=\"2\" valign=\"bottom\"\u003e\n \u003cp\u003e35.7\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.906474820143885%\" valign=\"bottom\"\u003e\n \u003cp\u003e5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.964028776978417%\" colspan=\"3\" valign=\"bottom\"\u003e\n \u003cp\u003e40.0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.330935251798561%\" valign=\"bottom\"\u003e\n \u003cp\u003e14\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"1.1510791366906474%\" colspan=\"2\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"23.165467625899282%\" valign=\"bottom\"\u003e\n \u003cp\u003e35-44\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.625899280575539%\" valign=\"bottom\"\u003e\n \u003cp\u003e34.0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"4.028776978417266%\" valign=\"bottom\"\u003e\n \u003cp\u003e34\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.223021582733812%\" colspan=\"2\" valign=\"bottom\"\u003e\n \u003cp\u003e11.9\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.338129496402877%\" valign=\"bottom\"\u003e\n \u003cp\u003e29.4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.618705035971223%\" valign=\"bottom\"\u003e\n \u003cp\u003e15\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.647482014388489%\" colspan=\"2\" valign=\"bottom\"\u003e\n \u003cp\u003e50.0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.906474820143885%\" valign=\"bottom\"\u003e\n \u003cp\u003e7\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.964028776978417%\" colspan=\"3\" valign=\"bottom\"\u003e\n \u003cp\u003e34.3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.330935251798561%\" valign=\"bottom\"\u003e\n \u003cp\u003e12\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"1.1510791366906474%\" colspan=\"2\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"23.165467625899282%\" valign=\"bottom\"\u003e\n \u003cp\u003e45-54\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.625899280575539%\" valign=\"bottom\"\u003e\n \u003cp\u003e11.0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"4.028776978417266%\" valign=\"bottom\"\u003e\n \u003cp\u003e11\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.223021582733812%\" colspan=\"2\" valign=\"bottom\"\u003e\n \u003cp\u003e8.0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.338129496402877%\" valign=\"bottom\"\u003e\n \u003cp\u003e17.7\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.618705035971223%\" valign=\"bottom\"\u003e\n \u003cp\u003e9\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.647482014388489%\" colspan=\"2\" valign=\"bottom\"\u003e\n \u003cp\u003e7.1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.906474820143885%\" valign=\"bottom\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.964028776978417%\" colspan=\"3\" valign=\"bottom\"\u003e\n \u003cp\u003e2.9\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.330935251798561%\" valign=\"bottom\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"1.1510791366906474%\" colspan=\"2\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"23.165467625899282%\" valign=\"bottom\"\u003e\n \u003cp\u003e\u0026gt;=55\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.625899280575539%\" valign=\"bottom\"\u003e\n \u003cp\u003e15.0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"4.028776978417266%\" valign=\"bottom\"\u003e\n \u003cp\u003e15\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.223021582733812%\" colspan=\"2\" valign=\"bottom\"\u003e\n \u003cp\u003e13.6\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.338129496402877%\" valign=\"bottom\"\u003e\n \u003cp\u003e11.8\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.618705035971223%\" valign=\"bottom\"\u003e\n \u003cp\u003e6\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.647482014388489%\" colspan=\"2\" valign=\"bottom\"\u003e\n \u003cp\u003e7.1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.906474820143885%\" valign=\"bottom\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.964028776978417%\" colspan=\"3\" valign=\"bottom\"\u003e\n \u003cp\u003e22.9\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.330935251798561%\" valign=\"bottom\"\u003e\n \u003cp\u003e8\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"1.1510791366906474%\" colspan=\"2\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"23.165467625899282%\" valign=\"bottom\"\u003e\n \u003cp\u003e\u003cstrong\u003eGender\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.625899280575539%\" valign=\"bottom\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"4.028776978417266%\" valign=\"bottom\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"11.223021582733812%\" colspan=\"2\" valign=\"bottom\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"7.338129496402877%\" valign=\"bottom\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"6.618705035971223%\" valign=\"bottom\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"10.647482014388489%\" colspan=\"2\" valign=\"bottom\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"6.906474820143885%\" valign=\"bottom\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"14.964028776978417%\" colspan=\"3\" valign=\"bottom\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"6.330935251798561%\" valign=\"bottom\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"1.1510791366906474%\" colspan=\"2\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"23.165467625899282%\" valign=\"bottom\"\u003e\n \u003cp\u003eMale\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.625899280575539%\" valign=\"bottom\"\u003e\n \u003cp\u003e30.0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"4.028776978417266%\" valign=\"bottom\"\u003e\n \u003cp\u003e30\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.223021582733812%\" colspan=\"2\" valign=\"bottom\"\u003e\n \u003cp\u003e11.7\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.338129496402877%\" valign=\"bottom\"\u003e\n \u003cp\u003e31.4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.618705035971223%\" valign=\"bottom\"\u003e\n \u003cp\u003e16\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.647482014388489%\" colspan=\"2\" valign=\"bottom\"\u003e\n \u003cp\u003e28.6\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.906474820143885%\" valign=\"bottom\"\u003e\n \u003cp\u003e4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.964028776978417%\" colspan=\"3\" valign=\"bottom\"\u003e\n \u003cp\u003e28.6\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.330935251798561%\" valign=\"bottom\"\u003e\n \u003cp\u003e10\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"1.1510791366906474%\" colspan=\"2\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"23.165467625899282%\" valign=\"bottom\"\u003e\n \u003cp\u003eFemale\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.625899280575539%\" valign=\"bottom\"\u003e\n \u003cp\u003e65.0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"4.028776978417266%\" valign=\"bottom\"\u003e\n \u003cp\u003e65\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.223021582733812%\" colspan=\"2\" valign=\"bottom\"\u003e\n \u003cp\u003e11.0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.338129496402877%\" valign=\"bottom\"\u003e\n \u003cp\u003e64.7\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.618705035971223%\" valign=\"bottom\"\u003e\n \u003cp\u003e33\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.647482014388489%\" colspan=\"2\" valign=\"bottom\"\u003e\n \u003cp\u003e64.3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.906474820143885%\" valign=\"bottom\"\u003e\n \u003cp\u003e9\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.964028776978417%\" colspan=\"3\" valign=\"bottom\"\u003e\n \u003cp\u003e65.7\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.330935251798561%\" valign=\"bottom\"\u003e\n \u003cp\u003e23\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"1.1510791366906474%\" colspan=\"2\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"23.165467625899282%\" valign=\"bottom\"\u003e\n \u003cp\u003eOther\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.625899280575539%\" valign=\"bottom\"\u003e\n \u003cp\u003e5.0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"4.028776978417266%\" valign=\"bottom\"\u003e\n \u003cp\u003e5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.223021582733812%\" colspan=\"2\" valign=\"bottom\"\u003e\n \u003cp\u003e14.8\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.338129496402877%\" valign=\"bottom\"\u003e\n \u003cp\u003e3.9\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.618705035971223%\" valign=\"bottom\"\u003e\n \u003cp\u003e2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.647482014388489%\" colspan=\"2\" valign=\"bottom\"\u003e\n \u003cp\u003e7.1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.906474820143885%\" valign=\"bottom\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.964028776978417%\" colspan=\"3\" valign=\"bottom\"\u003e\n \u003cp\u003e5.7\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.330935251798561%\" valign=\"bottom\"\u003e\n \u003cp\u003e2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"1.1510791366906474%\" colspan=\"2\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"23.165467625899282%\" valign=\"bottom\"\u003e\n \u003cp\u003e\u003cstrong\u003eEducation\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.625899280575539%\" valign=\"bottom\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"4.028776978417266%\" valign=\"bottom\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"11.223021582733812%\" colspan=\"2\" valign=\"bottom\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"7.338129496402877%\" valign=\"bottom\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"6.618705035971223%\" valign=\"bottom\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"10.647482014388489%\" colspan=\"2\" valign=\"bottom\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"6.906474820143885%\" valign=\"bottom\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"14.964028776978417%\" colspan=\"3\" valign=\"bottom\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"6.330935251798561%\" valign=\"bottom\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"1.1510791366906474%\" colspan=\"2\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"23.165467625899282%\" valign=\"bottom\"\u003e\n \u003cp\u003eBelow degree\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.625899280575539%\" valign=\"bottom\"\u003e\n \u003cp\u003e14.0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"4.028776978417266%\" valign=\"bottom\"\u003e\n \u003cp\u003e14\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.223021582733812%\" colspan=\"2\" valign=\"bottom\"\u003e\n \u003cp\u003e11.9\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.338129496402877%\" valign=\"bottom\"\u003e\n \u003cp\u003e11.8\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.618705035971223%\" valign=\"bottom\"\u003e\n \u003cp\u003e6\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.647482014388489%\" colspan=\"2\" valign=\"bottom\"\u003e\n \u003cp\u003e14.3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.906474820143885%\" valign=\"bottom\"\u003e\n \u003cp\u003e2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.964028776978417%\" colspan=\"3\" valign=\"bottom\"\u003e\n \u003cp\u003e17.1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.330935251798561%\" valign=\"bottom\"\u003e\n \u003cp\u003e6\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"1.1510791366906474%\" colspan=\"2\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"23.165467625899282%\" valign=\"bottom\"\u003e\n \u003cp\u003eDegree or higher\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.625899280575539%\" valign=\"bottom\"\u003e\n \u003cp\u003e86.0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"4.028776978417266%\" valign=\"bottom\"\u003e\n \u003cp\u003e86\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.223021582733812%\" colspan=\"2\" valign=\"bottom\"\u003e\n \u003cp\u003e11.4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.338129496402877%\" valign=\"bottom\"\u003e\n \u003cp\u003e88.2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.618705035971223%\" valign=\"bottom\"\u003e\n \u003cp\u003e45\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.647482014388489%\" colspan=\"2\" valign=\"bottom\"\u003e\n \u003cp\u003e85.7\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.906474820143885%\" valign=\"bottom\"\u003e\n \u003cp\u003e12\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.964028776978417%\" colspan=\"3\" valign=\"bottom\"\u003e\n \u003cp\u003e82.9\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.330935251798561%\" valign=\"bottom\"\u003e\n \u003cp\u003e29\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"1.1510791366906474%\" colspan=\"2\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"23.165467625899282%\" valign=\"bottom\"\u003e\n \u003cp\u003e\u003cstrong\u003eEmployment\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.625899280575539%\" valign=\"bottom\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"4.028776978417266%\" valign=\"bottom\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"11.223021582733812%\" colspan=\"2\" valign=\"bottom\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"7.338129496402877%\" valign=\"bottom\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"6.618705035971223%\" valign=\"bottom\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"10.647482014388489%\" colspan=\"2\" valign=\"bottom\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"6.906474820143885%\" valign=\"bottom\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"14.964028776978417%\" colspan=\"3\" valign=\"bottom\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"6.330935251798561%\" valign=\"bottom\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"1.1510791366906474%\" colspan=\"2\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"23.165467625899282%\" valign=\"bottom\"\u003e\n \u003cp\u003eUnemployed\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.625899280575539%\" valign=\"bottom\"\u003e\n \u003cp\u003e20.0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"4.028776978417266%\" valign=\"bottom\"\u003e\n \u003cp\u003e20\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.223021582733812%\" colspan=\"2\" valign=\"bottom\"\u003e\n \u003cp\u003e10.9\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.338129496402877%\" valign=\"bottom\"\u003e\n \u003cp\u003e23.5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.618705035971223%\" valign=\"bottom\"\u003e\n \u003cp\u003e12\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.647482014388489%\" colspan=\"2\" valign=\"bottom\"\u003e\n \u003cp\u003e7.1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.906474820143885%\" valign=\"bottom\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.964028776978417%\" colspan=\"3\" valign=\"bottom\"\u003e\n \u003cp\u003e20.0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.330935251798561%\" valign=\"bottom\"\u003e\n \u003cp\u003e7\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"1.1510791366906474%\" colspan=\"2\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"23.165467625899282%\" valign=\"bottom\"\u003e\n \u003cp\u003eEmployed\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.625899280575539%\" valign=\"bottom\"\u003e\n \u003cp\u003e80.0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"4.028776978417266%\" valign=\"bottom\"\u003e\n \u003cp\u003e80\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.223021582733812%\" colspan=\"2\" valign=\"bottom\"\u003e\n \u003cp\u003e11.6\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.338129496402877%\" valign=\"bottom\"\u003e\n \u003cp\u003e76.5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.618705035971223%\" valign=\"bottom\"\u003e\n \u003cp\u003e39\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.647482014388489%\" colspan=\"2\" valign=\"bottom\"\u003e\n \u003cp\u003e92.9\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.906474820143885%\" valign=\"bottom\"\u003e\n \u003cp\u003e13\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.964028776978417%\" colspan=\"3\" valign=\"bottom\"\u003e\n \u003cp\u003e80.0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.330935251798561%\" valign=\"bottom\"\u003e\n \u003cp\u003e28\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"1.1510791366906474%\" colspan=\"2\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"23.165467625899282%\" valign=\"bottom\"\u003e\n \u003cp\u003e\u003cstrong\u003eAnnual household income\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.625899280575539%\" valign=\"bottom\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"4.028776978417266%\" valign=\"bottom\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"11.223021582733812%\" colspan=\"2\" valign=\"bottom\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"7.338129496402877%\" valign=\"bottom\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"6.618705035971223%\" valign=\"bottom\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"10.647482014388489%\" colspan=\"2\" valign=\"bottom\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"6.906474820143885%\" valign=\"bottom\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"14.964028776978417%\" colspan=\"3\" valign=\"bottom\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"6.330935251798561%\" valign=\"bottom\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"1.1510791366906474%\" colspan=\"2\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"23.165467625899282%\" valign=\"bottom\"\u003e\n \u003cp\u003eUnder $52,000\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.625899280575539%\" valign=\"bottom\"\u003e\n \u003cp\u003e16.7\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"4.028776978417266%\" valign=\"bottom\"\u003e\n \u003cp\u003e14\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.223021582733812%\" colspan=\"2\" valign=\"bottom\"\u003e\n \u003cp\u003e13.4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.338129496402877%\" valign=\"bottom\"\u003e\n \u003cp\u003e9.5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.618705035971223%\" valign=\"bottom\"\u003e\n \u003cp\u003e4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.647482014388489%\" colspan=\"2\" valign=\"bottom\"\u003e\n \u003cp\u003e33.3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.906474820143885%\" valign=\"bottom\"\u003e\n \u003cp\u003e4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.964028776978417%\" colspan=\"3\" valign=\"bottom\"\u003e\n \u003cp\u003e20.0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.330935251798561%\" valign=\"bottom\"\u003e\n \u003cp\u003e6\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"1.1510791366906474%\" colspan=\"2\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"23.165467625899282%\" valign=\"bottom\"\u003e\n \u003cp\u003e$52,001-$104,000\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.625899280575539%\" valign=\"bottom\"\u003e\n \u003cp\u003e32.1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"4.028776978417266%\" valign=\"bottom\"\u003e\n \u003cp\u003e27\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.223021582733812%\" colspan=\"2\" valign=\"bottom\"\u003e\n \u003cp\u003e10.7\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.338129496402877%\" valign=\"bottom\"\u003e\n \u003cp\u003e35.7\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.618705035971223%\" valign=\"bottom\"\u003e\n \u003cp\u003e15\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.647482014388489%\" colspan=\"2\" valign=\"bottom\"\u003e\n \u003cp\u003e25.0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.906474820143885%\" valign=\"bottom\"\u003e\n \u003cp\u003e3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.964028776978417%\" colspan=\"3\" valign=\"bottom\"\u003e\n \u003cp\u003e30.0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.330935251798561%\" valign=\"bottom\"\u003e\n \u003cp\u003e9\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"1.1510791366906474%\" colspan=\"2\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"23.165467625899282%\" valign=\"bottom\"\u003e\n \u003cp\u003eOver $104,001\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.625899280575539%\" valign=\"bottom\"\u003e\n \u003cp\u003e51.2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"4.028776978417266%\" valign=\"bottom\"\u003e\n \u003cp\u003e43\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.223021582733812%\" colspan=\"2\" valign=\"bottom\"\u003e\n \u003cp\u003e11.5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.338129496402877%\" valign=\"bottom\"\u003e\n \u003cp\u003e54.8\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.618705035971223%\" valign=\"bottom\"\u003e\n \u003cp\u003e23\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.647482014388489%\" colspan=\"2\" valign=\"bottom\"\u003e\n \u003cp\u003e41.7\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.906474820143885%\" valign=\"bottom\"\u003e\n \u003cp\u003e5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.964028776978417%\" colspan=\"3\" valign=\"bottom\"\u003e\n \u003cp\u003e50.0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.330935251798561%\" valign=\"bottom\"\u003e\n \u003cp\u003e15\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"1.1510791366906474%\" colspan=\"2\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"23.165467625899282%\" valign=\"bottom\"\u003e\n \u003cp\u003e\u003cstrong\u003eHousing tenure\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.625899280575539%\" valign=\"bottom\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"4.028776978417266%\" valign=\"bottom\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"11.223021582733812%\" colspan=\"2\" valign=\"bottom\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"7.338129496402877%\" valign=\"bottom\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"6.618705035971223%\" valign=\"bottom\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"10.647482014388489%\" colspan=\"2\" valign=\"bottom\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"6.906474820143885%\" valign=\"bottom\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"14.964028776978417%\" colspan=\"3\" valign=\"bottom\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"6.330935251798561%\" valign=\"bottom\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"1.1510791366906474%\" colspan=\"2\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"23.165467625899282%\" valign=\"bottom\"\u003e\n \u003cp\u003eRenter\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.625899280575539%\" valign=\"bottom\"\u003e\n \u003cp\u003e54.0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"4.028776978417266%\" valign=\"bottom\"\u003e\n \u003cp\u003e54\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.223021582733812%\" colspan=\"2\" valign=\"bottom\"\u003e\n \u003cp\u003e11.3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.338129496402877%\" valign=\"bottom\"\u003e\n \u003cp\u003e54.9\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.618705035971223%\" valign=\"bottom\"\u003e\n \u003cp\u003e28\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.647482014388489%\" colspan=\"2\" valign=\"bottom\"\u003e\n \u003cp\u003e64.3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.906474820143885%\" valign=\"bottom\"\u003e\n \u003cp\u003e9\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.964028776978417%\" colspan=\"3\" valign=\"bottom\"\u003e\n \u003cp\u003e48.6\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.330935251798561%\" valign=\"bottom\"\u003e\n \u003cp\u003e17\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"1.1510791366906474%\" colspan=\"2\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"23.165467625899282%\" valign=\"bottom\"\u003e\n \u003cp\u003eOwner\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.625899280575539%\" valign=\"bottom\"\u003e\n \u003cp\u003e46.0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"4.028776978417266%\" valign=\"bottom\"\u003e\n \u003cp\u003e46\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.223021582733812%\" colspan=\"2\" valign=\"bottom\"\u003e\n \u003cp\u003e11.6\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.338129496402877%\" valign=\"bottom\"\u003e\n \u003cp\u003e45.1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.618705035971223%\" valign=\"bottom\"\u003e\n \u003cp\u003e23\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.647482014388489%\" colspan=\"2\" valign=\"bottom\"\u003e\n \u003cp\u003e35.7\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.906474820143885%\" valign=\"bottom\"\u003e\n \u003cp\u003e5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.964028776978417%\" colspan=\"3\" valign=\"bottom\"\u003e\n \u003cp\u003e51.4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.330935251798561%\" valign=\"bottom\"\u003e\n \u003cp\u003e18\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"1.1510791366906474%\" colspan=\"2\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"23.165467625899282%\" valign=\"bottom\"\u003e\n \u003cp\u003e\u003cstrong\u003eMajor structural issues\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.625899280575539%\" valign=\"bottom\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"4.028776978417266%\" valign=\"bottom\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"11.223021582733812%\" colspan=\"2\" valign=\"bottom\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"7.338129496402877%\" valign=\"bottom\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"6.618705035971223%\" valign=\"bottom\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"10.647482014388489%\" colspan=\"2\" valign=\"bottom\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"6.906474820143885%\" valign=\"bottom\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"14.964028776978417%\" colspan=\"3\" valign=\"bottom\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"6.330935251798561%\" valign=\"bottom\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"1.1510791366906474%\" colspan=\"2\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"23.165467625899282%\" valign=\"bottom\"\u003e\n \u003cp\u003eMajor cracks in walls/floors\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.625899280575539%\" valign=\"bottom\"\u003e\n \u003cp\u003e28.0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"4.028776978417266%\" valign=\"bottom\"\u003e\n \u003cp\u003e28\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.223021582733812%\" colspan=\"2\" valign=\"bottom\"\u003e\n \u003cp\u003e13.6\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.338129496402877%\" valign=\"bottom\"\u003e\n \u003cp\u003e23.5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.618705035971223%\" valign=\"bottom\"\u003e\n \u003cp\u003e12\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.647482014388489%\" colspan=\"2\" valign=\"bottom\"\u003e\n \u003cp\u003e35.7\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.906474820143885%\" valign=\"bottom\"\u003e\n \u003cp\u003e5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.964028776978417%\" colspan=\"3\" valign=\"bottom\"\u003e\n \u003cp\u003e31.4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.330935251798561%\" valign=\"bottom\"\u003e\n \u003cp\u003e11\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"1.1510791366906474%\" colspan=\"2\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"23.165467625899282%\" valign=\"bottom\"\u003e\n \u003cp\u003eSinking/moving foundations\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.625899280575539%\" valign=\"bottom\"\u003e\n \u003cp\u003e19.0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"4.028776978417266%\" valign=\"bottom\"\u003e\n \u003cp\u003e19\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.223021582733812%\" colspan=\"2\" valign=\"bottom\"\u003e\n \u003cp\u003e13.4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.338129496402877%\" valign=\"bottom\"\u003e\n \u003cp\u003e13.7\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.618705035971223%\" valign=\"bottom\"\u003e\n \u003cp\u003e7\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.647482014388489%\" colspan=\"2\" valign=\"bottom\"\u003e\n \u003cp\u003e21.4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.906474820143885%\" valign=\"bottom\"\u003e\n \u003cp\u003e3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.964028776978417%\" colspan=\"3\" valign=\"bottom\"\u003e\n \u003cp\u003e25.7\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.330935251798561%\" valign=\"bottom\"\u003e\n \u003cp\u003e9\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"1.1510791366906474%\" colspan=\"2\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"23.165467625899282%\" valign=\"bottom\"\u003e\n \u003cp\u003eWood rot/termite damage\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.625899280575539%\" valign=\"bottom\"\u003e\n \u003cp\u003e15.0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"4.028776978417266%\" valign=\"bottom\"\u003e\n \u003cp\u003e15\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.223021582733812%\" colspan=\"2\" valign=\"bottom\"\u003e\n \u003cp\u003e12.9\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.338129496402877%\" valign=\"bottom\"\u003e\n \u003cp\u003e9.8\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.618705035971223%\" valign=\"bottom\"\u003e\n \u003cp\u003e5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.647482014388489%\" colspan=\"2\" valign=\"bottom\"\u003e\n \u003cp\u003e21.4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.906474820143885%\" valign=\"bottom\"\u003e\n \u003cp\u003e3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.964028776978417%\" colspan=\"3\" valign=\"bottom\"\u003e\n \u003cp\u003e20.0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.330935251798561%\" valign=\"bottom\"\u003e\n \u003cp\u003e7\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"1.1510791366906474%\" colspan=\"2\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"23.165467625899282%\" valign=\"bottom\"\u003e\n \u003cp\u003eMajor plumbing problems\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.625899280575539%\" valign=\"bottom\"\u003e\n \u003cp\u003e6.0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"4.028776978417266%\" valign=\"bottom\"\u003e\n \u003cp\u003e6\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.223021582733812%\" colspan=\"2\" valign=\"bottom\"\u003e\n \u003cp\u003e17.0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.338129496402877%\" valign=\"bottom\"\u003e\n \u003cp\u003e2.0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.618705035971223%\" valign=\"bottom\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.647482014388489%\" colspan=\"2\" valign=\"bottom\"\u003e\n \u003cp\u003e14.3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.906474820143885%\" valign=\"bottom\"\u003e\n \u003cp\u003e2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.964028776978417%\" colspan=\"3\" valign=\"bottom\"\u003e\n \u003cp\u003e8.6\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.330935251798561%\" valign=\"bottom\"\u003e\n \u003cp\u003e3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"1.1510791366906474%\" colspan=\"2\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"23.165467625899282%\" valign=\"bottom\"\u003e\n \u003cp\u003eWalls/windows not level\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.625899280575539%\" valign=\"bottom\"\u003e\n \u003cp\u003e25.0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"4.028776978417266%\" valign=\"bottom\"\u003e\n \u003cp\u003e25\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.223021582733812%\" colspan=\"2\" valign=\"bottom\"\u003e\n \u003cp\u003e11.8\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.338129496402877%\" valign=\"bottom\"\u003e\n \u003cp\u003e19.6\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.618705035971223%\" valign=\"bottom\"\u003e\n \u003cp\u003e10\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.647482014388489%\" colspan=\"2\" valign=\"bottom\"\u003e\n \u003cp\u003e35.7\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.906474820143885%\" valign=\"bottom\"\u003e\n \u003cp\u003e5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.964028776978417%\" colspan=\"3\" valign=\"bottom\"\u003e\n \u003cp\u003e28.6\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.330935251798561%\" valign=\"bottom\"\u003e\n \u003cp\u003e10\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"1.1510791366906474%\" colspan=\"2\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"23.165467625899282%\" valign=\"bottom\"\u003e\n \u003cp\u003eMajor roof defect\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.625899280575539%\" valign=\"bottom\"\u003e\n \u003cp\u003e13.0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"4.028776978417266%\" valign=\"bottom\"\u003e\n \u003cp\u003e13\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.223021582733812%\" colspan=\"2\" valign=\"bottom\"\u003e\n \u003cp\u003e13.7\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.338129496402877%\" valign=\"bottom\"\u003e\n \u003cp\u003e9.8\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.618705035971223%\" valign=\"bottom\"\u003e\n \u003cp\u003e5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.647482014388489%\" colspan=\"2\" valign=\"bottom\"\u003e\n \u003cp\u003e14.3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.906474820143885%\" valign=\"bottom\"\u003e\n \u003cp\u003e2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.964028776978417%\" colspan=\"3\" valign=\"bottom\"\u003e\n \u003cp\u003e17.1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.330935251798561%\" valign=\"bottom\"\u003e\n \u003cp\u003e6\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"1.1510791366906474%\" colspan=\"2\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"23.165467625899282%\" valign=\"bottom\"\u003e\n \u003cp\u003e\u003cstrong\u003eInsulation\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.625899280575539%\" valign=\"bottom\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"4.028776978417266%\" valign=\"bottom\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"11.223021582733812%\" colspan=\"2\" valign=\"bottom\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"7.338129496402877%\" valign=\"bottom\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"6.618705035971223%\" valign=\"bottom\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"10.647482014388489%\" colspan=\"2\" valign=\"bottom\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"6.906474820143885%\" valign=\"bottom\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"14.964028776978417%\" colspan=\"3\" valign=\"bottom\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"6.330935251798561%\" valign=\"bottom\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"1.1510791366906474%\" colspan=\"2\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"23.165467625899282%\" valign=\"bottom\"\u003e\n \u003cp\u003ePoorly insulated\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.625899280575539%\" valign=\"bottom\"\u003e\n \u003cp\u003e73.0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"4.028776978417266%\" valign=\"bottom\"\u003e\n \u003cp\u003e61\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.223021582733812%\" colspan=\"2\" valign=\"bottom\"\u003e\n \u003cp\u003e12.8\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.338129496402877%\" valign=\"bottom\"\u003e\n \u003cp\u003e69.0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.618705035971223%\" valign=\"bottom\"\u003e\n \u003cp\u003e29\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.647482014388489%\" colspan=\"2\" valign=\"bottom\"\u003e\n \u003cp\u003e72.7\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.906474820143885%\" valign=\"bottom\"\u003e\n \u003cp\u003e8\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.964028776978417%\" colspan=\"3\" valign=\"bottom\"\u003e\n \u003cp\u003e77.4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.330935251798561%\" valign=\"bottom\"\u003e\n \u003cp\u003e24\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"1.1510791366906474%\" colspan=\"2\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"23.165467625899282%\" valign=\"bottom\"\u003e\n \u003cp\u003eWell insulated\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.625899280575539%\" valign=\"bottom\"\u003e\n \u003cp\u003e27.0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"4.028776978417266%\" valign=\"bottom\"\u003e\n \u003cp\u003e23\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.223021582733812%\" colspan=\"2\" valign=\"bottom\"\u003e\n \u003cp\u003e9.8\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.338129496402877%\" valign=\"bottom\"\u003e\n \u003cp\u003e31.0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.618705035971223%\" valign=\"bottom\"\u003e\n \u003cp\u003e13\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.647482014388489%\" colspan=\"2\" valign=\"bottom\"\u003e\n \u003cp\u003e27.3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.906474820143885%\" valign=\"bottom\"\u003e\n \u003cp\u003e3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.964028776978417%\" colspan=\"3\" valign=\"bottom\"\u003e\n \u003cp\u003e22.6\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.330935251798561%\" valign=\"bottom\"\u003e\n \u003cp\u003e7\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"1.1510791366906474%\" colspan=\"2\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"23.165467625899282%\" valign=\"bottom\"\u003e\n \u003cp\u003e\u003cstrong\u003eDwelling type\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.625899280575539%\" valign=\"bottom\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"4.028776978417266%\" valign=\"bottom\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"11.223021582733812%\" colspan=\"2\" valign=\"bottom\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"7.338129496402877%\" valign=\"bottom\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"6.618705035971223%\" valign=\"bottom\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"10.647482014388489%\" colspan=\"2\" valign=\"bottom\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"6.906474820143885%\" valign=\"bottom\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"14.964028776978417%\" colspan=\"3\" valign=\"bottom\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"6.330935251798561%\" valign=\"bottom\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"1.1510791366906474%\" colspan=\"2\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"23.165467625899282%\" valign=\"bottom\"\u003e\n \u003cp\u003eFlat/unit/apartment\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.625899280575539%\" valign=\"bottom\"\u003e\n \u003cp\u003e39.0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"4.028776978417266%\" valign=\"bottom\"\u003e\n \u003cp\u003e39\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.223021582733812%\" colspan=\"2\" valign=\"bottom\"\u003e\n \u003cp\u003e9.4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.338129496402877%\" valign=\"bottom\"\u003e\n \u003cp\u003e45.1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.618705035971223%\" valign=\"bottom\"\u003e\n \u003cp\u003e23\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.647482014388489%\" colspan=\"2\" valign=\"bottom\"\u003e\n \u003cp\u003e57.1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.906474820143885%\" valign=\"bottom\"\u003e\n \u003cp\u003e8\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.964028776978417%\" colspan=\"3\" valign=\"bottom\"\u003e\n \u003cp\u003e22.9\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.330935251798561%\" valign=\"bottom\"\u003e\n \u003cp\u003e8\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"1.1510791366906474%\" colspan=\"2\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"23.165467625899282%\" valign=\"bottom\"\u003e\n \u003cp\u003eHouse\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.625899280575539%\" valign=\"bottom\"\u003e\n \u003cp\u003e61.0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"4.028776978417266%\" valign=\"bottom\"\u003e\n \u003cp\u003e61\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.223021582733812%\" colspan=\"2\" valign=\"bottom\"\u003e\n \u003cp\u003e12.8\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.338129496402877%\" valign=\"bottom\"\u003e\n \u003cp\u003e54.9\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.618705035971223%\" valign=\"bottom\"\u003e\n \u003cp\u003e28\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.647482014388489%\" colspan=\"2\" valign=\"bottom\"\u003e\n \u003cp\u003e42.9\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.906474820143885%\" valign=\"bottom\"\u003e\n \u003cp\u003e6\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.964028776978417%\" colspan=\"3\" valign=\"bottom\"\u003e\n \u003cp\u003e77.1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.330935251798561%\" valign=\"bottom\"\u003e\n \u003cp\u003e27\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"1.1510791366906474%\" colspan=\"2\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"23.165467625899282%\" valign=\"bottom\"\u003e\n \u003cp\u003e\u003cstrong\u003eAllergies\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.625899280575539%\" valign=\"bottom\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"4.028776978417266%\" valign=\"bottom\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"11.223021582733812%\" colspan=\"2\" valign=\"bottom\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"7.338129496402877%\" valign=\"bottom\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"6.618705035971223%\" valign=\"bottom\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"10.647482014388489%\" colspan=\"2\" valign=\"bottom\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"6.906474820143885%\" valign=\"bottom\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"14.964028776978417%\" colspan=\"3\" valign=\"bottom\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"6.330935251798561%\" valign=\"bottom\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"1.1510791366906474%\" colspan=\"2\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"23.165467625899282%\" valign=\"bottom\"\u003e\n \u003cp\u003eNo\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.625899280575539%\" valign=\"bottom\"\u003e\n \u003cp\u003e50.0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"4.028776978417266%\" valign=\"bottom\"\u003e\n \u003cp\u003e50\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.223021582733812%\" colspan=\"2\" valign=\"bottom\"\u003e\n \u003cp\u003e10.1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.338129496402877%\" valign=\"bottom\"\u003e\n \u003cp\u003e54.9\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.618705035971223%\" valign=\"bottom\"\u003e\n \u003cp\u003e28\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.647482014388489%\" colspan=\"2\" valign=\"bottom\"\u003e\n \u003cp\u003e57.1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.906474820143885%\" valign=\"bottom\"\u003e\n \u003cp\u003e8\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.964028776978417%\" colspan=\"3\" valign=\"bottom\"\u003e\n \u003cp\u003e40.0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.330935251798561%\" valign=\"bottom\"\u003e\n \u003cp\u003e14\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"1.1510791366906474%\" colspan=\"2\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"23.165467625899282%\" valign=\"bottom\"\u003e\n \u003cp\u003eYes\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.625899280575539%\" valign=\"bottom\"\u003e\n \u003cp\u003e50.0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"4.028776978417266%\" valign=\"bottom\"\u003e\n \u003cp\u003e50\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.223021582733812%\" colspan=\"2\" valign=\"bottom\"\u003e\n \u003cp\u003e12.8\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.338129496402877%\" valign=\"bottom\"\u003e\n \u003cp\u003e45.1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.618705035971223%\" valign=\"bottom\"\u003e\n \u003cp\u003e23\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.647482014388489%\" colspan=\"2\" valign=\"bottom\"\u003e\n \u003cp\u003e42.9\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.906474820143885%\" valign=\"bottom\"\u003e\n \u003cp\u003e6\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.964028776978417%\" colspan=\"3\" valign=\"bottom\"\u003e\n \u003cp\u003e60.0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.330935251798561%\" valign=\"bottom\"\u003e\n \u003cp\u003e21\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"1.1510791366906474%\" colspan=\"2\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"23.165467625899282%\" valign=\"bottom\"\u003e\n \u003cp\u003e\u003cstrong\u003eAsthma\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.625899280575539%\" valign=\"bottom\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"4.028776978417266%\" valign=\"bottom\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"11.223021582733812%\" colspan=\"2\" valign=\"bottom\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"7.338129496402877%\" valign=\"bottom\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"6.618705035971223%\" valign=\"bottom\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"10.647482014388489%\" colspan=\"2\" valign=\"bottom\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"6.906474820143885%\" valign=\"bottom\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"14.964028776978417%\" colspan=\"3\" valign=\"bottom\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"6.330935251798561%\" valign=\"bottom\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"1.1510791366906474%\" colspan=\"2\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"23.165467625899282%\" valign=\"bottom\"\u003e\n \u003cp\u003eNo\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.625899280575539%\" valign=\"bottom\"\u003e\n \u003cp\u003e77.0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"4.028776978417266%\" valign=\"bottom\"\u003e\n \u003cp\u003e77\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.223021582733812%\" colspan=\"2\" valign=\"bottom\"\u003e\n \u003cp\u003e12.0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.338129496402877%\" valign=\"bottom\"\u003e\n \u003cp\u003e72.6\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.618705035971223%\" valign=\"bottom\"\u003e\n \u003cp\u003e37\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.647482014388489%\" colspan=\"2\" valign=\"bottom\"\u003e\n \u003cp\u003e71.4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.906474820143885%\" valign=\"bottom\"\u003e\n \u003cp\u003e10\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.964028776978417%\" colspan=\"3\" valign=\"bottom\"\u003e\n \u003cp\u003e85.7\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.330935251798561%\" valign=\"bottom\"\u003e\n \u003cp\u003e30\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"1.1510791366906474%\" colspan=\"2\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"23.165467625899282%\" valign=\"bottom\"\u003e\n \u003cp\u003eYes\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.625899280575539%\" valign=\"bottom\"\u003e\n \u003cp\u003e23.0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"4.028776978417266%\" valign=\"bottom\"\u003e\n \u003cp\u003e23\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.223021582733812%\" colspan=\"2\" valign=\"bottom\"\u003e\n \u003cp\u003e9.5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.338129496402877%\" valign=\"bottom\"\u003e\n \u003cp\u003e27.5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.618705035971223%\" valign=\"bottom\"\u003e\n \u003cp\u003e14\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.647482014388489%\" colspan=\"2\" valign=\"bottom\"\u003e\n \u003cp\u003e28.6\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.906474820143885%\" valign=\"bottom\"\u003e\n \u003cp\u003e4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.964028776978417%\" colspan=\"3\" valign=\"bottom\"\u003e\n \u003cp\u003e14.3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.330935251798561%\" valign=\"bottom\"\u003e\n \u003cp\u003e5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"1.1510791366906474%\" colspan=\"2\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"23.165467625899282%\" valign=\"bottom\"\u003e\n \u003cp\u003e\u003cstrong\u003eResidential location\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.625899280575539%\" valign=\"bottom\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"4.028776978417266%\" valign=\"bottom\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"11.223021582733812%\" colspan=\"2\" valign=\"bottom\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"7.338129496402877%\" valign=\"bottom\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"6.618705035971223%\" valign=\"bottom\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"10.647482014388489%\" colspan=\"2\" valign=\"bottom\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"6.906474820143885%\" valign=\"bottom\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"14.964028776978417%\" colspan=\"3\" valign=\"bottom\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"6.330935251798561%\" valign=\"bottom\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"1.1510791366906474%\" colspan=\"2\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"23.165467625899282%\" valign=\"bottom\"\u003e\n \u003cp\u003eVIC\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.625899280575539%\" valign=\"bottom\"\u003e\n \u003cp\u003e65.0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"4.028776978417266%\" valign=\"bottom\"\u003e\n \u003cp\u003e65\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.223021582733812%\" colspan=\"2\" valign=\"bottom\"\u003e\n \u003cp\u003e9.1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.338129496402877%\" valign=\"bottom\"\u003e\n \u003cp\u003e80.4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.618705035971223%\" valign=\"bottom\"\u003e\n \u003cp\u003e41\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.647482014388489%\" colspan=\"2\" valign=\"bottom\"\u003e\n \u003cp\u003e71.4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.906474820143885%\" valign=\"bottom\"\u003e\n \u003cp\u003e10\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.964028776978417%\" colspan=\"3\" valign=\"bottom\"\u003e\n \u003cp\u003e40.0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.330935251798561%\" valign=\"bottom\"\u003e\n \u003cp\u003e14\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"1.1510791366906474%\" colspan=\"2\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"23.165467625899282%\" valign=\"bottom\"\u003e\n \u003cp\u003eNSW\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.625899280575539%\" valign=\"bottom\"\u003e\n \u003cp\u003e35.0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"4.028776978417266%\" valign=\"bottom\"\u003e\n \u003cp\u003e35\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.223021582733812%\" colspan=\"2\" valign=\"bottom\"\u003e\n \u003cp\u003e15.8\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.338129496402877%\" valign=\"bottom\"\u003e\n \u003cp\u003e19.6\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.618705035971223%\" valign=\"bottom\"\u003e\n \u003cp\u003e10\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.647482014388489%\" colspan=\"2\" valign=\"bottom\"\u003e\n \u003cp\u003e28.6\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.906474820143885%\" valign=\"bottom\"\u003e\n \u003cp\u003e4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.964028776978417%\" colspan=\"3\" valign=\"bottom\"\u003e\n \u003cp\u003e60.0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.330935251798561%\" valign=\"bottom\"\u003e\n \u003cp\u003e21\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"1.1510791366906474%\" colspan=\"2\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"23.165467625899282%\" valign=\"bottom\"\u003e\n \u003cp\u003e\u003cstrong\u003eSelf-report mould measures\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.625899280575539%\" valign=\"bottom\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"4.028776978417266%\" valign=\"bottom\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"11.223021582733812%\" colspan=\"2\" valign=\"bottom\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"7.338129496402877%\" valign=\"bottom\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"6.618705035971223%\" valign=\"bottom\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"10.647482014388489%\" colspan=\"2\" valign=\"bottom\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"6.906474820143885%\" valign=\"bottom\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"14.964028776978417%\" colspan=\"3\" valign=\"bottom\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"6.330935251798561%\" valign=\"bottom\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"1.1510791366906474%\" colspan=\"2\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"23.165467625899282%\" valign=\"bottom\"\u003e\n \u003cp\u003eMould visibility\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.625899280575539%\" valign=\"bottom\"\u003e\n \u003cp\u003e61.0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"4.028776978417266%\" valign=\"bottom\"\u003e\n \u003cp\u003e61\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.223021582733812%\" colspan=\"2\" valign=\"bottom\"\u003e\n \u003cp\u003e13.7\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.338129496402877%\" valign=\"bottom\"\u003e\n \u003cp\u003e49.0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.618705035971223%\" valign=\"bottom\"\u003e\n \u003cp\u003e25\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.647482014388489%\" colspan=\"2\" valign=\"bottom\"\u003e\n \u003cp\u003e71.4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.906474820143885%\" valign=\"bottom\"\u003e\n \u003cp\u003e10\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.964028776978417%\" colspan=\"3\" valign=\"bottom\"\u003e\n \u003cp\u003e74.3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.330935251798561%\" valign=\"bottom\"\u003e\n \u003cp\u003e26\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"1.1510791366906474%\" colspan=\"2\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"23.165467625899282%\" valign=\"bottom\"\u003e\n \u003cp\u003eMould size\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.625899280575539%\" valign=\"bottom\"\u003e\n \u003cp\u003e21.0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"4.028776978417266%\" valign=\"bottom\"\u003e\n \u003cp\u003e21\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.223021582733812%\" colspan=\"2\" valign=\"bottom\"\u003e\n \u003cp\u003e11.9\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.338129496402877%\" valign=\"bottom\"\u003e\n \u003cp\u003e21.6\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.618705035971223%\" valign=\"bottom\"\u003e\n \u003cp\u003e11\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.647482014388489%\" colspan=\"2\" valign=\"bottom\"\u003e\n \u003cp\u003e28.6\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.906474820143885%\" valign=\"bottom\"\u003e\n \u003cp\u003e4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.964028776978417%\" colspan=\"3\" valign=\"bottom\"\u003e\n \u003cp\u003e17.1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.330935251798561%\" valign=\"bottom\"\u003e\n \u003cp\u003e6\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"1.1510791366906474%\" colspan=\"2\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"23.165467625899282%\" valign=\"bottom\"\u003e\n \u003cp\u003eMould odour\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.625899280575539%\" valign=\"bottom\"\u003e\n \u003cp\u003e39.0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"4.028776978417266%\" valign=\"bottom\"\u003e\n \u003cp\u003e39\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.223021582733812%\" colspan=\"2\" valign=\"bottom\"\u003e\n \u003cp\u003e11.7\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.338129496402877%\" valign=\"bottom\"\u003e\n \u003cp\u003e35.3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.618705035971223%\" valign=\"bottom\"\u003e\n \u003cp\u003e18\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.647482014388489%\" colspan=\"2\" valign=\"bottom\"\u003e\n \u003cp\u003e42.9\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.906474820143885%\" valign=\"bottom\"\u003e\n \u003cp\u003e6\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.964028776978417%\" colspan=\"3\" valign=\"bottom\"\u003e\n \u003cp\u003e42.9\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.330935251798561%\" valign=\"bottom\"\u003e\n \u003cp\u003e15\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"1.1510791366906474%\" colspan=\"2\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"23.165467625899282%\" valign=\"bottom\"\u003e\n \u003cp\u003eDampness\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.625899280575539%\" valign=\"bottom\"\u003e\n \u003cp\u003e32.0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"4.028776978417266%\" valign=\"bottom\"\u003e\n \u003cp\u003e32\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.223021582733812%\" colspan=\"2\" valign=\"bottom\"\u003e\n \u003cp\u003e12.3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.338129496402877%\" valign=\"bottom\"\u003e\n \u003cp\u003e29.4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.618705035971223%\" valign=\"bottom\"\u003e\n \u003cp\u003e15\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.647482014388489%\" colspan=\"2\" valign=\"bottom\"\u003e\n \u003cp\u003e35.7\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.906474820143885%\" valign=\"bottom\"\u003e\n \u003cp\u003e5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.964028776978417%\" colspan=\"3\" valign=\"bottom\"\u003e\n \u003cp\u003e34.3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.330935251798561%\" valign=\"bottom\"\u003e\n \u003cp\u003e12\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"1.1510791366906474%\" colspan=\"2\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"23.165467625899282%\" valign=\"bottom\"\u003e\n \u003cp\u003eWater damage\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.625899280575539%\" valign=\"bottom\"\u003e\n \u003cp\u003e27.0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"4.028776978417266%\" valign=\"bottom\"\u003e\n \u003cp\u003e27\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.223021582733812%\" colspan=\"2\" valign=\"bottom\"\u003e\n \u003cp\u003e13.0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.338129496402877%\" valign=\"bottom\"\u003e\n \u003cp\u003e23.5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.618705035971223%\" valign=\"bottom\"\u003e\n \u003cp\u003e12\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.647482014388489%\" colspan=\"2\" valign=\"bottom\"\u003e\n \u003cp\u003e42.9\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.906474820143885%\" valign=\"bottom\"\u003e\n \u003cp\u003e6\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.964028776978417%\" colspan=\"3\" valign=\"bottom\"\u003e\n \u003cp\u003e25.7\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.330935251798561%\" valign=\"bottom\"\u003e\n \u003cp\u003e9\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"1.1510791366906474%\" colspan=\"2\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"23.165467625899282%\" valign=\"bottom\"\u003e\n \u003cp\u003eSuspicion of invisible mould\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.625899280575539%\" valign=\"bottom\"\u003e\n \u003cp\u003e61.0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"4.028776978417266%\" valign=\"bottom\"\u003e\n \u003cp\u003e61\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.223021582733812%\" colspan=\"2\" valign=\"bottom\"\u003e\n \u003cp\u003e12.9\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.338129496402877%\" valign=\"bottom\"\u003e\n \u003cp\u003e49.0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.618705035971223%\" valign=\"bottom\"\u003e\n \u003cp\u003e25\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.647482014388489%\" colspan=\"2\" valign=\"bottom\"\u003e\n \u003cp\u003e78.6\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.906474820143885%\" valign=\"bottom\"\u003e\n \u003cp\u003e11\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.964028776978417%\" colspan=\"3\" valign=\"bottom\"\u003e\n \u003cp\u003e71.4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.330935251798561%\" valign=\"bottom\"\u003e\n \u003cp\u003e25\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"1.1510791366906474%\" colspan=\"2\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"23.165467625899282%\" valign=\"bottom\"\u003e\n \u003cp\u003eMould severity\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.625899280575539%\" valign=\"bottom\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"4.028776978417266%\" valign=\"bottom\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"11.223021582733812%\" colspan=\"2\" valign=\"bottom\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"7.338129496402877%\" valign=\"bottom\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"6.618705035971223%\" valign=\"bottom\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"10.647482014388489%\" colspan=\"2\" valign=\"bottom\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"6.906474820143885%\" valign=\"bottom\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"14.964028776978417%\" colspan=\"3\" valign=\"bottom\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"6.330935251798561%\" valign=\"bottom\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"1.1510791366906474%\" colspan=\"2\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"23.165467625899282%\" valign=\"bottom\"\u003e\n \u003cp\u003eNo mould\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.625899280575539%\" valign=\"bottom\"\u003e\n \u003cp\u003e32.0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"4.028776978417266%\" valign=\"bottom\"\u003e\n \u003cp\u003e32\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.223021582733812%\" colspan=\"2\" valign=\"bottom\"\u003e\n \u003cp\u003e7.7\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.338129496402877%\" valign=\"bottom\"\u003e\n \u003cp\u003e43.1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.618705035971223%\" valign=\"bottom\"\u003e\n \u003cp\u003e22\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.647482014388489%\" colspan=\"2\" valign=\"bottom\"\u003e\n \u003cp\u003e28.6\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.906474820143885%\" valign=\"bottom\"\u003e\n \u003cp\u003e4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.964028776978417%\" colspan=\"3\" valign=\"bottom\"\u003e\n \u003cp\u003e17.1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.330935251798561%\" valign=\"bottom\"\u003e\n \u003cp\u003e6\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"1.1510791366906474%\" colspan=\"2\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"23.165467625899282%\" valign=\"bottom\"\u003e\n \u003cp\u003eMild mould\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.625899280575539%\" valign=\"bottom\"\u003e\n \u003cp\u003e45.0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"4.028776978417266%\" valign=\"bottom\"\u003e\n \u003cp\u003e45\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.223021582733812%\" colspan=\"2\" valign=\"bottom\"\u003e\n \u003cp\u003e13.7\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.338129496402877%\" valign=\"bottom\"\u003e\n \u003cp\u003e33.3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.618705035971223%\" valign=\"bottom\"\u003e\n \u003cp\u003e17\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.647482014388489%\" colspan=\"2\" valign=\"bottom\"\u003e\n \u003cp\u003e50.0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.906474820143885%\" valign=\"bottom\"\u003e\n \u003cp\u003e7\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.964028776978417%\" colspan=\"3\" valign=\"bottom\"\u003e\n \u003cp\u003e60.0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.330935251798561%\" valign=\"bottom\"\u003e\n \u003cp\u003e21\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"1.1510791366906474%\" colspan=\"2\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"23.165467625899282%\" valign=\"bottom\"\u003e\n \u003cp\u003eModerate Mould\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.625899280575539%\" valign=\"bottom\"\u003e\n \u003cp\u003e20.0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"4.028776978417266%\" valign=\"bottom\"\u003e\n \u003cp\u003e20\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.223021582733812%\" colspan=\"2\" valign=\"bottom\"\u003e\n \u003cp\u003e11.0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.338129496402877%\" valign=\"bottom\"\u003e\n \u003cp\u003e23.5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.618705035971223%\" valign=\"bottom\"\u003e\n \u003cp\u003e12\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.647482014388489%\" colspan=\"2\" valign=\"bottom\"\u003e\n \u003cp\u003e14.3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.906474820143885%\" valign=\"bottom\"\u003e\n \u003cp\u003e2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.964028776978417%\" colspan=\"3\" valign=\"bottom\"\u003e\n \u003cp\u003e17.1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.330935251798561%\" valign=\"bottom\"\u003e\n \u003cp\u003e6\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"1.1510791366906474%\" colspan=\"2\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"23.165467625899282%\" valign=\"bottom\"\u003e\n \u003cp\u003eSevere mould\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.625899280575539%\" valign=\"bottom\"\u003e\n \u003cp\u003e3.0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"4.028776978417266%\" valign=\"bottom\"\u003e\n \u003cp\u003e3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.223021582733812%\" colspan=\"2\" valign=\"bottom\"\u003e\n \u003cp\u003e20.0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.338129496402877%\" valign=\"bottom\"\u003e\n \u003cp\u003e0.0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.618705035971223%\" valign=\"bottom\"\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.647482014388489%\" colspan=\"2\" valign=\"bottom\"\u003e\n \u003cp\u003e7.1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.906474820143885%\" valign=\"bottom\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.964028776978417%\" colspan=\"3\" valign=\"bottom\"\u003e\n \u003cp\u003e5.7\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.330935251798561%\" valign=\"bottom\"\u003e\n \u003cp\u003e2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"1.1510791366906474%\" colspan=\"2\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003eTable 2.\u0026nbsp;Results on self-reported diagnoses of mould compared to lab tested mould status\u003c/p\u003e\n\u003ctable border=\"0\" cellspacing=\"0\" cellpadding=\"0\" width=\"832\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd width=\"29.567307692307693%\" valign=\"bottom\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"9.134615384615385%\" valign=\"bottom\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"61.29807692307692%\" colspan=\"8\" valign=\"top\"\u003e\n \u003cp\u003e(a) Abilities of self-reported mould measures to identify moderate/severe mould\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"29.461077844311376%\" valign=\"bottom\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"9.10179640718563%\" valign=\"bottom\"\u003e\n \u003cp\u003ePrevalence\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.10179640718563%\" valign=\"bottom\"\u003e\n \u003cp\u003eSensitivity\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.10179640718563%\" valign=\"bottom\"\u003e\n \u003cp\u003eSpecificity\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.10179640718563%\" valign=\"bottom\"\u003e\n \u003cp\u003ePositive predictive value\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.10179640718563%\" valign=\"bottom\"\u003e\n \u003cp\u003eNegative predictive value\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.10179640718563%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003eAgreement\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"2.2754491017964074%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.826347305389222%\" valign=\"bottom\"\u003e\n \u003cp\u003eKappa stats\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.826347305389222%\" valign=\"bottom\"\u003e\n \u003cp\u003eKappa P-value\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"29.461077844311376%\" valign=\"bottom\"\u003e\n \u003cp\u003eLab tested moderate/severe mould (HERTSMI2 Score\u0026ge;11)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.10179640718563%\" valign=\"bottom\"\u003e\n \u003cp\u003e49.0%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.10179640718563%\" valign=\"bottom\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"9.10179640718563%\" valign=\"bottom\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"9.10179640718563%\" valign=\"bottom\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"9.10179640718563%\" valign=\"bottom\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"9.10179640718563%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"2.2754491017964074%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.826347305389222%\" valign=\"bottom\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"6.826347305389222%\" valign=\"bottom\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"29.461077844311376%\" valign=\"bottom\"\u003e\n \u003cp\u003eSelf-reported visibility\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.10179640718563%\" valign=\"bottom\"\u003e\n \u003cp\u003e61.0%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.10179640718563%\" valign=\"bottom\"\u003e\n \u003cp\u003e73.5%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.10179640718563%\" valign=\"bottom\"\u003e\n \u003cp\u003e51.0%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.10179640718563%\" valign=\"bottom\"\u003e\n \u003cp\u003e59.0%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.10179640718563%\" valign=\"bottom\"\u003e\n \u003cp\u003e66.7%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.10179640718563%\" valign=\"top\"\u003e\n \u003cp\u003e62.00%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"2.2754491017964074%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.826347305389222%\" valign=\"bottom\"\u003e\n \u003cp\u003e\u003cstrong\u003e0.24\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.826347305389222%\" valign=\"bottom\"\u003e\n \u003cp\u003e0.01\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"29.461077844311376%\" valign=\"bottom\"\u003e\n \u003cp\u003eSelf-reported size\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.10179640718563%\" valign=\"bottom\"\u003e\n \u003cp\u003e21.0%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.10179640718563%\" valign=\"bottom\"\u003e\n \u003cp\u003e20.4%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.10179640718563%\" valign=\"bottom\"\u003e\n \u003cp\u003e78.4%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.10179640718563%\" valign=\"bottom\"\u003e\n \u003cp\u003e47.6%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.10179640718563%\" valign=\"bottom\"\u003e\n \u003cp\u003e50.6%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.10179640718563%\" valign=\"top\"\u003e\n \u003cp\u003e50.00%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"2.2754491017964074%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.826347305389222%\" valign=\"bottom\"\u003e\n \u003cp\u003e-0.01\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.826347305389222%\" valign=\"bottom\"\u003e\n \u003cp\u003e0.56\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"29.461077844311376%\" valign=\"bottom\"\u003e\n \u003cp\u003eSelf-reported odour\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.10179640718563%\" valign=\"bottom\"\u003e\n \u003cp\u003e39.0%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.10179640718563%\" valign=\"bottom\"\u003e\n \u003cp\u003e42.9%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.10179640718563%\" valign=\"bottom\"\u003e\n \u003cp\u003e64.7%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.10179640718563%\" valign=\"bottom\"\u003e\n \u003cp\u003e53.8%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.10179640718563%\" valign=\"bottom\"\u003e\n \u003cp\u003e54.1%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.10179640718563%\" valign=\"top\"\u003e\n \u003cp\u003e54.00%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"2.2754491017964074%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.826347305389222%\" valign=\"bottom\"\u003e\n \u003cp\u003e0.08\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.826347305389222%\" valign=\"bottom\"\u003e\n \u003cp\u003e0.22\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"29.461077844311376%\" valign=\"bottom\"\u003e\n \u003cp\u003eSelf-reported dampness\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.10179640718563%\" valign=\"bottom\"\u003e\n \u003cp\u003e32.0%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.10179640718563%\" valign=\"bottom\"\u003e\n \u003cp\u003e34.7%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.10179640718563%\" valign=\"bottom\"\u003e\n \u003cp\u003e70.6%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.10179640718563%\" valign=\"bottom\"\u003e\n \u003cp\u003e53.1%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.10179640718563%\" valign=\"bottom\"\u003e\n \u003cp\u003e52.9%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.10179640718563%\" valign=\"top\"\u003e\n \u003cp\u003e53.00%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"2.2754491017964074%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.826347305389222%\" valign=\"bottom\"\u003e\n \u003cp\u003e0.05\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.826347305389222%\" valign=\"bottom\"\u003e\n \u003cp\u003e0.29\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"29.461077844311376%\" valign=\"bottom\"\u003e\n \u003cp\u003eSelf-reported water damage\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.10179640718563%\" valign=\"bottom\"\u003e\n \u003cp\u003e27.0%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.10179640718563%\" valign=\"bottom\"\u003e\n \u003cp\u003e30.6%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.10179640718563%\" valign=\"bottom\"\u003e\n \u003cp\u003e76.5%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.10179640718563%\" valign=\"bottom\"\u003e\n \u003cp\u003e55.6%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.10179640718563%\" valign=\"bottom\"\u003e\n \u003cp\u003e53.4%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.10179640718563%\" valign=\"top\"\u003e\n \u003cp\u003e54.00%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"2.2754491017964074%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.826347305389222%\" valign=\"bottom\"\u003e\n \u003cp\u003e0.07\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.826347305389222%\" valign=\"bottom\"\u003e\n \u003cp\u003e0.21\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"29.461077844311376%\" valign=\"bottom\"\u003e\n \u003cp\u003eSelf-reported suspicion of invisible mould\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.10179640718563%\" valign=\"bottom\"\u003e\n \u003cp\u003e61.0%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.10179640718563%\" valign=\"bottom\"\u003e\n \u003cp\u003e73.5%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.10179640718563%\" valign=\"bottom\"\u003e\n \u003cp\u003e51.0%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.10179640718563%\" valign=\"bottom\"\u003e\n \u003cp\u003e59.0%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.10179640718563%\" valign=\"bottom\"\u003e\n \u003cp\u003e66.7%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.10179640718563%\" valign=\"top\"\u003e\n \u003cp\u003e62.00%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"2.2754491017964074%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.826347305389222%\" valign=\"bottom\"\u003e\n \u003cp\u003e\u003cstrong\u003e0.24\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.826347305389222%\" valign=\"bottom\"\u003e\n \u003cp\u003e0.01\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"29.567307692307693%\" valign=\"bottom\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"9.134615384615385%\" valign=\"bottom\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"61.29807692307692%\" colspan=\"8\" valign=\"top\"\u003e\n \u003cp\u003e(b) Abilities of self-reported mould measures to identify severe mould\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"29.461077844311376%\" valign=\"bottom\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"9.10179640718563%\" valign=\"bottom\"\u003e\n \u003cp\u003ePrevalence\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.10179640718563%\" valign=\"bottom\"\u003e\n \u003cp\u003eSensitivity\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.10179640718563%\" valign=\"bottom\"\u003e\n \u003cp\u003eSpecificity\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.10179640718563%\" valign=\"bottom\"\u003e\n \u003cp\u003ePositive predictive value\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.10179640718563%\" valign=\"bottom\"\u003e\n \u003cp\u003eNegative predictive value\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.10179640718563%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003eAgreement\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"2.2754491017964074%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.826347305389222%\" valign=\"bottom\"\u003e\n \u003cp\u003eKappa stats\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.826347305389222%\" valign=\"bottom\"\u003e\n \u003cp\u003eKappa P-value\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"29.461077844311376%\" valign=\"bottom\"\u003e\n \u003cp\u003eLab tested severe mould\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e(HERTSMI2 Score\u0026gt;15)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.10179640718563%\" valign=\"bottom\"\u003e\n \u003cp\u003e35.0%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.10179640718563%\" valign=\"bottom\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"9.10179640718563%\" valign=\"bottom\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"9.10179640718563%\" valign=\"bottom\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"9.10179640718563%\" valign=\"bottom\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"9.10179640718563%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"2.2754491017964074%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.826347305389222%\" valign=\"bottom\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"6.826347305389222%\" valign=\"bottom\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"29.461077844311376%\" valign=\"bottom\"\u003e\n \u003cp\u003eSelf-reported visibility\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.10179640718563%\" valign=\"bottom\"\u003e\n \u003cp\u003e61.0%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.10179640718563%\" valign=\"bottom\"\u003e\n \u003cp\u003e74.30%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.10179640718563%\" valign=\"bottom\"\u003e\n \u003cp\u003e46.20%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.10179640718563%\" valign=\"bottom\"\u003e\n \u003cp\u003e42.60%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.10179640718563%\" valign=\"bottom\"\u003e\n \u003cp\u003e76.90%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.10179640718563%\" valign=\"top\"\u003e\n \u003cp\u003e56.00%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"2.2754491017964074%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.826347305389222%\" valign=\"bottom\"\u003e\n \u003cp\u003e\u003cstrong\u003e0.17\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.826347305389222%\" valign=\"bottom\"\u003e\n \u003cp\u003e0.02\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"29.461077844311376%\" valign=\"bottom\"\u003e\n \u003cp\u003eSelf-reported size\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.10179640718563%\" valign=\"bottom\"\u003e\n \u003cp\u003e21.0%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.10179640718563%\" valign=\"bottom\"\u003e\n \u003cp\u003e17.10%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.10179640718563%\" valign=\"bottom\"\u003e\n \u003cp\u003e76.90%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.10179640718563%\" valign=\"bottom\"\u003e\n \u003cp\u003e28.60%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.10179640718563%\" valign=\"bottom\"\u003e\n \u003cp\u003e63.30%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.10179640718563%\" valign=\"top\"\u003e\n \u003cp\u003e56.00%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"2.2754491017964074%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.826347305389222%\" valign=\"bottom\"\u003e\n \u003cp\u003e-0.07\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.826347305389222%\" valign=\"bottom\"\u003e\n \u003cp\u003e0.76\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"29.461077844311376%\" valign=\"bottom\"\u003e\n \u003cp\u003eSelf-reported odour\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.10179640718563%\" valign=\"bottom\"\u003e\n \u003cp\u003e39.0%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.10179640718563%\" valign=\"bottom\"\u003e\n \u003cp\u003e42.90%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.10179640718563%\" valign=\"bottom\"\u003e\n \u003cp\u003e63.10%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.10179640718563%\" valign=\"bottom\"\u003e\n \u003cp\u003e38.50%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.10179640718563%\" valign=\"bottom\"\u003e\n \u003cp\u003e67.20%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.10179640718563%\" valign=\"top\"\u003e\n \u003cp\u003e56.00%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"2.2754491017964074%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.826347305389222%\" valign=\"bottom\"\u003e\n \u003cp\u003e0.06\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.826347305389222%\" valign=\"bottom\"\u003e\n \u003cp\u003e0.28\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"29.461077844311376%\" valign=\"bottom\"\u003e\n \u003cp\u003eSelf-reported dampness\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.10179640718563%\" valign=\"bottom\"\u003e\n \u003cp\u003e32.0%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.10179640718563%\" valign=\"bottom\"\u003e\n \u003cp\u003e34.30%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.10179640718563%\" valign=\"bottom\"\u003e\n \u003cp\u003e69.20%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.10179640718563%\" valign=\"bottom\"\u003e\n \u003cp\u003e37.50%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.10179640718563%\" valign=\"bottom\"\u003e\n \u003cp\u003e66.20%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.10179640718563%\" valign=\"top\"\u003e\n \u003cp\u003e57.00%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"2.2754491017964074%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.826347305389222%\" valign=\"bottom\"\u003e\n \u003cp\u003e0.04\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.826347305389222%\" valign=\"bottom\"\u003e\n \u003cp\u003e0.36\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"29.461077844311376%\" valign=\"bottom\"\u003e\n \u003cp\u003eSelf-reported water damage\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.10179640718563%\" valign=\"bottom\"\u003e\n \u003cp\u003e27.0%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.10179640718563%\" valign=\"bottom\"\u003e\n \u003cp\u003e25.70%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.10179640718563%\" valign=\"bottom\"\u003e\n \u003cp\u003e72.30%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.10179640718563%\" valign=\"bottom\"\u003e\n \u003cp\u003e33.30%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.10179640718563%\" valign=\"bottom\"\u003e\n \u003cp\u003e64.40%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.10179640718563%\" valign=\"top\"\u003e\n \u003cp\u003e56.00%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"2.2754491017964074%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.826347305389222%\" valign=\"bottom\"\u003e\n \u003cp\u003e-0.02\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.826347305389222%\" valign=\"bottom\"\u003e\n \u003cp\u003e0.58\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"29.461077844311376%\" valign=\"bottom\"\u003e\n \u003cp\u003eSelf-reported suspicion of invisible mould\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.10179640718563%\" valign=\"bottom\"\u003e\n \u003cp\u003e61.0%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.10179640718563%\" valign=\"bottom\"\u003e\n \u003cp\u003e71.40%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.10179640718563%\" valign=\"bottom\"\u003e\n \u003cp\u003e44.60%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.10179640718563%\" valign=\"bottom\"\u003e\n \u003cp\u003e41.0%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.10179640718563%\" valign=\"bottom\"\u003e\n \u003cp\u003e74.40%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.10179640718563%\" valign=\"top\"\u003e\n \u003cp\u003e54.00%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"2.2754491017964074%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.826347305389222%\" valign=\"bottom\"\u003e\n \u003cp\u003e\u003cstrong\u003e0.14\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.826347305389222%\" valign=\"bottom\"\u003e\n \u003cp\u003e0.06\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003eTable 3.\u0026nbsp;Results on the performance of combination of self-reported mould measures in predicting lab tested moderate/severe mould\u003c/p\u003e\n\u003ctable border=\"0\" cellspacing=\"0\" cellpadding=\"0\" width=\"849\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd width=\"37.80918727915194%\" valign=\"bottom\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"8.95170789163722%\" valign=\"bottom\"\u003e\n \u003cp\u003eAUC\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.843345111896348%\" colspan=\"2\" valign=\"bottom\"\u003e\n \u003cp\u003e95% CI\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"36.39575971731449%\" colspan=\"5\" valign=\"bottom\"\u003e\n \u003cp\u003eTest on equality of AUC (P-value)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"37.85377358490566%\" valign=\"bottom\"\u003e\n \u003cp\u003e\u003cstrong\u003eSingle self-reported measure\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.962264150943396%\" valign=\"bottom\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"6.839622641509434%\" valign=\"bottom\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"10.023584905660377%\" valign=\"bottom\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"7.783018867924528%\" valign=\"bottom\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"7.0754716981132075%\" valign=\"bottom\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"7.0754716981132075%\" valign=\"bottom\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"7.0754716981132075%\" valign=\"bottom\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"7.311320754716981%\" valign=\"bottom\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"37.85377358490566%\" valign=\"bottom\"\u003e\n \u003cp\u003eVisibility\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.962264150943396%\" valign=\"bottom\"\u003e\n \u003cp\u003e\u003cu\u003e0.622\u003c/u\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.839622641509434%\" valign=\"bottom\"\u003e\n \u003cp\u003e0.529\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.023584905660377%\" valign=\"bottom\"\u003e\n \u003cp\u003e0.716\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.783018867924528%\" valign=\"bottom\"\u003e\n \u003cp\u003eBaseline\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.0754716981132075%\" valign=\"bottom\"\u003e\n \u003cp\u003e0.280\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.0754716981132075%\" valign=\"bottom\"\u003e\n \u003cp\u003e0.368\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.0754716981132075%\" valign=\"bottom\"\u003e\n \u003cp\u003e0.347\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.311320754716981%\" valign=\"bottom\"\u003e\n \u003cp\u003e0.590\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"37.85377358490566%\" valign=\"bottom\"\u003e\n \u003cp\u003eSize\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.962264150943396%\" valign=\"bottom\"\u003e\n \u003cp\u003e0.494\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.839622641509434%\" valign=\"bottom\"\u003e\n \u003cp\u003e0.414\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.023584905660377%\" valign=\"bottom\"\u003e\n \u003cp\u003e0.575\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.783018867924528%\" valign=\"bottom\"\u003e\n \u003cp\u003e\u003cstrong\u003e0.010\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.0754716981132075%\" valign=\"bottom\"\u003e\n \u003cp\u003e\u003cstrong\u003e0.025\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.0754716981132075%\" valign=\"bottom\"\u003e\n \u003cp\u003e\u003cstrong\u003e0.028\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.0754716981132075%\" valign=\"bottom\"\u003e\n \u003cp\u003e\u003cstrong\u003e0.027\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.311320754716981%\" valign=\"bottom\"\u003e\n \u003cp\u003e\u003cstrong\u003e0.042\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"37.85377358490566%\" valign=\"bottom\"\u003e\n \u003cp\u003eOdour\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.962264150943396%\" valign=\"bottom\"\u003e\n \u003cp\u003e0.538\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.839622641509434%\" valign=\"bottom\"\u003e\n \u003cp\u003e0.441\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.023584905660377%\" valign=\"bottom\"\u003e\n \u003cp\u003e0.634\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.783018867924528%\" valign=\"bottom\"\u003e\n \u003cp\u003e0.132\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.0754716981132075%\" valign=\"bottom\"\u003e\n \u003cp\u003e\u003cstrong\u003e0.076\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.0754716981132075%\" valign=\"bottom\"\u003e\n \u003cp\u003e0.109\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.0754716981132075%\" valign=\"bottom\"\u003e\n \u003cp\u003e0.106\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.311320754716981%\" valign=\"bottom\"\u003e\n \u003cp\u003e0.101\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"37.85377358490566%\" valign=\"bottom\"\u003e\n \u003cp\u003eDampness\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.962264150943396%\" valign=\"bottom\"\u003e\n \u003cp\u003e0.526\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.839622641509434%\" valign=\"bottom\"\u003e\n \u003cp\u003e0.434\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.023584905660377%\" valign=\"bottom\"\u003e\n \u003cp\u003e0.619\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.783018867924528%\" valign=\"bottom\"\u003e\n \u003cp\u003e\u003cstrong\u003e0.072\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.0754716981132075%\" valign=\"bottom\"\u003e\n \u003cp\u003e\u003cstrong\u003e0.046\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.0754716981132075%\" valign=\"bottom\"\u003e\n \u003cp\u003e\u003cstrong\u003e0.092\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.0754716981132075%\" valign=\"bottom\"\u003e\n \u003cp\u003e\u003cstrong\u003e0.089\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.311320754716981%\" valign=\"bottom\"\u003e\n \u003cp\u003e0.105\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"37.85377358490566%\" valign=\"bottom\"\u003e\n \u003cp\u003eWater damage\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.962264150943396%\" valign=\"bottom\"\u003e\n \u003cp\u003e0.535\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.839622641509434%\" valign=\"bottom\"\u003e\n \u003cp\u003e0.448\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.023584905660377%\" valign=\"bottom\"\u003e\n \u003cp\u003e0.623\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.783018867924528%\" valign=\"bottom\"\u003e\n \u003cp\u003e\u003cstrong\u003e0.090\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.0754716981132075%\" valign=\"bottom\"\u003e\n \u003cp\u003e\u003cstrong\u003e0.064\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.0754716981132075%\" valign=\"bottom\"\u003e\n \u003cp\u003e\u003cstrong\u003e0.087\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.0754716981132075%\" valign=\"bottom\"\u003e\n \u003cp\u003e\u003cstrong\u003e0.069\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.311320754716981%\" valign=\"bottom\"\u003e\n \u003cp\u003e\u003cstrong\u003e0.082\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"37.85377358490566%\" valign=\"bottom\"\u003e\n \u003cp\u003eSuspicion\u0026nbsp;of invisible mould\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.962264150943396%\" valign=\"top\"\u003e\n \u003cp\u003e0.622\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.839622641509434%\" valign=\"top\"\u003e\n \u003cp\u003e0.529\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.023584905660377%\" valign=\"top\"\u003e\n \u003cp\u003e0.716\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.783018867924528%\" valign=\"top\"\u003e\n \u003cp\u003e1.000\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.0754716981132075%\" valign=\"top\"\u003e\n \u003cp\u003e0.734\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.0754716981132075%\" valign=\"top\"\u003e\n \u003cp\u003e0.741\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.0754716981132075%\" valign=\"top\"\u003e\n \u003cp\u003e0.725\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.311320754716981%\" valign=\"top\"\u003e\n \u003cp\u003e0.827\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"37.85377358490566%\" valign=\"bottom\"\u003e\n \u003cp\u003eSeverity scale (no, mild, moderate, or severe mould)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.962264150943396%\" valign=\"bottom\"\u003e\n \u003cp\u003e0.591\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.839622641509434%\" valign=\"bottom\"\u003e\n \u003cp\u003e0.485\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.023584905660377%\" valign=\"bottom\"\u003e\n \u003cp\u003e0.697\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.783018867924528%\" valign=\"bottom\"\u003e\n \u003cp\u003e0.393\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.0754716981132075%\" valign=\"bottom\"\u003e\n \u003cp\u003e0.266\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.0754716981132075%\" valign=\"bottom\"\u003e\n \u003cp\u003e0.319\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.0754716981132075%\" valign=\"bottom\"\u003e\n \u003cp\u003e0.303\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.311320754716981%\" valign=\"bottom\"\u003e\n \u003cp\u003e0.379\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"37.85377358490566%\" valign=\"bottom\"\u003e\n \u003cp\u003e\u003cstrong\u003eTwo self-reported measures\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.962264150943396%\" valign=\"bottom\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"6.839622641509434%\" valign=\"bottom\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"10.023584905660377%\" valign=\"bottom\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"7.783018867924528%\" valign=\"bottom\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"7.0754716981132075%\" valign=\"bottom\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"7.0754716981132075%\" valign=\"bottom\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"7.0754716981132075%\" valign=\"bottom\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"7.311320754716981%\" valign=\"bottom\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"37.85377358490566%\" valign=\"bottom\"\u003e\n \u003cp\u003eVisibility + Size\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.962264150943396%\" valign=\"bottom\"\u003e\n \u003cp\u003e\u003cu\u003e0.647\u003c/u\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.839622641509434%\" valign=\"bottom\"\u003e\n \u003cp\u003e0.546\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.023584905660377%\" valign=\"bottom\"\u003e\n \u003cp\u003e0.748\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.783018867924528%\" valign=\"bottom\"\u003e\n \u003cp\u003e0.280\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.0754716981132075%\" valign=\"bottom\"\u003e\n \u003cp\u003eBaseline\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.0754716981132075%\" valign=\"bottom\"\u003e\n \u003cp\u003e0.979\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.0754716981132075%\" valign=\"bottom\"\u003e\n \u003cp\u003e0.894\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.311320754716981%\" valign=\"bottom\"\u003e\n \u003cp\u003e0.645\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"37.85377358490566%\" valign=\"bottom\"\u003e\n \u003cp\u003eVisibility + Odour\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.962264150943396%\" valign=\"bottom\"\u003e\n \u003cp\u003e0.632\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.839622641509434%\" valign=\"bottom\"\u003e\n \u003cp\u003e0.526\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.023584905660377%\" valign=\"bottom\"\u003e\n \u003cp\u003e0.738\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.783018867924528%\" valign=\"bottom\"\u003e\n \u003cp\u003e0.704\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.0754716981132075%\" valign=\"bottom\"\u003e\n \u003cp\u003e0.652\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.0754716981132075%\" valign=\"bottom\"\u003e\n \u003cp\u003e0.628\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.0754716981132075%\" valign=\"bottom\"\u003e\n \u003cp\u003e0.590\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.311320754716981%\" valign=\"bottom\"\u003e\n \u003cp\u003e0.882\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"37.85377358490566%\" valign=\"bottom\"\u003e\n \u003cp\u003eVisibility + Dampness\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.962264150943396%\" valign=\"bottom\"\u003e\n \u003cp\u003e0.636\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.839622641509434%\" valign=\"bottom\"\u003e\n \u003cp\u003e0.531\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.023584905660377%\" valign=\"bottom\"\u003e\n \u003cp\u003e0.740\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.783018867924528%\" valign=\"bottom\"\u003e\n \u003cp\u003e0.594\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.0754716981132075%\" valign=\"bottom\"\u003e\n \u003cp\u003e0.708\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.0754716981132075%\" valign=\"bottom\"\u003e\n \u003cp\u003e0.575\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.0754716981132075%\" valign=\"bottom\"\u003e\n \u003cp\u003e0.535\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.311320754716981%\" valign=\"bottom\"\u003e\n \u003cp\u003e0.928\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"37.85377358490566%\" valign=\"bottom\"\u003e\n \u003cp\u003eVisibility + Water damage\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.962264150943396%\" valign=\"bottom\"\u003e\n \u003cp\u003e0.624\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.839622641509434%\" valign=\"bottom\"\u003e\n \u003cp\u003e0.521\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.023584905660377%\" valign=\"bottom\"\u003e\n \u003cp\u003e0.728\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.783018867924528%\" valign=\"bottom\"\u003e\n \u003cp\u003e0.926\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.0754716981132075%\" valign=\"bottom\"\u003e\n \u003cp\u003e0.407\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.0754716981132075%\" valign=\"bottom\"\u003e\n \u003cp\u003e0.408\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.0754716981132075%\" valign=\"bottom\"\u003e\n \u003cp\u003e0.443\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.311320754716981%\" valign=\"bottom\"\u003e\n \u003cp\u003e0.710\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"37.85377358490566%\" valign=\"bottom\"\u003e\n \u003cp\u003eSize + Odour\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.962264150943396%\" valign=\"bottom\"\u003e\n \u003cp\u003e0.539\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.839622641509434%\" valign=\"bottom\"\u003e\n \u003cp\u003e0.434\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.023584905660377%\" valign=\"bottom\"\u003e\n \u003cp\u003e0.644\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.783018867924528%\" valign=\"bottom\"\u003e\n \u003cp\u003e0.201\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.0754716981132075%\" valign=\"bottom\"\u003e\n \u003cp\u003e\u003cstrong\u003e0.090\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.0754716981132075%\" valign=\"bottom\"\u003e\n \u003cp\u003e0.125\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.0754716981132075%\" valign=\"bottom\"\u003e\n \u003cp\u003e0.121\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.311320754716981%\" valign=\"bottom\"\u003e\n \u003cp\u003e0.116\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"37.85377358490566%\" valign=\"bottom\"\u003e\n \u003cp\u003eSize + Dampness\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.962264150943396%\" valign=\"bottom\"\u003e\n \u003cp\u003e0.525\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.839622641509434%\" valign=\"bottom\"\u003e\n \u003cp\u003e0.423\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.023584905660377%\" valign=\"bottom\"\u003e\n \u003cp\u003e0.627\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.783018867924528%\" valign=\"bottom\"\u003e\n \u003cp\u003e0.121\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.0754716981132075%\" valign=\"bottom\"\u003e\n \u003cp\u003e\u003cstrong\u003e0.052\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.0754716981132075%\" valign=\"bottom\"\u003e\n \u003cp\u003e0.101\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.0754716981132075%\" valign=\"bottom\"\u003e\n \u003cp\u003e\u003cstrong\u003e0.097\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.311320754716981%\" valign=\"bottom\"\u003e\n \u003cp\u003e0.113\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"37.85377358490566%\" valign=\"bottom\"\u003e\n \u003cp\u003eSize + Water damage\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.962264150943396%\" valign=\"bottom\"\u003e\n \u003cp\u003e0.547\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.839622641509434%\" valign=\"bottom\"\u003e\n \u003cp\u003e0.451\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.023584905660377%\" valign=\"bottom\"\u003e\n \u003cp\u003e0.644\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.783018867924528%\" valign=\"bottom\"\u003e\n \u003cp\u003e0.209\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.0754716981132075%\" valign=\"bottom\"\u003e\n \u003cp\u003e0.108\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.0754716981132075%\" valign=\"bottom\"\u003e\n \u003cp\u003e0.138\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.0754716981132075%\" valign=\"bottom\"\u003e\n \u003cp\u003e0.114\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.311320754716981%\" valign=\"bottom\"\u003e\n \u003cp\u003e0.131\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"37.85377358490566%\" valign=\"bottom\"\u003e\n \u003cp\u003eOdour + Dampness\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.962264150943396%\" valign=\"bottom\"\u003e\n \u003cp\u003e0.539\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.839622641509434%\" valign=\"bottom\"\u003e\n \u003cp\u003e0.436\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.023584905660377%\" valign=\"bottom\"\u003e\n \u003cp\u003e0.643\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.783018867924528%\" valign=\"bottom\"\u003e\n \u003cp\u003e0.136\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.0754716981132075%\" valign=\"bottom\"\u003e\n \u003cp\u003e\u003cstrong\u003e0.084\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.0754716981132075%\" valign=\"bottom\"\u003e\n \u003cp\u003e0.133\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.0754716981132075%\" valign=\"bottom\"\u003e\n \u003cp\u003e0.129\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.311320754716981%\" valign=\"bottom\"\u003e\n \u003cp\u003e0.130\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"37.85377358490566%\" valign=\"bottom\"\u003e\n \u003cp\u003eOdour + Water damage\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.962264150943396%\" valign=\"bottom\"\u003e\n \u003cp\u003e0.553\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.839622641509434%\" valign=\"bottom\"\u003e\n \u003cp\u003e0.449\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.023584905660377%\" valign=\"bottom\"\u003e\n \u003cp\u003e0.658\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.783018867924528%\" valign=\"bottom\"\u003e\n \u003cp\u003e0.195\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.0754716981132075%\" valign=\"bottom\"\u003e\n \u003cp\u003e0.128\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.0754716981132075%\" valign=\"bottom\"\u003e\n \u003cp\u003e0.171\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.0754716981132075%\" valign=\"bottom\"\u003e\n \u003cp\u003e0.151\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.311320754716981%\" valign=\"bottom\"\u003e\n \u003cp\u003e0.149\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"37.85377358490566%\" valign=\"bottom\"\u003e\n \u003cp\u003eDampness + Water damage\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.962264150943396%\" valign=\"bottom\"\u003e\n \u003cp\u003e0.546\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.839622641509434%\" valign=\"bottom\"\u003e\n \u003cp\u003e0.446\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.023584905660377%\" valign=\"bottom\"\u003e\n \u003cp\u003e0.647\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.783018867924528%\" valign=\"bottom\"\u003e\n \u003cp\u003e0.145\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.0754716981132075%\" valign=\"bottom\"\u003e\n \u003cp\u003e0.101\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.0754716981132075%\" valign=\"bottom\"\u003e\n \u003cp\u003e0.154\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.0754716981132075%\" valign=\"bottom\"\u003e\n \u003cp\u003e0.136\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.311320754716981%\" valign=\"bottom\"\u003e\n \u003cp\u003e0.157\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"37.85377358490566%\" valign=\"bottom\"\u003e\n \u003cp\u003e\u003cstrong\u003eThree self-reported measures\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.962264150943396%\" valign=\"bottom\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"6.839622641509434%\" valign=\"bottom\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"10.023584905660377%\" valign=\"bottom\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"7.783018867924528%\" valign=\"bottom\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"7.0754716981132075%\" valign=\"bottom\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"7.0754716981132075%\" valign=\"bottom\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"7.0754716981132075%\" valign=\"bottom\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"7.311320754716981%\" valign=\"bottom\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"37.85377358490566%\" valign=\"bottom\"\u003e\n \u003cp\u003eVisibility + Size + Dampness\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.962264150943396%\" valign=\"bottom\"\u003e\n \u003cp\u003e\u003cu\u003e0.647\u003c/u\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.839622641509434%\" valign=\"bottom\"\u003e\n \u003cp\u003e0.541\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.023584905660377%\" valign=\"bottom\"\u003e\n \u003cp\u003e0.753\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.783018867924528%\" valign=\"bottom\"\u003e\n \u003cp\u003e0.368\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.0754716981132075%\" valign=\"bottom\"\u003e\n \u003cp\u003e0.979\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.0754716981132075%\" valign=\"bottom\"\u003e\n \u003cp\u003eBaseline\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.0754716981132075%\" valign=\"bottom\"\u003e\n \u003cp\u003e0.769\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.311320754716981%\" valign=\"bottom\"\u003e\n \u003cp\u003e0.589\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"37.85377358490566%\" valign=\"bottom\"\u003e\n \u003cp\u003eVisibility + Size + Odour\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.962264150943396%\" valign=\"bottom\"\u003e\n \u003cp\u003e0.644\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.839622641509434%\" valign=\"bottom\"\u003e\n \u003cp\u003e0.537\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.023584905660377%\" valign=\"bottom\"\u003e\n \u003cp\u003e0.752\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.783018867924528%\" valign=\"bottom\"\u003e\n \u003cp\u003e0.445\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.0754716981132075%\" valign=\"bottom\"\u003e\n \u003cp\u003e0.880\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.0754716981132075%\" valign=\"bottom\"\u003e\n \u003cp\u003e0.863\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.0754716981132075%\" valign=\"bottom\"\u003e\n \u003cp\u003e0.787\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.311320754716981%\" valign=\"bottom\"\u003e\n \u003cp\u003e0.831\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"37.85377358490566%\" valign=\"bottom\"\u003e\n \u003cp\u003eVisibility + Size + Water damage\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.962264150943396%\" valign=\"bottom\"\u003e\n \u003cp\u003e0.647\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.839622641509434%\" valign=\"bottom\"\u003e\n \u003cp\u003e0.542\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.023584905660377%\" valign=\"bottom\"\u003e\n \u003cp\u003e0.751\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.783018867924528%\" valign=\"bottom\"\u003e\n \u003cp\u003e0.350\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.0754716981132075%\" valign=\"bottom\"\u003e\n \u003cp\u003e1.000\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.0754716981132075%\" valign=\"bottom\"\u003e\n \u003cp\u003e0.986\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.0754716981132075%\" valign=\"bottom\"\u003e\n \u003cp\u003e0.916\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.311320754716981%\" valign=\"bottom\"\u003e\n \u003cp\u003e0.645\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"37.85377358490566%\" valign=\"bottom\"\u003e\n \u003cp\u003eVisibility + Odour + Dampness\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.962264150943396%\" valign=\"bottom\"\u003e\n \u003cp\u003e0.634\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.839622641509434%\" valign=\"bottom\"\u003e\n \u003cp\u003e0.526\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.023584905660377%\" valign=\"bottom\"\u003e\n \u003cp\u003e0.741\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.783018867924528%\" valign=\"bottom\"\u003e\n \u003cp\u003e0.696\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.0754716981132075%\" valign=\"bottom\"\u003e\n \u003cp\u003e0.684\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.0754716981132075%\" valign=\"bottom\"\u003e\n \u003cp\u003e0.573\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.0754716981132075%\" valign=\"bottom\"\u003e\n \u003cp\u003e0.542\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.311320754716981%\" valign=\"bottom\"\u003e\n \u003cp\u003e0.860\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"37.85377358490566%\" valign=\"bottom\"\u003e\n \u003cp\u003eVisibility + Odour + Water damage\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.962264150943396%\" valign=\"bottom\"\u003e\n \u003cp\u003e0.624\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.839622641509434%\" valign=\"bottom\"\u003e\n \u003cp\u003e0.516\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.023584905660377%\" valign=\"bottom\"\u003e\n \u003cp\u003e0.732\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.783018867924528%\" valign=\"bottom\"\u003e\n \u003cp\u003e0.949\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.0754716981132075%\" valign=\"bottom\"\u003e\n \u003cp\u003e0.455\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.0754716981132075%\" valign=\"bottom\"\u003e\n \u003cp\u003e0.405\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.0754716981132075%\" valign=\"bottom\"\u003e\n \u003cp\u003e0.430\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.311320754716981%\" valign=\"bottom\"\u003e\n \u003cp\u003e0.729\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"37.85377358490566%\" valign=\"bottom\"\u003e\n \u003cp\u003eVisibility + Dampness + Water damage\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.962264150943396%\" valign=\"bottom\"\u003e\n \u003cp\u003e0.633\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.839622641509434%\" valign=\"bottom\"\u003e\n \u003cp\u003e0.526\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.023584905660377%\" valign=\"bottom\"\u003e\n \u003cp\u003e0.739\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.783018867924528%\" valign=\"bottom\"\u003e\n \u003cp\u003e0.702\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.0754716981132075%\" valign=\"bottom\"\u003e\n \u003cp\u003e0.632\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.0754716981132075%\" valign=\"bottom\"\u003e\n \u003cp\u003e0.484\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.0754716981132075%\" valign=\"bottom\"\u003e\n \u003cp\u003e0.498\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.311320754716981%\" valign=\"bottom\"\u003e\n \u003cp\u003e0.860\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"37.85377358490566%\" valign=\"bottom\"\u003e\n \u003cp\u003eSize + Odour + Dampness\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.962264150943396%\" valign=\"bottom\"\u003e\n \u003cp\u003e0.541\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.839622641509434%\" valign=\"bottom\"\u003e\n \u003cp\u003e0.433\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.023584905660377%\" valign=\"bottom\"\u003e\n \u003cp\u003e0.650\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.783018867924528%\" valign=\"bottom\"\u003e\n \u003cp\u003e0.214\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.0754716981132075%\" valign=\"bottom\"\u003e\n \u003cp\u003e\u003cstrong\u003e0.095\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.0754716981132075%\" valign=\"bottom\"\u003e\n \u003cp\u003e0.143\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.0754716981132075%\" valign=\"bottom\"\u003e\n \u003cp\u003e0.138\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.311320754716981%\" valign=\"bottom\"\u003e\n \u003cp\u003e0.137\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"37.85377358490566%\" valign=\"bottom\"\u003e\n \u003cp\u003eSize + Odour + Water damage\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.962264150943396%\" valign=\"bottom\"\u003e\n \u003cp\u003e0.569\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.839622641509434%\" valign=\"bottom\"\u003e\n \u003cp\u003e0.462\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.023584905660377%\" valign=\"bottom\"\u003e\n \u003cp\u003e0.676\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.783018867924528%\" valign=\"bottom\"\u003e\n \u003cp\u003e0.382\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.0754716981132075%\" valign=\"bottom\"\u003e\n \u003cp\u003e0.206\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.0754716981132075%\" valign=\"bottom\"\u003e\n \u003cp\u003e0.256\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.0754716981132075%\" valign=\"bottom\"\u003e\n \u003cp\u003e0.229\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.311320754716981%\" valign=\"bottom\"\u003e\n \u003cp\u003e0.236\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"37.85377358490566%\" valign=\"bottom\"\u003e\n \u003cp\u003eSize + Dampness + Water damage\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.962264150943396%\" valign=\"bottom\"\u003e\n \u003cp\u003e0.567\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.839622641509434%\" valign=\"bottom\"\u003e\n \u003cp\u003e0.463\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.023584905660377%\" valign=\"bottom\"\u003e\n \u003cp\u003e0.671\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.783018867924528%\" valign=\"bottom\"\u003e\n \u003cp\u003e0.358\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.0754716981132075%\" valign=\"bottom\"\u003e\n \u003cp\u003e0.195\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.0754716981132075%\" valign=\"bottom\"\u003e\n \u003cp\u003e0.258\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.0754716981132075%\" valign=\"bottom\"\u003e\n \u003cp\u003e0.232\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.311320754716981%\" valign=\"bottom\"\u003e\n \u003cp\u003e0.266\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"37.85377358490566%\" valign=\"bottom\"\u003e\n \u003cp\u003eOdour + Dampness + Water damage\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.962264150943396%\" valign=\"bottom\"\u003e\n \u003cp\u003e0.558\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.839622641509434%\" valign=\"bottom\"\u003e\n \u003cp\u003e0.452\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.023584905660377%\" valign=\"bottom\"\u003e\n \u003cp\u003e0.665\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.783018867924528%\" valign=\"bottom\"\u003e\n \u003cp\u003e0.251\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.0754716981132075%\" valign=\"bottom\"\u003e\n \u003cp\u003e0.163\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.0754716981132075%\" valign=\"bottom\"\u003e\n \u003cp\u003e0.196\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.0754716981132075%\" valign=\"bottom\"\u003e\n \u003cp\u003e0.173\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.311320754716981%\" valign=\"bottom\"\u003e\n \u003cp\u003e0.174\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"37.85377358490566%\" valign=\"bottom\"\u003e\n \u003cp\u003e\u003cstrong\u003eFour self-reported measures\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.962264150943396%\" valign=\"bottom\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"6.839622641509434%\" valign=\"bottom\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"10.023584905660377%\" valign=\"bottom\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"7.783018867924528%\" valign=\"bottom\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"7.0754716981132075%\" valign=\"bottom\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"7.0754716981132075%\" valign=\"bottom\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"7.0754716981132075%\" valign=\"bottom\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"7.311320754716981%\" valign=\"bottom\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"37.85377358490566%\" valign=\"bottom\"\u003e\n \u003cp\u003eVisibility + Size + Dampness + Water damage\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.962264150943396%\" valign=\"bottom\"\u003e\n \u003cp\u003e\u003cu\u003e0.649\u003c/u\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.839622641509434%\" valign=\"bottom\"\u003e\n \u003cp\u003e0.542\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.023584905660377%\" valign=\"bottom\"\u003e\n \u003cp\u003e0.756\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.783018867924528%\" valign=\"bottom\"\u003e\n \u003cp\u003e0.347\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.0754716981132075%\" valign=\"bottom\"\u003e\n \u003cp\u003e0.894\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.0754716981132075%\" valign=\"bottom\"\u003e\n \u003cp\u003e0.769\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.0754716981132075%\" valign=\"bottom\"\u003e\n \u003cp\u003eBaseline\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.311320754716981%\" valign=\"bottom\"\u003e\n \u003cp\u003e0.447\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"37.85377358490566%\" valign=\"bottom\"\u003e\n \u003cp\u003eVisibility + Size + Odour + Dampness\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.962264150943396%\" valign=\"bottom\"\u003e\n \u003cp\u003e0.648\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.839622641509434%\" valign=\"bottom\"\u003e\n \u003cp\u003e0.540\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.023584905660377%\" valign=\"bottom\"\u003e\n \u003cp\u003e0.755\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.783018867924528%\" valign=\"bottom\"\u003e\n \u003cp\u003e0.391\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.0754716981132075%\" valign=\"bottom\"\u003e\n \u003cp\u003e0.966\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.0754716981132075%\" valign=\"bottom\"\u003e\n \u003cp\u003e0.968\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.0754716981132075%\" valign=\"bottom\"\u003e\n \u003cp\u003e0.909\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.311320754716981%\" valign=\"bottom\"\u003e\n \u003cp\u003e0.484\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"37.85377358490566%\" valign=\"bottom\"\u003e\n \u003cp\u003eVisibility + Size + Odour + Water damage\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.962264150943396%\" valign=\"bottom\"\u003e\n \u003cp\u003e0.641\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.839622641509434%\" valign=\"bottom\"\u003e\n \u003cp\u003e0.532\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.023584905660377%\" valign=\"bottom\"\u003e\n \u003cp\u003e0.750\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.783018867924528%\" valign=\"bottom\"\u003e\n \u003cp\u003e0.526\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.0754716981132075%\" valign=\"bottom\"\u003e\n \u003cp\u003e0.767\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.0754716981132075%\" valign=\"bottom\"\u003e\n \u003cp\u003e0.804\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.0754716981132075%\" valign=\"bottom\"\u003e\n \u003cp\u003e0.715\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.311320754716981%\" valign=\"bottom\"\u003e\n \u003cp\u003e0.905\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"37.85377358490566%\" valign=\"bottom\"\u003e\n \u003cp\u003eVisibility + Odour + Dampness + Water damage\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.962264150943396%\" valign=\"bottom\"\u003e\n \u003cp\u003e0.636\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.839622641509434%\" valign=\"bottom\"\u003e\n \u003cp\u003e0.527\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.023584905660377%\" valign=\"bottom\"\u003e\n \u003cp\u003e0.745\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.783018867924528%\" valign=\"bottom\"\u003e\n \u003cp\u003e0.641\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.0754716981132075%\" valign=\"bottom\"\u003e\n \u003cp\u003e0.739\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.0754716981132075%\" valign=\"bottom\"\u003e\n \u003cp\u003e0.643\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.0754716981132075%\" valign=\"bottom\"\u003e\n \u003cp\u003e0.626\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.311320754716981%\" valign=\"bottom\"\u003e\n \u003cp\u003e0.940\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"37.85377358490566%\" valign=\"bottom\"\u003e\n \u003cp\u003eSize + Odour + Dampness + Water damage\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.962264150943396%\" valign=\"bottom\"\u003e\n \u003cp\u003e0.569\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.839622641509434%\" valign=\"bottom\"\u003e\n \u003cp\u003e0.461\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.023584905660377%\" valign=\"bottom\"\u003e\n \u003cp\u003e0.677\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.783018867924528%\" valign=\"bottom\"\u003e\n \u003cp\u003e0.389\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.0754716981132075%\" valign=\"bottom\"\u003e\n \u003cp\u003e0.214\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.0754716981132075%\" valign=\"bottom\"\u003e\n \u003cp\u003e0.254\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.0754716981132075%\" valign=\"bottom\"\u003e\n \u003cp\u003e0.226\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.311320754716981%\" valign=\"bottom\"\u003e\n \u003cp\u003e0.231\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"37.85377358490566%\" valign=\"bottom\"\u003e\n \u003cp\u003e\u003cstrong\u003eFive self-reported measures\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.962264150943396%\" valign=\"bottom\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"6.839622641509434%\" valign=\"bottom\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"10.023584905660377%\" valign=\"bottom\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"7.783018867924528%\" valign=\"bottom\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"7.0754716981132075%\" valign=\"bottom\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"7.0754716981132075%\" valign=\"bottom\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"7.0754716981132075%\" valign=\"bottom\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"7.311320754716981%\" valign=\"bottom\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"37.85377358490566%\" valign=\"bottom\"\u003e\n \u003cp\u003eVisibility + Size + Odour + Dampness + Water damage\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.962264150943396%\" valign=\"bottom\"\u003e\n \u003cp\u003e0.638\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.839622641509434%\" valign=\"bottom\"\u003e\n \u003cp\u003e0.530\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.023584905660377%\" valign=\"bottom\"\u003e\n \u003cp\u003e0.747\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.783018867924528%\" valign=\"bottom\"\u003e\n \u003cp\u003e0.590\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.0754716981132075%\" valign=\"bottom\"\u003e\n \u003cp\u003e0.645\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.0754716981132075%\" valign=\"bottom\"\u003e\n \u003cp\u003e0.589\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.0754716981132075%\" valign=\"bottom\"\u003e\n \u003cp\u003e0.447\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.311320754716981%\" valign=\"bottom\"\u003e\n \u003cp\u003eBaseline\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003eTable 4. Results on the performance of combination of self-reported mould measures in predicting lab-tested severe mould\u003c/p\u003e\n\u003ctable border=\"0\" cellspacing=\"0\" cellpadding=\"0\" width=\"843\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd width=\"37.05463182897862%\" valign=\"bottom\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"8.669833729216151%\" valign=\"bottom\"\u003e\n \u003cp\u003eAUC\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.945368171021377%\" colspan=\"2\" valign=\"bottom\"\u003e\n \u003cp\u003e95% CI\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"41.33016627078385%\" colspan=\"5\" valign=\"bottom\"\u003e\n \u003cp\u003eTest on equality of AUC (P-value)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"36.96682464454976%\" valign=\"bottom\"\u003e\n \u003cp\u003e\u003cstrong\u003eSingle self-reported measure\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.649289099526067%\" valign=\"bottom\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"7.701421800947867%\" valign=\"bottom\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"5.213270142180095%\" valign=\"bottom\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"12.085308056872037%\" valign=\"bottom\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"7.345971563981043%\" valign=\"bottom\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"7.345971563981043%\" valign=\"bottom\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"7.345971563981043%\" valign=\"bottom\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"7.345971563981043%\" valign=\"bottom\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"36.96682464454976%\" valign=\"bottom\"\u003e\n \u003cp\u003eVisibility\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.649289099526067%\" valign=\"bottom\"\u003e\n \u003cp\u003e\u003cu\u003e0.602\u003c/u\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.701421800947867%\" valign=\"bottom\"\u003e\n \u003cp\u003e0.507\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"5.213270142180095%\" valign=\"bottom\"\u003e\n \u003cp\u003e0.698\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.085308056872037%\" valign=\"bottom\"\u003e\n \u003cp\u003eBaseline\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.345971563981043%\" valign=\"bottom\"\u003e\n \u003cp\u003e0.139\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.345971563981043%\" valign=\"bottom\"\u003e\n \u003cp\u003e0.177\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.345971563981043%\" valign=\"bottom\"\u003e\n \u003cp\u003e\u003cstrong\u003e0.090\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.345971563981043%\" valign=\"bottom\"\u003e\n \u003cp\u003e0.117\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"36.96682464454976%\" valign=\"bottom\"\u003e\n \u003cp\u003eSize\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.649289099526067%\" valign=\"bottom\"\u003e\n \u003cp\u003e0.470\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.701421800947867%\" valign=\"bottom\"\u003e\n \u003cp\u003e0.389\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"5.213270142180095%\" valign=\"bottom\"\u003e\n \u003cp\u003e0.552\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.085308056872037%\" valign=\"bottom\"\u003e\n \u003cp\u003e\u003cstrong\u003e0.012\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.345971563981043%\" valign=\"bottom\"\u003e\n \u003cp\u003e\u003cstrong\u003e0.020\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.345971563981043%\" valign=\"bottom\"\u003e\n \u003cp\u003e\u003cstrong\u003e0.022\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.345971563981043%\" valign=\"bottom\"\u003e\n \u003cp\u003e\u003cstrong\u003e0.012\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.345971563981043%\" valign=\"bottom\"\u003e\n \u003cp\u003e\u003cstrong\u003e0.013\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"36.96682464454976%\" valign=\"bottom\"\u003e\n \u003cp\u003eOdour\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.649289099526067%\" valign=\"bottom\"\u003e\n \u003cp\u003e0.530\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.701421800947867%\" valign=\"bottom\"\u003e\n \u003cp\u003e0.428\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"5.213270142180095%\" valign=\"bottom\"\u003e\n \u003cp\u003e0.632\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.085308056872037%\" valign=\"bottom\"\u003e\n \u003cp\u003e0.262\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.345971563981043%\" valign=\"bottom\"\u003e\n \u003cp\u003e0.126\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.345971563981043%\" valign=\"bottom\"\u003e\n \u003cp\u003e0.154\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.345971563981043%\" valign=\"bottom\"\u003e\n \u003cp\u003e\u003cstrong\u003e0.081\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.345971563981043%\" valign=\"bottom\"\u003e\n \u003cp\u003e\u003cstrong\u003e0.057\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"36.96682464454976%\" valign=\"bottom\"\u003e\n \u003cp\u003eDampness\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.649289099526067%\" valign=\"bottom\"\u003e\n \u003cp\u003e0.518\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.701421800947867%\" valign=\"bottom\"\u003e\n \u003cp\u003e0.420\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"5.213270142180095%\" valign=\"bottom\"\u003e\n \u003cp\u003e0.615\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.085308056872037%\" valign=\"bottom\"\u003e\n \u003cp\u003e0.155\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.345971563981043%\" valign=\"bottom\"\u003e\n \u003cp\u003e\u003cstrong\u003e0.077\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.345971563981043%\" valign=\"bottom\"\u003e\n \u003cp\u003e0.122\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.345971563981043%\" valign=\"bottom\"\u003e\n \u003cp\u003e\u003cstrong\u003e0.041\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.345971563981043%\" valign=\"bottom\"\u003e\n \u003cp\u003e\u003cstrong\u003e0.045\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"36.96682464454976%\" valign=\"bottom\"\u003e\n \u003cp\u003eWater damage\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.649289099526067%\" valign=\"bottom\"\u003e\n \u003cp\u003e0.490\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.701421800947867%\" valign=\"bottom\"\u003e\n \u003cp\u003e0.398\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"5.213270142180095%\" valign=\"bottom\"\u003e\n \u003cp\u003e0.582\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.085308056872037%\" valign=\"bottom\"\u003e\n \u003cp\u003e\u003cstrong\u003e0.035\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.345971563981043%\" valign=\"bottom\"\u003e\n \u003cp\u003e\u003cstrong\u003e0.021\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.345971563981043%\" valign=\"bottom\"\u003e\n \u003cp\u003e\u003cstrong\u003e0.031\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.345971563981043%\" valign=\"bottom\"\u003e\n \u003cp\u003e\u003cstrong\u003e0.025\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.345971563981043%\" valign=\"bottom\"\u003e\n \u003cp\u003e\u003cstrong\u003e0.026\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"36.96682464454976%\" valign=\"bottom\"\u003e\n \u003cp\u003eSuspicion\u0026nbsp;of invisible mould\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.649289099526067%\" valign=\"bottom\"\u003e\n \u003cp\u003e0.420\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.701421800947867%\" valign=\"bottom\"\u003e\n \u003cp\u003e0.322\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"5.213270142180095%\" valign=\"bottom\"\u003e\n \u003cp\u003e0.517\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.085308056872037%\" valign=\"bottom\"\u003e\n \u003cp\u003e0.753\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.345971563981043%\" valign=\"bottom\"\u003e\n \u003cp\u003e0.443\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.345971563981043%\" valign=\"bottom\"\u003e\n \u003cp\u003e0.434\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.345971563981043%\" valign=\"bottom\"\u003e\n \u003cp\u003e0.332\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.345971563981043%\" valign=\"bottom\"\u003e\n \u003cp\u003e0.322\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"36.96682464454976%\" valign=\"bottom\"\u003e\n \u003cp\u003eSeverity scale (no, mild, moderate, or severe mould)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.649289099526067%\" valign=\"bottom\"\u003e\n \u003cp\u003e0.592\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.701421800947867%\" valign=\"bottom\"\u003e\n \u003cp\u003e0.487\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"5.213270142180095%\" valign=\"bottom\"\u003e\n \u003cp\u003e0.697\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.085308056872037%\" valign=\"bottom\"\u003e\n \u003cp\u003e0.803\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.345971563981043%\" valign=\"bottom\"\u003e\n \u003cp\u003e0.404\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.345971563981043%\" valign=\"bottom\"\u003e\n \u003cp\u003e0.412\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.345971563981043%\" valign=\"bottom\"\u003e\n \u003cp\u003e0.296\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.345971563981043%\" valign=\"bottom\"\u003e\n \u003cp\u003e0.305\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"36.96682464454976%\" valign=\"bottom\"\u003e\n \u003cp\u003e\u003cstrong\u003eTwo self-reported measures\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.649289099526067%\" valign=\"bottom\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"7.701421800947867%\" valign=\"bottom\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"5.213270142180095%\" valign=\"bottom\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"12.085308056872037%\" valign=\"bottom\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"7.345971563981043%\" valign=\"bottom\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"7.345971563981043%\" valign=\"bottom\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"7.345971563981043%\" valign=\"bottom\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"7.345971563981043%\" valign=\"bottom\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"36.96682464454976%\" valign=\"bottom\"\u003e\n \u003cp\u003eVisibility + Size\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.649289099526067%\" valign=\"bottom\"\u003e\n \u003cp\u003e\u003cu\u003e0.638\u003c/u\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.701421800947867%\" valign=\"bottom\"\u003e\n \u003cp\u003e0.532\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"5.213270142180095%\" valign=\"bottom\"\u003e\n \u003cp\u003e0.744\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.085308056872037%\" valign=\"bottom\"\u003e\n \u003cp\u003e0.139\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.345971563981043%\" valign=\"bottom\"\u003e\n \u003cp\u003eBaseline\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.345971563981043%\" valign=\"bottom\"\u003e\n \u003cp\u003e0.751\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.345971563981043%\" valign=\"bottom\"\u003e\n \u003cp\u003e0.429\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.345971563981043%\" valign=\"bottom\"\u003e\n \u003cp\u003e0.530\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"36.96682464454976%\" valign=\"bottom\"\u003e\n \u003cp\u003eVisibility + Odour\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.649289099526067%\" valign=\"bottom\"\u003e\n \u003cp\u003e0.617\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.701421800947867%\" valign=\"bottom\"\u003e\n \u003cp\u003e0.500\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"5.213270142180095%\" valign=\"bottom\"\u003e\n \u003cp\u003e0.734\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.085308056872037%\" valign=\"bottom\"\u003e\n \u003cp\u003e0.621\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.345971563981043%\" valign=\"bottom\"\u003e\n \u003cp\u003e0.562\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.345971563981043%\" valign=\"bottom\"\u003e\n \u003cp\u003e0.424\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.345971563981043%\" valign=\"bottom\"\u003e\n \u003cp\u003e0.398\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.345971563981043%\" valign=\"bottom\"\u003e\n \u003cp\u003e0.478\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"36.96682464454976%\" valign=\"bottom\"\u003e\n \u003cp\u003eVisibility + Dampness\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.649289099526067%\" valign=\"bottom\"\u003e\n \u003cp\u003e0.619\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.701421800947867%\" valign=\"bottom\"\u003e\n \u003cp\u003e0.506\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"5.213270142180095%\" valign=\"bottom\"\u003e\n \u003cp\u003e0.731\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.085308056872037%\" valign=\"bottom\"\u003e\n \u003cp\u003e0.552\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.345971563981043%\" valign=\"bottom\"\u003e\n \u003cp\u003e0.556\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.345971563981043%\" valign=\"bottom\"\u003e\n \u003cp\u003e0.260\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.345971563981043%\" valign=\"bottom\"\u003e\n \u003cp\u003e0.398\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.345971563981043%\" valign=\"bottom\"\u003e\n \u003cp\u003e0.424\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"36.96682464454976%\" valign=\"bottom\"\u003e\n \u003cp\u003eVisibility + Water damage\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.649289099526067%\" valign=\"bottom\"\u003e\n \u003cp\u003e0.628\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.701421800947867%\" valign=\"bottom\"\u003e\n \u003cp\u003e0.521\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"5.213270142180095%\" valign=\"bottom\"\u003e\n \u003cp\u003e0.736\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.085308056872037%\" valign=\"bottom\"\u003e\n \u003cp\u003e0.308\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.345971563981043%\" valign=\"bottom\"\u003e\n \u003cp\u003e0.735\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.345971563981043%\" valign=\"bottom\"\u003e\n \u003cp\u003e0.602\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.345971563981043%\" valign=\"bottom\"\u003e\n \u003cp\u003e0.277\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.345971563981043%\" valign=\"bottom\"\u003e\n \u003cp\u003e0.356\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"36.96682464454976%\" valign=\"bottom\"\u003e\n \u003cp\u003eSize + Odour\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.649289099526067%\" valign=\"bottom\"\u003e\n \u003cp\u003e0.564\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.701421800947867%\" valign=\"bottom\"\u003e\n \u003cp\u003e0.454\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"5.213270142180095%\" valign=\"bottom\"\u003e\n \u003cp\u003e0.674\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.085308056872037%\" valign=\"bottom\"\u003e\n \u003cp\u003e0.633\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.345971563981043%\" valign=\"bottom\"\u003e\n \u003cp\u003e0.296\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.345971563981043%\" valign=\"bottom\"\u003e\n \u003cp\u003e0.307\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.345971563981043%\" valign=\"bottom\"\u003e\n \u003cp\u003e0.207\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.345971563981043%\" valign=\"bottom\"\u003e\n \u003cp\u003e0.180\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"36.96682464454976%\" valign=\"bottom\"\u003e\n \u003cp\u003eSize + Dampness\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.649289099526067%\" valign=\"bottom\"\u003e\n \u003cp\u003e0.544\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.701421800947867%\" valign=\"bottom\"\u003e\n \u003cp\u003e0.439\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"5.213270142180095%\" valign=\"bottom\"\u003e\n \u003cp\u003e0.648\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.085308056872037%\" valign=\"bottom\"\u003e\n \u003cp\u003e0.447\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.345971563981043%\" valign=\"bottom\"\u003e\n \u003cp\u003e0.161\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.345971563981043%\" valign=\"bottom\"\u003e\n \u003cp\u003e0.199\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.345971563981043%\" valign=\"bottom\"\u003e\n \u003cp\u003e\u003cstrong\u003e0.096\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.345971563981043%\" valign=\"bottom\"\u003e\n \u003cp\u003e0.100\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"36.96682464454976%\" valign=\"bottom\"\u003e\n \u003cp\u003eSize + Water damage\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.649289099526067%\" valign=\"bottom\"\u003e\n \u003cp\u003e0.529\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.701421800947867%\" valign=\"bottom\"\u003e\n \u003cp\u003e0.429\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"5.213270142180095%\" valign=\"bottom\"\u003e\n \u003cp\u003e0.628\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.085308056872037%\" valign=\"bottom\"\u003e\n \u003cp\u003e0.319\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.345971563981043%\" valign=\"bottom\"\u003e\n \u003cp\u003e\u003cstrong\u003e0.085\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.345971563981043%\" valign=\"bottom\"\u003e\n \u003cp\u003e\u003cstrong\u003e0.095\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.345971563981043%\" valign=\"bottom\"\u003e\n \u003cp\u003e\u003cstrong\u003e0.076\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.345971563981043%\" valign=\"bottom\"\u003e\n \u003cp\u003e\u003cstrong\u003e0.076\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"36.96682464454976%\" valign=\"bottom\"\u003e\n \u003cp\u003eOdour + Dampness\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.649289099526067%\" valign=\"bottom\"\u003e\n \u003cp\u003e0.529\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.701421800947867%\" valign=\"bottom\"\u003e\n \u003cp\u003e0.419\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"5.213270142180095%\" valign=\"bottom\"\u003e\n \u003cp\u003e0.639\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.085308056872037%\" valign=\"bottom\"\u003e\n \u003cp\u003e0.260\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.345971563981043%\" valign=\"bottom\"\u003e\n \u003cp\u003e0.132\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.345971563981043%\" valign=\"bottom\"\u003e\n \u003cp\u003e0.174\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.345971563981043%\" valign=\"bottom\"\u003e\n \u003cp\u003e\u003cstrong\u003e0.081\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.345971563981043%\" valign=\"bottom\"\u003e\n \u003cp\u003e\u003cstrong\u003e0.066\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"36.96682464454976%\" valign=\"bottom\"\u003e\n \u003cp\u003eOdour + Water damage\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.649289099526067%\" valign=\"bottom\"\u003e\n \u003cp\u003e0.542\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.701421800947867%\" valign=\"bottom\"\u003e\n \u003cp\u003e0.433\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"5.213270142180095%\" valign=\"bottom\"\u003e\n \u003cp\u003e0.650\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.085308056872037%\" valign=\"bottom\"\u003e\n \u003cp\u003e0.401\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.345971563981043%\" valign=\"bottom\"\u003e\n \u003cp\u003e0.204\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.345971563981043%\" valign=\"bottom\"\u003e\n \u003cp\u003e0.224\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.345971563981043%\" valign=\"bottom\"\u003e\n \u003cp\u003e0.122\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.345971563981043%\" valign=\"bottom\"\u003e\n \u003cp\u003e\u003cstrong\u003e0.091\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"36.96682464454976%\" valign=\"bottom\"\u003e\n \u003cp\u003eDampness + Water damage\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.649289099526067%\" valign=\"bottom\"\u003e\n \u003cp\u003e0.529\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.701421800947867%\" valign=\"bottom\"\u003e\n \u003cp\u003e0.424\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"5.213270142180095%\" valign=\"bottom\"\u003e\n \u003cp\u003e0.634\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.085308056872037%\" valign=\"bottom\"\u003e\n \u003cp\u003e0.272\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.345971563981043%\" valign=\"bottom\"\u003e\n \u003cp\u003e0.137\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.345971563981043%\" valign=\"bottom\"\u003e\n \u003cp\u003e0.186\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.345971563981043%\" valign=\"bottom\"\u003e\n \u003cp\u003e\u003cstrong\u003e0.067\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.345971563981043%\" valign=\"bottom\"\u003e\n \u003cp\u003e\u003cstrong\u003e0.073\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"36.96682464454976%\" valign=\"bottom\"\u003e\n \u003cp\u003e\u003cstrong\u003eThree self-reported measures\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.649289099526067%\" valign=\"bottom\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"7.701421800947867%\" valign=\"bottom\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"5.213270142180095%\" valign=\"bottom\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"12.085308056872037%\" valign=\"bottom\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"7.345971563981043%\" valign=\"bottom\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"7.345971563981043%\" valign=\"bottom\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"7.345971563981043%\" valign=\"bottom\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"7.345971563981043%\" valign=\"bottom\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"36.96682464454976%\" valign=\"bottom\"\u003e\n \u003cp\u003eVisibility + Size + Dampness\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.649289099526067%\" valign=\"bottom\"\u003e\n \u003cp\u003e0.644\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.701421800947867%\" valign=\"bottom\"\u003e\n \u003cp\u003e0.529\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"5.213270142180095%\" valign=\"bottom\"\u003e\n \u003cp\u003e0.759\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.085308056872037%\" valign=\"bottom\"\u003e\n \u003cp\u003e0.177\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.345971563981043%\" valign=\"bottom\"\u003e\n \u003cp\u003e0.751\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.345971563981043%\" valign=\"bottom\"\u003e\n \u003cp\u003eBaseline\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.345971563981043%\" valign=\"bottom\"\u003e\n \u003cp\u003e0.762\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.345971563981043%\" valign=\"bottom\"\u003e\n \u003cp\u003e0.798\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"36.96682464454976%\" valign=\"bottom\"\u003e\n \u003cp\u003eVisibility + Size + Odour\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.649289099526067%\" valign=\"bottom\"\u003e\n \u003cp\u003e0.639\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.701421800947867%\" valign=\"bottom\"\u003e\n \u003cp\u003e0.531\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"5.213270142180095%\" valign=\"bottom\"\u003e\n \u003cp\u003e0.747\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.085308056872037%\" valign=\"bottom\"\u003e\n \u003cp\u003e0.230\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.345971563981043%\" valign=\"bottom\"\u003e\n \u003cp\u003e0.957\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.345971563981043%\" valign=\"bottom\"\u003e\n \u003cp\u003e0.891\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.345971563981043%\" valign=\"bottom\"\u003e\n \u003cp\u003e0.571\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.345971563981043%\" valign=\"bottom\"\u003e\n \u003cp\u003e0.492\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"36.96682464454976%\" valign=\"bottom\"\u003e\n \u003cp\u003eVisibility + Size + Water damage\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.649289099526067%\" valign=\"bottom\"\u003e\n \u003cp\u003e\u003cu\u003e0.649\u003c/u\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.701421800947867%\" valign=\"bottom\"\u003e\n \u003cp\u003e0.540\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"5.213270142180095%\" valign=\"bottom\"\u003e\n \u003cp\u003e0.758\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.085308056872037%\" valign=\"bottom\"\u003e\n \u003cp\u003e\u003cstrong\u003e0.093\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.345971563981043%\" valign=\"bottom\"\u003e\n \u003cp\u003e0.431\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.345971563981043%\" valign=\"bottom\"\u003e\n \u003cp\u003e0.769\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.345971563981043%\" valign=\"bottom\"\u003e\n \u003cp\u003e0.775\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.345971563981043%\" valign=\"bottom\"\u003e\n \u003cp\u003e0.877\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"36.96682464454976%\" valign=\"bottom\"\u003e\n \u003cp\u003eVisibility + Odour + Dampness\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.649289099526067%\" valign=\"bottom\"\u003e\n \u003cp\u003e0.616\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.701421800947867%\" valign=\"bottom\"\u003e\n \u003cp\u003e0.503\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"5.213270142180095%\" valign=\"bottom\"\u003e\n \u003cp\u003e0.729\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.085308056872037%\" valign=\"bottom\"\u003e\n \u003cp\u003e0.656\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.345971563981043%\" valign=\"bottom\"\u003e\n \u003cp\u003e0.535\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.345971563981043%\" valign=\"bottom\"\u003e\n \u003cp\u003e0.298\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.345971563981043%\" valign=\"bottom\"\u003e\n \u003cp\u003e0.388\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.345971563981043%\" valign=\"bottom\"\u003e\n \u003cp\u003e0.365\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"36.96682464454976%\" valign=\"bottom\"\u003e\n \u003cp\u003eVisibility + Odour + Water damage\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.649289099526067%\" valign=\"bottom\"\u003e\n \u003cp\u003e0.630\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.701421800947867%\" valign=\"bottom\"\u003e\n \u003cp\u003e0.522\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"5.213270142180095%\" valign=\"bottom\"\u003e\n \u003cp\u003e0.737\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.085308056872037%\" valign=\"bottom\"\u003e\n \u003cp\u003e0.383\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.345971563981043%\" valign=\"bottom\"\u003e\n \u003cp\u003e0.803\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.345971563981043%\" valign=\"bottom\"\u003e\n \u003cp\u003e0.719\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.345971563981043%\" valign=\"bottom\"\u003e\n \u003cp\u003e0.347\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.345971563981043%\" valign=\"bottom\"\u003e\n \u003cp\u003e0.259\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"36.96682464454976%\" valign=\"bottom\"\u003e\n \u003cp\u003eVisibility + Dampness + Water damage\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.649289099526067%\" valign=\"bottom\"\u003e\n \u003cp\u003e0.628\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.701421800947867%\" valign=\"bottom\"\u003e\n \u003cp\u003e0.520\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"5.213270142180095%\" valign=\"bottom\"\u003e\n \u003cp\u003e0.736\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.085308056872037%\" valign=\"bottom\"\u003e\n \u003cp\u003e0.382\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.345971563981043%\" valign=\"bottom\"\u003e\n \u003cp\u003e0.761\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.345971563981043%\" valign=\"bottom\"\u003e\n \u003cp\u003e0.697\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.345971563981043%\" valign=\"bottom\"\u003e\n \u003cp\u003e0.229\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.345971563981043%\" valign=\"bottom\"\u003e\n \u003cp\u003e0.320\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"36.96682464454976%\" valign=\"bottom\"\u003e\n \u003cp\u003eSize + Odour + Dampness\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.649289099526067%\" valign=\"bottom\"\u003e\n \u003cp\u003e0.561\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.701421800947867%\" valign=\"bottom\"\u003e\n \u003cp\u003e0.447\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"5.213270142180095%\" valign=\"bottom\"\u003e\n \u003cp\u003e0.674\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.085308056872037%\" valign=\"bottom\"\u003e\n \u003cp\u003e0.603\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.345971563981043%\" valign=\"bottom\"\u003e\n \u003cp\u003e0.273\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.345971563981043%\" valign=\"bottom\"\u003e\n \u003cp\u003e0.299\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.345971563981043%\" valign=\"bottom\"\u003e\n \u003cp\u003e0.183\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.345971563981043%\" valign=\"bottom\"\u003e\n \u003cp\u003e0.163\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"36.96682464454976%\" valign=\"bottom\"\u003e\n \u003cp\u003eSize + Odour + Water damage\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.649289099526067%\" valign=\"bottom\"\u003e\n \u003cp\u003e0.571\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.701421800947867%\" valign=\"bottom\"\u003e\n \u003cp\u003e0.458\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"5.213270142180095%\" valign=\"bottom\"\u003e\n \u003cp\u003e0.684\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.085308056872037%\" valign=\"bottom\"\u003e\n \u003cp\u003e0.706\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.345971563981043%\" valign=\"bottom\"\u003e\n \u003cp\u003e0.367\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.345971563981043%\" valign=\"bottom\"\u003e\n \u003cp\u003e0.368\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.345971563981043%\" valign=\"bottom\"\u003e\n \u003cp\u003e0.252\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.345971563981043%\" valign=\"bottom\"\u003e\n \u003cp\u003e0.223\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"36.96682464454976%\" valign=\"bottom\"\u003e\n \u003cp\u003eSize + Dampness + Water damage\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.649289099526067%\" valign=\"bottom\"\u003e\n \u003cp\u003e0.541\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.701421800947867%\" valign=\"bottom\"\u003e\n \u003cp\u003e0.432\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"5.213270142180095%\" valign=\"bottom\"\u003e\n \u003cp\u003e0.650\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.085308056872037%\" valign=\"bottom\"\u003e\n \u003cp\u003e0.450\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.345971563981043%\" valign=\"bottom\"\u003e\n \u003cp\u003e0.179\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.345971563981043%\" valign=\"bottom\"\u003e\n \u003cp\u003e0.214\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.345971563981043%\" valign=\"bottom\"\u003e\n \u003cp\u003e\u003cstrong\u003e0.099\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.345971563981043%\" valign=\"bottom\"\u003e\n \u003cp\u003e0.104\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"36.96682464454976%\" valign=\"bottom\"\u003e\n \u003cp\u003eOdour + Dampness + Water damage\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.649289099526067%\" valign=\"bottom\"\u003e\n \u003cp\u003e0.529\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.701421800947867%\" valign=\"bottom\"\u003e\n \u003cp\u003e0.417\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"5.213270142180095%\" valign=\"bottom\"\u003e\n \u003cp\u003e0.641\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.085308056872037%\" valign=\"bottom\"\u003e\n \u003cp\u003e0.327\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.345971563981043%\" valign=\"bottom\"\u003e\n \u003cp\u003e0.162\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.345971563981043%\" valign=\"bottom\"\u003e\n \u003cp\u003e0.190\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.345971563981043%\" valign=\"bottom\"\u003e\n \u003cp\u003e\u003cstrong\u003e0.080\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.345971563981043%\" valign=\"bottom\"\u003e\n \u003cp\u003e\u003cstrong\u003e0.062\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"36.96682464454976%\" valign=\"bottom\"\u003e\n \u003cp\u003e\u003cstrong\u003eFour self-reported measures\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.649289099526067%\" valign=\"bottom\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"7.701421800947867%\" valign=\"bottom\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"5.213270142180095%\" valign=\"bottom\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"12.085308056872037%\" valign=\"bottom\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"7.345971563981043%\" valign=\"bottom\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"7.345971563981043%\" valign=\"bottom\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"7.345971563981043%\" valign=\"bottom\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"7.345971563981043%\" valign=\"bottom\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"36.96682464454976%\" valign=\"bottom\"\u003e\n \u003cp\u003eVisibility + Size + Dampness + Water damage\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.649289099526067%\" valign=\"bottom\"\u003e\n \u003cp\u003e0.653\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.701421800947867%\" valign=\"bottom\"\u003e\n \u003cp\u003e0.544\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"5.213270142180095%\" valign=\"bottom\"\u003e\n \u003cp\u003e0.761\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.085308056872037%\" valign=\"bottom\"\u003e\n \u003cp\u003e\u003cstrong\u003e0.090\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.345971563981043%\" valign=\"bottom\"\u003e\n \u003cp\u003e0.429\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.345971563981043%\" valign=\"bottom\"\u003e\n \u003cp\u003e0.762\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.345971563981043%\" valign=\"bottom\"\u003e\n \u003cp\u003eBaseline\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.345971563981043%\" valign=\"bottom\"\u003e\n \u003cp\u003e0.943\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"36.96682464454976%\" valign=\"bottom\"\u003e\n \u003cp\u003eVisibility + Size + Odour + Dampness\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.649289099526067%\" valign=\"bottom\"\u003e\n \u003cp\u003e0.645\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.701421800947867%\" valign=\"bottom\"\u003e\n \u003cp\u003e0.531\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"5.213270142180095%\" valign=\"bottom\"\u003e\n \u003cp\u003e0.759\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.085308056872037%\" valign=\"bottom\"\u003e\n \u003cp\u003e0.187\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.345971563981043%\" valign=\"bottom\"\u003e\n \u003cp\u003e0.746\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.345971563981043%\" valign=\"bottom\"\u003e\n \u003cp\u003e0.925\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.345971563981043%\" valign=\"bottom\"\u003e\n \u003cp\u003e0.802\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.345971563981043%\" valign=\"bottom\"\u003e\n \u003cp\u003e0.807\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"36.96682464454976%\" valign=\"bottom\"\u003e\n \u003cp\u003eVisibility + Size + Odour + Water damage\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.649289099526067%\" valign=\"bottom\"\u003e\n \u003cp\u003e\u003cu\u003e0.653\u003c/u\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.701421800947867%\" valign=\"bottom\"\u003e\n \u003cp\u003e0.546\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"5.213270142180095%\" valign=\"bottom\"\u003e\n \u003cp\u003e0.761\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.085308056872037%\" valign=\"bottom\"\u003e\n \u003cp\u003e0.103\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.345971563981043%\" valign=\"bottom\"\u003e\n \u003cp\u003e0.475\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.345971563981043%\" valign=\"bottom\"\u003e\n \u003cp\u003e0.745\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.345971563981043%\" valign=\"bottom\"\u003e\n \u003cp\u003e0.962\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.345971563981043%\" valign=\"bottom\"\u003e\n \u003cp\u003e0.705\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"36.96682464454976%\" valign=\"bottom\"\u003e\n \u003cp\u003eVisibility + Odour + Dampness + Water damage\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.649289099526067%\" valign=\"bottom\"\u003e\n \u003cp\u003e0.633\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.701421800947867%\" valign=\"bottom\"\u003e\n \u003cp\u003e0.525\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"5.213270142180095%\" valign=\"bottom\"\u003e\n \u003cp\u003e0.742\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.085308056872037%\" valign=\"bottom\"\u003e\n \u003cp\u003e0.323\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.345971563981043%\" valign=\"bottom\"\u003e\n \u003cp\u003e0.893\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.345971563981043%\" valign=\"bottom\"\u003e\n \u003cp\u003e0.784\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.345971563981043%\" valign=\"bottom\"\u003e\n \u003cp\u003e0.464\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.345971563981043%\" valign=\"bottom\"\u003e\n \u003cp\u003e0.380\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"36.96682464454976%\" valign=\"bottom\"\u003e\n \u003cp\u003eSize + Odour + Dampness + Water damage\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.649289099526067%\" valign=\"bottom\"\u003e\n \u003cp\u003e0.558\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.701421800947867%\" valign=\"bottom\"\u003e\n \u003cp\u003e0.443\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"5.213270142180095%\" valign=\"bottom\"\u003e\n \u003cp\u003e0.672\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.085308056872037%\" valign=\"bottom\"\u003e\n \u003cp\u003e0.582\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.345971563981043%\" valign=\"bottom\"\u003e\n \u003cp\u003e0.271\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.345971563981043%\" valign=\"bottom\"\u003e\n \u003cp\u003e0.299\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.345971563981043%\" valign=\"bottom\"\u003e\n \u003cp\u003e0.172\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.345971563981043%\" valign=\"bottom\"\u003e\n \u003cp\u003e0.152\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"36.96682464454976%\" valign=\"bottom\"\u003e\n \u003cp\u003e\u003cstrong\u003eFive self-reported measures\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.649289099526067%\" valign=\"bottom\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"7.701421800947867%\" valign=\"bottom\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"5.213270142180095%\" valign=\"bottom\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"12.085308056872037%\" valign=\"bottom\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"7.345971563981043%\" valign=\"bottom\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"7.345971563981043%\" valign=\"bottom\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"7.345971563981043%\" valign=\"bottom\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"7.345971563981043%\" valign=\"bottom\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"36.96682464454976%\" valign=\"bottom\"\u003e\n \u003cp\u003eVisibility + Size + Odour + Dampness + Water damage\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.649289099526067%\" valign=\"bottom\"\u003e\n \u003cp\u003e0.652\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.701421800947867%\" valign=\"bottom\"\u003e\n \u003cp\u003e0.544\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"5.213270142180095%\" valign=\"bottom\"\u003e\n \u003cp\u003e0.760\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.085308056872037%\" valign=\"bottom\"\u003e\n \u003cp\u003e0.117\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.345971563981043%\" valign=\"bottom\"\u003e\n \u003cp\u003e0.530\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.345971563981043%\" valign=\"bottom\"\u003e\n \u003cp\u003e0.798\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.345971563981043%\" valign=\"bottom\"\u003e\n \u003cp\u003e0.943\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.345971563981043%\" valign=\"bottom\"\u003e\n \u003cp\u003eBaseline\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003e\u0026nbsp;Table 5. Effects of the covariate on the ROC curve for moderate/severe mould\u003c/p\u003e\n\u003ctable border=\"0\" cellspacing=\"0\" cellpadding=\"0\" width=\"1021\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd width=\"16.666666666666668%\" valign=\"bottom\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"51.86274509803921%\" colspan=\"10\" valign=\"bottom\"\u003e\n \u003cp\u003eSociodemographic status\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"5.588235294117647%\" valign=\"bottom\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"4.607843137254902%\" valign=\"bottom\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.274509803921568%\" colspan=\"4\" valign=\"bottom\"\u003e\n \u003cp\u003eHealth condition\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"16.666666666666668%\" valign=\"bottom\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"9.901960784313726%\" colspan=\"2\" valign=\"bottom\"\u003e\n \u003cp\u003eOlder age\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.901960784313726%\" colspan=\"2\" valign=\"bottom\"\u003e\n \u003cp\u003eMale vs female\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.07843137254902%\" colspan=\"2\" valign=\"bottom\"\u003e\n \u003cp\u003eHigher education\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.784313725490197%\" colspan=\"2\" valign=\"bottom\"\u003e\n \u003cp\u003eEmployed\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.196078431372548%\" colspan=\"2\" valign=\"bottom\"\u003e\n \u003cp\u003eLower household income\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.196078431372548%\" colspan=\"2\" valign=\"bottom\"\u003e\n \u003cp\u003eOwner occupancy\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.196078431372548%\" colspan=\"2\" valign=\"bottom\"\u003e\n \u003cp\u003eAllergy conditions\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.07843137254902%\" colspan=\"2\" valign=\"bottom\"\u003e\n \u003cp\u003eAsthma conditions\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"16.666666666666668%\" rowspan=\"2\" valign=\"bottom\"\u003e\n \u003cp\u003eVisibility\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"5.490196078431373%\" valign=\"bottom\"\u003e\n \u003cp\u003e1.325\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"4.313725490196078%\" valign=\"bottom\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"4.901960784313726%\" valign=\"bottom\"\u003e\n \u003cp\u003e-0.266\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"4.901960784313726%\" valign=\"bottom\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"5.588235294117647%\" valign=\"bottom\"\u003e\n \u003cp\u003e0.240\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"5.490196078431373%\" valign=\"bottom\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"5.294117647058823%\" valign=\"bottom\"\u003e\n \u003cp\u003e-2.825\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"5.588235294117647%\" valign=\"bottom\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"5.490196078431373%\" valign=\"bottom\"\u003e\n \u003cp\u003e\u003cstrong\u003e2.778\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"4.705882352941177%\" valign=\"bottom\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"5.588235294117647%\" valign=\"bottom\"\u003e\n \u003cp\u003e1.549\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"4.607843137254902%\" valign=\"bottom\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"5.588235294117647%\" valign=\"bottom\"\u003e\n \u003cp\u003e1.951\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"4.607843137254902%\" valign=\"bottom\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"5.588235294117647%\" valign=\"bottom\"\u003e\n \u003cp\u003e1.388\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"5.588235294117647%\" valign=\"bottom\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"6.588235294117647%\" valign=\"bottom\"\u003e\n \u003cp\u003e-0.918\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"5.176470588235294%\" valign=\"bottom\"\u003e\n \u003cp\u003e2.476\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"5.882352941176471%\" valign=\"bottom\"\u003e\n \u003cp\u003e-1.101\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"5.882352941176471%\" valign=\"bottom\"\u003e\n \u003cp\u003e2.308\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.705882352941177%\" valign=\"bottom\"\u003e\n \u003cp\u003e-1.737\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.588235294117647%\" valign=\"bottom\"\u003e\n \u003cp\u003e1.710\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.352941176470588%\" valign=\"bottom\"\u003e\n \u003cp\u003e-4.933\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.705882352941177%\" valign=\"bottom\"\u003e\n \u003cp\u003e0.000\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.588235294117647%\" valign=\"bottom\"\u003e\n \u003cp\u003e1.999\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"5.647058823529412%\" valign=\"bottom\"\u003e\n \u003cp\u003e3.800\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.705882352941177%\" valign=\"bottom\"\u003e\n \u003cp\u003e-0.432\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"5.529411764705882%\" valign=\"bottom\"\u003e\n \u003cp\u003e3.238\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.705882352941177%\" valign=\"bottom\"\u003e\n \u003cp\u003e-0.321\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"5.529411764705882%\" valign=\"bottom\"\u003e\n \u003cp\u003e4.094\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.705882352941177%\" valign=\"bottom\"\u003e\n \u003cp\u003e-1.075\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.705882352941177%\" valign=\"bottom\"\u003e\n \u003cp\u003e2.977\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"16.666666666666668%\" rowspan=\"2\" valign=\"bottom\"\u003e\n \u003cp\u003eSize\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"5.490196078431373%\" valign=\"bottom\"\u003e\n \u003cp\u003e\u003cstrong\u003e1.223\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"4.313725490196078%\" valign=\"bottom\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"4.901960784313726%\" valign=\"bottom\"\u003e\n \u003cp\u003e\u003cstrong\u003e-1.420\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"4.901960784313726%\" valign=\"bottom\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"5.588235294117647%\" valign=\"bottom\"\u003e\n \u003cp\u003e-1.937\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"5.490196078431373%\" valign=\"bottom\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"5.294117647058823%\" valign=\"bottom\"\u003e\n \u003cp\u003e0.199\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"5.588235294117647%\" valign=\"bottom\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"5.490196078431373%\" valign=\"bottom\"\u003e\n \u003cp\u003e\u003cstrong\u003e1.855\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"4.705882352941177%\" valign=\"bottom\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"5.588235294117647%\" valign=\"bottom\"\u003e\n \u003cp\u003e-1.104\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"4.607843137254902%\" valign=\"bottom\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"5.588235294117647%\" valign=\"bottom\"\u003e\n \u003cp\u003e-0.384\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"4.607843137254902%\" valign=\"bottom\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"5.588235294117647%\" valign=\"bottom\"\u003e\n \u003cp\u003e1.643\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"5.588235294117647%\" valign=\"bottom\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"6.588235294117647%\" valign=\"bottom\"\u003e\n \u003cp\u003e0.416\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"5.176470588235294%\" valign=\"bottom\"\u003e\n \u003cp\u003e2.214\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"5.882352941176471%\" valign=\"bottom\"\u003e\n \u003cp\u003e-2.277\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"5.882352941176471%\" valign=\"bottom\"\u003e\n \u003cp\u003e-0.725\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.705882352941177%\" valign=\"bottom\"\u003e\n \u003cp\u003e-2.976\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.588235294117647%\" valign=\"bottom\"\u003e\n \u003cp\u003e0.000\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.352941176470588%\" valign=\"bottom\"\u003e\n \u003cp\u003e-0.722\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.705882352941177%\" valign=\"bottom\"\u003e\n \u003cp\u003e1.116\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.588235294117647%\" valign=\"bottom\"\u003e\n \u003cp\u003e0.973\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"5.647058823529412%\" valign=\"bottom\"\u003e\n \u003cp\u003e2.737\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.705882352941177%\" valign=\"bottom\"\u003e\n \u003cp\u003e-2.593\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"5.529411764705882%\" valign=\"bottom\"\u003e\n \u003cp\u003e1.130\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.705882352941177%\" valign=\"bottom\"\u003e\n \u003cp\u003e-1.399\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"5.529411764705882%\" valign=\"bottom\"\u003e\n \u003cp\u003e2.310\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.705882352941177%\" valign=\"bottom\"\u003e\n \u003cp\u003e0.000\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.705882352941177%\" valign=\"bottom\"\u003e\n \u003cp\u003e2.710\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"16.666666666666668%\" rowspan=\"2\" valign=\"bottom\"\u003e\n \u003cp\u003eOdour\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"5.490196078431373%\" valign=\"bottom\"\u003e\n \u003cp\u003e\u003cstrong\u003e1.067\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"4.313725490196078%\" valign=\"bottom\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"4.901960784313726%\" valign=\"bottom\"\u003e\n \u003cp\u003e\u003cstrong\u003e-1.125\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"4.901960784313726%\" valign=\"bottom\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"5.588235294117647%\" valign=\"bottom\"\u003e\n \u003cp\u003e-1.214\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"5.490196078431373%\" valign=\"bottom\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"5.294117647058823%\" valign=\"bottom\"\u003e\n \u003cp\u003e\u003cstrong\u003e-1.716\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"5.588235294117647%\" valign=\"bottom\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"5.490196078431373%\" valign=\"bottom\"\u003e\n \u003cp\u003e\u003cstrong\u003e1.750\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"4.705882352941177%\" valign=\"bottom\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"5.588235294117647%\" valign=\"bottom\"\u003e\n \u003cp\u003e0.383\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"4.607843137254902%\" valign=\"bottom\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"5.588235294117647%\" valign=\"bottom\"\u003e\n \u003cp\u003e0.930\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"4.607843137254902%\" valign=\"bottom\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"5.588235294117647%\" valign=\"bottom\"\u003e\n \u003cp\u003e0.892\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"5.588235294117647%\" valign=\"bottom\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"6.588235294117647%\" valign=\"bottom\"\u003e\n \u003cp\u003e0.324\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"5.176470588235294%\" valign=\"bottom\"\u003e\n \u003cp\u003e1.797\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"5.882352941176471%\" valign=\"bottom\"\u003e\n \u003cp\u003e-2.285\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"5.882352941176471%\" valign=\"bottom\"\u003e\n \u003cp\u003e-0.413\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.705882352941177%\" valign=\"bottom\"\u003e\n \u003cp\u003e-2.052\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.588235294117647%\" valign=\"bottom\"\u003e\n \u003cp\u003e0.754\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.352941176470588%\" valign=\"bottom\"\u003e\n \u003cp\u003e-3.050\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.705882352941177%\" valign=\"bottom\"\u003e\n \u003cp\u003e-0.013\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.588235294117647%\" valign=\"bottom\"\u003e\n \u003cp\u003e0.027\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"5.647058823529412%\" valign=\"bottom\"\u003e\n \u003cp\u003e2.785\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.705882352941177%\" valign=\"bottom\"\u003e\n \u003cp\u003e-1.702\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"5.529411764705882%\" valign=\"bottom\"\u003e\n \u003cp\u003e1.170\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.705882352941177%\" valign=\"bottom\"\u003e\n \u003cp\u003e-1.070\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"5.529411764705882%\" valign=\"bottom\"\u003e\n \u003cp\u003e1.795\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.705882352941177%\" valign=\"bottom\"\u003e\n \u003cp\u003e-1.413\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.705882352941177%\" valign=\"bottom\"\u003e\n \u003cp\u003e1.706\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"16.666666666666668%\" rowspan=\"2\" valign=\"bottom\"\u003e\n \u003cp\u003eDampness\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"5.490196078431373%\" valign=\"bottom\"\u003e\n \u003cp\u003e\u003cstrong\u003e0.843\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"4.313725490196078%\" valign=\"bottom\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"4.901960784313726%\" valign=\"bottom\"\u003e\n \u003cp\u003e1.065\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"4.901960784313726%\" valign=\"bottom\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"5.588235294117647%\" valign=\"bottom\"\u003e\n \u003cp\u003e-0.998\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"5.490196078431373%\" valign=\"bottom\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"5.294117647058823%\" valign=\"bottom\"\u003e\n \u003cp\u003e-0.404\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"5.588235294117647%\" valign=\"bottom\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"5.490196078431373%\" valign=\"bottom\"\u003e\n 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width=\"5.176470588235294%\" valign=\"bottom\"\u003e\n \u003cp\u003e1.571\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"5.882352941176471%\" valign=\"bottom\"\u003e\n \u003cp\u003e-0.904\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"5.882352941176471%\" valign=\"bottom\"\u003e\n \u003cp\u003e2.028\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.705882352941177%\" valign=\"bottom\"\u003e\n \u003cp\u003e-1.996\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.588235294117647%\" valign=\"bottom\"\u003e\n \u003cp\u003e0.000\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.352941176470588%\" valign=\"bottom\"\u003e\n \u003cp\u003e-1.992\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.705882352941177%\" valign=\"bottom\"\u003e\n \u003cp\u003e0.844\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.588235294117647%\" valign=\"bottom\"\u003e\n \u003cp\u003e-0.030\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"5.647058823529412%\" valign=\"bottom\"\u003e\n 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width=\"4.705882352941177%\" valign=\"bottom\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"5.588235294117647%\" valign=\"bottom\"\u003e\n \u003cp\u003e\u003cstrong\u003e0.708\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"4.607843137254902%\" valign=\"bottom\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"5.588235294117647%\" valign=\"bottom\"\u003e\n \u003cp\u003e\u003cstrong\u003e2.683\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"4.607843137254902%\" valign=\"bottom\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"5.588235294117647%\" valign=\"bottom\"\u003e\n \u003cp\u003e1.255\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"5.588235294117647%\" valign=\"bottom\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"6.588235294117647%\" valign=\"bottom\"\u003e\n \u003cp\u003e-1.246\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"5.176470588235294%\" valign=\"bottom\"\u003e\n \u003cp\u003e1.975\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"5.882352941176471%\" valign=\"bottom\"\u003e\n \u003cp\u003e-0.719\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"5.882352941176471%\" valign=\"bottom\"\u003e\n \u003cp\u003e2.148\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.705882352941177%\" valign=\"bottom\"\u003e\n \u003cp\u003e-2.049\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.588235294117647%\" valign=\"bottom\"\u003e\n \u003cp\u003e-0.789\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.352941176470588%\" valign=\"bottom\"\u003e\n \u003cp\u003e-1.580\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.705882352941177%\" valign=\"bottom\"\u003e\n \u003cp\u003e1.383\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.588235294117647%\" valign=\"bottom\"\u003e\n \u003cp\u003e0.430\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"5.647058823529412%\" valign=\"bottom\"\u003e\n \u003cp\u003e2.443\u003c/p\u003e\n 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valign=\"bottom\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"5.588235294117647%\" valign=\"bottom\"\u003e\n \u003cp\u003e1.050\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"4.607843137254902%\" valign=\"bottom\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"5.588235294117647%\" valign=\"bottom\"\u003e\n \u003cp\u003e1.116\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"4.607843137254902%\" valign=\"bottom\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"5.588235294117647%\" valign=\"bottom\"\u003e\n \u003cp\u003e-0.589\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"5.588235294117647%\" valign=\"bottom\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"6.588235294117647%\" valign=\"bottom\"\u003e\n \u003cp\u003e0.844\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"5.176470588235294%\" valign=\"bottom\"\u003e\n \u003cp\u003e3.523\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"5.882352941176471%\" valign=\"bottom\"\u003e\n \u003cp\u003e-2.308\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"5.882352941176471%\" valign=\"bottom\"\u003e\n \u003cp\u003e1.310\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.705882352941177%\" valign=\"bottom\"\u003e\n \u003cp\u003e-1.239\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.588235294117647%\" valign=\"bottom\"\u003e\n \u003cp\u003e2.848\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.352941176470588%\" valign=\"bottom\"\u003e\n \u003cp\u003e-2.249\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.705882352941177%\" valign=\"bottom\"\u003e\n \u003cp\u003e1.577\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.588235294117647%\" valign=\"bottom\"\u003e\n \u003cp\u003e-1.265\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"5.647058823529412%\" valign=\"bottom\"\u003e\n \u003cp\u003e2.346\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.705882352941177%\" valign=\"bottom\"\u003e\n 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valign=\"bottom\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"4.901960784313726%\" valign=\"bottom\"\u003e\n \u003cp\u003e-0.218\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"4.901960784313726%\" valign=\"bottom\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"5.588235294117647%\" valign=\"bottom\"\u003e\n \u003cp\u003e-1.030\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"5.490196078431373%\" valign=\"bottom\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"5.294117647058823%\" valign=\"bottom\"\u003e\n \u003cp\u003e\u003cstrong\u003e-2.259\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"5.588235294117647%\" valign=\"bottom\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"5.490196078431373%\" valign=\"bottom\"\u003e\n \u003cp\u003e\u003cstrong\u003e1.611\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"4.705882352941177%\" valign=\"bottom\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"5.588235294117647%\" valign=\"bottom\"\u003e\n \u003cp\u003e0.689\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"4.607843137254902%\" valign=\"bottom\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"5.588235294117647%\" valign=\"bottom\"\u003e\n \u003cp\u003e0.175\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"4.607843137254902%\" valign=\"bottom\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"5.588235294117647%\" valign=\"bottom\"\u003e\n \u003cp\u003e0.767\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"5.588235294117647%\" valign=\"bottom\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"6.588235294117647%\" valign=\"bottom\"\u003e\n \u003cp\u003e-0.278\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"5.176470588235294%\" valign=\"bottom\"\u003e\n \u003cp\u003e1.546\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"5.882352941176471%\" valign=\"bottom\"\u003e\n \u003cp\u003e-1.179\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"5.882352941176471%\" valign=\"bottom\"\u003e\n \u003cp\u003e1.186\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.705882352941177%\" valign=\"bottom\"\u003e\n \u003cp\u003e-2.268\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.588235294117647%\" valign=\"bottom\"\u003e\n \u003cp\u003e0.367\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.352941176470588%\" valign=\"bottom\"\u003e\n \u003cp\u003e-3.387\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.705882352941177%\" valign=\"bottom\"\u003e\n \u003cp\u003e-1.083\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.588235294117647%\" valign=\"bottom\"\u003e\n \u003cp\u003e0.844\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"5.647058823529412%\" valign=\"bottom\"\u003e\n \u003cp\u003e3.129\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.705882352941177%\" valign=\"bottom\"\u003e\n \u003cp\u003e-0.169\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"5.529411764705882%\" valign=\"bottom\"\u003e\n \u003cp\u003e1.944\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.705882352941177%\" valign=\"bottom\"\u003e\n \u003cp\u003e-0.715\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"5.529411764705882%\" valign=\"bottom\"\u003e\n \u003cp\u003e1.743\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.705882352941177%\" valign=\"bottom\"\u003e\n \u003cp\u003e-0.440\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.705882352941177%\" valign=\"bottom\"\u003e\n \u003cp\u003e2.099\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"16.65034280117532%\" valign=\"bottom\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"83.34965719882469%\" colspan=\"16\" valign=\"bottom\"\u003e\n \u003cp\u003eDwelling condition\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"16.666666666666668%\" valign=\"bottom\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"9.901960784313726%\" colspan=\"2\" valign=\"bottom\"\u003e\n \u003cp\u003eMajor cracks in walls/floors\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.901960784313726%\" colspan=\"2\" valign=\"bottom\"\u003e\n \u003cp\u003eSinking/moving foundations\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.07843137254902%\" colspan=\"2\" valign=\"bottom\"\u003e\n \u003cp\u003eWood rot/termite damage\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.784313725490197%\" colspan=\"2\" valign=\"bottom\"\u003e\n \u003cp\u003eMajor plumbing problems\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.196078431372548%\" colspan=\"2\" valign=\"bottom\"\u003e\n \u003cp\u003eWalls/windows not level\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.196078431372548%\" colspan=\"2\" valign=\"bottom\"\u003e\n \u003cp\u003eMajor roof defect\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.196078431372548%\" colspan=\"2\" valign=\"bottom\"\u003e\n \u003cp\u003eWell-insulated dwelling\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.07843137254902%\" colspan=\"2\" valign=\"bottom\"\u003e\n \u003cp\u003e(Semi)Detached house\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"16.666666666666668%\" rowspan=\"2\" valign=\"bottom\"\u003e\n \u003cp\u003eVisibility\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"5.490196078431373%\" valign=\"bottom\"\u003e\n \u003cp\u003e-0.458\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"4.313725490196078%\" valign=\"bottom\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"4.901960784313726%\" valign=\"bottom\"\u003e\n \u003cp\u003e-0.008\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"4.901960784313726%\" valign=\"bottom\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"5.588235294117647%\" valign=\"bottom\"\u003e\n \u003cp\u003e-0.109\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"5.490196078431373%\" valign=\"bottom\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"5.294117647058823%\" valign=\"bottom\"\u003e\n \u003cp\u003e.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"5.588235294117647%\" valign=\"bottom\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"5.490196078431373%\" valign=\"bottom\"\u003e\n \u003cp\u003e1.950\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"4.705882352941177%\" valign=\"bottom\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"5.588235294117647%\" valign=\"bottom\"\u003e\n \u003cp\u003e-0.240\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"4.607843137254902%\" valign=\"bottom\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"5.588235294117647%\" valign=\"bottom\"\u003e\n \u003cp\u003e2.212\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"4.607843137254902%\" valign=\"bottom\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"5.588235294117647%\" valign=\"bottom\"\u003e\n \u003cp\u003e-0.742\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"5.588235294117647%\" valign=\"bottom\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"6.588235294117647%\" valign=\"bottom\"\u003e\n \u003cp\u003e-1.395\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"5.176470588235294%\" valign=\"bottom\"\u003e\n \u003cp\u003e0.230\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"5.882352941176471%\" valign=\"bottom\"\u003e\n \u003cp\u003e-0.949\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"5.882352941176471%\" valign=\"bottom\"\u003e\n \u003cp\u003e2.351\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.705882352941177%\" valign=\"bottom\"\u003e\n \u003cp\u003e-1.003\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.588235294117647%\" valign=\"bottom\"\u003e\n \u003cp\u003e0.858\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.352941176470588%\" valign=\"bottom\"\u003e\n \u003cp\u003e.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.705882352941177%\" valign=\"bottom\"\u003e\n \u003cp\u003e.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.588235294117647%\" valign=\"bottom\"\u003e\n \u003cp\u003e0.000\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"5.647058823529412%\" valign=\"bottom\"\u003e\n \u003cp\u003e3.895\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.705882352941177%\" valign=\"bottom\"\u003e\n \u003cp\u003e-1.194\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"5.529411764705882%\" valign=\"bottom\"\u003e\n \u003cp\u003e1.595\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.705882352941177%\" valign=\"bottom\"\u003e\n \u003cp\u003e0.000\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"5.529411764705882%\" valign=\"bottom\"\u003e\n \u003cp\u003e3.964\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.705882352941177%\" valign=\"bottom\"\u003e\n \u003cp\u003e-1.526\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.705882352941177%\" valign=\"bottom\"\u003e\n \u003cp\u003e0.344\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"16.666666666666668%\" rowspan=\"2\" valign=\"bottom\"\u003e\n \u003cp\u003eSize\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"5.490196078431373%\" valign=\"bottom\"\u003e\n \u003cp\u003e-0.157\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"4.313725490196078%\" valign=\"bottom\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"4.901960784313726%\" valign=\"bottom\"\u003e\n \u003cp\u003e0.440\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"4.901960784313726%\" valign=\"bottom\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"5.588235294117647%\" valign=\"bottom\"\u003e\n \u003cp\u003e1.879\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"5.490196078431373%\" valign=\"bottom\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"5.294117647058823%\" valign=\"bottom\"\u003e\n \u003cp\u003e\u003cstrong\u003e2.687\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"5.588235294117647%\" valign=\"bottom\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"5.490196078431373%\" valign=\"bottom\"\u003e\n \u003cp\u003e1.857\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"4.705882352941177%\" valign=\"bottom\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"5.588235294117647%\" valign=\"bottom\"\u003e\n \u003cp\u003e1.737\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"4.607843137254902%\" valign=\"bottom\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"5.588235294117647%\" valign=\"bottom\"\u003e\n \u003cp\u003e1.330\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"4.607843137254902%\" valign=\"bottom\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"5.588235294117647%\" valign=\"bottom\"\u003e\n \u003cp\u003e\u003cstrong\u003e-0.914\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"5.588235294117647%\" valign=\"bottom\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"6.588235294117647%\" valign=\"bottom\"\u003e\n \u003cp\u003e-1.579\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"5.176470588235294%\" valign=\"bottom\"\u003e\n \u003cp\u003e2.015\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"5.882352941176471%\" valign=\"bottom\"\u003e\n \u003cp\u003e-0.933\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"5.882352941176471%\" valign=\"bottom\"\u003e\n \u003cp\u003e1.659\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.705882352941177%\" valign=\"bottom\"\u003e\n \u003cp\u003e-0.265\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.588235294117647%\" valign=\"bottom\"\u003e\n \u003cp\u003e2.945\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.352941176470588%\" valign=\"bottom\"\u003e\n \u003cp\u003e0.907\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.705882352941177%\" valign=\"bottom\"\u003e\n \u003cp\u003e4.466\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.588235294117647%\" valign=\"bottom\"\u003e\n \u003cp\u003e-0.291\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"5.647058823529412%\" valign=\"bottom\"\u003e\n \u003cp\u003e3.319\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.705882352941177%\" valign=\"bottom\"\u003e\n \u003cp\u003e-0.194\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"5.529411764705882%\" valign=\"bottom\"\u003e\n \u003cp\u003e2.955\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.705882352941177%\" valign=\"bottom\"\u003e\n \u003cp\u003e-0.727\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"5.529411764705882%\" valign=\"bottom\"\u003e\n \u003cp\u003e2.385\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.705882352941177%\" valign=\"bottom\"\u003e\n \u003cp\u003e-1.840\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.705882352941177%\" valign=\"bottom\"\u003e\n \u003cp\u003e-0.300\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"16.666666666666668%\" rowspan=\"2\" valign=\"bottom\"\u003e\n \u003cp\u003eOdour\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"5.490196078431373%\" valign=\"bottom\"\u003e\n \u003cp\u003e0.105\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"4.313725490196078%\" valign=\"bottom\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"4.901960784313726%\" valign=\"bottom\"\u003e\n \u003cp\u003e0.440\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"4.901960784313726%\" valign=\"bottom\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"5.588235294117647%\" valign=\"bottom\"\u003e\n \u003cp\u003e-0.381\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"5.490196078431373%\" valign=\"bottom\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"5.294117647058823%\" valign=\"bottom\"\u003e\n \u003cp\u003e\u003cstrong\u003e2.285\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"5.588235294117647%\" valign=\"bottom\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"5.490196078431373%\" valign=\"bottom\"\u003e\n \u003cp\u003e0.137\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"4.705882352941177%\" valign=\"bottom\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"5.588235294117647%\" valign=\"bottom\"\u003e\n \u003cp\u003e0.496\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"4.607843137254902%\" valign=\"bottom\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"5.588235294117647%\" valign=\"bottom\"\u003e\n \u003cp\u003e0.442\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"4.607843137254902%\" valign=\"bottom\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"5.588235294117647%\" valign=\"bottom\"\u003e\n \u003cp\u003e-1.020\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"5.588235294117647%\" valign=\"bottom\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"6.588235294117647%\" valign=\"bottom\"\u003e\n \u003cp\u003e-0.928\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"5.176470588235294%\" valign=\"bottom\"\u003e\n \u003cp\u003e1.848\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"5.882352941176471%\" valign=\"bottom\"\u003e\n \u003cp\u003e-0.629\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"5.882352941176471%\" valign=\"bottom\"\u003e\n \u003cp\u003e2.232\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.705882352941177%\" valign=\"bottom\"\u003e\n \u003cp\u003e-1.360\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.588235294117647%\" valign=\"bottom\"\u003e\n \u003cp\u003e1.589\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.352941176470588%\" valign=\"bottom\"\u003e\n \u003cp\u003e0.154\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.705882352941177%\" valign=\"bottom\"\u003e\n \u003cp\u003e4.416\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.588235294117647%\" valign=\"bottom\"\u003e\n \u003cp\u003e-0.804\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"5.647058823529412%\" valign=\"bottom\"\u003e\n \u003cp\u003e1.894\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.705882352941177%\" valign=\"bottom\"\u003e\n \u003cp\u003e-0.287\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"5.529411764705882%\" valign=\"bottom\"\u003e\n \u003cp\u003e2.462\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.705882352941177%\" valign=\"bottom\"\u003e\n \u003cp\u003e-0.814\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"5.529411764705882%\" valign=\"bottom\"\u003e\n \u003cp\u003e1.059\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.705882352941177%\" valign=\"bottom\"\u003e\n \u003cp\u003e-1.906\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.705882352941177%\" valign=\"bottom\"\u003e\n \u003cp\u003e1.022\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"16.666666666666668%\" rowspan=\"2\" valign=\"bottom\"\u003e\n \u003cp\u003eDampness\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"5.490196078431373%\" valign=\"bottom\"\u003e\n \u003cp\u003e-0.030\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"4.313725490196078%\" valign=\"bottom\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"4.901960784313726%\" valign=\"bottom\"\u003e\n \u003cp\u003e0.093\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"4.901960784313726%\" valign=\"bottom\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"5.588235294117647%\" valign=\"bottom\"\u003e\n \u003cp\u003e0.034\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"5.490196078431373%\" valign=\"bottom\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"5.294117647058823%\" valign=\"bottom\"\u003e\n \u003cp\u003e\u003cstrong\u003e2.636\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"5.588235294117647%\" valign=\"bottom\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"5.490196078431373%\" valign=\"bottom\"\u003e\n \u003cp\u003e0.275\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"4.705882352941177%\" valign=\"bottom\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"5.588235294117647%\" valign=\"bottom\"\u003e\n \u003cp\u003e0.285\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"4.607843137254902%\" valign=\"bottom\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"5.588235294117647%\" valign=\"bottom\"\u003e\n \u003cp\u003e0.895\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"4.607843137254902%\" valign=\"bottom\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"5.588235294117647%\" valign=\"bottom\"\u003e\n \u003cp\u003e-1.507\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"5.588235294117647%\" valign=\"bottom\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"6.588235294117647%\" valign=\"bottom\"\u003e\n \u003cp\u003e-1.374\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"5.176470588235294%\" valign=\"bottom\"\u003e\n \u003cp\u003e1.709\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"5.882352941176471%\" valign=\"bottom\"\u003e\n \u003cp\u003e-0.987\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"5.882352941176471%\" valign=\"bottom\"\u003e\n \u003cp\u003e1.965\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.705882352941177%\" valign=\"bottom\"\u003e\n \u003cp\u003e-1.257\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.588235294117647%\" valign=\"bottom\"\u003e\n \u003cp\u003e1.738\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.352941176470588%\" valign=\"bottom\"\u003e\n \u003cp\u003e2.179\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.705882352941177%\" valign=\"bottom\"\u003e\n \u003cp\u003e3.255\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.588235294117647%\" valign=\"bottom\"\u003e\n \u003cp\u003e-0.838\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"5.647058823529412%\" valign=\"bottom\"\u003e\n \u003cp\u003e1.800\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.705882352941177%\" valign=\"bottom\"\u003e\n \u003cp\u003e-0.705\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"5.529411764705882%\" valign=\"bottom\"\u003e\n 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valign=\"bottom\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"5.588235294117647%\" valign=\"bottom\"\u003e\n \u003cp\u003e1.191\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"4.607843137254902%\" valign=\"bottom\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"5.588235294117647%\" valign=\"bottom\"\u003e\n \u003cp\u003e-0.967\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"5.588235294117647%\" valign=\"bottom\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"6.588235294117647%\" valign=\"bottom\"\u003e\n \u003cp\u003e-1.134\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"5.176470588235294%\" valign=\"bottom\"\u003e\n \u003cp\u003e1.851\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"5.882352941176471%\" valign=\"bottom\"\u003e\n \u003cp\u003e-0.592\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"5.882352941176471%\" valign=\"bottom\"\u003e\n \u003cp\u003e1.755\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.705882352941177%\" valign=\"bottom\"\u003e\n \u003cp\u003e-1.179\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.588235294117647%\" valign=\"bottom\"\u003e\n \u003cp\u003e1.919\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.352941176470588%\" valign=\"bottom\"\u003e\n \u003cp\u003e2.310\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.705882352941177%\" valign=\"bottom\"\u003e\n \u003cp\u003e3.560\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.588235294117647%\" valign=\"bottom\"\u003e\n \u003cp\u003e-1.093\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"5.647058823529412%\" valign=\"bottom\"\u003e\n \u003cp\u003e1.666\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.705882352941177%\" valign=\"bottom\"\u003e\n \u003cp\u003e-0.527\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"5.529411764705882%\" valign=\"bottom\"\u003e\n \u003cp\u003e2.112\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.705882352941177%\" valign=\"bottom\"\u003e\n 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valign=\"bottom\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"5.588235294117647%\" valign=\"bottom\"\u003e\n \u003cp\u003e-0.109\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"5.490196078431373%\" valign=\"bottom\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"5.294117647058823%\" valign=\"bottom\"\u003e\n \u003cp\u003e\u003cstrong\u003e0.696\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"5.588235294117647%\" valign=\"bottom\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"5.490196078431373%\" valign=\"bottom\"\u003e\n \u003cp\u003e0.122\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"4.705882352941177%\" valign=\"bottom\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"5.588235294117647%\" valign=\"bottom\"\u003e\n \u003cp\u003e0.394\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"4.607843137254902%\" valign=\"bottom\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"5.588235294117647%\" valign=\"bottom\"\u003e\n 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width=\"6.588235294117647%\" valign=\"bottom\"\u003e\n \u003cp\u003e1.224\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.352941176470588%\" valign=\"bottom\"\u003e\n \u003cp\u003e0.254\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.705882352941177%\" valign=\"bottom\"\u003e\n \u003cp\u003e1.032\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.588235294117647%\" valign=\"bottom\"\u003e\n \u003cp\u003e-0.617\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"5.647058823529412%\" valign=\"bottom\"\u003e\n \u003cp\u003e3.029\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.705882352941177%\" valign=\"bottom\"\u003e\n \u003cp\u003e0.000\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"5.529411764705882%\" valign=\"bottom\"\u003e\n \u003cp\u003e1.024\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.705882352941177%\" valign=\"bottom\"\u003e\n \u003cp\u003e-0.463\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"5.529411764705882%\" valign=\"bottom\"\u003e\n \u003cp\u003e2.875\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.705882352941177%\" valign=\"bottom\"\u003e\n \u003cp\u003e-2.911\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.705882352941177%\" valign=\"bottom\"\u003e\n \u003cp\u003e1.116\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"16.666666666666668%\" rowspan=\"2\" valign=\"bottom\"\u003e\n \u003cp\u003eSeverity\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"5.490196078431373%\" valign=\"bottom\"\u003e\n \u003cp\u003e0.113\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"4.313725490196078%\" valign=\"bottom\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"4.901960784313726%\" valign=\"bottom\"\u003e\n \u003cp\u003e0.747\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"4.901960784313726%\" valign=\"bottom\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"5.588235294117647%\" valign=\"bottom\"\u003e\n \u003cp\u003e0.175\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"5.490196078431373%\" valign=\"bottom\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"5.294117647058823%\" valign=\"bottom\"\u003e\n \u003cp\u003e\u003cstrong\u003e3.089\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"5.588235294117647%\" valign=\"bottom\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"5.490196078431373%\" valign=\"bottom\"\u003e\n \u003cp\u003e0.428\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"4.705882352941177%\" valign=\"bottom\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"5.588235294117647%\" valign=\"bottom\"\u003e\n \u003cp\u003e0.675\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"4.607843137254902%\" valign=\"bottom\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"5.588235294117647%\" valign=\"bottom\"\u003e\n \u003cp\u003e0.870\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"4.607843137254902%\" valign=\"bottom\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"5.588235294117647%\" valign=\"bottom\"\u003e\n \u003cp\u003e0.004\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"5.588235294117647%\" valign=\"bottom\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"6.588235294117647%\" valign=\"bottom\"\u003e\n \u003cp\u003e-1.216\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"5.176470588235294%\" valign=\"bottom\"\u003e\n \u003cp\u003e0.817\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"5.882352941176471%\" valign=\"bottom\"\u003e\n \u003cp\u003e-1.014\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"5.882352941176471%\" valign=\"bottom\"\u003e\n \u003cp\u003e1.698\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.705882352941177%\" valign=\"bottom\"\u003e\n \u003cp\u003e-1.230\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.588235294117647%\" valign=\"bottom\"\u003e\n \u003cp\u003e1.059\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.352941176470588%\" valign=\"bottom\"\u003e\n \u003cp\u003e2.608\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.705882352941177%\" valign=\"bottom\"\u003e\n \u003cp\u003e4.141\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.588235294117647%\" valign=\"bottom\"\u003e\n \u003cp\u003e-0.776\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"5.647058823529412%\" valign=\"bottom\"\u003e\n \u003cp\u003e1.593\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.705882352941177%\" valign=\"bottom\"\u003e\n \u003cp\u003e-0.663\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"5.529411764705882%\" valign=\"bottom\"\u003e\n \u003cp\u003e2.945\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.705882352941177%\" valign=\"bottom\"\u003e\n \u003cp\u003e-0.531\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"5.529411764705882%\" valign=\"bottom\"\u003e\n \u003cp\u003e1.733\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.705882352941177%\" valign=\"bottom\"\u003e\n \u003cp\u003e-0.618\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.705882352941177%\" valign=\"bottom\"\u003e\n \u003cp\u003e1.314\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003eNotes: Coefficients and 95%CI are reported.\u003cbr\u003e\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eTable 6. Effects of the covariate on the ROC curve for severe mould\u003c/p\u003e\n\u003ctable border=\"0\" cellspacing=\"0\" cellpadding=\"0\" width=\"1014\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd width=\"16.765285996055226%\" valign=\"bottom\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"63.01775147928994%\" colspan=\"12\" valign=\"bottom\"\u003e\n \u003cp\u003eSociodemographic status\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"20.216962524654832%\" colspan=\"4\" valign=\"bottom\"\u003e\n \u003cp\u003eHealth condition\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"16.765285996055226%\" valign=\"bottom\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"10.355029585798816%\" colspan=\"2\" valign=\"bottom\"\u003e\n \u003cp\u003eOlder age\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.045364891518737%\" colspan=\"2\" valign=\"bottom\"\u003e\n \u003cp\u003eMale vs female\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.045364891518737%\" colspan=\"2\" valign=\"bottom\"\u003e\n \u003cp\u003eHigher education\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.355029585798816%\" colspan=\"2\" valign=\"bottom\"\u003e\n \u003cp\u003eEmployed\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.355029585798816%\" colspan=\"2\" valign=\"bottom\"\u003e\n \u003cp\u003eLower household income\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.861932938856016%\" colspan=\"2\" valign=\"bottom\"\u003e\n \u003cp\u003eOwner occupancy\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.368836291913215%\" colspan=\"2\" valign=\"bottom\"\u003e\n \u003cp\u003eAllergy conditions\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.848126232741617%\" colspan=\"2\" valign=\"bottom\"\u003e\n \u003cp\u003eAsthma conditions\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"16.765285996055226%\" rowspan=\"2\" valign=\"bottom\"\u003e\n \u003cp\u003eVisibility\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"5.522682445759369%\" valign=\"bottom\"\u003e\n \u003cp\u003e0.781\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"4.832347140039448%\" valign=\"bottom\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"5.522682445759369%\" valign=\"bottom\"\u003e\n \u003cp\u003e-0.477\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"5.522682445759369%\" valign=\"bottom\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"5.522682445759369%\" valign=\"bottom\"\u003e\n \u003cp\u003e0.202\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"5.522682445759369%\" valign=\"bottom\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"4.832347140039448%\" valign=\"bottom\"\u003e\n \u003cp\u003e-2.851\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"5.522682445759369%\" valign=\"bottom\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"5.522682445759369%\" valign=\"bottom\"\u003e\n \u003cp\u003e0.007\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"4.832347140039448%\" valign=\"bottom\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"5.522682445759369%\" valign=\"bottom\"\u003e\n \u003cp\u003e1.549\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"4.339250493096647%\" valign=\"bottom\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"5.029585798816568%\" valign=\"bottom\"\u003e\n \u003cp\u003e-0.318\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"4.339250493096647%\" valign=\"bottom\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"4.930966469428008%\" valign=\"bottom\"\u003e\n \u003cp\u003e1.803\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"5.9171597633136095%\" valign=\"bottom\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"6.6350710900473935%\" valign=\"bottom\"\u003e\n \u003cp\u003e-2.207\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"5.805687203791469%\" valign=\"bottom\"\u003e\n \u003cp\u003e1.949\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.6350710900473935%\" valign=\"bottom\"\u003e\n \u003cp\u003e-1.370\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.6350710900473935%\" valign=\"bottom\"\u003e\n \u003cp\u003e1.714\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.6350710900473935%\" valign=\"bottom\"\u003e\n \u003cp\u003e-3.100\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.6350710900473935%\" valign=\"bottom\"\u003e\n \u003cp\u003e1.128\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"5.805687203791469%\" valign=\"bottom\"\u003e\n \u003cp\u003e-5.025\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.6350710900473935%\" valign=\"bottom\"\u003e\n \u003cp\u003e0.000\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.6350710900473935%\" valign=\"bottom\"\u003e\n \u003cp\u003e-1.027\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"5.805687203791469%\" valign=\"bottom\"\u003e\n \u003cp\u003e2.858\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.6350710900473935%\" valign=\"bottom\"\u003e\n \u003cp\u003e-0.432\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"5.213270142180095%\" valign=\"bottom\"\u003e\n \u003cp\u003e3.238\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.042654028436019%\" valign=\"bottom\"\u003e\n \u003cp\u003e-1.644\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"5.213270142180095%\" valign=\"bottom\"\u003e\n \u003cp\u003e2.509\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"5.924170616113744%\" valign=\"bottom\"\u003e\n \u003cp\u003e-1.045\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.109004739336493%\" valign=\"bottom\"\u003e\n \u003cp\u003e3.862\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"16.765285996055226%\" rowspan=\"2\" valign=\"bottom\"\u003e\n \u003cp\u003eSize\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"5.522682445759369%\" valign=\"bottom\"\u003e\n \u003cp\u003e0.863\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"4.832347140039448%\" valign=\"bottom\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"5.522682445759369%\" valign=\"bottom\"\u003e\n \u003cp\u003e.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"5.522682445759369%\" valign=\"bottom\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"5.522682445759369%\" valign=\"bottom\"\u003e\n \u003cp\u003e0.361\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"5.522682445759369%\" valign=\"bottom\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"4.832347140039448%\" valign=\"bottom\"\u003e\n \u003cp\u003e-0.069\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"5.522682445759369%\" valign=\"bottom\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"5.522682445759369%\" valign=\"bottom\"\u003e\n \u003cp\u003e\u003cstrong\u003e1.991\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"4.832347140039448%\" valign=\"bottom\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"5.522682445759369%\" valign=\"bottom\"\u003e\n \u003cp\u003e-1.104\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"4.339250493096647%\" valign=\"bottom\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"5.029585798816568%\" valign=\"bottom\"\u003e\n \u003cp\u003e-0.202\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"4.339250493096647%\" valign=\"bottom\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"4.930966469428008%\" valign=\"bottom\"\u003e\n \u003cp\u003e\u003cstrong\u003e1.891\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"5.9171597633136095%\" valign=\"bottom\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"6.6350710900473935%\" valign=\"bottom\"\u003e\n \u003cp\u003e-1.634\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"5.805687203791469%\" valign=\"bottom\"\u003e\n \u003cp\u003e1.918\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.6350710900473935%\" valign=\"bottom\"\u003e\n \u003cp\u003e.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.6350710900473935%\" valign=\"bottom\"\u003e\n \u003cp\u003e.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.6350710900473935%\" valign=\"bottom\"\u003e\n \u003cp\u003e0.000\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.6350710900473935%\" valign=\"bottom\"\u003e\n \u003cp\u003e0.830\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"5.805687203791469%\" valign=\"bottom\"\u003e\n \u003cp\u003e-2.099\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.6350710900473935%\" valign=\"bottom\"\u003e\n \u003cp\u003e0.729\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.6350710900473935%\" valign=\"bottom\"\u003e\n \u003cp\u003e0.331\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"5.805687203791469%\" valign=\"bottom\"\u003e\n \u003cp\u003e3.651\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.6350710900473935%\" valign=\"bottom\"\u003e\n \u003cp\u003e-2.593\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"5.213270142180095%\" valign=\"bottom\"\u003e\n \u003cp\u003e1.130\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.042654028436019%\" valign=\"bottom\"\u003e\n \u003cp\u003e-1.631\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"5.213270142180095%\" valign=\"bottom\"\u003e\n \u003cp\u003e0.328\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"5.924170616113744%\" valign=\"bottom\"\u003e\n \u003cp\u003e0.059\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.109004739336493%\" valign=\"bottom\"\u003e\n \u003cp\u003e3.722\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"16.765285996055226%\" rowspan=\"2\" valign=\"bottom\"\u003e\n \u003cp\u003eOdour\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"5.522682445759369%\" valign=\"bottom\"\u003e\n \u003cp\u003e0.825\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"4.832347140039448%\" valign=\"bottom\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"5.522682445759369%\" valign=\"bottom\"\u003e\n \u003cp\u003e-1.715\u003c/p\u003e\n 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valign=\"bottom\"\u003e\n \u003cp\u003e1.322\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"4.339250493096647%\" valign=\"bottom\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"4.930966469428008%\" valign=\"bottom\"\u003e\n \u003cp\u003e1.270\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"5.9171597633136095%\" valign=\"bottom\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"6.6350710900473935%\" valign=\"bottom\"\u003e\n \u003cp\u003e-0.711\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"5.805687203791469%\" valign=\"bottom\"\u003e\n \u003cp\u003e1.728\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.6350710900473935%\" valign=\"bottom\"\u003e\n \u003cp\u003e-2.812\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.6350710900473935%\" valign=\"bottom\"\u003e\n \u003cp\u003e0.000\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.6350710900473935%\" valign=\"bottom\"\u003e\n \u003cp\u003e.\u003c/p\u003e\n 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valign=\"bottom\"\u003e\n \u003cp\u003e2.576\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"5.924170616113744%\" valign=\"bottom\"\u003e\n \u003cp\u003e0.000\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.109004739336493%\" valign=\"bottom\"\u003e\n \u003cp\u003e2.456\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"16.765285996055226%\" rowspan=\"2\" valign=\"bottom\"\u003e\n \u003cp\u003eDampness\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"5.522682445759369%\" valign=\"bottom\"\u003e\n \u003cp\u003e\u003cstrong\u003e0.775\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"4.832347140039448%\" valign=\"bottom\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"5.522682445759369%\" valign=\"bottom\"\u003e\n \u003cp\u003e\u003cstrong\u003e-1.718\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"5.522682445759369%\" valign=\"bottom\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"5.522682445759369%\" valign=\"bottom\"\u003e\n \u003cp\u003e-1.004\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"5.522682445759369%\" valign=\"bottom\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"4.832347140039448%\" valign=\"bottom\"\u003e\n \u003cp\u003e-0.306\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"5.522682445759369%\" valign=\"bottom\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"5.522682445759369%\" valign=\"bottom\"\u003e\n \u003cp\u003e-0.352\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"4.832347140039448%\" valign=\"bottom\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"5.522682445759369%\" valign=\"bottom\"\u003e\n \u003cp\u003e1.147\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"4.339250493096647%\" valign=\"bottom\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"5.029585798816568%\" valign=\"bottom\"\u003e\n \u003cp\u003e-0.447\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"4.339250493096647%\" valign=\"bottom\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"4.930966469428008%\" valign=\"bottom\"\u003e\n \u003cp\u003e1.447\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"5.9171597633136095%\" valign=\"bottom\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"6.6350710900473935%\" valign=\"bottom\"\u003e\n \u003cp\u003e0.127\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"5.805687203791469%\" valign=\"bottom\"\u003e\n \u003cp\u003e1.632\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.6350710900473935%\" valign=\"bottom\"\u003e\n \u003cp\u003e-2.501\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.6350710900473935%\" valign=\"bottom\"\u003e\n \u003cp\u003e-1.314\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.6350710900473935%\" valign=\"bottom\"\u003e\n \u003cp\u003e-1.754\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.6350710900473935%\" valign=\"bottom\"\u003e\n \u003cp\u003e0.000\u003c/p\u003e\n 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valign=\"bottom\"\u003e\n \u003cp\u003e0.000\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.109004739336493%\" valign=\"bottom\"\u003e\n \u003cp\u003e2.509\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"16.765285996055226%\" rowspan=\"2\" valign=\"bottom\"\u003e\n \u003cp\u003eWater damage\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"5.522682445759369%\" valign=\"bottom\"\u003e\n \u003cp\u003e0.850\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"4.832347140039448%\" valign=\"bottom\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"5.522682445759369%\" valign=\"bottom\"\u003e\n \u003cp\u003e1.224\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"5.522682445759369%\" valign=\"bottom\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"5.522682445759369%\" valign=\"bottom\"\u003e\n \u003cp\u003e\u003cstrong\u003e-1.242\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"5.522682445759369%\" valign=\"bottom\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"4.832347140039448%\" valign=\"bottom\"\u003e\n \u003cp\u003e\u003cstrong\u003e-2.034\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"5.522682445759369%\" valign=\"bottom\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"5.522682445759369%\" valign=\"bottom\"\u003e\n \u003cp\u003e-0.779\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"4.832347140039448%\" valign=\"bottom\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"5.522682445759369%\" valign=\"bottom\"\u003e\n \u003cp\u003e\u003cstrong\u003e0.708\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"4.339250493096647%\" valign=\"bottom\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"5.029585798816568%\" valign=\"bottom\"\u003e\n \u003cp\u003e0.035\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"4.339250493096647%\" valign=\"bottom\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"4.930966469428008%\" valign=\"bottom\"\u003e\n \u003cp\u003e1.317\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"5.9171597633136095%\" valign=\"bottom\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"6.6350710900473935%\" valign=\"bottom\"\u003e\n \u003cp\u003e-1.069\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"5.805687203791469%\" valign=\"bottom\"\u003e\n \u003cp\u003e2.327\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.6350710900473935%\" valign=\"bottom\"\u003e\n \u003cp\u003e-0.728\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.6350710900473935%\" valign=\"bottom\"\u003e\n \u003cp\u003e2.437\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.6350710900473935%\" valign=\"bottom\"\u003e\n \u003cp\u003e-2.370\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.6350710900473935%\" valign=\"bottom\"\u003e\n \u003cp\u003e-0.115\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"5.805687203791469%\" valign=\"bottom\"\u003e\n \u003cp\u003e-3.295\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.6350710900473935%\" valign=\"bottom\"\u003e\n \u003cp\u003e-0.746\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.6350710900473935%\" valign=\"bottom\"\u003e\n \u003cp\u003e-2.505\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"5.805687203791469%\" valign=\"bottom\"\u003e\n \u003cp\u003e0.946\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.6350710900473935%\" valign=\"bottom\"\u003e\n \u003cp\u003e0.059\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"5.213270142180095%\" valign=\"bottom\"\u003e\n \u003cp\u003e1.641\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.042654028436019%\" valign=\"bottom\"\u003e\n \u003cp\u003e-0.390\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"5.213270142180095%\" valign=\"bottom\"\u003e\n \u003cp\u003e0.955\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"5.924170616113744%\" valign=\"bottom\"\u003e\n \u003cp\u003e0.000\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.109004739336493%\" valign=\"bottom\"\u003e\n \u003cp\u003e2.526\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"16.765285996055226%\" rowspan=\"2\" valign=\"bottom\"\u003e\n \u003cp\u003eSuspicion\u0026nbsp;of invisible mould\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"5.522682445759369%\" valign=\"bottom\"\u003e\n \u003cp\u003e1.504\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"4.832347140039448%\" valign=\"bottom\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"5.522682445759369%\" valign=\"bottom\"\u003e\n \u003cp\u003e-1.113\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"5.522682445759369%\" valign=\"bottom\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"5.522682445759369%\" valign=\"bottom\"\u003e\n \u003cp\u003e\u003cstrong\u003e-1.495\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"5.522682445759369%\" valign=\"bottom\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"4.832347140039448%\" valign=\"bottom\"\u003e\n \u003cp\u003e\u003cstrong\u003e-2.562\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"5.522682445759369%\" valign=\"bottom\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"5.522682445759369%\" valign=\"bottom\"\u003e\n \u003cp\u003e\u003cstrong\u003e2.436\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"4.832347140039448%\" valign=\"bottom\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"5.522682445759369%\" valign=\"bottom\"\u003e\n \u003cp\u003e1.050\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"4.339250493096647%\" valign=\"bottom\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"5.029585798816568%\" valign=\"bottom\"\u003e\n \u003cp\u003e\u003cstrong\u003e1.447\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"4.339250493096647%\" valign=\"bottom\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"4.930966469428008%\" valign=\"bottom\"\u003e\n \u003cp\u003e-0.625\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"5.9171597633136095%\" valign=\"bottom\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"6.6350710900473935%\" valign=\"bottom\"\u003e\n \u003cp\u003e-0.805\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"5.805687203791469%\" valign=\"bottom\"\u003e\n \u003cp\u003e4.196\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.6350710900473935%\" valign=\"bottom\"\u003e\n \u003cp\u003e-2.540\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.6350710900473935%\" valign=\"bottom\"\u003e\n \u003cp\u003e1.304\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.6350710900473935%\" valign=\"bottom\"\u003e\n \u003cp\u003e-3.260\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.6350710900473935%\" valign=\"bottom\"\u003e\n \u003cp\u003e-0.881\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"5.805687203791469%\" valign=\"bottom\"\u003e\n \u003cp\u003e-6.706\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.6350710900473935%\" valign=\"bottom\"\u003e\n \u003cp\u003e-0.197\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.6350710900473935%\" valign=\"bottom\"\u003e\n \u003cp\u003e0.680\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"5.805687203791469%\" valign=\"bottom\"\u003e\n \u003cp\u003e4.761\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.6350710900473935%\" valign=\"bottom\"\u003e\n \u003cp\u003e-0.591\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"5.213270142180095%\" valign=\"bottom\"\u003e\n \u003cp\u003e2.598\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.042654028436019%\" valign=\"bottom\"\u003e\n \u003cp\u003e0.731\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"5.213270142180095%\" valign=\"bottom\"\u003e\n \u003cp\u003e2.720\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"5.924170616113744%\" valign=\"bottom\"\u003e\n \u003cp\u003e-2.230\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.109004739336493%\" valign=\"bottom\"\u003e\n \u003cp\u003e0.199\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"16.765285996055226%\" rowspan=\"2\" valign=\"bottom\"\u003e\n \u003cp\u003eSeverity\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"5.522682445759369%\" valign=\"bottom\"\u003e\n \u003cp\u003e0.363\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"4.832347140039448%\" valign=\"bottom\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"5.522682445759369%\" valign=\"bottom\"\u003e\n \u003cp\u003e-0.506\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"5.522682445759369%\" valign=\"bottom\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"5.522682445759369%\" valign=\"bottom\"\u003e\n \u003cp\u003e-0.617\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"5.522682445759369%\" valign=\"bottom\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"4.832347140039448%\" valign=\"bottom\"\u003e\n \u003cp\u003e\u003cstrong\u003e-2.519\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"5.522682445759369%\" valign=\"bottom\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"5.522682445759369%\" valign=\"bottom\"\u003e\n \u003cp\u003e1.234\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"4.832347140039448%\" valign=\"bottom\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"5.522682445759369%\" valign=\"bottom\"\u003e\n \u003cp\u003e0.689\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"4.339250493096647%\" valign=\"bottom\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"5.029585798816568%\" valign=\"bottom\"\u003e\n \u003cp\u003e0.320\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"4.339250493096647%\" valign=\"bottom\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"4.930966469428008%\" valign=\"bottom\"\u003e\n \u003cp\u003e1.263\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"5.9171597633136095%\" valign=\"bottom\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"6.6350710900473935%\" valign=\"bottom\"\u003e\n \u003cp\u003e-1.301\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"5.805687203791469%\" valign=\"bottom\"\u003e\n \u003cp\u003e1.399\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.6350710900473935%\" valign=\"bottom\"\u003e\n \u003cp\u003e-1.537\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.6350710900473935%\" valign=\"bottom\"\u003e\n \u003cp\u003e1.079\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.6350710900473935%\" valign=\"bottom\"\u003e\n \u003cp\u003e-2.121\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.6350710900473935%\" valign=\"bottom\"\u003e\n \u003cp\u003e0.751\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"5.805687203791469%\" valign=\"bottom\"\u003e\n \u003cp\u003e-4.779\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.6350710900473935%\" valign=\"bottom\"\u003e\n \u003cp\u003e-1.128\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.6350710900473935%\" valign=\"bottom\"\u003e\n \u003cp\u003e-0.362\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"5.805687203791469%\" valign=\"bottom\"\u003e\n \u003cp\u003e2.831\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.6350710900473935%\" valign=\"bottom\"\u003e\n \u003cp\u003e-0.169\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"5.213270142180095%\" valign=\"bottom\"\u003e\n \u003cp\u003e1.944\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.042654028436019%\" valign=\"bottom\"\u003e\n \u003cp\u003e-0.627\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"5.213270142180095%\" valign=\"bottom\"\u003e\n \u003cp\u003e2.093\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"5.924170616113744%\" valign=\"bottom\"\u003e\n \u003cp\u003e0.000\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.109004739336493%\" valign=\"bottom\"\u003e\n \u003cp\u003e3.166\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"16.765285996055226%\" valign=\"bottom\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"83.23471400394477%\" colspan=\"16\" valign=\"bottom\"\u003e\n \u003cp\u003eDwelling condition\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"16.765285996055226%\" valign=\"bottom\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"10.355029585798816%\" colspan=\"2\" valign=\"bottom\"\u003e\n \u003cp\u003eMajor cracks in walls/floors\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.045364891518737%\" colspan=\"2\" valign=\"bottom\"\u003e\n \u003cp\u003eSinking/moving foundations\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.045364891518737%\" colspan=\"2\" valign=\"bottom\"\u003e\n \u003cp\u003eWood rot/termite damage\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.355029585798816%\" colspan=\"2\" valign=\"bottom\"\u003e\n \u003cp\u003eMajor plumbing problems\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.355029585798816%\" colspan=\"2\" valign=\"bottom\"\u003e\n \u003cp\u003eWalls/windows not level\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.861932938856016%\" colspan=\"2\" valign=\"bottom\"\u003e\n \u003cp\u003eMajor roof defect\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.368836291913215%\" colspan=\"2\" valign=\"bottom\"\u003e\n \u003cp\u003eWell-insulated dwelling\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.848126232741617%\" colspan=\"2\" valign=\"bottom\"\u003e\n \u003cp\u003e(Semi)Detached house\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"16.765285996055226%\" rowspan=\"2\" valign=\"bottom\"\u003e\n \u003cp\u003eVisibility\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"5.522682445759369%\" valign=\"bottom\"\u003e\n \u003cp\u003e0.095\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"4.832347140039448%\" valign=\"bottom\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"5.522682445759369%\" valign=\"bottom\"\u003e\n \u003cp\u003e-0.185\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"5.522682445759369%\" valign=\"bottom\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"5.522682445759369%\" valign=\"bottom\"\u003e\n \u003cp\u003e0.015\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"5.522682445759369%\" valign=\"bottom\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"4.832347140039448%\" valign=\"bottom\"\u003e\n \u003cp\u003e\u003cstrong\u003e0.669\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"5.522682445759369%\" valign=\"bottom\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"5.522682445759369%\" valign=\"bottom\"\u003e\n \u003cp\u003e1.438\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"4.832347140039448%\" valign=\"bottom\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"5.522682445759369%\" valign=\"bottom\"\u003e\n \u003cp\u003e0.244\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"4.339250493096647%\" valign=\"bottom\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"5.029585798816568%\" valign=\"bottom\"\u003e\n \u003cp\u003e\u003cstrong\u003e3.636\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"4.339250493096647%\" valign=\"bottom\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"4.930966469428008%\" valign=\"bottom\"\u003e\n \u003cp\u003e-0.795\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"5.9171597633136095%\" valign=\"bottom\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"6.6350710900473935%\" valign=\"bottom\"\u003e\n \u003cp\u003e-0.842\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"5.805687203791469%\" valign=\"bottom\"\u003e\n \u003cp\u003e3.694\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.6350710900473935%\" valign=\"bottom\"\u003e\n \u003cp\u003e-1.210\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.6350710900473935%\" valign=\"bottom\"\u003e\n \u003cp\u003e2.633\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.6350710900473935%\" valign=\"bottom\"\u003e\n \u003cp\u003e-0.920\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.6350710900473935%\" valign=\"bottom\"\u003e\n \u003cp\u003e2.446\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"5.805687203791469%\" valign=\"bottom\"\u003e\n \u003cp\u003e0.168\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.6350710900473935%\" valign=\"bottom\"\u003e\n \u003cp\u003e1.036\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.6350710900473935%\" valign=\"bottom\"\u003e\n \u003cp\u003e-0.895\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"5.805687203791469%\" valign=\"bottom\"\u003e\n \u003cp\u003e3.572\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.6350710900473935%\" valign=\"bottom\"\u003e\n \u003cp\u003e-0.385\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"5.213270142180095%\" valign=\"bottom\"\u003e\n \u003cp\u003e4.118\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.042654028436019%\" valign=\"bottom\"\u003e\n \u003cp\u003e2.804\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"5.213270142180095%\" valign=\"bottom\"\u003e\n \u003cp\u003e7.976\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"5.924170616113744%\" valign=\"bottom\"\u003e\n \u003cp\u003e-1.997\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.109004739336493%\" valign=\"bottom\"\u003e\n \u003cp\u003e0.770\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"16.765285996055226%\" rowspan=\"2\" valign=\"bottom\"\u003e\n \u003cp\u003eSize\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"5.522682445759369%\" valign=\"bottom\"\u003e\n \u003cp\u003e-0.897\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"4.832347140039448%\" valign=\"bottom\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"5.522682445759369%\" valign=\"bottom\"\u003e\n \u003cp\u003e0.299\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"5.522682445759369%\" valign=\"bottom\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"5.522682445759369%\" valign=\"bottom\"\u003e\n \u003cp\u003e-0.483\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"5.522682445759369%\" valign=\"bottom\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"4.832347140039448%\" valign=\"bottom\"\u003e\n \u003cp\u003e0.539\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"5.522682445759369%\" valign=\"bottom\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"5.522682445759369%\" valign=\"bottom\"\u003e\n \u003cp\u003e-0.821\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"4.832347140039448%\" valign=\"bottom\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"5.522682445759369%\" valign=\"bottom\"\u003e\n \u003cp\u003e.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"4.339250493096647%\" valign=\"bottom\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"5.029585798816568%\" valign=\"bottom\"\u003e\n \u003cp\u003e1.616\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"4.339250493096647%\" valign=\"bottom\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"4.930966469428008%\" valign=\"bottom\"\u003e\n \u003cp\u003e-0.814\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"5.9171597633136095%\" valign=\"bottom\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"6.6350710900473935%\" valign=\"bottom\"\u003e\n \u003cp\u003e-1.690\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"5.805687203791469%\" valign=\"bottom\"\u003e\n \u003cp\u003e0.000\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.6350710900473935%\" valign=\"bottom\"\u003e\n \u003cp\u003e-0.823\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.6350710900473935%\" valign=\"bottom\"\u003e\n \u003cp\u003e1.825\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.6350710900473935%\" valign=\"bottom\"\u003e\n 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width=\"5.213270142180095%\" valign=\"bottom\"\u003e\n \u003cp\u003e2.842\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"5.924170616113744%\" valign=\"bottom\"\u003e\n \u003cp\u003e-1.711\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.109004739336493%\" valign=\"bottom\"\u003e\n \u003cp\u003e0.000\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"16.765285996055226%\" rowspan=\"2\" valign=\"bottom\"\u003e\n \u003cp\u003eOdour\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"5.522682445759369%\" valign=\"bottom\"\u003e\n \u003cp\u003e0.129\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"4.832347140039448%\" valign=\"bottom\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"5.522682445759369%\" valign=\"bottom\"\u003e\n \u003cp\u003e0.301\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"5.522682445759369%\" valign=\"bottom\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"5.522682445759369%\" valign=\"bottom\"\u003e\n 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width=\"4.930966469428008%\" valign=\"bottom\"\u003e\n \u003cp\u003e-1.503\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"5.9171597633136095%\" valign=\"bottom\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"6.6350710900473935%\" valign=\"bottom\"\u003e\n \u003cp\u003e-1.364\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"5.805687203791469%\" valign=\"bottom\"\u003e\n \u003cp\u003e1.578\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.6350710900473935%\" valign=\"bottom\"\u003e\n \u003cp\u003e-0.875\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.6350710900473935%\" valign=\"bottom\"\u003e\n \u003cp\u003e1.563\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.6350710900473935%\" valign=\"bottom\"\u003e\n \u003cp\u003e-1.479\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.6350710900473935%\" valign=\"bottom\"\u003e\n \u003cp\u003e1.357\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"5.805687203791469%\" valign=\"bottom\"\u003e\n \u003cp\u003e-0.655\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.6350710900473935%\" valign=\"bottom\"\u003e\n \u003cp\u003e1.709\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.6350710900473935%\" valign=\"bottom\"\u003e\n \u003cp\u003e-0.991\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"5.805687203791469%\" valign=\"bottom\"\u003e\n \u003cp\u003e1.801\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.6350710900473935%\" valign=\"bottom\"\u003e\n \u003cp\u003e-0.559\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"5.213270142180095%\" valign=\"bottom\"\u003e\n \u003cp\u003e1.365\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.042654028436019%\" valign=\"bottom\"\u003e\n \u003cp\u003e-0.516\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"5.213270142180095%\" valign=\"bottom\"\u003e\n \u003cp\u003e1.417\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"5.924170616113744%\" valign=\"bottom\"\u003e\n 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valign=\"bottom\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"4.832347140039448%\" valign=\"bottom\"\u003e\n \u003cp\u003e1.586\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"5.522682445759369%\" valign=\"bottom\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"5.522682445759369%\" valign=\"bottom\"\u003e\n \u003cp\u003e0.484\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"4.832347140039448%\" valign=\"bottom\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"5.522682445759369%\" valign=\"bottom\"\u003e\n \u003cp\u003e0.302\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"4.339250493096647%\" valign=\"bottom\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"5.029585798816568%\" valign=\"bottom\"\u003e\n \u003cp\u003e1.070\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"4.339250493096647%\" valign=\"bottom\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"4.930966469428008%\" valign=\"bottom\"\u003e\n \u003cp\u003e0.499\u003c/p\u003e\n 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width=\"6.6350710900473935%\" valign=\"bottom\"\u003e\n \u003cp\u003e2.440\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.6350710900473935%\" valign=\"bottom\"\u003e\n \u003cp\u003e-0.724\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"5.805687203791469%\" valign=\"bottom\"\u003e\n \u003cp\u003e2.125\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.6350710900473935%\" valign=\"bottom\"\u003e\n \u003cp\u003e-0.828\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"5.213270142180095%\" valign=\"bottom\"\u003e\n \u003cp\u003e1.807\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.042654028436019%\" valign=\"bottom\"\u003e\n \u003cp\u003e-0.063\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"5.213270142180095%\" valign=\"bottom\"\u003e\n \u003cp\u003e1.921\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"5.924170616113744%\" valign=\"bottom\"\u003e\n \u003cp\u003e-1.155\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.109004739336493%\" valign=\"bottom\"\u003e\n 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width=\"5.522682445759369%\" valign=\"bottom\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"5.522682445759369%\" valign=\"bottom\"\u003e\n \u003cp\u003e-0.297\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"4.832347140039448%\" valign=\"bottom\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"5.522682445759369%\" valign=\"bottom\"\u003e\n \u003cp\u003e0.603\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"4.339250493096647%\" valign=\"bottom\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"5.029585798816568%\" valign=\"bottom\"\u003e\n \u003cp\u003e1.051\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"4.339250493096647%\" valign=\"bottom\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"4.930966469428008%\" valign=\"bottom\"\u003e\n \u003cp\u003e\u003cstrong\u003e-1.143\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"5.9171597633136095%\" valign=\"bottom\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"6.6350710900473935%\" valign=\"bottom\"\u003e\n \u003cp\u003e-1.132\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"5.805687203791469%\" valign=\"bottom\"\u003e\n \u003cp\u003e2.072\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.6350710900473935%\" valign=\"bottom\"\u003e\n \u003cp\u003e-0.722\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.6350710900473935%\" valign=\"bottom\"\u003e\n \u003cp\u003e1.652\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.6350710900473935%\" valign=\"bottom\"\u003e\n \u003cp\u003e-1.239\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.6350710900473935%\" valign=\"bottom\"\u003e\n \u003cp\u003e1.475\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"5.805687203791469%\" valign=\"bottom\"\u003e\n \u003cp\u003e-0.128\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.6350710900473935%\" valign=\"bottom\"\u003e\n \u003cp\u003e2.219\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.6350710900473935%\" valign=\"bottom\"\u003e\n \u003cp\u003e-1.358\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"5.805687203791469%\" valign=\"bottom\"\u003e\n \u003cp\u003e0.618\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.6350710900473935%\" valign=\"bottom\"\u003e\n \u003cp\u003e-0.487\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"5.213270142180095%\" valign=\"bottom\"\u003e\n \u003cp\u003e2.093\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.042654028436019%\" valign=\"bottom\"\u003e\n \u003cp\u003e-0.978\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"5.213270142180095%\" valign=\"bottom\"\u003e\n \u003cp\u003e2.058\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"5.924170616113744%\" valign=\"bottom\"\u003e\n \u003cp\u003e-2.581\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.109004739336493%\" valign=\"bottom\"\u003e\n \u003cp\u003e-0.342\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"16.765285996055226%\" rowspan=\"2\" valign=\"bottom\"\u003e\n \u003cp\u003eSuspicion\u0026nbsp;of invisible mould\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"5.522682445759369%\" valign=\"bottom\"\u003e\n \u003cp\u003e-0.255\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"4.832347140039448%\" valign=\"bottom\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"5.522682445759369%\" valign=\"bottom\"\u003e\n \u003cp\u003e-0.133\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"5.522682445759369%\" valign=\"bottom\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"5.522682445759369%\" valign=\"bottom\"\u003e\n \u003cp\u003e0.027\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"5.522682445759369%\" valign=\"bottom\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"4.832347140039448%\" valign=\"bottom\"\u003e\n \u003cp\u003e0.282\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"5.522682445759369%\" valign=\"bottom\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"5.522682445759369%\" valign=\"bottom\"\u003e\n \u003cp\u003e-0.083\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"4.832347140039448%\" valign=\"bottom\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"5.522682445759369%\" valign=\"bottom\"\u003e\n \u003cp\u003e0.359\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"4.339250493096647%\" valign=\"bottom\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"5.029585798816568%\" valign=\"bottom\"\u003e\n \u003cp\u003e1.265\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"4.339250493096647%\" valign=\"bottom\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"4.930966469428008%\" valign=\"bottom\"\u003e\n \u003cp\u003e-1.680\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"5.9171597633136095%\" valign=\"bottom\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"6.6350710900473935%\" valign=\"bottom\"\u003e\n \u003cp\u003e-1.335\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"5.805687203791469%\" valign=\"bottom\"\u003e\n \u003cp\u003e0.284\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.6350710900473935%\" valign=\"bottom\"\u003e\n \u003cp\u003e-1.320\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.6350710900473935%\" valign=\"bottom\"\u003e\n \u003cp\u003e0.344\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.6350710900473935%\" valign=\"bottom\"\u003e\n \u003cp\u003e-1.002\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.6350710900473935%\" valign=\"bottom\"\u003e\n \u003cp\u003e2.193\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"5.805687203791469%\" valign=\"bottom\"\u003e\n \u003cp\u003e-0.593\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.6350710900473935%\" valign=\"bottom\"\u003e\n \u003cp\u003e0.705\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.6350710900473935%\" valign=\"bottom\"\u003e\n \u003cp\u003e-1.243\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"5.805687203791469%\" valign=\"bottom\"\u003e\n \u003cp\u003e1.922\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.6350710900473935%\" valign=\"bottom\"\u003e\n \u003cp\u003e-0.397\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"5.213270142180095%\" valign=\"bottom\"\u003e\n \u003cp\u003e0.854\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.042654028436019%\" valign=\"bottom\"\u003e\n \u003cp\u003e-0.186\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"5.213270142180095%\" valign=\"bottom\"\u003e\n \u003cp\u003e3.694\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"5.924170616113744%\" valign=\"bottom\"\u003e\n \u003cp\u003e-4.285\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.109004739336493%\" valign=\"bottom\"\u003e\n \u003cp\u003e-0.532\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"16.765285996055226%\" rowspan=\"2\" valign=\"bottom\"\u003e\n \u003cp\u003eSeverity\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"5.522682445759369%\" valign=\"bottom\"\u003e\n \u003cp\u003e0.316\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"4.832347140039448%\" valign=\"bottom\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"5.522682445759369%\" valign=\"bottom\"\u003e\n \u003cp\u003e0.628\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"5.522682445759369%\" valign=\"bottom\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"5.522682445759369%\" valign=\"bottom\"\u003e\n \u003cp\u003e0.340\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"5.522682445759369%\" valign=\"bottom\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"4.832347140039448%\" valign=\"bottom\"\u003e\n \u003cp\u003e1.645\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"5.522682445759369%\" valign=\"bottom\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"5.522682445759369%\" valign=\"bottom\"\u003e\n \u003cp\u003e0.232\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"4.832347140039448%\" valign=\"bottom\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"5.522682445759369%\" valign=\"bottom\"\u003e\n \u003cp\u003e0.827\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"4.339250493096647%\" valign=\"bottom\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"5.029585798816568%\" valign=\"bottom\"\u003e\n \u003cp\u003e1.221\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"4.339250493096647%\" valign=\"bottom\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"4.930966469428008%\" valign=\"bottom\"\u003e\n \u003cp\u003e-0.282\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"5.9171597633136095%\" valign=\"bottom\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"6.6350710900473935%\" valign=\"bottom\"\u003e\n \u003cp\u003e-0.647\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"5.805687203791469%\" valign=\"bottom\"\u003e\n \u003cp\u003e1.501\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.6350710900473935%\" valign=\"bottom\"\u003e\n \u003cp\u003e-1.298\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.6350710900473935%\" valign=\"bottom\"\u003e\n \u003cp\u003e1.708\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.6350710900473935%\" valign=\"bottom\"\u003e\n \u003cp\u003e-0.572\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.6350710900473935%\" valign=\"bottom\"\u003e\n \u003cp\u003e1.874\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"5.805687203791469%\" valign=\"bottom\"\u003e\n \u003cp\u003e0.000\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.6350710900473935%\" valign=\"bottom\"\u003e\n \u003cp\u003e4.154\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.6350710900473935%\" valign=\"bottom\"\u003e\n \u003cp\u003e-1.327\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"5.805687203791469%\" valign=\"bottom\"\u003e\n \u003cp\u003e1.179\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.6350710900473935%\" valign=\"bottom\"\u003e\n \u003cp\u003e-0.729\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"5.213270142180095%\" valign=\"bottom\"\u003e\n \u003cp\u003e3.359\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.042654028436019%\" valign=\"bottom\"\u003e\n \u003cp\u003e0.000\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"5.213270142180095%\" valign=\"bottom\"\u003e\n \u003cp\u003e2.095\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"5.924170616113744%\" valign=\"bottom\"\u003e\n \u003cp\u003e-1.427\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.109004739336493%\" valign=\"bottom\"\u003e\n \u003cp\u003e0.998\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003eNotes: Coefficients and 95%CI are reported.\u003c/p\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":true,"hideJournal":true,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true},"keywords":"","lastPublishedDoi":"10.21203/rs.3.rs-4162197/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-4162197/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003eMould growth is indicative of unhealthy indoor environments and, with a warming climate, increasingly poses a health risk. Understanding the prevalence and scope of the exposure largely relies on resident self-diagnosis; yet there is little guidance on how to optimise self-reported measures of mould in homes to achieve more accurate diagnosis of exposure. We compared the predictive performance of a range of self-reported measures that varied by their vernacular, framing, reference period, and severity of mould to be identified, against measures of mould taken from dust samples in 100 homes and analyzed using the quantitative polymerase chain reaction (qPCR) tests. Kappa and areas under the receiver operating characteristic curve (AUC) statistics were used to test the validity and accuracy of self-diagnosis of domestic mould. We find moderate agreement between self-reported and lab tested mould measures. Occupants tended to overestimate the presence of mould when asked about visible mould and suspicion of mould and to underestimate the presence of mould when asked about mould size, odour, dampness, and water damage. Identification of visible mould had the highest sensitivity while identification of mould larger than an A4 sheet of paper had the highest specificity. Combining self-reported visible mould and mould size achieved the best accuracy. When using self-rated mould severity (no, mild, moderate, or severe mould), grouping mild, moderate, and severe mould best detected actual mould presence. Prediction accuracy also varies by occupant sociodemographic and residential factors, with older age, lower household income, and major plumbing problems associated with better accuracy of self-diagnosed mould.\u003c/p\u003e","manuscriptTitle":"How best to diagnose in-home mould exposure: The validity and accuracy of self-reported measures","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2024-03-27 12:33:39","doi":"10.21203/rs.3.rs-4162197/v1","editorialEvents":[{"type":"communityComments","content":0}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"37627bdd-93ff-48fe-929e-b3dc9a62183f","owner":[],"postedDate":"March 27th, 2024","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[{"id":29891555,"name":"Earth and environmental sciences/Environmental sciences"},{"id":29891556,"name":"Earth and environmental sciences/Environmental social sciences"}],"tags":[],"updatedAt":"2024-04-03T20:21:12+00:00","versionOfRecord":[],"versionCreatedAt":"2024-03-27 12:33:39","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-4162197","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-4162197","identity":"rs-4162197","version":["v1"]},"buildId":"qtupq5eGEP_6zYnWcrvyt","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}