Subjective socioeconomic status: an alternative to objective socioeconomic status

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Here, we sought to compare a ladder score to a measure of SES that includes data on water and sanitation, asset ownership, education, and income (WAMI). Methods Leveraging an ongoing study of adult patients with tuberculosis in Lima, Peru, we compared results of the WAMI survey to the MacArthur Scale of Subjective Social Status. We assessed the relationship between WAMI and the ladder scores using Kappa scores and Spearman’s rank correlation coefficient. We used Akaike information criterion (AIC) to compare the predictability of logistic regression models that evaluated the association between SES and history of asthma. Results Among 595 participants who completed both questionnaires, the MacArthur ladder and WAMI scores were within two or less points (on a scale of 10 points) of each other for 84% of participants. The correlation coefficient was 0.34 (p < 0.001). Among 36 participants with a repeated ladder test, the 18 individuals who were selected for initially having dissimilar ladder and WAMI scores had a greater median decrease in their retested ladder scores (median 5, IQR: 1.25 to 6) compared to the 18 individuals who had similar scores (median 2, IQR: 0 to 3). When initial ladder scores were replaced with the repeated responses, the overall correlation coefficient increased to 0.40 (p < 0.001) and the variability in the difference between the ladder scores and WAMI decreased. Both SES scores were associated with history of asthma. Conclusion Our findings demonstrate that the MacArthur SES ladder is positively correlated to WAMI and performs similarly to WAMI in predicting a socio-economically sensitive health outcome. Researchers should consider subjective SES tools as an alternative method for measuring SES, particularly in large health studies where data collection is a burden. Tuberculosis Subjective socioeconomic status Objective socioeconomic status MacArthur Scale of Subjective Social Status Figures Figure 1 Figure 2 Figure 3 Figure 4 Background Social determinants of health result in a gradient in health outcomes that has been studied extensively in numerous contexts. Socioeconomic status can serve two distinct purposes in epidemiological studies: first as a predictor of health outcomes and secondly as a confounder that must be controlled to elucidate the relationship between health outcomes and other key determinants.( 1 , 2 ) Investigators traditionally capture SES using “objective” quantitative measure; most commonly, these include assets, income, education, and occupation. Epidemiologists have adopted composite objective SES measurements based on ownership of durables, access to services and housing characteristics, arguing that these are more reliable and easier to collect than income or consumptions expenditure.( 3 , 4 ) The WAMI is one such SES index. It is composed of four parts (access to improved W ater and sanitation, A sset ownership, M aternal education and household I ncome) and has been shown to have a stronger association with health outcomes than other composite SES indices.( 5 ) Despite the widespread use of SES indices like the WAMI, some have argued that they are not a reliable measure of SES, resulting in different SES classifications and varying associations to health outcomes depending on which SES indicator is used.( 6 – 10 ) Self-reported or “subjective” SES is an alternative measurement, which captures individuals’ perception of their own social standing relative to the community around them. Social scientists commonly use the MacArthur’s Scale of Subjective Social status (referred to as the ladder tool henceforth), which presents individuals with a pictorial ladder scale on which they are asked to rate their socio-economic standing in relation to their community.( 11 ) Several lines of research motivate the use of subjective SES. First, over the last two decades, researchers found that subjective indicators are associated with a range of health outcomes, including self-rated health, mental health, cardiovascular health and mortality.( 12 – 18 ) Subjective SES has been shown to be independently associated with other objective indicators, to be a stronger predictor of health outcomes than objective measures, and to mediate the relationship between objective SES and health.( 14 , 18 – 21 ) Secondly, researchers have described self-reported SES as a comprehensive measure where individuals can judge which objective SES factors are the most important contributors to their subjective SES.( 12 ) Third, the “averaging hypothesis” proposes that subjective SES is a more dynamic assessment since individuals can evaluate their past, current and future prospects within the context of their social and cultural environment.( 13 ) In contrast, objective SES is a single snapshot in time of current resources. Moreover, researchers are able to easily administer the tool in large scale, population studies, reducing the burden of data collection. Here, we sought to assess if a subjective SES measure is comparable to a composite objective SES and could serve as an alternative tool. Using data collected from tuberculosis (TB) patients in Lima, Peru, we estimated the correlation between the ladder and WAMI, assessed the reliability of the ladder over a time period of 6 to 8 months and evaluated the comparative performance of the ladder and WAMI in predicting a health outcome known to be associated with SES in this setting. Methods Survey of Study Population We embedded this investigation in an ongoing cohort study of treatment outcomes of patients who are age 14 years or older with TB disease. Briefly, we recruited participants when they were diagnosed with pulmonary TB disease at district health centers in a defined catchment area in Lima, Peru. Enrollment took place when patients were first diagnosed, at which time we obtained data and clinical samples, including socio-demographic and clinical information as well as blood samples for various assays, sputum samples for microbiological testing and chest X-rays. Participants also completed a questionnaire that included information on race, ethnicity, education (level and years), guardian education (level and years) for minors, job status, self-reported socioeconomic status using the ladder tool, source of drinking water, sanitation facilities, housing characteristics and materials (floor, roof, wall), household size, income and asset ownership ( Table 1 ) . Income was reported as average monthly income in Peruvian soles and converted to US dollars using a conversion rate of (1 Peruvian Sol = 0.25 USD). For this evaluation, participants are shown the pictorial ladder shown in Fig. 1 and asked to identify their location. After 6 to 8 months, we retested 36 patients on the MacArthur ladder in a subset of individuals to assess if there were any changes in responses. Field workers administered the questionnaires in person or by telephone using the same initial protocol Table 1 Socio-economic status characteristics of TB patient cohort (n = 595) All (n = 595) Female 220 (36.2%) Age 30 (23–50) Educational Level No school 11 (1.8%) Primary School 59 (9.9%) High School 345 (58%) Technical studies or University 179 (30%) Unknown 1 Employed 177 (30%) WAMI Improved Drinking Water 584 (98%) Improved Sanitation 584 (98%) Educational Years 11.0 (9.5–13.0) Income $ 324 152 (25%) Asset Ownership Iron 57% Bed 99% Chair or Bench 96% Sofa 61% Cupboard 69% Table 1 94% Electric Fan 26% Radio or Transistor 62% Computer 45% Television 93% Mobile Phone 95% Refrigerator 77% Water or Clock 53% Bike 28% Bank Account 66% . SES Scores We calculated a WAMI score based on responses to questions on improved W ater and sanitation, durable A sset ownership, M aternal education or participant’s education and I ncome. Each category is ranked from 0–8 and summed for a total out of 32 ( Table 2 ) . Table 2 Table 2 WAMI criteria and scoring system WAMI Criteria Range Water and Sanitation Based on WHO criteria, households with improved sources for drinking water and/or sanitation were allotted a score of 4 for each and scores were summed. 0–8 Assets Principal component analysis was performed using ownership of the 15 assets surveyed, and loading scores from the first principal component were used as the asset score. Scores were normalized from 0 to 1 then scaled based on 9 intervals evenly spaced along the range of loading scores. 0–8 Maternal Education Educational scores were scaled based on 9 intervals evenly spaced along the range of education years of the participant if 20 years old or older, and maternal education if younger than 20 years old. 0–8 Income Participants reported their monthly household income reported in soles using the following categories: 0 ( 1650). 0–8 Total Each category was summed for the total. 32 Water For water and sanitation, we defined improved conditions based on the World Health Organization’s guidelines. Drinking water source and sanitation were considered independently and given a score of 4 each if conditions were improved. Assets For durable assets, we asked participants if they owned the following 15 items: iron (either charcoal or electric), bed, chair or bench, sofa, cupboard, table, electric fan, radio or transistor, computer, television, mobile phone with paid monthly billing, refrigerator, watch or clock, bike and bank account. We created an assets score using principal component analysis of a correlation matrix of the asset ownership as binary variables.( 4 , 22 ) We used the principal component score for the first component of the asset score since it explains the most variance in the data (24.36%). Finally, we divided the range into 9 equal intervals to scale the scores from 0 to 8. Education For education, participants reported the number of educational years if they were 20 years old or older, and the number of educational years of their guardian if they were younger than 20 years old. Taking the range of educational years, we divided it into 9 equal intervals to assign a score from 0 to 8. Income For income, we first sampled the precise income of 120 participants and selected the ranges for income groups to be 12.5 increment percentiles to create 9 categories. Participants chose the following category that best described their average monthly income fell into (measured in soles and converted to USD): 0 ( $ 411). WAMI vs. Self-reported Ladder To measure the agreement between the WAMI and the MacArthur ladder scores, we scaled the WAMI scores to align to the ten-point MacArthur ladder scale using rank correlation. For the that ranked themselves on the lowest level of the ladder, we selected the same number of participants with the lowest WAMI scores to occupy the bottom level of the WAMI measure. This process was repeated for each level from 1 to 10, resulting in matching distributions between WAMI and the ladder scores with equal variance. Reassessment of the Ladder To evaluate if inconsistencies between the MacArthur ladder and WAMI were persistent findings, we first selected 18 participants from the individuals whose differences in their SES scores fell outside the range of two standard deviations (3.86 points). We then identified a control group with 18 participants whose ladder and WAMI scores were aligned within 2 SD. We reassessed the ladder score in both groups 6 to 8 months after the initial survey. Association of SES and Asthma In order to determine whether the ladder and WAMI scores had similar predictive power for a health related outcome, we compared the odds ratio of each for asthma, an outcome which previously has been shown to have an increased risk with increased SES.( 23 – 25 ) We stratified WAMI and ladder scores into three categories using cutoffs based on tertiles (0–4, 5, and 6–10). Data Analysis To assess agreement between the WAMI and ladder scores, we calculated Cohen’s Kappa, first using an unweighted Kappa statistic to assess agreement between the scoring systems, and then with the Fleiss-Cohen’s Kappa, which more heavily weighs the results of participants with the least difference in their scores.( 26 , 27 ) In addition, we calculated a Spearman’s rank correlation coefficient to evaluate the association. We used a logistic regression model to evaluate the association between SES and history of asthma. We compared the predictability of SES models to history of asthma using Akaike information criterion (AIC). Statistical analyses were conducted in R. ( https://www.r-project.org ). Results We enrolled 595 TB patients of whom 220 (36.2%) were female and the median age was 30 ( Table 1 ) . Table 1 shows that 345 (58%) attended or completed high school and 179 (30%) attended or completed technical school or university over a median 11 years of education and that 30% were employed. The median MacArthur ladder score was 5 (IQR: 4–6): 584 (98%) of the participants reported improved drinking water sources and sanitation; 238 (40%) an average monthly income between 100 and 224 dollars, 205 (34%) between 224 and 324 dollars, and 152 (25%) above 324 dollars. Some assets (bed, chair, table, television, and mobile phone) were owned by almost all of the cohort while possession of others (iron, sofa, cupboard, radio, refrigerator, watch and bank account) varied across the cohort ( Table 1 ) . WAMI scores ranged from 8 to 32 (out of a total of 32) with a median of 23 (IQR: 20–26) ( Fig. 2 a ) . After we transformed the WAMI scores to a 10-point scale, both scores had a median of 5 (IQR: 4–6) ( Fig. 2 b ) and were positively associated (correlation coefficient of 0.34, p-value < 0.001) ( Table 3 , Fig. 3 a ) . Correlation coefficients were also significant for the association between the ladder score and some individual components of the WAMI score including assets (r = 0.31), education (r = 0.28) and income (r = 0.27) but not for water and sanitation (r = 0.038). However, a piecewise correlation revealed that the relationship between WAMI and ladder was diminished below a score of 3 (R s : 0.091) and inverse above a score of 8 (R s : -0.094). Table 3 Table 3 Association between MacArthur ladder and SES indicators SES Indicator Correlation Coefficient with Ladder 1 p-value WAMI Initial 0.34 < 0.001 Water and Sanitation 0.038 0.36 Assets 0.31 < 0.001 Education 0.28 < 0.001 Income 0.27 < 0.001 WAMI Retest 0.4 < 0.001 1 Spearman's Rank Correlation Coefficient McArthur scores were identical to WAMI scores for 29% of participants and within one point of each other for 31% ( Table 4 ) . Unweighted and weighted Kappa statistics comparing the two scores were 0.083 and 0.33, respectively. When we stratified patients into three groups (Group 1: WAMI 5), we found that patients in Group 1 tended to rate themselves higher on the ladder than their WAMI while Group 3 tended to do rate themselves lower ( Fig. 3 b ). Table 4 Table 4 Agreement between MacArthur Ladder and WAMI Ladder Score % in agreement with WAMI Same group 29 Moved 1 group 31 Moved 2 groups 24 Moved 3 groups 9.4 Moved 4 + groups 7.1 Unweighted Kappa 0.083 Weighted Kappa 0.33 When retested with the MacArthur ladder 6 to 8 months after the initial survey, the 18 individuals with inconsistent scores had a median decrease in their retested ladder score of 5 (IQR: 1.25 to 6) compared to their initial ladder scores while individuals with similar scores had a median decrease of 2 (IQR: 0 to 3) ( Fig. 4 a ) . While initially the individual with inconsistent scores had a significant median difference between their WAMI and ladder score of -5 (IQR: -6 to 4), their score became more aligned with less variability (median difference of 2, IQR: -0.75 to 2.0). The difference between the WAMI and ladder scores remained relatively consistent for the individuals with similar scores, whose median difference was initially − 0.5 (IQR: -1 to 0) and retested median difference was 1 (IQR: 0 to 2) ( Fig. 4 ) . When retested ladder scores were used in replacement of the initial scores for all 36 retested individuals, we found stronger agreement with the WAMI score with the correlation coefficient increasing from 0.34 to 0.40 ( Table 3 ). Compared to those in the lowest ladder tertile, individuals in the highest ladder tertile were 2.0 (95% CI 0.89–4.48) fold more likely to report a history of asthma, which was similar to the effect size we saw when WAMI was used as a predictor with a 1.99 (95% CI 0.88–4.45) increased risk ( Table 5 ). When determining which model was a better fit given our asthma data, we found that the AIC was comparable between WAMI (AIC: 312.41) and ladder (AIC: 312.37).( 28 ) Table 5 Table 5 Relationship between Asthma and SES SES Odds Ratios (95% CI) AIC with outliers WAMI 0–4 points Ref 312.41 5 points 1.38 (0.63 to 3.03) 6–10 points 1.99 (0.88 to 4.45) Ladder 0–4 points Ref 312.37 5 points 1.4 (0.64 to 3.06) 6–10 points 2.0 (0.89 to 4.48) Discussion Here, we found the self-reported MacArthur ladder score for SES correlated reasonably well with a more in-depth assessment of socio-economic status that included water and sanitation, assets, educational level and income. When we reassessed outlying scores 6–8 months later, most outliers fell closer to the mean and the correlation between the ladder and WAMI improved. The ladder and WAMI scores were also similarly accurate in predicting an association with asthma, a health outcome known to be associated with SES in this setting. Taken together, these results suggest that the less cumbersome ladder score can be used to replace the more detailed WAMI with no loss of the ability to predict health outcomes or adjust for possible confounding by SES. Our finding of a correlation of .34-.40 between the ladder and WAMI scores is highly consistent with previous studies comparing objective and subjective SES measurements. These were summarized in a meta-analysis that compiled 432 associations from 357 studies which found that the ladder score was associated with any of a number of different “objective” scores with a mean correlation coefficient of 0.323.( 29 ) These results suggest that objective measures are consistently an important factor considered in self-reported SES. Previous qualitative analyses have reported that respondents mentioned income, material wealth, education as well as social comparison when asked what factors they considered when they self-rate using the ladder score, which is consistent with our findings that assets, income and education had a correlation of 0.27–0.31 with the ladder.( 29 ) In addition, the prevalence of asthma in Lima, Peru has previously been shown to be positively associated with SES, and the ladder and WAMI scores performed nearly identically in identifying this association.( 24 ) We note several limitations to this study. First, the participants completed the initial SES assessments at the time they were first diagnosed with TB, so the results of both scores might have been affected by their ongoing illness or the possibly temporary impact of their illness on their immediate socio-economic status. Because the McArthur ladder score is more dependent on subjective state, it may have been more likely to reflect the impact of the disease state. This interpretation is supported by the fact that agreement between the ladder and WAMI improved on retesting 6–8 months later, at a time when TB treatment should have improved the participants health status. Second, our study was conducted in a distinct population of people with lower SES in Lima, and therefore, our results may not be generalizable to a different population. Third, our finding that the median and mode was 5 for the ladder score raises the possibility of a bias introduced by a responder preference for rounding off the numbers to 5, which would coarsen the data. Another possible explanation for the frequency of the 5 score is a frame-of-reference bias which might occur if individual participants are not familiar with the full range of possible socio-economic levels in their society and have little interaction with people in other social classes. In this case, wealthier individuals, who may be unaware of poorer individuals’ impoverished circumstances, might tend to rate themselves lower while poorer individuals tend to rate themselves higher.( 3 , 30 ) Future studies using the ladder scale might benefit from implementing methods to address scale heterogeneity and ensure interpersonal comparability of the ladder tool.( 31 – 35 ) One way to address these issues is to incorporate into the questionnaires anchoring vignettes which describe hypothetical individuals representing a specific anchor, or common, points on the ladder scale. Since the vignettes are consistent across respondents, any variation between individuals is then due to interpersonal inconsistencies, and statistical methods can be used to rescale individuals’ self-reported SES. Expanding the use of anchoring vignettes to SES with the MacArthur ladder has yet to be explored and is a potential solution to improve the inter-person reliability and discriminatory power of subjective SES tools. Conclusions Epidemiological studies have traditionally measured socioeconomic status, an integral determinant of health outcomes, via objective markers and has overlooked subjective SES measurements, such as the MacArthur ladder tool, as an alternative. We demonstrated here that the ladder tool correlates well with WAMI, an objective SES index, in categorizing patients into SES levels and performs comparably in predicting health outcomes related to SES. Given that the ladder scale is simple and easy to administer, it is a tool that could reduce the burden of data collection in large, population-based health studies while still capturing patients’ SES in a robust manner. Abbreviations SES – socioeconomic status WAMI – Water and sanitation, Asset ownership, Maternal education and household Income score Ladder score – MacArthur’s Scale of Subjective Social status TB – tuberculosis AIC - Akaike information criterion Declarations Ethics approval and consent to participate Before study participation, adult study participants provided voluntary, written informed consent. For children, a guardian provided written informed consent and the children provided assent. The Harvard School of Public Health and Peru’s Research Ethics Committee of the National Institute of Health provided Institutional Review Board approval. All methods were performed in accordance with the relevant guidelines and regulations. Consent for publication Not Applicable Availability of data and materials The datasets used and/or analysed during the current study are available from the corresponding author on reasonable request. Competing interests The authors declare that they have no competing interests. Funding The work reported in this publication was supported by the National Institutes of Health and the National Institute of Allergy and Infectious Diseases grant U19 AI142793-03. Authors' contributions MM and CC conceived of the study. LL, MM and XT implemented the study protocol in Peru and obtained the data to be analyzed. MZ analyzed and interpreted the survey data and wrote the first draft of the manuscript. All authors contributed to and approved the final manuscript. Acknowledgements Not Applicable References Hanna DR, Campbell JA, Walker RJ, Dawson AZ, Egede LE. Association between Health and Wealth among Kenyan Adults with Hypertension. Glob J Health Sci. 2021;13(4):86–94. 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Additional Declarations No competing interests reported. Cite Share Download PDF Status: Published Journal Publication published 28 Mar, 2023 Read the published version in BMC Medical Research Methodology → Version 1 posted Editorial decision: Major revision 14 Oct, 2022 Reviews received at journal 12 Oct, 2022 Reviews received at journal 13 Sep, 2022 Reviewers agreed at journal 01 Sep, 2022 Reviewers invited by journal 26 Aug, 2022 Editor assigned by journal 22 Aug, 2022 Editor invited by journal 01 Aug, 2022 Submission checks completed at journal 01 Aug, 2022 First submitted to journal 14 Jul, 2022 You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. 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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-1858867","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":125415397,"identity":"4848c7e3-5ae6-4e0d-84e9-8b54c42654a1","order_by":0,"name":"Maryann Zhao","email":"","orcid":"","institution":"Harvard Medical School","correspondingAuthor":false,"submittingAuthor":false,"prefix":"","firstName":"Maryann","middleName":"","lastName":"Zhao","suffix":""},{"id":125415398,"identity":"6ccf1e20-74b6-4836-bec3-73a895273dfa","order_by":1,"name":"Chuan-Chin Huang","email":"","orcid":"","institution":"Harvard Medical School","correspondingAuthor":false,"submittingAuthor":false,"prefix":"","firstName":"Chuan-Chin","middleName":"","lastName":"Huang","suffix":""},{"id":125415399,"identity":"b3202e86-0e75-49eb-99ef-eed7c9fc31a4","order_by":2,"name":"Milagros Mendoza","email":"","orcid":"","institution":"Socios En Salud","correspondingAuthor":false,"submittingAuthor":false,"prefix":"","firstName":"Milagros","middleName":"","lastName":"Mendoza","suffix":""},{"id":125415400,"identity":"455f99c9-5f97-4b60-ac2a-c83281347a2e","order_by":3,"name":"Ximena Tovar","email":"","orcid":"","institution":"Harvard Medical School","correspondingAuthor":false,"submittingAuthor":false,"prefix":"","firstName":"Ximena","middleName":"","lastName":"Tovar","suffix":""},{"id":125415401,"identity":"3c5e6d65-33d5-4a8e-9b77-bb99ee51ab87","order_by":4,"name":"Leonid Lecca","email":"","orcid":"","institution":"Socios En Salud","correspondingAuthor":false,"submittingAuthor":false,"prefix":"","firstName":"Leonid","middleName":"","lastName":"Lecca","suffix":""},{"id":125415402,"identity":"1354ed0a-bf2e-4950-82a7-a4723aa49496","order_by":5,"name":"Megan Murray","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAABD0lEQVRIiWNgGAWjYCgAHn4QmVBAihbJBpAWA1KsMTgAJnEr0G1vv/i5gGFb4vbZh59JMFTckTE+vzrxwwMDBnl+sQNYtZidOVMsPYPhduKcc2lmEgxnnvGY3Xi7WQLoMMOZsxOwa7mRkyDNA9Qyg4fBTIKx7TBQy9kNIC0JBrdxaLn/Jvk3RAv7NwnGf4d5jGec3fwDr5Yb7MegtvAAbWk4zGPA37sNvy1nctiseQxuGwO1FFskHHvGI3GDd5tFgoEEbr8cP/74Nk/FbVmgwzbe+FBzx56//+zmmz8qbOT5pbFrAcadASwWWCQSGA4wMEiAVUrgUA4C7A9gLOYPDCAt/AfwqB4Fo2AUjIKRCAD1zV+95yTJYAAAAABJRU5ErkJggg==","orcid":"","institution":"Harvard Medical School","correspondingAuthor":true,"submittingAuthor":false,"prefix":"","firstName":"Megan","middleName":"","lastName":"Murray","suffix":""}],"badges":[],"createdAt":"2022-07-14 16:29:10","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-1858867/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-1858867/v1","draftVersion":[],"editorialEvents":[{"content":"https://doi.org/10.1186/s12874-023-01890-z","type":"published","date":"2023-03-28T20:16:28+00:00"}],"editorialNote":"","failedWorkflow":false,"files":[{"id":24739984,"identity":"16f3e7da-6866-4d42-b768-1fe3f9976993","added_by":"auto","created_at":"2022-08-03 18:06:10","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":179396,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eMacArthur Subjective Social Status pictorial ladder tool\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\u003cp\u003eThe pictorial ladder represents the place that people in society occupy, where the top of the ladder represents those with more money, education and better jobs and the bottom represents those with less money, education, and worse jobs. Looking at this picture, participants are asked to identify their location\u003cem\u003e.\u0026nbsp;\u003c/em\u003e\u003c/p\u003e","description":"","filename":"BMCFigure1.png","url":"https://assets-eu.researchsquare.com/files/rs-1858867/v1/0d7ee9e564c55307c3f9ef42.png"},{"id":24739981,"identity":"bfdd0471-25a1-4e71-a121-885e076c1efc","added_by":"auto","created_at":"2022-08-03 18:06:09","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":217824,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eHistogram of WAMI and Ladder scores\u003c/strong\u003e\u0026nbsp;\u003c/p\u003e\u003cp\u003eA)\u0026nbsp;\u0026nbsp;WAMI scores was distributed around a median of 23 (IQR: 20-26), denoted by the red dashed line. B) WAMI scores were rescaled from 0-32 to 1-10 to match the ten-point ladder using a nonparametric method. If N participants had a ladder score of 1, then the same number of participants were assigned a WAMI score of 1. The resulting distribution had a median of 5 (IQR: 4-6).\u0026nbsp;\u003c/p\u003e","description":"","filename":"BMCFigure2.png","url":"https://assets-eu.researchsquare.com/files/rs-1858867/v1/ec926f2f422d603a291f52ea.png"},{"id":24740622,"identity":"c20ce7b5-c1b6-4af6-8274-dc25c92db3d7","added_by":"auto","created_at":"2022-08-03 18:11:10","extension":"png","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":471919,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eComparison of self-reported ladder scores to WAMI scores\u003c/strong\u003e\u003c/p\u003e\u003cp\u003eA)\u0026nbsp;\u0026nbsp;Violin plots demonstrated a general increase in the median WAMI score with increasing ladder score although a piecewise correlation revealed an inverse relationship above a score of 8. Outliers were identified if the difference between WAMI and ladder was greater than 2 SD (3.86 points, red line). B) Patients grouped based on their WAMI scores: 1) less than 5, 2) equal to 5, and 3) greater than 5. Median differences between WAMI and ladder showed group 1 was more likely to rate their SES higher and group 3 was likely to score themselves lower. Group 2 had a median difference of 0.\u003c/p\u003e","description":"","filename":"BMCFigure3.png","url":"https://assets-eu.researchsquare.com/files/rs-1858867/v1/19671cb95af9e3ab46993cc5.png"},{"id":24739982,"identity":"6fa2ef02-a5b4-46ce-a811-b9020c06a88a","added_by":"auto","created_at":"2022-08-03 18:06:10","extension":"png","order_by":4,"title":"Figure 4","display":"","copyAsset":false,"role":"figure","size":312733,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eLadder Retest \u003c/strong\u003e\u003c/p\u003e\u003cp\u003eA) For 36 patients with retested ladder scores, 18 outliers (pink) had a median decrease 5 (IQR: 1.25 to 6) and were primarily located on the lower and upper ends of the scale, while the remaining patients (blue) had a median decrease of 2 (IQR: 0 to 3). B) Patients who were outliers generally fell on the higher end of either the ladder or WAMI scale while perfect agreement falls on the grey line. C) Retested ladder scores agreed more closely with WAMI, falling closer to the grey line.\u0026nbsp;\u003c/p\u003e","description":"","filename":"BMCFigure4.png","url":"https://assets-eu.researchsquare.com/files/rs-1858867/v1/3bb91e70191a04c7681d810e.png"},{"id":44723903,"identity":"fc0d9b57-35d4-44a6-ba95-36845b1b7b34","added_by":"auto","created_at":"2023-10-16 20:22:55","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":1010758,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-1858867/v1/9a8c0d1a-15bc-4846-ab88-a846bf8acf27.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"Subjective socioeconomic status: an alternative to objective socioeconomic status","fulltext":[{"header":"Background","content":"\u003cp\u003eSocial determinants of health result in a gradient in health outcomes that has been studied extensively in numerous contexts. Socioeconomic status can serve two distinct purposes in epidemiological studies: first as a predictor of health outcomes and secondly as a confounder that must be controlled to elucidate the relationship between health outcomes and other key determinants.(\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e, \u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e) Investigators traditionally capture SES using \u0026ldquo;objective\u0026rdquo; quantitative measure; most commonly, these include assets, income, education, and occupation. Epidemiologists have adopted composite objective SES measurements based on ownership of durables, access to services and housing characteristics, arguing that these are more reliable and easier to collect than income or consumptions expenditure.(\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e, \u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e) The WAMI is one such SES index. It is composed of four parts (access to improved \u003cb\u003eW\u003c/b\u003eater and sanitation, \u003cb\u003eA\u003c/b\u003esset ownership, \u003cb\u003eM\u003c/b\u003eaternal education and household \u003cb\u003eI\u003c/b\u003encome) and has been shown to have a stronger association with health outcomes than other composite SES indices.(\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e) Despite the widespread use of SES indices like the WAMI, some have argued that they are not a reliable measure of SES, resulting in different SES classifications and varying associations to health outcomes depending on which SES indicator is used.(\u003cspan additionalcitationids=\"CR7 CR8 CR9\" citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e)\u003c/p\u003e \u003cp\u003eSelf-reported or \u0026ldquo;subjective\u0026rdquo; SES is an alternative measurement, which captures individuals\u0026rsquo; perception of their own social standing relative to the community around them. Social scientists commonly use the MacArthur\u0026rsquo;s Scale of Subjective Social status (referred to as the ladder tool henceforth), which presents individuals with a pictorial ladder scale on which they are asked to rate their socio-economic standing in relation to their community.(\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e) Several lines of research motivate the use of subjective SES. First, over the last two decades, researchers found that subjective indicators are associated with a range of health outcomes, including self-rated health, mental health, cardiovascular health and mortality.(\u003cspan additionalcitationids=\"CR13 CR14 CR15 CR16 CR17\" citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e) Subjective SES has been shown to be independently associated with other objective indicators, to be a stronger predictor of health outcomes than objective measures, and to mediate the relationship between objective SES and health.(\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e, \u003cspan additionalcitationids=\"CR19 CR20\" citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e) Secondly, researchers have described self-reported SES as a comprehensive measure where individuals can judge which objective SES factors are the most important contributors to their subjective SES.(\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e) Third, the \u0026ldquo;averaging hypothesis\u0026rdquo; proposes that subjective SES is a more dynamic assessment since individuals can evaluate their past, current and future prospects within the context of their social and cultural environment.(\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e) In contrast, objective SES is a single snapshot in time of current resources. Moreover, researchers are able to easily administer the tool in large scale, population studies, reducing the burden of data collection.\u003c/p\u003e \u003cp\u003eHere, we sought to assess if a subjective SES measure is comparable to a composite objective SES and could serve as an alternative tool. Using data collected from tuberculosis (TB) patients in Lima, Peru, we estimated the correlation between the ladder and WAMI, assessed the reliability of the ladder over a time period of 6 to 8 months and evaluated the comparative performance of the ladder and WAMI in predicting a health outcome known to be associated with SES in this setting.\u003c/p\u003e"},{"header":"Methods","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e \u003ch2\u003eSurvey of Study Population\u003c/h2\u003e \u003cp\u003eWe embedded this investigation in an ongoing cohort study of treatment outcomes of patients who are age 14 years or older with TB disease. Briefly, we recruited participants when they were diagnosed with pulmonary TB disease at district health centers in a defined catchment area in Lima, Peru. Enrollment took place when patients were first diagnosed, at which time we obtained data and clinical samples, including socio-demographic and clinical information as well as blood samples for various assays, sputum samples for microbiological testing and chest X-rays. Participants also completed a questionnaire that included information on race, ethnicity, education (level and years), guardian education (level and years) for minors, job status, self-reported socioeconomic status using the ladder tool, source of drinking water, sanitation facilities, housing characteristics and materials (floor, roof, wall), household size, income and asset ownership \u003cb\u003e(\u003c/b\u003eTable\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e\u003cb\u003e)\u003c/b\u003e. Income was reported as average monthly income in Peruvian soles and converted to US dollars using a conversion rate of (1 Peruvian Sol\u0026thinsp;=\u0026thinsp;0.25 USD). For this evaluation, participants are shown the pictorial ladder shown in Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e1\u003c/span\u003e and asked to identify their location. After 6 to 8 months, we retested 36 patients on the MacArthur ladder in a subset of individuals to assess if there were any changes in responses. Field workers administered the questionnaires in person or by telephone using the same initial protocol\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab1\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 1\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eSocio-economic status characteristics of TB patient cohort (n\u0026thinsp;=\u0026thinsp;595)\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"2\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eAll (n\u0026thinsp;=\u0026thinsp;595)\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eFemale\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e220 (36.2%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAge\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e30 (23\u0026ndash;50)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eEducational Level\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNo school\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e11 (1.8%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePrimary School\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e59 (9.9%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHigh School\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e345 (58%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eTechnical studies or University\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e179 (30%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eUnknown\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eEmployed\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e177 (30%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eWAMI\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eImproved Drinking Water\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e584 (98%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eImproved Sanitation\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e584 (98%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eEducational Years\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e11.0 (9.5\u0026ndash;13.0)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eIncome\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u0026lt; \u003cspan\u003e$\u003c/span\u003e100\u0026ndash;224\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e238 (40%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cspan\u003e$\u003c/span\u003e224\u0026ndash;324\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e205 (34%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u0026gt; \u003cspan\u003e$\u003c/span\u003e324\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e152 (25%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAsset Ownership\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eIron\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e57%\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eBed\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e99%\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eChair or Bench\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e96%\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSofa\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e61%\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCupboard\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e69%\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eTable\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e94%\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eElectric Fan\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e26%\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eRadio or Transistor\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e62%\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eComputer\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e45%\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eTelevision\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e93%\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMobile Phone\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e95%\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eRefrigerator\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e77%\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eWater or Clock\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e53%\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eBike\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e28%\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eBank Account\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e66%\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003ctfoot\u003e \u003ctr\u003e\u003ctd colspan=\"2\"\u003e.\u003c/td\u003e\u003c/tr\u003e \u003c/tfoot\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec4\" class=\"Section2\"\u003e \u003ch2\u003eSES Scores\u003c/h2\u003e \u003cp\u003eWe calculated a WAMI score based on responses to questions on improved \u003cb\u003eW\u003c/b\u003eater and sanitation, durable \u003cb\u003eA\u003c/b\u003esset ownership, \u003cb\u003eM\u003c/b\u003eaternal education or participant\u0026rsquo;s education and \u003cb\u003eI\u003c/b\u003encome. Each category is ranked from 0\u0026ndash;8 and summed for a total out of 32 \u003cb\u003e(\u003c/b\u003eTable\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e\u003cb\u003e)\u003c/b\u003e.\u003c/p\u003e \u003cp\u003eTable\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab2\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 2\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eWAMI criteria and scoring system\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"3\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eWAMI\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eCriteria\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eRange\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eWater and Sanitation\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eBased on WHO criteria, households with improved sources for drinking water and/or sanitation were allotted a score of 4 for each and scores were summed.\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0\u0026ndash;8\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAssets\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003ePrincipal component analysis was performed using ownership of the 15 assets surveyed, and loading scores from the first principal component were used as the asset score. Scores were normalized from 0 to 1 then scaled based on 9 intervals evenly spaced along the range of loading scores.\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0\u0026ndash;8\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMaternal Education\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eEducational scores were scaled based on 9 intervals evenly spaced along the range of education years of the participant if 20 years old or older, and maternal education if younger than 20 years old.\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0\u0026ndash;8\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eIncome\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eParticipants reported their monthly household income reported in soles using the following categories: 0 (\u0026lt;\u0026thinsp;400), 1 (400\u0026ndash;600), 2 (600\u0026ndash;700), 3 (700\u0026ndash;800), 4 (800\u0026ndash;900), 5 (900\u0026ndash;1000), 6 (1000\u0026ndash;1300), 7 (1300\u0026ndash;1650), 8 (\u0026gt;\u0026thinsp;1650).\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0\u0026ndash;8\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eTotal\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eEach category was summed for the total.\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e32\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cdiv id=\"Sec5\" class=\"Section3\"\u003e \u003ch2\u003eWater\u003c/h2\u003e \u003cp\u003e For water and sanitation, we defined improved conditions based on the World Health Organization\u0026rsquo;s guidelines. Drinking water source and sanitation were considered independently and given a score of 4 each if conditions were improved.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec6\" class=\"Section3\"\u003e \u003ch2\u003eAssets\u003c/h2\u003e \u003cp\u003eFor durable assets, we asked participants if they owned the following 15 items: iron (either charcoal or electric), bed, chair or bench, sofa, cupboard, table, electric fan, radio or transistor, computer, television, mobile phone with paid monthly billing, refrigerator, watch or clock, bike and bank account. We created an assets score using principal component analysis of a correlation matrix of the asset ownership as binary variables.(\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e, \u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e) We used the principal component score for the first component of the asset score since it explains the most variance in the data (24.36%). Finally, we divided the range into 9 equal intervals to scale the scores from 0 to 8.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec7\" class=\"Section3\"\u003e \u003ch2\u003eEducation\u003c/h2\u003e \u003cp\u003eFor education, participants reported the number of educational years if they were 20 years old or older, and the number of educational years of their guardian if they were younger than 20 years old. Taking the range of educational years, we divided it into 9 equal intervals to assign a score from 0 to 8.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec8\" class=\"Section3\"\u003e \u003ch2\u003eIncome\u003c/h2\u003e \u003cp\u003eFor income, we first sampled the precise income of 120 participants and selected the ranges for income groups to be 12.5 increment percentiles to create 9 categories. Participants chose the following category that best described their average monthly income fell into (measured in soles and converted to USD): 0 (\u0026lt; \u003cspan\u003e$\u003c/span\u003e100), 1 (\u003cspan\u003e$\u003c/span\u003e100\u0026ndash;150), 2 (\u003cspan\u003e$\u003c/span\u003e150\u0026ndash;175), 3 (\u003cspan\u003e$\u003c/span\u003e175\u0026ndash;200), 4 (\u003cspan\u003e$\u003c/span\u003e200\u0026ndash;225), 5 (\u003cspan\u003e$\u003c/span\u003e225\u0026ndash;250), 6 (\u003cspan\u003e$\u003c/span\u003e250\u0026ndash;324), 7 (\u003cspan\u003e$\u003c/span\u003e324\u0026ndash;411), 8 (\u0026gt; \u003cspan\u003e$\u003c/span\u003e411).\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv id=\"Sec9\" class=\"Section2\"\u003e \u003ch2\u003eWAMI vs. Self-reported Ladder\u003c/h2\u003e \u003cp\u003e To measure the agreement between the WAMI and the MacArthur ladder scores, we scaled the WAMI scores to align to the ten-point MacArthur ladder scale using rank correlation. For the that ranked themselves on the lowest level of the ladder, we selected the same number of participants with the lowest WAMI scores to occupy the bottom level of the WAMI measure. This process was repeated for each level from 1 to 10, resulting in matching distributions between WAMI and the ladder scores with equal variance.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec10\" class=\"Section2\"\u003e \u003ch2\u003eReassessment of the Ladder\u003c/h2\u003e \u003cp\u003eTo evaluate if inconsistencies between the MacArthur ladder and WAMI were persistent findings, we first selected 18 participants from the individuals whose differences in their SES scores fell outside the range of two standard deviations (3.86 points). We then identified a control group with 18 participants whose ladder and WAMI scores were aligned within 2 SD. We reassessed the ladder score in both groups 6 to 8 months after the initial survey.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec11\" class=\"Section2\"\u003e \u003ch2\u003eAssociation of SES and Asthma\u003c/h2\u003e \u003cp\u003eIn order to determine whether the ladder and WAMI scores had similar predictive power for a health related outcome, we compared the odds ratio of each for asthma, an outcome which previously has been shown to have an increased risk with increased SES.(\u003cspan additionalcitationids=\"CR24\" citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e) We stratified WAMI and ladder scores into three categories using cutoffs based on tertiles (0\u0026ndash;4, 5, and 6\u0026ndash;10).\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec12\" class=\"Section2\"\u003e \u003ch2\u003eData Analysis\u003c/h2\u003e \u003cp\u003e To assess agreement between the WAMI and ladder scores, we calculated Cohen\u0026rsquo;s Kappa, first using an unweighted Kappa statistic to assess agreement between the scoring systems, and then with the Fleiss-Cohen\u0026rsquo;s Kappa, which more heavily weighs the results of participants with the least difference in their scores.(\u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e, \u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e) In addition, we calculated a Spearman\u0026rsquo;s rank correlation coefficient to evaluate the association. We used a logistic regression model to evaluate the association between SES and history of asthma. We compared the predictability of SES models to history of asthma using Akaike information criterion (AIC). Statistical analyses were conducted in R. (\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://www.r-project.org\u003c/span\u003e\u003cspan address=\"https://www.r-project.org\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003cspan type=\"Underline\" class=\"Underline\" name=\"Emphasis\"\u003e).\u003c/span\u003e\u003c/p\u003e \u003c/div\u003e"},{"header":"Results","content":"\u003cp\u003eWe enrolled 595 TB patients of whom 220 (36.2%) were female and the median age was 30 \u003cb\u003e(\u003c/b\u003eTable\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e\u003cb\u003e)\u003c/b\u003e. Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e shows that 345 (58%) attended or completed high school and 179 (30%) attended or completed technical school or university over a median 11 years of education and that 30% were employed. The median MacArthur ladder score was 5 (IQR: 4\u0026ndash;6): 584 (98%) of the participants reported improved drinking water sources and sanitation; 238 (40%) an average monthly income between 100 and 224 dollars, 205 (34%) between 224 and 324 dollars, and 152 (25%) above 324 dollars. Some assets (bed, chair, table, television, and mobile phone) were owned by almost all of the cohort while possession of others (iron, sofa, cupboard, radio, refrigerator, watch and bank account) varied across the cohort \u003cb\u003e(\u003c/b\u003eTable\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e\u003cb\u003e)\u003c/b\u003e.\u003c/p\u003e \u003cp\u003eWAMI scores ranged from 8 to 32 (out of a total of 32) with a median of 23 (IQR: 20\u0026ndash;26) \u003cb\u003e(\u003c/b\u003eFig.\u0026nbsp;\u003cspan refid=\"Fig6\" class=\"InternalRef\"\u003e2\u003c/span\u003ea\u003cb\u003e)\u003c/b\u003e. After we transformed the WAMI scores to a 10-point scale, both scores had a median of 5 (IQR: 4\u0026ndash;6) \u003cb\u003e(\u003c/b\u003eFig.\u0026nbsp;\u003cspan refid=\"Fig6\" class=\"InternalRef\"\u003e2\u003c/span\u003eb\u003cb\u003e)\u003c/b\u003e and were positively associated (correlation coefficient of 0.34, p-value\u0026thinsp;\u0026lt;\u0026thinsp;0.001) \u003cb\u003e(\u003c/b\u003eTable\u0026nbsp;\u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e3\u003c/span\u003e, Fig.\u0026nbsp;\u003cspan refid=\"Fig7\" class=\"InternalRef\"\u003e3\u003c/span\u003ea\u003cb\u003e)\u003c/b\u003e. Correlation coefficients were also significant for the association between the ladder score and some individual components of the WAMI score including assets (r\u0026thinsp;=\u0026thinsp;0.31), education (r\u0026thinsp;=\u0026thinsp;0.28) and income (r\u0026thinsp;=\u0026thinsp;0.27) but not for water and sanitation (r\u0026thinsp;=\u0026thinsp;0.038). However, a piecewise correlation revealed that the relationship between WAMI and ladder was diminished below a score of 3 (R\u003csub\u003es\u003c/sub\u003e: 0.091) and inverse above a score of 8 (R\u003csub\u003es\u003c/sub\u003e: -0.094).\u003c/p\u003e \u003cp\u003eTable\u0026nbsp;\u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e3\u003c/span\u003e\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab3\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 3\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eAssociation between MacArthur ladder and SES indicators\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"3\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSES Indicator\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eCorrelation Coefficient with Ladder\u003csup\u003e1\u003c/sup\u003e\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003ep-value\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eWAMI Initial\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.34\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eWater and Sanitation\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.038\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.36\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAssets\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.31\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eEducation\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.28\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eIncome\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.27\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eWAMI Retest\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e \u003cp\u003e\u003csup\u003e1\u003c/sup\u003e Spearman's Rank Correlation Coefficient\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003eMcArthur scores were identical to WAMI scores for 29% of participants and within one point of each other for 31% \u003cb\u003e(\u003c/b\u003eTable\u0026nbsp;\u003cspan refid=\"Tab4\" class=\"InternalRef\"\u003e4\u003c/span\u003e\u003cb\u003e)\u003c/b\u003e. Unweighted and weighted Kappa statistics comparing the two scores were 0.083 and 0.33, respectively. When we stratified patients into three groups (Group 1: WAMI\u0026thinsp;\u0026lt;\u0026thinsp;5; Group 2: WAMI\u0026thinsp;=\u0026thinsp;5; Group 3: WAMI\u0026thinsp;\u0026gt;\u0026thinsp;5), we found that patients in Group 1 tended to rate themselves higher on the ladder than their WAMI while Group 3 tended to do rate themselves lower \u003cb\u003e(\u003c/b\u003eFig.\u0026nbsp;\u003cspan refid=\"Fig7\" class=\"InternalRef\"\u003e3\u003c/span\u003eb\u003cb\u003e).\u003c/b\u003e\u003c/p\u003e \u003cp\u003eTable\u0026nbsp;\u003cspan refid=\"Tab4\" class=\"InternalRef\"\u003e4\u003c/span\u003e\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab4\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 4\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eAgreement between MacArthur Ladder and WAMI\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"2\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eLadder Score\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003e% in agreement with WAMI\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSame group\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e29\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMoved 1 group\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e31\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMoved 2 groups\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e24\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMoved 3 groups\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e9.4\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMoved 4\u0026thinsp;+\u0026thinsp;groups\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e7.1\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eUnweighted Kappa\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.083\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eWeighted Kappa\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.33\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003eWhen retested with the MacArthur ladder 6 to 8 months after the initial survey, the 18 individuals with inconsistent scores had a median decrease in their retested ladder score of 5 (IQR: 1.25 to 6) compared to their initial ladder scores while individuals with similar scores had a median decrease of 2 (IQR: 0 to 3) \u003cb\u003e(\u003c/b\u003eFig.\u0026nbsp;\u003cspan refid=\"Fig8\" class=\"InternalRef\"\u003e4\u003c/span\u003ea\u003cb\u003e)\u003c/b\u003e. While initially the individual with inconsistent scores had a significant median difference between their WAMI and ladder score of -5 (IQR: -6 to 4), their score became more aligned with less variability (median difference of 2, IQR: -0.75 to 2.0). The difference between the WAMI and ladder scores remained relatively consistent for the individuals with similar scores, whose median difference was initially \u0026minus;\u0026thinsp;0.5 (IQR: -1 to 0) and retested median difference was 1 (IQR: 0 to 2) \u003cb\u003e(\u003c/b\u003eFig.\u0026nbsp;\u003cspan refid=\"Fig8\" class=\"InternalRef\"\u003e4\u003c/span\u003e\u003cb\u003e)\u003c/b\u003e. When retested ladder scores were used in replacement of the initial scores for all 36 retested individuals, we found stronger agreement with the WAMI score with the correlation coefficient increasing from 0.34 to 0.40 \u003cb\u003e(\u003c/b\u003eTable\u0026nbsp;\u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e3\u003c/span\u003e\u003cb\u003e).\u003c/b\u003e\u003c/p\u003e \u003cp\u003eCompared to those in the lowest ladder tertile, individuals in the highest ladder tertile were 2.0 (95% CI 0.89\u0026ndash;4.48) fold more likely to report a history of asthma, which was similar to the effect size we saw when WAMI was used as a predictor with a 1.99 (95% CI 0.88\u0026ndash;4.45) increased risk \u003cb\u003e(\u003c/b\u003eTable\u0026nbsp;\u003cspan refid=\"Tab5\" class=\"InternalRef\"\u003e5\u003c/span\u003e\u003cb\u003e).\u003c/b\u003e When determining which model was a better fit given our asthma data, we found that the AIC was comparable between WAMI (AIC: 312.41) and ladder (AIC: 312.37).(\u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e)\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab5\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 5\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e\u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"3\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e \u003cp\u003eTable\u0026nbsp;\u003cspan refid=\"Tab5\" class=\"InternalRef\"\u003e5\u003c/span\u003e Relationship between Asthma and SES\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSES\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eOdds Ratios (95% CI)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eAIC with outliers\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eWAMI\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e0\u0026ndash;4 points\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eRef\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e312.41\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e5 points\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1.38 (0.63 to 3.03)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e6\u0026ndash;10 points\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1.99 (0.88 to 4.45)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eLadder\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e0\u0026ndash;4 points\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eRef\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e312.37\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e5 points\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1.4 (0.64 to 3.06)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e6\u0026ndash;10 points\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e2.0 (0.89 to 4.48)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e"},{"header":"Discussion","content":"\u003cp\u003eHere, we found the self-reported MacArthur ladder score for SES correlated reasonably well with a more in-depth assessment of socio-economic status that included water and sanitation, assets, educational level and income. When we reassessed outlying scores 6\u0026ndash;8 months later, most outliers fell closer to the mean and the correlation between the ladder and WAMI improved. The ladder and WAMI scores were also similarly accurate in predicting an association with asthma, a health outcome known to be associated with SES in this setting. Taken together, these results suggest that the less cumbersome ladder score can be used to replace the more detailed WAMI with no loss of the ability to predict health outcomes or adjust for possible confounding by SES.\u003c/p\u003e \u003cp\u003eOur finding of a correlation of .34-.40 between the ladder and WAMI scores is highly consistent with previous studies comparing objective and subjective SES measurements. These were summarized in a meta-analysis that compiled 432 associations from 357 studies which found that the ladder score was associated with any of a number of different \u0026ldquo;objective\u0026rdquo; scores with a mean correlation coefficient of 0.323.(\u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e29\u003c/span\u003e) These results suggest that objective measures are consistently an important factor considered in self-reported SES. Previous qualitative analyses have reported that respondents mentioned income, material wealth, education as well as social comparison when asked what factors they considered when they self-rate using the ladder score, which is consistent with our findings that assets, income and education had a correlation of 0.27\u0026ndash;0.31 with the ladder.(\u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e29\u003c/span\u003e) In addition, the prevalence of asthma in Lima, Peru has previously been shown to be positively associated with SES, and the ladder and WAMI scores performed nearly identically in identifying this association.(\u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e)\u003c/p\u003e \u003cp\u003eWe note several limitations to this study. First, the participants completed the initial SES assessments at the time they were first diagnosed with TB, so the results of both scores might have been affected by their ongoing illness or the possibly temporary impact of their illness on their immediate socio-economic status. Because the McArthur ladder score is more dependent on subjective state, it may have been more likely to reflect the impact of the disease state. This interpretation is supported by the fact that agreement between the ladder and WAMI improved on retesting 6\u0026ndash;8 months later, at a time when TB treatment should have improved the participants health status. Second, our study was conducted in a distinct population of people with lower SES in Lima, and therefore, our results may not be generalizable to a different population. Third, our finding that the median and mode was 5 for the ladder score raises the possibility of a bias introduced by a responder preference for rounding off the numbers to 5, which would coarsen the data. Another possible explanation for the frequency of the 5 score is a frame-of-reference bias which might occur if individual participants are not familiar with the full range of possible socio-economic levels in their society and have little interaction with people in other social classes. In this case, wealthier individuals, who may be unaware of poorer individuals\u0026rsquo; impoverished circumstances, might tend to rate themselves lower while poorer individuals tend to rate themselves higher.(\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e, \u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e30\u003c/span\u003e)\u003c/p\u003e \u003cp\u003eFuture studies using the ladder scale might benefit from implementing methods to address scale heterogeneity and ensure interpersonal comparability of the ladder tool.(\u003cspan additionalcitationids=\"CR32 CR33 CR34\" citationid=\"CR31\" class=\"CitationRef\"\u003e31\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e35\u003c/span\u003e) One way to address these issues is to incorporate into the questionnaires anchoring vignettes which describe hypothetical individuals representing a specific anchor, or common, points on the ladder scale. Since the vignettes are consistent across respondents, any variation between individuals is then due to interpersonal inconsistencies, and statistical methods can be used to rescale individuals\u0026rsquo; self-reported SES. Expanding the use of anchoring vignettes to SES with the MacArthur ladder has yet to be explored and is a potential solution to improve the inter-person reliability and discriminatory power of subjective SES tools.\u003c/p\u003e"},{"header":"Conclusions","content":"\u003cp\u003eEpidemiological studies have traditionally measured socioeconomic status, an integral determinant of health outcomes, via objective markers and has overlooked subjective SES measurements, such as the MacArthur ladder tool, as an alternative. We demonstrated here that the ladder tool correlates well with WAMI, an objective SES index, in categorizing patients into SES levels and performs comparably in predicting health outcomes related to SES. Given that the ladder scale is simple and easy to administer, it is a tool that could reduce the burden of data collection in large, population-based health studies while still capturing patients\u0026rsquo; SES in a robust manner.\u003c/p\u003e"},{"header":"Abbreviations","content":"\u003cp\u003e\u003cstrong\u003eSES\u003c/strong\u003e \u0026ndash; socioeconomic status\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eWAMI\u003c/strong\u003e \u0026ndash; Water and sanitation, Asset ownership, Maternal education and household Income score\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eLadder score\u003c/strong\u003e \u0026ndash;\u0026nbsp;MacArthur\u0026rsquo;s Scale of Subjective Social status\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eTB\u003c/strong\u003e \u0026ndash; tuberculosis\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAIC\u003c/strong\u003e - Akaike information criterion\u0026nbsp;\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eEthics approval and consent to participate\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eBefore study participation, adult study participants provided voluntary, written informed consent.\u0026nbsp;For children, a guardian provided written informed consent and the children provided assent.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eThe Harvard School of Public Health and Peru’s Research Ethics Committee of the National Institute of Health provided Institutional Review Board approval. All methods were performed in accordance with the relevant guidelines and regulations.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConsent for publication\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eNot Applicable\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAvailability of data and materials\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe datasets used and/or analysed during the current study are available from the corresponding author on reasonable request.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eCompeting interests\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe authors declare that they have no competing interests.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFunding\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe work reported in this publication was supported by the National Institutes of Health and the National Institute of Allergy and Infectious Diseases grant U19 AI142793-03.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAuthors' contributions\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eMM and CC conceived of the study. LL, MM and XT implemented the study protocol in Peru and obtained the data to be analyzed. MZ analyzed and interpreted the survey data and wrote the first draft of the manuscript. All authors contributed to and approved the final manuscript.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAcknowledgements\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eNot Applicable\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\u003cli\u003e\u003cspan\u003eHanna DR, Campbell JA, Walker RJ, Dawson AZ, Egede LE. Association between Health and Wealth among Kenyan Adults with Hypertension. Glob J Health Sci. 2021;13(4):86\u0026ndash;94.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003ePoirier MJP, Grignon M, Gr\u0026eacute;pin KA, Dion ML. Transnational wealth-related health inequality measurement. 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Political Analysis. 2007;15:46\u0026ndash;66.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eRavallion M, Himelein K, Beegle K. Can Subjective Questions on Economic Welfare Be Trusted? Economic Development and Cultural Change [Internet]. 2016 May 18 [cited 2021 Jul 22]; Available from: \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://www.journals.uchicago.edu/doi/abs/10.1086/686793\u003c/span\u003e\u003cspan address=\"https://www.journals.uchicago.edu/doi/abs/10.1086/686793\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003ed\u0026rsquo;Uva TB, Doorslaer EV, Lindeboom M, O\u0026rsquo;Donnell O. Does reporting heterogeneity bias the measurement of health disparities? Health Economics. 2008;17(3):351\u0026ndash;75.\u003c/span\u003e\u003c/li\u003e\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":false,"highlight":"","institution":"","isAcceptedByJournal":true,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"bmc-medical-research-methodology","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"bmrm","sideBox":"Learn more about [BMC Medical Research Methodology](http://bmcmedresmethodol.biomedcentral.com/)","snPcode":"","submissionUrl":"https://www.editorialmanager.com/bmrm/default.aspx","title":"BMC Medical Research Methodology","twitterHandle":"BMC_series","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"em","reportingPortfolio":"BMC Series","inReviewEnabled":true,"inReviewRevisionsEnabled":true},"keywords":"Tuberculosis, Subjective socioeconomic status, Objective socioeconomic status, MacArthur Scale of Subjective Social Status","lastPublishedDoi":"10.21203/rs.3.rs-1858867/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-1858867/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003ch2\u003eBackground\u003c/h2\u003e \u003cp\u003eSubjective \u0026ldquo;ladder\u0026rdquo; measurements of socio-economic status (SES) are easy-to-administer tools that ask respondents to rate their own SES, allowing them to evaluate where they believe their material resources place them relative to their community. Here, we sought to compare a ladder score to a measure of SES that includes data on water and sanitation, asset ownership, education, and income (WAMI).\u003c/p\u003e\u003ch2\u003eMethods\u003c/h2\u003e \u003cp\u003eLeveraging an ongoing study of adult patients with tuberculosis in Lima, Peru, we compared results of the WAMI survey to the MacArthur Scale of Subjective Social Status. We assessed the relationship between WAMI and the ladder scores using Kappa scores and Spearman\u0026rsquo;s rank correlation coefficient. We used Akaike information criterion (AIC) to compare the predictability of logistic regression models that evaluated the association between SES and history of asthma.\u003c/p\u003e\u003ch2\u003eResults\u003c/h2\u003e \u003cp\u003eAmong 595 participants who completed both questionnaires, the MacArthur ladder and WAMI scores were within two or less points (on a scale of 10 points) of each other for 84% of participants. The correlation coefficient was 0.34 (p\u0026thinsp;\u0026lt;\u0026thinsp;0.001). Among 36 participants with a repeated ladder test, the 18 individuals who were selected for initially having dissimilar ladder and WAMI scores had a greater median decrease in their retested ladder scores (median 5, IQR: 1.25 to 6) compared to the 18 individuals who had similar scores (median 2, IQR: 0 to 3). When initial ladder scores were replaced with the repeated responses, the overall correlation coefficient increased to 0.40 (p\u0026thinsp;\u0026lt;\u0026thinsp;0.001) and the variability in the difference between the ladder scores and WAMI decreased. Both SES scores were associated with history of asthma.\u003c/p\u003e\u003ch2\u003eConclusion\u003c/h2\u003e \u003cp\u003eOur findings demonstrate that the MacArthur SES ladder is positively correlated to WAMI and performs similarly to WAMI in predicting a socio-economically sensitive health outcome. Researchers should consider subjective SES tools as an alternative method for measuring SES, particularly in large health studies where data collection is a burden.\u003c/p\u003e","manuscriptTitle":"Subjective socioeconomic status: an alternative to objective socioeconomic status","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2022-08-03 18:06:07","doi":"10.21203/rs.3.rs-1858867/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"decision","content":"Major revision","date":"2022-10-14T04:18:20+00:00","index":"","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2022-10-13T02:36:15+00:00","index":"hide","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2022-09-13T10:07:09+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"039bcee5-94fd-408f-b167-0058ae7c02b6","date":"2022-09-01T08:05:20+00:00","index":"hide","fulltext":""},{"type":"reviewersInvited","content":"","date":"2022-08-26T07:54:58+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2022-08-22T14:04:29+00:00","index":"","fulltext":""},{"type":"editorInvited","content":"","date":"2022-08-01T06:56:17+00:00","index":"","fulltext":""},{"type":"checksComplete","content":"","date":"2022-08-01T06:51:59+00:00","index":"","fulltext":""},{"type":"submitted","content":"BMC Medical Research Methodology","date":"2022-07-14T16:16:14+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"bmc-medical-research-methodology","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"bmrm","sideBox":"Learn more about [BMC Medical Research Methodology](http://bmcmedresmethodol.biomedcentral.com/)","snPcode":"","submissionUrl":"https://www.editorialmanager.com/bmrm/default.aspx","title":"BMC Medical Research Methodology","twitterHandle":"BMC_series","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"em","reportingPortfolio":"BMC Series","inReviewEnabled":true,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"af86fad8-4fb8-44b3-9ec8-b7aea287df1c","owner":[],"postedDate":"August 3rd, 2022","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"published-in-journal","subjectAreas":[],"tags":[],"updatedAt":"2023-10-16T20:20:16+00:00","versionOfRecord":{"articleIdentity":"rs-1858867","link":"https://doi.org/10.1186/s12874-023-01890-z","journal":{"identity":"bmc-medical-research-methodology","isVorOnly":false,"title":"BMC Medical Research Methodology"},"publishedOn":"2023-03-28 20:16:28","publishedOnDateReadable":"March 28th, 2023"},"versionCreatedAt":"2022-08-03 18:06:07","video":"","vorDoi":"10.1186/s12874-023-01890-z","vorDoiUrl":"https://doi.org/10.1186/s12874-023-01890-z","workflowStages":[]},"version":"v1","identity":"rs-1858867","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-1858867","identity":"rs-1858867","version":["v1"]},"buildId":"cBFmMYwuxLRRLfASyISRj","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}