Occupational Heat Risk Perceptions and Behavioral Adaptation Strategies Among Construction and Welding Workers in Bangladesh

Occupational Heat Risk Perceptions and Behavioral Adaptation Strategies Among Construction and Welding Workers in Bangladesh | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article Occupational Heat Risk Perceptions and Behavioral Adaptation Strategies Among Construction and Welding Workers in Bangladesh Ashiqur Rahman Tamim, Muhammad Mainuddin Patwary, Mondira Bardhan, and 8 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-8123494/v1 This work is licensed under a CC BY 4.0 License Status: Posted Version 1 posted You are reading this latest preprint version Abstract The increasing frequency and intensity of extreme heat events pose severe health risks to outdoor workers. Despite growing global recognition of occupational heat illness, evidence from low- and middle-income countries (LMICs) remains limited. This cross-sectional study surveyed 320 construction and welding workers to assess perceived heat-related health risk and behavioral adaptation in Bangladesh. Multinomial logistic regression examined factors associated with adaptive behaviors. Over 80% of workers perceived themselves as vulnerable, commonly reporting excessive sweating, thirst, cramps, irritability, and emotional instability. Construction workers were more likely than welding workers to take regular breaks (OR = 9.49, 95%CI: 2.45–36.74), wear loose clothing (OR = 4.26, 95%CI: 1.14–15.90), and use electric fans (OR = 2.84, 95%CI: 1.12–7.22). Conversely, welding workers more often slowed work pace (OR = 14.20, 95%CI: 2.03–99.21) or scheduled tasks during cooler hours (OR = 4.81, 95%CI: 2.22–46.80). Long work experience was associated with using cooling options (OR = 6.97, 95%CI: 1.97–24.68) and following weather forecasts (OR = 3.81, 95%CI: 1.01–14.37). Workers who experienced burns or memory decline adopted specific protective measures. Surprisingly, higher education was linked to lower participation in heat-safety training. These findings highlight the urgent need for occupation-specific heat standards, awareness campaigns, and targeted interventions to safeguard vulnerable outdoor workers in Bangladesh. Environmental Policy Occupational Medicine Climatology Health Policy Occupational Heat Stress Heat-Related Illness Heatwave Adaptation Climate Change LMICs Figures Figure 1 Figure 2 Figure 3 1. Introduction Climate change and rising global temperatures are causing increasingly frequent and devastating heatwaves 1 , 2 , with global heat-related mortality projected to rise by 0.5–2.5% under 1.5–3°C warming scenarios 3 . By 2100, working-age populations in high-emission regions may experience a dramatic surge—up to 16 times higher exposure to extreme heat compared to recent decades 4 ; this exposure may affect half of the world’s population by the same timeframe, even with stringent mitigation measures 5 . Furthermore, extreme heat threatens the economy, ecology, and human health 5 – 7 , with workplace productivity declining by 30% during heat stress and a 2.6% loss per °C above 24°C 6 . These losses were exacerbated by reduced worktime policies 8 , heat-induced sick leave 9 , and workforce attrition 10 , 11 , collectively slowing economic development, altering migratory patterns, aggravating poverty, and widening social inequality 12 – 15 . Heat vulnerability in individuals has been shaped by socioeconomic, demographic, health, and environmental factors 16 , with lower socioeconomic status, poverty, and limited education correlating strongly with heat-related mortality 17 – 21 . This risk is amplified in elderly populations, who experience higher hospitalization and mortality rates during extreme heat events 22 – 25 , and in workers with preexisting health conditions such as cardiovascular disease 20 , diabetes 26 , or mental health disorders 27 . These vulnerabilities are compounded by occupational settings; workers in strenuous outdoor roles (e.g., construction, welding) or poorly ventilated indoor environments face heightened risks due to prolonged heat exposure, inadequate cooling systems, and proximity to heat sources 28 – 33 . Construction workers endure extreme temperatures without access to drinking water, shade, or workplace policies addressing heat safety 34 – 36 , exacerbating heat-related illnesses risks such as cramps, fatigue, and stroke 37 – 41 . Such conditions impair mental and physical performance 42 , 43 , increasing the likelihood of occupational accidents, fatalities, and chronic health outcomes like skin cancer and immunological dysfunction 6 , 16 , 44 – 50 . Heat adaptive capacity (HAC) is a key factor in determining heat stress vulnerability. The outdoor workers with low HAC often suffer more with health issues and work efficiency due to heat exposure 51 . A study on Australian workers indicated that they have strong heat adaptability, largely due to their use of personal adaptive practices 52 . Chinese construction workers adopted some behavioral strategies like having cold water, changing work schedules, taking rest in shaded areas, putting on protective headwear, and stopping work when temperatures get very high 31 . Research has also suggested that a 40-minute break can enable 94% recovery from heat-related impacts 28 . A study with Bangladeshi workers revealed that higher water consumption, allowing air flow, and avoiding outdoor exposure were the main behavioral adaptations during hot weather 53 . Additionally, favorable clothing can help alleviate heat stress 28 , 31 . Bangladesh is highly vulnerable to climate change, with heatwaves emerging as a growing concern 54 . From 2003 to 2007, heatwaves were associated with an annual mortality rate of approximately 1,500 deaths 55 . Beyond health impacts, occupational heat stress carries profound economic implications, with the International Labor Organization (2019) projecting global productivity losses equivalent to 80 million full-time jobs and an estimated economic cost of USD 2.4 trillion 56 . While heat risk perception plays a role in shaping responses, evidence suggests that heightened awareness alone is insufficient to prevent adverse outcomes such as heat stroke in the absence of effective adaptive behaviors 57 . Importantly, adaptive practices are shaped by local climatic conditions, socioeconomic realities, and workplace settings, with factors such as age, income, access to cooling, and marital status influencing how individuals respond to heat stress 58 . Despite these realities, research on occupational heat exposure in Bangladesh remains limited. Existing studies have primarily focused on risk perceptions in specific industries—for instance, garment workers 59 and petroleum workers 60 , without addressing heat-related risks or adaptive strategies. More recently, Shahrujjaman et al. 53 examined adaptation among informal workers in Dhaka, but the findings were constrained by their focus on a single urban sector and potential recall biases from post-summer data collection. As such, there is still a lack of comprehensive, multi-sector evidence on how outdoor workers in Bangladesh perceive heat risks and adopt behavioral strategies to cope with them. To address this gap, the present study investigated the climate change and occupational heat risk perceptions, heat-illness risk, alongside self-regulated adaptive behaviors among construction and welding workers across multiple cities in Bangladesh. By identifying existing strategies and barriers, the study aims to generate actionable insights for policymakers and the scientific community, ultimately supporting interventions to reduce health burdens and improve worker productivity. 2. Methods 2.1. Study area The study was carried out in Bangladesh, a rapidly developing country in South Asia 61 . The country is characterized by a tropical monsoon climate with three distinct seasons: hot summer (March to early June), rainy season (June to early October), and dry winter (mid-October to late February). However, climatic conditions vary across the country. During the hot summer, temperatures range from 23.0 to 25.8 ºC on average, with peaks reaching 31.3 to 35.3 ºC 54 . The current study was conducted on three divisional cities of Bangladesh (Dhaka, Khulna, Barishal). These cities were selected to represent diverse geographic regions and demographic characteristics, encompassing coastal and inland areas, commercial centers, and regions with significant migration and population growth. Notably, Heat waves are most prevalent between April and June, peaking in May and occasionally extending into the monsoon season until September 54 . Relative humidity follows a similar pattern, peaking at around 90% during the early stages of the monsoon season and gradually decreasing towards the end of the rainy season, following the peak in maximum temperature 54 . 2.2. Study design and participants A cross-sectional survey was conducted among construction and welding workers at 3 different cities (Dhaka, Khulna, Barishal) in Bangladesh from May 2 to July 5, 2024. This timeframe was selected to align with Bangladesh's heat wave occurrences and make it simple for respondents to remember and connect to the problems and consequences of urban heat waves during this period. Recently, Bangladesh experienced unprecedented heatwaves during this timeframe, marking it as one of the most intense periods of heat in the country's history. The record-breaking heatwave in April 2024 was the longest continuous heatwave since 1948, lasting 26 consecutive days 62 . ​Elevated temperatures continued into May and June, affecting large parts of the country, including the Dhaka, Khulna, and Barishal divisions. Participants were selected using a purposive snowball sampling technique, which targeted people working outdoors with high exposure to ambient heat. Participants recruitment took place in two individual industries (welding and construction) with a focus on outdoor work environments from Dhaka, Khulna, and Barishal. All participants provided their consent before taking the survey and were given the option to stop the survey at any time. The survey did not require the disclosure of personal information such as names or email addresses. The study was approved by the research ethical clearance committee of Khulna University, Bangladesh (KUECC-2023/09/51). A pre-test (pilot study) of the questionnaire was conducted among 10 workers (5 from each occupation) in another urban area in Bangladesh. Feedback from the pre-test was used to refine question wording, response options, and skip patterns. No major structural changes were required, but minor adjustments were made to improve clarity and comprehension. A team of six trained enumerators conducted the suveys. Prior to data collection, enumerators received an online training session on the study objectives, ethical considerations, survey content, interviewing techniques, and data recording procedures. The training also included mock interviews and role-playing exercises to standardize interviewer behavior and minimize interviewer bias. The Bengali version of the questionnaire was used during all interviews. Enumerators used Google Forms (Bengali version) for data collection, which were later translated into English and checked for completeness and consistency by other members of the research team. Any discrepancies or missing values were resolved through follow-up with the enumerators. Notably, participants were made aware that their involvement in the study was entirely voluntary and that they might leave at any moment without facing any consequences. The sample size for this study was determined using a single population proportion formula, appropriate for cross-sectional surveys assessing perception and preparedness levels in a defined population 63 . In the absence of prior evidence on occupational heat perception among outdoor workers in Bangladesh, a conservative prevalence of 50% was assumed to maximize the required sample size. A 95% confidence level (Z = 1.96) and a 5.5% margin of error were applied in the calculation. This resulted in a minimum required sample of 318 participants. Given the very large size of the national working (employed) population (70.5 million) 64 , the finite population correction was negligible and did not alter the estimate. In total, 320 participants were recruited. The inclusion criteria to be a participant were construction and welding workers who must be 18 years or older. 2.3. Questionnaire design The questionnaire was created after a thorough evaluation of relevant studies on heat exposure and occupational health 65 , 66 . The final questionnaire consists of five parts and 36 questions about working settings, climate change risk perceptions, occupational heat stress risks, perceived heat stress symptoms and adaptation strategies. The detailed questionnaire is provided in the Supplementary Materials. The first section of the questionnaire included screening questions such as the respondent’s current place of residence and age. The second section evaluated climate change risk perceptions, which consisted of six questions related to urban heat and climate change knowledge. The first and second questions assessed the respondents' knowledge of climate change by asking, " Are you aware of climate change ?” and “ What are the signs of climate change ?" The third question asked “ Do you think climate change could affect the frequency or severity of heat-related stress in your workplace ?” In addition, the fourth and fifth questions asked about the environmental and work-related factors that influenced heat exposure in the workplace. The last question evaluated their concern about the potential impacts of climate change on occupational heat stress risks. Respondents were asked to rate the severity on a five-point Likert scale, ranging from 1 (not at all concerned) to 5 (extremely concerned) . The third section focused on workers’ perceptions of occupational heat risks. Participants were asked about their concerns regarding workplace heat exposure. They were also asked about the concern towards the developing of heat-related illnesses, with responses ranging from 1 ( not at all concerned) to 5 ( extremely concerned) . In addition, workers were asked whether they were concerned about heat-related injuries and to report any personal experiences of such incidents. Injury types included falls, trips, and slips; hitting stationary objects; being struck by moving objects; burns; and loss of grip or control due to sweaty hands. Workers were also asked about the presence of common heat-related symptoms, including heavy sweating, excessive thirst or dry cough, muscle cramps, fatigue or weakness, headache, dizziness, cold, clammy skin, nausea or vomiting, feelings of excessive heat, and fainting. Additionally, participants were asked about the expereince of psychological illnesses they suffered due to heat stress, such as emotional irritability, difficulty controlling temper, low mood, decline of memory, insomnia, trouble concentrating, lack of interest, and poor appetite. Finally, participants were asked about workplace preparedness, including the availability of workplace guidelines for hot weather, training sessions on heat safety, and whether they had received information or warnings from employers, authorities, or health organizations regarding protection against extreme heat exposure. The fourth section of the questionnaire focused on the workers’ adaptation strategies to occupational heat exposure. Participants were asked about the measures they used to cope with heat stress. The items assessed the frequency of specific adaptive behaviors, including following weather forecasts, drinking cool water, wearing loose and light-colored clothing, taking regular breaks, and planning and carrying out heavy routine outdoor work in the early morning or evening hours or in shaded areas. Additionally, participants were asked about their involvement in training programs on working safety in the heat, slowing down work rates, use of personal protective equipment (PPE), and cooling systems like electric fans in the workplace. Responses were measured on a six-point (1 − 6) scale: never do it , decreases a lot , decreases , unchanged , increases , and increases a lot . The final section asked about respondents' demographic characteristics, such as gender, age, education, occupation (working sector), number of family members, monthly income (normal day and hot day), and perceived health condition. Additionally, this section inquired about daily working hours, proximity to heat sources, time spent outdoors, and frequency of work performed near heat sources to understand their working conditions more comprehensively. 2.4. Data analysis Descriptive statistics were used to summarize participants’ sociodemographic characteristics and occupational factors. Categorical variables were presented as frequencies and percentages, while continuous variables were described using means and standard deviations. Normality tests were performed using the Shapiro-Wilk test. Due to the non-normal distribution of the data, differences between construction and welding workers were examined using non-parametric tests. Specifically, the Mann–Whitney U test was applied for comparisons between two groups, while the Kruskal–Wallis test was used for comparisons involving more than two groups. For categorical variables, differences were assessed using Pearson’s chi-square tests. To identify the factors associated with workers’ adaptation strategies to occupational heat exposure, we estimated a series of multinomial logit (MNL) models. The MNL model is an extension of the binary logit framework that allows analysis when the dependent variable has more than two unordered and mutually exclusive outcomes 67 . In this study, the dependent variables were the extent to which respondents reported adopting behaviours that mitigated high workplace heat exposure. For each behavior, respondents initially selected from six options: never do it , decreases a lot , decreases , no change , increases , or increases a lot . Participants who selected never do it were excluded from the analysis. For interpretability, the two “decreases” categories were combined into a single decreases outcome, and the two “increases” categories were combined into a single increases outcome, resulting in three final options: decreases , no change , and increases . Each adaptive behavior was modeled separately to assess the determinants of perceived changes in adaptive behaviors. Independent variables encompassed a wide range of sociodemographic and occupational characteristics, including gender, age group, education level, income category, years of work experience, daily working hours, outdoor work duration during hot weather, workplace environment (indoor/outdoor), the presence and frequency of working around heat sources. Additional covariates captured perceptions and concerns, including concern about heat exposure, concern about heat-related illness and injury, prior injury experience, perceived heat-related symptoms, having heat-prevention training and the availability of workplace guidelines or warnings. Given that the dependent variables consisted of three unordered categories, the MNL model was used to estimate the probability of workers selecting increase or decrease relative to the reference outcome ( no change ). Model estimation was performed using maximum likelihood methods implemented in the multinom function of the R package nnet . To address potential multicollinearity among independent variables, we examined pairwise correlation coefficients and visualized them using the R package corrplot . Variables with correlation coefficients greater than 0.7 were not simultaneously included in the models. The variables heat-prevention training, heat warnings, and heat guidelines were highly correlated (r > 0.7); thus, only heat-prevention training was retained for the final models. The coefficients from the MNL models represent the log odds of selecting a particular outcome relative to the reference category ( no change ). The results were reported as odds ratios (ORs) with 95% confidence intervals (CIs). An OR greater than 1 indicates a higher likelihood of reporting either increase or decrease in a behavior relative to no change , whereas an OR less than 1 indicates a lower likelihood, holding all other variables constant. 3. Results 3.1. Characteristics of respondents Table 1 summarizes the demographic and working characteristics of the study participants. The study included 320 workers, predominantly male (99.1%), with no significant gender difference between construction and welding workers. More than half (56.3%) were aged 18–30 years, with a slightly higher proportion of younger workers in construction (57.8%) than welding (54.1%), though this difference was not statistically significant. Education levels varied, with most having at least a secondary education (41.6%), while 13.1% had no formal education; construction workers were more likely to have no formal education, whereas welding workers had a higher proportion of respondents with secondary education, though the difference between the two groups was once again not statistically significant. Most workers (66.3%) earned between 10,001–20,000 BDT, with construction workers more likely to fall within this range (71.4%) than welding workers (59.3%), while welding workers had a higher proportion (25.9%) earning more than 20,000 BDT. Once again, the income difference between the two groups was not statistically significant. Nearly half of all respondents (46.6%) had 5–9 years of work experience. A statistically significant difference was observed between the two respondent groups in the number of daily working hours: 48.1% of all workers exceeded 8 hours, with welding workers (68.1%) working longer hours than construction workers (33.5%). Outdoor exposure in hot weather also varied statistically significantly between the two groups, with 87.5% of all workers spending more than 3 hours outdoors, but construction workers (94.6%) had greater outdoor exposure than welding workers (77.8%). The significant difference was in the workplace environment, with 96.8% of construction workers working entirely outdoors compared to 50.4% of welding workers. Despite most (93.8%) workers being exposed to heat, no significant difference was observed between the two groups, though welding workers were slightly more likely to report working near heat sources "often" or "always." Table 1 Characteristics of study respondents (n = 320). Descriptive Statistics Total (n = 320) Construction (n = 185) Welding (n = 135) χ2 (p) Gender 0.09 (0.755) Male 317 (99.1%) 183 (98.9%) 134 (99.3%) Female 3 (0.99%) 2 (1.1%) 1 (0.7%) Age 0.45 (0.503) 18–30 years 180 (56.3%) 107 (57.8%) 73 (54.1%) > 30 years 140 (43.8%) 78 (42.2%) 62 (45.9%) Education 6.11 (0.106) No formal education 42 (13.1%) 29 (15.7%) 13 (9.6%) Primary school level 101 (31.6%) 57 (30.8%) 44 (32.6%) Secondary school level 133 (41.6%) 69 (37.3%) 64 (47.4%) College or higher 44 (13.8%) 30 (16.2%) 14 (10.4%) Income 5.22 (0.073) 0-10000 BDT 41 (12.8%) 21 (11.4%) 20 (14.8%) 10001–20000 BDT 212 (66.3%) 132 (71.4%) 80 (59.3%) > 20000 BDT 67 (20.9%) 32 (17.3%) 35 (25.9%) Years of working 1.35 (0.510) < 5 years 84 (26.3%) 45 (24.3%) 39 (28.9%) 5–9 years 149 (46.6%) 91 (49.2%) 58 (43.0%) 9+ 87 (27.2%) 49 (26.5%) 38 (28.1%) Daily working hours 52.55 (0.000)*** 8h 110 (48.1%) 62 (33.5%) 92 (68.1%) Outdoor times during hot weather 20.31 (0.000)*** < 1h 10 (3.1%) 3 (1.6%) 7 (5.2%) 1-3h 30 (9.4%) 7 (3.8%) 23 (17.0%) 3-5h 280 (87.5%) 175 (94.6%) 105 (77.8%) Workplace environment 100.07 (0.000)*** Completely outdoor 91 (28.4%) 74 (40.0%) 17 (12.6%) Mainly outdoor 156 (48.8%) 105 (56.8%) 51 (37.8%) Completely indoor 18 (5.6%) 2 (1.1%) 16 (11.9%) Mainly indoor 55 (17.2%) 4 (2.2%) 51 (37.8%) Heat source exposure 0.07 (0.793) Yes 300 (93.8%) 11 (5.9%) 9 (6.7%) No 20 (6.3%) 174 (94.1%) 126 (93.3%) Frequency of working around heat source 6.74 (0.150) Never 3 (0.9%) 3 (1.6%) 8 (5.9%) Rarely 16 (5.0%) 8 (4.3%) 16 (11.9%) Sometimes 42 (13.1%) 26 (14.1%) 16 (11.9%) Often 167 (52.2%) 88 (47.8%) 79 (58.5%) Always 92 (28.7%) 60 (32.6%) 32 (23.7%) ***p < 0.001 significant at 1% level 3.2. Climate change risk perceptions Table 2 summarizes workers' awareness and concerns regarding climate change. The majority (75.6%) of workers were aware of climate change, with no significant difference (p = 0.615) between construction (74.6%) and welding workers (77%). Perceived signs of climate change varied significantly (p < 0.001) between workers. The most reported signs were increased temperature (71.3%) and irregular rainfall (67.2%), with welding workers more likely to note both (83.7% and 74.8%) compared to construction workers (62.2% and 61.6%). Most workers (92.5%) believed climate change affects heat-related stress, with no difference between groups (p = 0.707). However, significant differences existed in environmental factors influencing heat exposure (p = 0.003), with welding workers more likely to report hot air (77.0%) and high humidity (60.0%), while construction workers cited direct sunlight exposure (78.4%) more often. Significant differences were found in work-related heat exposure factors (p < 0.001). The majority of workers mentioned physical workload (95.3%), working hours (91.3%), duration of rest hours (71.9%) and access to cooling condition (54.1%) contributed to heat stress, with welding workers reporting longer working hours (97.8% vs. 86.5%) but less rest hours (69.6% vs 73.5%) and access to cooling (42.2% vs. 62.7%) (p < 0.001). Concerns about the impact of climate change on workplace heat stress also varied (p = 0.004), where 74.6% were very or extremely concerned, with welding workers more likely to be extremely concerned (39.3%) compared to construction workers (21.1%). Table 2 Awareness and concern about climate change among workers. Descriptive Statistics Total (n = 320) Construction (n = 185) Welding (n = 135) χ2 (p) Awareness of climate change 0.25 (0.615) Yes 242 (75.6%) 138 (74.6%) 104 (77%) No 78 (24.4%) 47 (25.4%) 31 (23%) Perceived signs of climate change 17.68 (0.000)*** Increase in temperature and hot weather 228 (71.3%) 115 (62.2%) 113 (83.7%) Irregular rainfall pattern 215 (67.2%) 114 (61.6%) 101 (74.8%) Increased frequency of cyclones and storms 158 (49.4%) 89 (48.1%) 69 (51.1%) Frequent floods 115 (35.9%) 77 (41.6%) 38 (28.1%) Prolong drought 96 (30.0%) 60 (32.4%) 36 (26.7%) Rising sea level 54 (16.9%) 41 (22.2%) 13 (9.6%) Lower water level 120 (37.5%) 73 (39.5%) 47 (34.8%) Saline water 71 (22.2%) 44 (23.8%) 27 (20.0%) No response 8 (2.5%) 4 (2.2%) 4 (3.0%) Belief that climate change could affect the frequency or severity of heat-related stress in the workplace 0.14 (0.707) Yes 296 (92.5%) 172 (93.0%) 124 (91.9%) No 24 (7.5%) 13 (7.0%) 11 (8.1%) Environmental factors influencing workplace heat exposure 8.54 (0.003)** Hot air around the workplace 218 (68.1%) 114 (61.6%) 104 (77.0%) High humidity in the workplace 158 (49.4%) 77 (41.6%) 81 (60.0%) Air flow around the workplace 153 (47.8%) 80 (43.2%) 73 (54.1%) Exposure to direct sunlight or other sources of radiant heat 217 (67.8%) 145 (78.4%) 72 (53.7%) Work-related factors influencing heat exposure 13.12 (0.000)*** Type of physical workload 305 (95.3%) 174 (94.1%) 131 (97.0%) Duration of working hours 292 (91.3%) 160 (86.5%) 132 (97.8%) Type of protective clothing 133 (41.6%) 86 (46.5%) 47 (34.8%) Access to cooling systems (e.g., air conditions & fans) 173 (54.1%) 116 (62.7%) 57 (42.2%) Duration of break/rest hours 230 (71.9%) 136 (73.5%) 94 (69.6%) Access to shade 147 (45.9%) 114 (61.6%) 33 (24.4%) Access to drinking water 83 (25.9%) 53 (28.6%) 30 (22.2%) Type of clothing 90 (28.1%) 61 (33.0%) 29 (21.5%) Level of concern about the impact of climate change on workplace heat stress 15.52 (0.004)** Not at all concerned 25 (7.8%) 13 (7.0%) 12 (8.9%) Slightly concerned 22 (6.9%) 15 (8.1%) 7 (5.2%) Moderately concerned 34 (10.6%) 25 (13.5%) 9 (6.7%) Highly concerned 147 (45.9%) 93 (50.3%) 54 (40.0%) Extremely concerned 92 (28.7%) 39 (21.1%) 53 (39.3%) *p < 0.05; **p < 0.01; ***p < 0.001; 3.3. Workplace heat risk perceptions Table 3 presents workers’ concerns and preparedness regarding heat exposure and heat-related injuries in the workplace. Most workers (80.6%) were concerned about heat exposure, with no significant difference between construction (78.4%) and welding (83.7%) workers (p = 0.234). However, concerns about heat illness risk at work varied (p = 0.047), with welding workers (31.6%) being more extremely concerned than construction workers (21.7%). Regarding heat-related injuries, 72.5% expressed concern, though differences between groups were not significant (p = 0.066). Among injury concerns, most workers cited risks of hitting objects, fear of burns, and worry about falls, trips, and slips. However, there were no significant differences between groups (p = 0.693). Burns were more frequently reported by welding workers (67.7%) than construction workers (26.2%), while falls (41.1%) and hitting objects (52.5%) were more common concerns among construction workers. Significant disparities were noted in workplace heat guidelines (p < 0.001), with more (42.7%) construction workers reporting their existence compared to welding workers (20.7%). Similarly, construction workers (42.7%) were more likely to receive heatwave warnings than welding workers (16.3%, p < 0.001). Training on heat-related injury prevention was also more common among construction workers (40.0%) than welding workers (10.4%, p < 0.001). Table 3 Occupational heat risk perception among workers. Descriptive Statistics Total (n = 320) Construction (n = 185) Welding (n = 135) χ2 (p) Concerns about heat exposure in the workplace 1.41 (0.234) Yes 258 (80.6%) 145 (78.4%) 113 (83.7%) No 62 (19.4%) 40 (21.6%) 22 (16.3%) Concern about heat illness risk in the workplace 9.61 (0.047)* Not at all concerned 34 (10.6%) 20 (10.9%) 14 (10.5%) Slightly concerned 28 (8.8%) 16 (8.7%) 12 (9.0%) Moderately concerned 44 (13.8%) 34 (18.5%) 10 (7.5%) Highly concerned 129 (40.3%) 74 (40.2%) 55 (41.4%) Extremely concerned 82 (25.6%) 40 (21.7%) 42 (31.6%) Heat-related injury concerns 5.44 (0.066) Yes 232 (72.5%) 42 (22.7%) 42 (31.1%) No 84 (26.3%) 139 (75.1%) 93 (68.9%) Don’t know/ Not sure 4 (1.3%) 4 (2.2%) 0 (0%) Injury experienced 5.44 (0.066) Falls, trips and slips 93 (29.1%) 58 (41.1%) 35 (37.6%) Hitting objects 122 (38.1%) 74 (52.5%) 48 (51.6%) Being hit by moving objects 58 (18.1%) 36 (25.5%) 22 (23.7%) Burn 100 (31.3%) 37 (26.2%) 63 (67.7%) Loss of grip and control due to sweaty hands 82 (25.6%) 48 (34.0%) 34 (36.6%) Working guidelines in the workplace during hot weather 24.40 (0.000)*** Yes 107 (33.4%) 79 (42.7%) 28 (20.7%) No 206 (64.4%) 99 (53.5%) 107 (79.3%) Don’t know/Not sure 9 (2.8%) 7 (3.8%) 0 (0%) Information or warnings from authorities or health organizations about safety during heatwaves 35.44 (0.000)*** Yes 101 (31.6%) 79 (42.7%) 22 (16.3%) No 210 (65.6%) 97 (52.4%) 113 (83.7%) Don’t know/Not sure 9 (2.8%) 9 (4.9%) 0 (0%) Workers training on the prevention of heat-related injuries 46.02 (0.000)*** Yes 88 (27.5%) 74 (40.0%) 14 (10.4%) No 222 (69.4%) 101 (54.6%) 121 (89.6%) Don’t know/Not sure 10 (3.1%) 10 (5.4%) 0 (0%) *p < 0.05; **p < 0.01; ***p < 0.001; 3.4. Heat-related illness symptoms Figure 1 & Table S1 summarizes the self-reported physical illness symptoms among the workers during hot weather. The most commonly reported symptoms included excessive sweating, frequent thirst, tiredness or weakness, and headaches. Significant differences were observed in heat-related physical illness symptoms (p < 0.05), with excessive sweating being more prevalent among welding workers (70.7%) than construction workers (51.3%). Frequent thirst was also higher among welding workers (57.8%) compared to construction workers (45.5%). Muscle cramps were reported more frequently by welding workers (27.0%) than by construction workers (14.3%). Nausea or vomiting was more common among construction workers (7.2%) than welding workers (2.6%). Fainting was significantly less frequent among welding workers (93.0%) than construction workers (70.9%, p < 0.001). No significant differences were found for tiredness or weakness, headache, or dizziness. Regarding specific psychological illnesses, emotional irritability (63.7%) and difficulty controlling temper (66.9%) were the most commonly reported issues. However, no significant differences were observed in mental health symptoms between groups. Emotional irritability (74.1%) and difficulty controlling temper (80.7%) were more common among welding workers than construction workers (56.2% and 56.8%, respectively). Low mood was reported at similar rates (43.7% vs. 37.8%). Insomnia was more frequent among construction workers (53.0%) than welding workers (40.7%). No substantial differences were noted in memory decline, concentration issues, lack of interest in activities, or poor appetite, though welding workers (35.6%) had slightly higher reports of poor appetite than construction workers (25.4%) (Fig. 2 & Table S1). 3.5. Behavioral adaptations during hot weather Most workers reported an increase in adaptive behaviors to mitigate heat exposure. The most commonly increased behaviors included drinking cool water before feeling thirsty (80%), taking regular breaks in shaded or cooler areas (69%), wearing loose and light-colored clothing (58%), slowing down the work rate to accommodate hot weather conditions (54%), and planning outdoor work during cooler times of the day (52%). However, a considerable proportion of workers indicated that they had not previously engaged in such adaptive behaviors, including participation in heat safety training programs (68%) and the use of PPE (60%) (Fig. 3 ). Significant differences were observed in the adaptive behaviors between occupational groups. A greater proportion of welding workers (71%) reported an increased practice of taking regular breaks in shaded or cooler areas compared to construction workers (68%, p = 0.004). The increased practice of planning outdoor work during cooler times was also more common among welding workers (73%) than construction workers (44%, p = 0.004). In contrast, participating in heat safety training programs was significantly higher among construction workers (25%) compared to welding workers (11%, p < 0.001). Similarly, the increased practice of using personal protective equipment during hot weather was more frequently reported among construction workers (27%) than welding workers (13%, p < 0.001). No significant differences were observed between the groups regarding the increased practice of following weather forecasts, drinking water before feeling thirsty, wearing light-colored clothing, slowing down the work rate, or using electric fans (Fig. 3 & Table S2). 3.6. Factors influencing the changes in heat adaptation behavior in workplace 3.6.1. Demographic and occupational differences in adaptation behavior Table 4 summarizes the factors influencing the behavioral adaptation by workers with odds ratios (ORs) and their 95% confidence intervals (CIs). The results revealed that workers with a college or higher level of education were less likely to increase their participation in heat − related safety training at their workplace (OR = 0.22, CI = 0.05 − 0.93). Construction workers, compared to welding workers, were nine times more likely to increase taking regular breaks during hot weather (OR = 9.49, CI = 2.45 − 36.74), four times more likely to increase wearing loose clothing (OR = 4.26, CI = 1.14 − 15.90), and nearly three times more likely to increase using electric fans to cool down (OR = 2.84, CI = 1.12 − 7.22). However, construction workers were four times less likely to plan to work during cooler periods of the day (OR = 4.81, CI = 2.22 − 46.80) and 14 times less likely to slow down their work rate as an adaptation to extreme heat (OR = 14.20, CI = 2.03 − 99.21) than welding workers. Workers with greater work experience (9 years or more) were seven times more likely to increase the use of cooling options, such as electric fans, (OR = 6.97, CI = 1.97 − 24.68) and nearly four times more likely to follow weather forecasts regularly (OR = 3.81, CI = 1.01 − 14.37), although they were nearly seven times less likely to adopt the behavior of slowing down their work rate (OR = 6.96, CI = 1.31 − 9.45) than those having lower work experience. Those working more than eight hours per day showed six times more increased tendency to drink water more frequently before feeling thirsty (OR = 6.41, CI = 1.45 − 28.35) and nearly ten times more willingness to follow weather forecasts to manage heat exposure (OR = 9.76, CI = 1.39 − 68.59) than their counterparts. In contrast, workers primarily engaged in outdoor activities were less likely to take regular breaks during hot weather, while workers engaged in indoor settings were less likely to wear loose clothing as an adaptive strategy. 3.6.2. Occupational risk perceptions and behavioral adaptation Perceptions of occupational heat risk significantly influenced adaptive behaviors. Workers who expressed concern about heat exposure at the workplace were less likely to increase the practice of wearing loose clothing. Workers who were slightly concerned about heat − illness risks were more likely to increase drinking water before feeling thirsty and to enhance the use of cooling options, such as electric fans. In contrast, workers who were moderately concerned were less likely to slow down their work rate. Workers who were very concerned about heat risks were more likely to increase behaviors such as following weather forecasts and slowing down their work rate, although they were less likely to increase the behavior of wearing loose clothing to adapt to extreme heat. Workers who were extremely concerned about heat risks were more likely to increase behaviors such as slowing down their work rate (Table 4 ). 3.6.3. Physical injuries, heat − stress symptoms and behavioral adaptation Workers who experienced injuries from hitting stationary objects in their workplace were 3.49 times more likely to increase the practice of taking regular breaks, while workers injured by moving objects were 7.90 times more likely to use cooling options (e.g., electric fans). Similarly, workers who suffered burns were 6.55 times more likely to plan their tasks during cooler hours of the day. Participate in heat − related training was also associated with a 6.50 − fold increase in the likelihood of adjusting work schedules to cooler periods. Workers reporting excessive sweating and tiredness or weakness were 6.35 and 3.19 times more likely to increase water intake, respectively, to mitigate heat stress. Experiencing muscle cramps or fainting was associated with a 2.42 and 2.64 times higher likelihood of wearing loose clothing, respectively. Additionally, those with muscle cramps were 1.95 times more likely to regularly follow weather forecasts. Workers who experienced mental health symptoms during hot weather at their workplace also showed changes in their adaptive behaviors. Workers who reported a decline in memory were 11.72 times more likely to increasingly use electric fans and 4.2 times more likely to increase the slowing down their work rate to cope with the heat. Workers who experienced insomnia were 8.67 times more likely to adopt the behavior of drinking water more frequently before feeling thirsty. Furthermore, those who reported having little interest or pleasure in doing things were 9.90 − fold more likely to shift their work to cooler times of the day (Table 4 ). Table 4 Factors affecting the behavioral adaptation by workers with red colours indicating a negative and green a positive effect at different levels of significance. Drink water before thirsty Take regular break Wear loose clothing Work in cooler hours Use cooling option (e.g., electric fans) Use PPE Follow weather forecast Slow down work rate Take heat safety training Decrease Increase Decrease Increase Decrease Increase Decrease Increase Decrease Increase Decrease Increase Decrease Increase Decrease Increase Decrease Increase Demographics : Gender Female Age > 30 years 0.07 (0.01 − 0.81) Education Primary school level Secondary school level College or higher 0.08 (0.01 − 0.94) 0.22 (0.05 − 0.93) Income 10001 − 20000 BDT More than 20000 BDT 0.03 (0.00 − 0.77) Working sectors Construction Site 9.17 (1.29 − 64.96) 9.49 (2.45 − 36.74) 4.26 (1.14 − 15.90) 34.81 (2.22 − 46.80) 2.84 (1.12 − 7.22) 14.20 (2.03 − 99.21) Years of working 5 − 9 years 3.19 (1.13 − 8.99) 9+ 6.97 (1.97 − 24.68) 3.81 (1.01 − 14.37) 6.96 (1.31 − 9.45) Daily working hours 8h 8h+ 6.41 (1.45 − 28.35) 9.76 (1.39 − 68.59) Outdoor times during hot weather 1 − 3h 3 − 5h 0.01 (0.00 − 0.56) Workplace environment Mainly outdoor 0.21 (0.06 − 0.69) Completely indoor 0.08 (0.01 − 0.69) Mainly indoor 0.05 (0.01 − 0.26) Heat Source Yes Frequency of your work around the heat source Rarely Sometimes Often Always Concern about heat Yes 0.11 (0.02 − 0.74) Concern about heat − illness risk Slightly concerned 31.85 (1.28 − 793.83) 7.14 (1.05 − 48.47) Moderately concerned 0.20 (0.04 − 0.93) Very concerned 0.06 (0.01 − 0.34) 5.21 (1.20 − 22.61) Extremely concerned 6.73 (1.12 − 40.49) Heat − related injury concern Yes Injury experienced Falls, trips and slips Hitting objects 3.49 (1.04 − 11.77) Being hit by moving objects 7.90 (1.81 − 34.56) Burn 6.55 (1.17 − 36.74) Loss of grip and controls due to sweaty hands Heat − related training Yes 6.50 (1.00 − 42.21) Perceived physical illness Excessive sweating 6.35 (1.67 − 24.14) Feeling thirsty Muscle cramp 0.17 (0.05 − 0.53) 2.42 (1.20 − 4.87) 1.95 (1.09 − 3.47) Tiredness or weakness 3.19 (1.22 − 8.35) 0.47 (0.23 − 0.95) Headache Dizziness Nausea or vomiting Fainting 2.64 (1.07 − 6.51) Perceived mental health symptoms Emotional irritability Difficulty to control temper Low mood Decline of memory 11.72 (2.04 − 67.38) 4.28 (1.01 − 18.14) Insomnia 8.67 (1.30 − 57.77) Trouble on concentration Little interest on things 9.90 (1.60 − 61.29) Poor appetite Note : The darkness of the colors corresponds to the level of significance. Dark red and green indicate a 1% significance level, light hues a 5% level; Reference: no change; Results reported as Odds Ratio (OR) with 95% confidence interval; PPE, Personal Protective Equipment. 4. Discussion 4.1. Climate change risk perceptions In our study of construction and welding workers in Bangladesh, we found that these heat − stressed workers showed reasonably high levels of awareness of climate change, consistent with previous studies reporting strong recognition of climate risks among outdoor workers in diverse settings 33 , 34 , 68 . Such awareness was likely reinforced by their occupational exposure to changing weather conditions. However, variations in perceived signs of climate change indicated the influence of job − specific environments. For instance, welding workers were more likely to report increased temperature and irregular rainfall, possibly due to combined exposure to ambient and process − generated heat, which may heighten their sensitivity to environmental change. This finding supported evidence that climate change perceptions often reflect lived occupational and environmental experiences 69 , 70 . Workers widely recognized the impact of climate change on heat − related stress, consistent with climatological trends of rising temperature, irregular rainfall, and extreme weather in the region 71 . Yet significant differences were observed in their identification of environmental heat factors. Welding workers emphasized hot air and humidity, while construction workers cited direct sunlight exposure, reflecting how task environments shape risk perceptions 72 . These variations are critical for policy considerations, as they point to differentiated vulnerabilities across occupational groups. Perceptions of work − related factors further revealed welding workers’ elevated risk: they more frequently reported longer working hours, fewer rest breaks, and limited access to cooling compared to construction workers. Such conditions explain their greater concern about workplace heat stress. Prior studies highlight rest regimes, shade, cooling systems, and hydration as essential for adaptation 33 , 72 . 4.2. Occupational risk perceptions The majority of workers expressed concern about workplace heat exposure, aligning with prior studies 33 , 73 . While overall concern did not differ significantly between construction and welding workers, welding workers were more likely to be extremely concerned about heat illness. This may reflect their more continuous exposure to process − generated heat, which amplifies vulnerability perceptions, echoing findings from other heat − intensive occupations 66 , 73 . Workers’ concerns about heat − related injuries were consistent with patterns reported elsewhere (Nunfam et al., 2019b; Stoecklin − Marois et al., 2013). Although group differences were not statistically significant, welding workers more frequently reported burns, reflecting dual risks of radiant heat and direct contact with hot surfaces, whereas construction workers mentioned falls, slips, and being struck by objects, often exacerbated by fatigue or dizziness. These task − specific differences parallel findings among mining and outdoor industrial workers, where exposure shaped diverse morbidity profiles 34 , 66 . An important disparity emerged in access to workplace heat guidelines, early warnings, and training, with construction workers significantly more likely to report such provisions. This suggests structural inequities in institutional support, echoing evidence that informal or small − enterprise workers often lack occupational health programs 75 . Prior research emphasizes that guidelines, training, and warning systems are critical for reducing heat stress and injuries 72 , 76 . 4.3. Perceived heat − related illness symptoms Physical symptoms such as excessive sweating, frequent thirst, and muscle cramps were commonly reported, with welding workers experiencing higher rates than construction workers, aligning with prior studies reported in other similar working settings 31 , 33 , 73 . This may result from intense thermal exposure, heavy physical exertion, and the use of protective clothing, which reduces sweat evaporation, traps heat, and elevates body temperature even under moderate conditions 73 , 77 – 79 . Symptoms such as headaches and dizziness did not significantly differ between groups, indicating general heat exposure effects. Psychological symptoms were also observed with no differences between welding workers and construction workers. However, welding workers reported higher irritability, potentially linked to both heat exposure and occupational manganese exposure, which has been associated with cognitive and mood disturbances 80 , 81 . Construction workers reported more insomnia, possibly related to irregular working hours or stress from outdoor work 82 , 83 . Welding workers experienced slightly more cases of poor appetite, likely due to dehydration, physical exhaustion, and prolonged exposure to high temperatures 84 . 4.4. Factors explaining differences in behavioral adaptation 4.4.1. Changes in hydration behavior Experienced workers were more likely to engage in proactive hydration, such as drinking water before feeling thirsty, consistent with previous studies in diverse occupational settings (Baby et al., 2021; Butani, 1988; Trillo − Cabello et al., 2021). Repeated exposure to heat, personal experience with dehydration, and witnessing workplace incidents may enhance internalization of self − protective practices. Experienced workers also serve as informal safety leaders, reinforcing hydration norms through peer influence 88 . Workers reporting excessive sweating, fatigue, or weakness were more likely to adopt anticipatory hydration. Studies from other occupational settings reported that exposure to extreme heat encourages self − regulatory behaviors, including proactive hydration, to prevent performance decline or illness (Al − Bouwarthan et al., 2020; Montazer et al., 2013). Sweating is the primary thermoregulatory mechanism during strenuous outdoor work, but heavy fluid loss can impair cardiovascular and muscular function (Ahasani et al., 1999; Al − Bouwarthan et al., 2019; Gagnon and Crandall, 2018; Krishnamurthy et al., 2017). Early − onset fatigue, often a precursor to heat exhaustion (Cunningham et al., 2022), has been frequently observed among outdoor workers exposed to prolonged solar radiation and physically strenuous labor 31 , 92 . Workers with insomnia were also more inclined to hydrate, possibly due to dysregulation of thermoregulatory and hormonal systems induced by poor 93 , 94 , which aligns with evidence linking sleep deprivation to higher perceived heat stress 95 . 4.4.2. Changes in working schedule Construction workers were more likely to take regular breaks during hot weather compared to welding workers, likely due to the physically demanding nature of their tasks and awareness of heat − related risks 96 – 98 . Work break and rest regimens were commonly employed to prevent heat stress 33 – 35 , and globally, similar practices have been formalized, such as mandatory ten − minute breaks every four hours in Austin 99 . In Bangladesh, construction sites are typically exposed to the full intensity of the tropical sun 100 , making breaks an essential physiological coping mechanism, consistent with patterns observed in other tropical climates 101 . Despite this, construction workers were reported to be less likely to plan work during cooler hours or slow their work pace compared to welding workers in this study, due to high − pressure, output − driven environments, strict timelines, contractual obligations, and client expectations, which limit flexibility 102 – 104 . Economic pressures, especially in settings with informal labor arrangements and piece − rate payments, further discourage adjustments to work schedules, as reduced pace or breaks directly affect wages 105 – 107 . Similar patterns have been reported in mining industries and other low − income country contexts, highlighting how economic vulnerability can override heat safety considerations 35 , 108 . Prior experience of workplace injuries influenced scheduling behaviors, such as workers who had burns or injuries were more likely to take breaks or plan work during cooler hours. Similar observations were reported among construction workers in China 31 . Burns, particularly common among welding workers due to intense radiant heat and sparks, are a severe and often traumatic form of injury 109 , 110 . Increased heat stress results in reduced job productivity and leads to occupational illnesses and injuries if enough breaks have not been maintained during work activities 111 . A direct and painful experience with severe heat can foster a deep concern for thermal dangers (e.g., burn), prompting workers to implement further preventive measures 112 , such as smart work scheduling. Workers who reported extreme concern about heat illness were more likely to slow their work pace, indicating that high perceived vulnerability serves as a strong motivator for adaptive behavior, consistent with previous occupational health studies 113 . Similarly, workers who received heat − related training were more likely to adjust their schedules, as training enhances understanding of heat risks, symptom recognition, and the rationale for adaptive practices such as shifting work hours 31 , 114 – 116 . In contrast, workers with greater work experience (≥ 9 years) were less likely to reduce their pace, possibly due to physiological acclimatization, psychological desensitization 51 , or a strong sense of duty and resilience compelling them to maintain productivity 117 . Likewise, workers with only moderate concern about heat − related illness tended not to slow their work, aligning with the Health Belief Model 118 , as they may rely on other preventive strategies, such as hydration or rest breaks, while perceiving they can manage risk without compromising output. Psychological factors are also related to workplace heat adaptation, with workers reporting reduced motivation or memory decline being more likely to adjust work schedules and slow their work pace Heat stress is well − documented to impair attention, concentration, and short − term memory, and workers experiencing such cognitive effects may consciously or subconsciously slow their work to prevent errors, accidents, or performance decline 119 – 121 . Evidence indicated that elevated temperatures exacerbate pre − existing mental health challenges, increasing irritability, fatigue, and impairing coping capacity 122 , 123 . Consequently, these workers proactively modify their schedules to cooler periods as a form of self − preservation. These findings underscore the importance of recognizing cognitive impairment as an early indicator of heat stress and integrating mental health considerations into occupational safety strategies, particularly in heat − exposed settings like Bangladesh, to support both physical and psychological well − being 124 . 4.4.3. Changes in personal comfort adaptation Construction workers commonly adopt adaptive clothing and cooling strategies to cope with extreme heat, with loose − fitting garments being the most prevalent. Loose clothing facilitates heat dissipation, reduces thermal discomfort, and lowers the risk of heat − related illness, a practice widely observed among physically demanding outdoor workers in tropical and subtropical climates 125 , 126 . In contrast, workers primarily indoors exhibited little adjustment in clothing may be linked to indoor employees tend to neglect the possibility of overheating, even when ventilation or climate control is inadequate 127 , 128 , despite evidence linking elevated indoor temperatures to reduced cognitive and physical performance, fatigue, and heat morbidity 129 . Personal cooling methods, particularly electric fans, were frequently reported among construction workers exposed to high solar radiation. Fans improve thermal comfort and mitigate heat stress when used alongside hydration and breaks, reflecting growing awareness of occupational heat risks 130 – 133 . Adoption of these practices correlated with work experience; employees with over five years of experience reported actively following adaptive measures, while those exceeding nine years often treated them as routine. Similarly, earlier studies found that workers with more years of experience demonstrated more consistent use of cooling strategies, including electric fans and rest breaks 134 . Perceived vulnerability was also related to personal adaptive behavior. Workers expressing even slight concern about heat − related illness were more likely to adopt cooling strategies, including shade seeking and adjusting work pace, supporting evidence that moderate risk perception promotes preventive actions 51 , 135 . Similarly, workers with a history of occupational injuries demonstrated higher engagement in heat mitigation, likely due to heightened risk awareness and sensitivity to environmental hazards 36 , 133 Psychological factors were further related to personal thermal adaptation. Outdoor workers reporting memory decline or reduced attention were more likely to implement cooling measures, reflecting a behavioral response to the cognitive strain imposed by heat stress. Elevated temperatures were known to impair attention, working memory, and executive function, and workers perceiving these effects appear to proactively adopt strategies to mitigate physical and cognitive risks 119 , 122 , 136 . 4.4.4. Environmental awareness and preparedness Experienced construction workers demonstrated greater attentiveness to weather forecasts than younger, less experienced colleagues. Previous research supports this pattern, showing that age and work experience positively influence safety attitudes and behaviors, whereas early − career workers tend to be more risk − taking and less cautious regarding occupational hazards 87 , 137 , 138 . Similarly, those working more than nine hours daily were more likely to monitor weather conditions, consistent with studies indicating that prolonged outdoor exposure fosters recognition of heat risks and motivates preventive behaviors 66 . Workers who experienced heat − related illnesses (e.g., muscle cramps) were also more inclined to follow weather forecasts. Such experiences reinforce the importance of proactive measures, including adjusting work hours, hydrating adequately, and seeking shade during peak heat 31 , 98 , 139 . Interestingly, workers with college or higher education were less likely to participate in heat − related training, diverging from prior studies showing greater engagement among educated employees 66 , 140 . Locally, this may reflect prioritization of career − focused training or financial incentives over occupational health programs, suggesting that perceived practical value strongly influences participation in preventive initiatives. 4.5. Policy and practice implications Our study suggests that effective heat adaptation among Bangladeshi outdoor workers requires behavioral, educational, and structural interventions. Policies should ensure regular work breaks, shaded rest areas, and access to cooling tools such as electric fans, particularly at high − exposure outdoor sites. Targeted training is needed for younger and less experienced workers to improve recognition of heat stress, adoption of safe work practices, and practical adaptation strategies. Workplace interventions should consider informal labor arrangements and economic pressures that prevent workers from slowing their pace or attending safety training. Integrating heat awareness into routine occupational health programs, with incentives, may improve engagement among educated workers who prioritize career − oriented training. Heat stress prevention must be included in workplace risk assessments and occupational health systems, with direct worker input. Guidelines should address both outdoor (construction) and indoor/high − heat (welding) environments, reflecting sector − specific challenges. Low participation in heat safety training highlights the need for accessible and practical programs. Policies should empower workers to self − pace and take breaks without fear of penalty. Monitoring systems tracking environmental conditions and worker health, combined with proactive scheduling based on weather forecasts, can reduce risks. Multi − sector collaboration among government, employers, labor organizations, and public health authorities is essential for the effective implementation and evaluation of interventions. 4.6. Strengths and limitations This study was one of the few in Bangladesh to examine outdoor workers’ perceptions and adaptations to heat exposure, providing important insights for policy. However, several limitations should be noted. The sample included only male workers, as construction and welding remain male − dominated sectors in Bangladesh, which limits the inclusion of female perspectives. Heat − related symptoms were self − reported and not objectively verified, and workplace temperatures or additional sources of heat from machinery and direct sunlight were not measured. Finally, the study focused on two occupational groups in selected cities, which may not represent all outdoor workers across different climatic zones of Bangladesh. 5. Conclusions This study showed that Bangladeshi construction and welding workers were generally aware of climate change and its impact on heat stress at work, but their ability to adapt varied. Most workers recognized factors like high temperature, humidity, and heavy workload as contributors to heat exposure. However, access to protective measures such as shade, cooling devices, and heat − related training was limited, especially among welding workers. Workers’ adaptive behaviors, such as drinking more water, taking breaks, using fans, wearing loose clothing, or adjusting work schedules, were influenced by previous heat − related symptoms, injuries, work experience, and their level of concern about heat risks. More experienced workers and those working longer hours tended to take more preventive actions, while younger or indoor workers adapted less. Furthermore, changes in working schedule and personal comfort had also been initiated to cope with the rising heat events. These outcomes highlight the urgent need for targeted policy interventions, occupational heat standards, and context − specific awareness programs to address urban heat exposure among outdoor workers in Bangladesh. The study also emphasizes the importance of integrating heat risk management into labor and urban planning policies, particularly for outdoor workers who are often excluded from mainstream protection frameworks. Declarations Data Availability Data can be made available on request to corresponding author. Human and Animal Rights and Informed Consent All participants provided their consent before taking the survey and were given the option to stop the survey at any time. The survey did not require the disclosure of personal information such as names or email addresses. The study was approved by the research ethical clearance committee of Khulna University, Bangladesh (KUECC−2023/09/51). Consent for publication All authors consent to publish this article in Scientific Reports. Declaration of Competing Interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper. Funding The study did not receive any funds, grants, or other support. References Klingelhöfer D, Braun M, Brüggmann D, Groneberg DA. 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Ind Health 2006; 44 : 474–80. Sponselee HCS, Kroeze W, Robroek SJW, Renders CM, Steenhuis IHM. Perceptions of employees with a low and medium level of education towards workplace health promotion programmes: a mixed-methods study. BMC Public Health 2022; 22 : 1617. Additional Declarations The authors declare no competing interests. Cite Share Download PDF Status: Posted Version 1 posted 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. We do this by developing innovative software and high quality services for the global research community. Our growing team is made up of researchers and industry professionals working together to solve the most critical problems facing scientific publishing. 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10:12:54","extension":"png","order_by":8,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":96167,"visible":true,"origin":"","legend":"","description":"","filename":"Onlinefloatimage3.png","url":"https://assets-eu.researchsquare.com/files/rs-8123494/v1/d967e5bacaa30f87ba9967c5.png"},{"id":96345932,"identity":"e2509f2b-b69b-4182-a10d-1372bb2895d4","added_by":"auto","created_at":"2025-11-20 06:03:12","extension":"xml","order_by":9,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":354093,"visible":true,"origin":"","legend":"","description":"","filename":"rs81234940structuring.xml","url":"https://assets-eu.researchsquare.com/files/rs-8123494/v1/8c2ab966a80a5b51cccc6410.xml"},{"id":96367387,"identity":"800dd117-21b2-4f79-9fe2-06c3045518a6","added_by":"auto","created_at":"2025-11-20 10:12:42","extension":"html","order_by":10,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":375953,"visible":true,"origin":"","legend":"","description":"","filename":"earlyproof.html","url":"https://assets-eu.researchsquare.com/files/rs-8123494/v1/728733586e08fcbe85e074f8.html"},{"id":96345919,"identity":"ffbe188b-883e-4330-869e-cc6b00189fc3","added_by":"auto","created_at":"2025-11-20 06:03:12","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":177648,"visible":true,"origin":"","legend":"\u003cp\u003eSelf-reported physical illness symptoms among workers during hot weather.\u003c/p\u003e","description":"","filename":"floatimage1.png","url":"https://assets-eu.researchsquare.com/files/rs-8123494/v1/55d201c3ca328f53110a08d6.png"},{"id":96367659,"identity":"0b477965-5f92-4471-848b-58aa086e4809","added_by":"auto","created_at":"2025-11-20 10:14:05","extension":"jpeg","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":247879,"visible":true,"origin":"","legend":"\u003cp\u003eSelf-reported mental illness symptoms among workers during hot weather.\u003c/p\u003e","description":"","filename":"floatimage2.jpeg","url":"https://assets-eu.researchsquare.com/files/rs-8123494/v1/16555ee623fc9b0121b5c4e2.jpeg"},{"id":96345925,"identity":"67d7b2fc-f46f-47bf-8f54-fcdfdfe86826","added_by":"auto","created_at":"2025-11-20 06:03:12","extension":"jpeg","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":488741,"visible":true,"origin":"","legend":"\u003cp\u003eBehavioral adaptations among workers to adapt with hot weather in workplace.\u003c/p\u003e","description":"","filename":"floatimage3.jpeg","url":"https://assets-eu.researchsquare.com/files/rs-8123494/v1/70302238f75580b43a4d2989.jpeg"},{"id":96369476,"identity":"52deda0e-13b1-42c0-8876-d17be166effa","added_by":"auto","created_at":"2025-11-20 10:21:06","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":3948894,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-8123494/v1/87d06460-0604-413a-b2d7-843520a3abb1.pdf"}],"financialInterests":"The authors declare no competing interests.","formattedTitle":"\u003cp\u003eOccupational Heat Risk Perceptions and Behavioral Adaptation Strategies Among Construction and Welding Workers in Bangladesh\u003c/p\u003e","fulltext":[{"header":"1. Introduction","content":"\u003cp\u003eClimate change and rising global temperatures are causing increasingly frequent and devastating heatwaves \u003csup\u003e\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e,\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e\u003c/sup\u003e, with global heat-related mortality projected to rise by 0.5\u0026ndash;2.5% under 1.5\u0026ndash;3\u0026deg;C warming scenarios \u003csup\u003e\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e\u003c/sup\u003e. By 2100, working-age populations in high-emission regions may experience a dramatic surge\u0026mdash;up to 16 times higher exposure to extreme heat compared to recent decades \u003csup\u003e\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e\u003c/sup\u003e; this exposure may affect half of the world\u0026rsquo;s population by the same timeframe, even with stringent mitigation measures \u003csup\u003e\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e\u003c/sup\u003e. Furthermore, extreme heat threatens the economy, ecology, and human health \u003csup\u003e\u003cspan additionalcitationids=\"CR6\" citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e\u003c/sup\u003e, with workplace productivity declining by 30% during heat stress and a 2.6% loss per \u0026deg;C above 24\u0026deg;C \u003csup\u003e6\u003c/sup\u003e. These losses were exacerbated by reduced worktime policies \u003csup\u003e\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e\u003c/sup\u003e, heat-induced sick leave \u003csup\u003e\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e\u003c/sup\u003e, and workforce attrition \u003csup\u003e\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e,\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e\u003c/sup\u003e, collectively slowing economic development, altering migratory patterns, aggravating poverty, and widening social inequality \u003csup\u003e\u003cspan additionalcitationids=\"CR13 CR14\" citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e\u003c/sup\u003e.\u003c/p\u003e\u003cp\u003eHeat vulnerability in individuals has been shaped by socioeconomic, demographic, health, and environmental factors \u003csup\u003e\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e\u003c/sup\u003e, with lower socioeconomic status, poverty, and limited education correlating strongly with heat-related mortality \u003csup\u003e\u003cspan additionalcitationids=\"CR18 CR19 CR20\" citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e\u003c/sup\u003e. This risk is amplified in elderly populations, who experience higher hospitalization and mortality rates during extreme heat events \u003csup\u003e\u003cspan additionalcitationids=\"CR23 CR24\" citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e\u003c/sup\u003e, and in workers with preexisting health conditions such as cardiovascular disease \u003csup\u003e\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e\u003c/sup\u003e, diabetes \u003csup\u003e\u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e\u003c/sup\u003e, or mental health disorders \u003csup\u003e\u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e\u003c/sup\u003e. These vulnerabilities are compounded by occupational settings; workers in strenuous outdoor roles (e.g., construction, welding) or poorly ventilated indoor environments face heightened risks due to prolonged heat exposure, inadequate cooling systems, and proximity to heat sources \u003csup\u003e\u003cspan additionalcitationids=\"CR29 CR30 CR31 CR32\" citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e33\u003c/span\u003e\u003c/sup\u003e. Construction workers endure extreme temperatures without access to drinking water, shade, or workplace policies addressing heat safety \u003csup\u003e\u003cspan additionalcitationids=\"CR35\" citationid=\"CR34\" class=\"CitationRef\"\u003e34\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR36\" class=\"CitationRef\"\u003e36\u003c/span\u003e\u003c/sup\u003e, exacerbating heat-related illnesses risks such as cramps, fatigue, and stroke \u003csup\u003e\u003cspan additionalcitationids=\"CR38 CR39 CR40\" citationid=\"CR37\" class=\"CitationRef\"\u003e37\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR41\" class=\"CitationRef\"\u003e41\u003c/span\u003e\u003c/sup\u003e. Such conditions impair mental and physical performance \u003csup\u003e\u003cspan citationid=\"CR42\" class=\"CitationRef\"\u003e42\u003c/span\u003e,\u003cspan citationid=\"CR43\" class=\"CitationRef\"\u003e43\u003c/span\u003e\u003c/sup\u003e, increasing the likelihood of occupational accidents, fatalities, and chronic health outcomes like skin cancer and immunological dysfunction \u003csup\u003e\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e,\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e,\u003cspan additionalcitationids=\"CR45 CR46 CR47 CR48 CR49\" citationid=\"CR44\" class=\"CitationRef\"\u003e44\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR50\" class=\"CitationRef\"\u003e50\u003c/span\u003e\u003c/sup\u003e.\u003c/p\u003e\u003cp\u003eHeat adaptive capacity (HAC) is a key factor in determining heat stress vulnerability. The outdoor workers with low HAC often suffer more with health issues and work efficiency due to heat exposure \u003csup\u003e\u003cspan citationid=\"CR51\" class=\"CitationRef\"\u003e51\u003c/span\u003e\u003c/sup\u003e. A study on Australian workers indicated that they have strong heat adaptability, largely due to their use of personal adaptive practices \u003csup\u003e\u003cspan citationid=\"CR52\" class=\"CitationRef\"\u003e52\u003c/span\u003e\u003c/sup\u003e. Chinese construction workers adopted some behavioral strategies like having cold water, changing work schedules, taking rest in shaded areas, putting on protective headwear, and stopping work when temperatures get very high \u003csup\u003e\u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e31\u003c/span\u003e\u003c/sup\u003e. Research has also suggested that a 40-minute break can enable 94% recovery from heat-related impacts \u003csup\u003e\u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e\u003c/sup\u003e. A study with Bangladeshi workers revealed that higher water consumption, allowing air flow, and avoiding outdoor exposure were the main behavioral adaptations during hot weather \u003csup\u003e\u003cspan citationid=\"CR53\" class=\"CitationRef\"\u003e53\u003c/span\u003e\u003c/sup\u003e. Additionally, favorable clothing can help alleviate heat stress \u003csup\u003e\u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e,\u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e31\u003c/span\u003e\u003c/sup\u003e.\u003c/p\u003e\u003cp\u003eBangladesh is highly vulnerable to climate change, with heatwaves emerging as a growing concern \u003csup\u003e\u003cspan citationid=\"CR54\" class=\"CitationRef\"\u003e54\u003c/span\u003e\u003c/sup\u003e. From 2003 to 2007, heatwaves were associated with an annual mortality rate of approximately 1,500 deaths \u003csup\u003e\u003cspan citationid=\"CR55\" class=\"CitationRef\"\u003e55\u003c/span\u003e\u003c/sup\u003e. Beyond health impacts, occupational heat stress carries profound economic implications, with the International Labor Organization (2019) projecting global productivity losses equivalent to 80\u0026nbsp;million full-time jobs and an estimated economic cost of USD 2.4 trillion \u003csup\u003e\u003cspan citationid=\"CR56\" class=\"CitationRef\"\u003e56\u003c/span\u003e\u003c/sup\u003e. While heat risk perception plays a role in shaping responses, evidence suggests that heightened awareness alone is insufficient to prevent adverse outcomes such as heat stroke in the absence of effective adaptive behaviors \u003csup\u003e\u003cspan citationid=\"CR57\" class=\"CitationRef\"\u003e57\u003c/span\u003e\u003c/sup\u003e. Importantly, adaptive practices are shaped by local climatic conditions, socioeconomic realities, and workplace settings, with factors such as age, income, access to cooling, and marital status influencing how individuals respond to heat stress \u003csup\u003e\u003cspan citationid=\"CR58\" class=\"CitationRef\"\u003e58\u003c/span\u003e\u003c/sup\u003e. Despite these realities, research on occupational heat exposure in Bangladesh remains limited. Existing studies have primarily focused on risk perceptions in specific industries\u0026mdash;for instance, garment workers \u003csup\u003e\u003cspan citationid=\"CR59\" class=\"CitationRef\"\u003e59\u003c/span\u003e\u003c/sup\u003e and petroleum workers \u003csup\u003e\u003cspan citationid=\"CR60\" class=\"CitationRef\"\u003e60\u003c/span\u003e\u003c/sup\u003e, without addressing heat-related risks or adaptive strategies. More recently, Shahrujjaman et al. \u003csup\u003e53\u003c/sup\u003e examined adaptation among informal workers in Dhaka, but the findings were constrained by their focus on a single urban sector and potential recall biases from post-summer data collection. As such, there is still a lack of comprehensive, multi-sector evidence on how outdoor workers in Bangladesh perceive heat risks and adopt behavioral strategies to cope with them. To address this gap, the present study investigated the climate change and occupational heat risk perceptions, heat-illness risk, alongside self-regulated adaptive behaviors among construction and welding workers across multiple cities in Bangladesh. By identifying existing strategies and barriers, the study aims to generate actionable insights for policymakers and the scientific community, ultimately supporting interventions to reduce health burdens and improve worker productivity.\u003c/p\u003e"},{"header":"2. Methods","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e\u003ch2\u003e2.1. Study area\u003c/h2\u003e\u003cp\u003eThe study was carried out in Bangladesh, a rapidly developing country in South Asia \u003csup\u003e\u003cspan citationid=\"CR61\" class=\"CitationRef\"\u003e61\u003c/span\u003e\u003c/sup\u003e. The country is characterized by a tropical monsoon climate with three distinct seasons: hot summer (March to early June), rainy season (June to early October), and dry winter (mid-October to late February). However, climatic conditions vary across the country. During the hot summer, temperatures range from 23.0 to 25.8 \u0026ordm;C on average, with peaks reaching 31.3 to 35.3 \u0026ordm;C \u003csup\u003e54\u003c/sup\u003e. The current study was conducted on three divisional cities of Bangladesh (Dhaka, Khulna, Barishal). These cities were selected to represent diverse geographic regions and demographic characteristics, encompassing coastal and inland areas, commercial centers, and regions with significant migration and population growth. Notably, Heat waves are most prevalent between April and June, peaking in May and occasionally extending into the monsoon season until September \u003csup\u003e\u003cspan citationid=\"CR54\" class=\"CitationRef\"\u003e54\u003c/span\u003e\u003c/sup\u003e. Relative humidity follows a similar pattern, peaking at around 90% during the early stages of the monsoon season and gradually decreasing towards the end of the rainy season, following the peak in maximum temperature \u003csup\u003e\u003cspan citationid=\"CR54\" class=\"CitationRef\"\u003e54\u003c/span\u003e\u003c/sup\u003e.\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec4\" class=\"Section2\"\u003e\u003ch2\u003e2.2. Study design and participants\u003c/h2\u003e\u003cp\u003eA cross-sectional survey was conducted among construction and welding workers at 3 different cities (Dhaka, Khulna, Barishal) in Bangladesh from May 2 to July 5, 2024. This timeframe was selected to align with Bangladesh's heat wave occurrences and make it simple for respondents to remember and connect to the problems and consequences of urban heat waves during this period. Recently, Bangladesh experienced unprecedented heatwaves during this timeframe, marking it as one of the most intense periods of heat in the country's history. The record-breaking heatwave in April 2024 was the longest continuous heatwave since 1948, lasting 26 consecutive days \u003csup\u003e\u003cspan citationid=\"CR62\" class=\"CitationRef\"\u003e62\u003c/span\u003e\u003c/sup\u003e. ​Elevated temperatures continued into May and June, affecting large parts of the country, including the Dhaka, Khulna, and Barishal divisions.\u003c/p\u003e\u003cp\u003eParticipants were selected using a purposive snowball sampling technique, which targeted people working outdoors with high exposure to ambient heat. Participants recruitment took place in two individual industries (welding and construction) with a focus on outdoor work environments from Dhaka, Khulna, and Barishal. All participants provided their consent before taking the survey and were given the option to stop the survey at any time. The survey did not require the disclosure of personal information such as names or email addresses. The study was approved by the research ethical clearance committee of Khulna University, Bangladesh (KUECC-2023/09/51).\u003c/p\u003e\u003cp\u003eA pre-test (pilot study) of the questionnaire was conducted among 10 workers (5 from each occupation) in another urban area in Bangladesh. Feedback from the pre-test was used to refine question wording, response options, and skip patterns. No major structural changes were required, but minor adjustments were made to improve clarity and comprehension. A team of six trained enumerators conducted the suveys. Prior to data collection, enumerators received an online training session on the study objectives, ethical considerations, survey content, interviewing techniques, and data recording procedures. The training also included mock interviews and role-playing exercises to standardize interviewer behavior and minimize interviewer bias. The Bengali version of the questionnaire was used during all interviews. Enumerators used Google Forms (Bengali version) for data collection, which were later translated into English and checked for completeness and consistency by other members of the research team. Any discrepancies or missing values were resolved through follow-up with the enumerators. Notably, participants were made aware that their involvement in the study was entirely voluntary and that they might leave at any moment without facing any consequences.\u003c/p\u003e\u003cp\u003eThe sample size for this study was determined using a single population proportion formula, appropriate for cross-sectional surveys assessing perception and preparedness levels in a defined population \u003csup\u003e\u003cspan citationid=\"CR63\" class=\"CitationRef\"\u003e63\u003c/span\u003e\u003c/sup\u003e. In the absence of prior evidence on occupational heat perception among outdoor workers in Bangladesh, a conservative prevalence of 50% was assumed to maximize the required sample size. A 95% confidence level (Z\u0026thinsp;=\u0026thinsp;1.96) and a 5.5% margin of error were applied in the calculation. This resulted in a minimum required sample of 318 participants. Given the very large size of the national working (employed) population (70.5\u0026nbsp;million) \u003csup\u003e\u003cspan citationid=\"CR64\" class=\"CitationRef\"\u003e64\u003c/span\u003e\u003c/sup\u003e, the finite population correction was negligible and did not alter the estimate. In total, 320 participants were recruited. The inclusion criteria to be a participant were construction and welding workers who must be 18 years or older.\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec5\" class=\"Section2\"\u003e\u003ch2\u003e2.3. Questionnaire design\u003c/h2\u003e\u003cp\u003eThe questionnaire was created after a thorough evaluation of relevant studies on heat exposure and occupational health \u003csup\u003e\u003cspan citationid=\"CR65\" class=\"CitationRef\"\u003e65\u003c/span\u003e,\u003cspan citationid=\"CR66\" class=\"CitationRef\"\u003e66\u003c/span\u003e\u003c/sup\u003e. The final questionnaire consists of five parts and 36 questions about working settings, climate change risk perceptions, occupational heat stress risks, perceived heat stress symptoms and adaptation strategies. The detailed questionnaire is provided in the Supplementary Materials.\u003c/p\u003e\u003cp\u003eThe first section of the questionnaire included screening questions such as the respondent\u0026rsquo;s current place of residence and age. The second section evaluated climate change risk perceptions, which consisted of six questions related to urban heat and climate change knowledge. The first and second questions assessed the respondents' knowledge of climate change by asking, \"\u003cem\u003eAre you aware of climate change\u003c/em\u003e?\u0026rdquo; and \u0026ldquo;\u003cem\u003eWhat are the signs of climate change\u003c/em\u003e?\" The third question asked \u0026ldquo;\u003cem\u003eDo you think climate change could affect the frequency or severity of heat-related stress in your workplace\u003c/em\u003e?\u0026rdquo; In addition, the fourth and fifth questions asked about the environmental and work-related factors that influenced heat exposure in the workplace. The last question evaluated their concern about the potential impacts of climate change on occupational heat stress risks. Respondents were asked to rate the severity on a five-point Likert scale, ranging from 1 \u003cem\u003e(not at all concerned)\u003c/em\u003e to 5 \u003cem\u003e(extremely concerned)\u003c/em\u003e.\u003c/p\u003e\u003cp\u003eThe third section focused on workers\u0026rsquo; perceptions of occupational heat risks. Participants were asked about their concerns regarding workplace heat exposure. They were also asked about the concern towards the developing of heat-related illnesses, with responses ranging from 1 (\u003cem\u003enot at all concerned)\u003c/em\u003e to 5 (\u003cem\u003eextremely concerned)\u003c/em\u003e. In addition, workers were asked whether they were concerned about heat-related injuries and to report any personal experiences of such incidents. Injury types included falls, trips, and slips; hitting stationary objects; being struck by moving objects; burns; and loss of grip or control due to sweaty hands. Workers were also asked about the presence of common heat-related symptoms, including heavy sweating, excessive thirst or dry cough, muscle cramps, fatigue or weakness, headache, dizziness, cold, clammy skin, nausea or vomiting, feelings of excessive heat, and fainting. Additionally, participants were asked about the expereince of psychological illnesses they suffered due to heat stress, such as emotional irritability, difficulty controlling temper, low mood, decline of memory, insomnia, trouble concentrating, lack of interest, and poor appetite. Finally, participants were asked about workplace preparedness, including the availability of workplace guidelines for hot weather, training sessions on heat safety, and whether they had received information or warnings from employers, authorities, or health organizations regarding protection against extreme heat exposure.\u003c/p\u003e\u003cp\u003eThe fourth section of the questionnaire focused on the workers\u0026rsquo; adaptation strategies to occupational heat exposure. Participants were asked about the measures they used to cope with heat stress. The items assessed the frequency of specific adaptive behaviors, including following weather forecasts, drinking cool water, wearing loose and light-colored clothing, taking regular breaks, and planning and carrying out heavy routine outdoor work in the early morning or evening hours or in shaded areas. Additionally, participants were asked about their involvement in training programs on working safety in the heat, slowing down work rates, use of personal protective equipment (PPE), and cooling systems like electric fans in the workplace. Responses were measured on a six-point (1\u0026thinsp;\u0026minus;\u0026thinsp;6) scale: \u003cem\u003enever do it\u003c/em\u003e, \u003cem\u003edecreases a lot\u003c/em\u003e, \u003cem\u003edecreases\u003c/em\u003e, \u003cem\u003eunchanged\u003c/em\u003e, \u003cem\u003eincreases\u003c/em\u003e, and \u003cem\u003eincreases a lot\u003c/em\u003e.\u003c/p\u003e\u003cp\u003eThe final section asked about respondents' demographic characteristics, such as gender, age, education, occupation (working sector), number of family members, monthly income (normal day and hot day), and perceived health condition. Additionally, this section inquired about daily working hours, proximity to heat sources, time spent outdoors, and frequency of work performed near heat sources to understand their working conditions more comprehensively.\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec6\" class=\"Section2\"\u003e\u003ch2\u003e2.4. Data analysis\u003c/h2\u003e\u003cp\u003eDescriptive statistics were used to summarize participants\u0026rsquo; sociodemographic characteristics and occupational factors. Categorical variables were presented as frequencies and percentages, while continuous variables were described using means and standard deviations. Normality tests were performed using the Shapiro-Wilk test. Due to the non-normal distribution of the data, differences between construction and welding workers were examined using non-parametric tests. Specifically, the Mann\u0026ndash;Whitney U test was applied for comparisons between two groups, while the Kruskal\u0026ndash;Wallis test was used for comparisons involving more than two groups. For categorical variables, differences were assessed using Pearson\u0026rsquo;s chi-square tests.\u003c/p\u003e\u003cp\u003eTo identify the factors associated with workers\u0026rsquo; adaptation strategies to occupational heat exposure, we estimated a series of multinomial logit (MNL) models. The MNL model is an extension of the binary logit framework that allows analysis when the dependent variable has more than two unordered and mutually exclusive outcomes \u003csup\u003e\u003cspan citationid=\"CR67\" class=\"CitationRef\"\u003e67\u003c/span\u003e\u003c/sup\u003e. In this study, the dependent variables were the extent to which respondents reported adopting behaviours that mitigated high workplace heat exposure. For each behavior, respondents initially selected from six options: \u003cem\u003enever do it\u003c/em\u003e, \u003cem\u003edecreases a lot\u003c/em\u003e, \u003cem\u003edecreases\u003c/em\u003e, \u003cem\u003eno change\u003c/em\u003e, \u003cem\u003eincreases\u003c/em\u003e, or \u003cem\u003eincreases a lot\u003c/em\u003e. Participants who selected \u003cem\u003enever do it\u003c/em\u003e were excluded from the analysis. For interpretability, the two \u0026ldquo;decreases\u0026rdquo; categories were combined into a single \u003cem\u003edecreases\u003c/em\u003e outcome, and the two \u0026ldquo;increases\u0026rdquo; categories were combined into a single \u003cem\u003eincreases\u003c/em\u003e outcome, resulting in three final options: \u003cem\u003edecreases\u003c/em\u003e, \u003cem\u003eno change\u003c/em\u003e, and \u003cem\u003eincreases\u003c/em\u003e. Each adaptive behavior was modeled separately to assess the determinants of perceived changes in adaptive behaviors. Independent variables encompassed a wide range of sociodemographic and occupational characteristics, including gender, age group, education level, income category, years of work experience, daily working hours, outdoor work duration during hot weather, workplace environment (indoor/outdoor), the presence and frequency of working around heat sources. Additional covariates captured perceptions and concerns, including concern about heat exposure, concern about heat-related illness and injury, prior injury experience, perceived heat-related symptoms, having heat-prevention training and the availability of workplace guidelines or warnings.\u003c/p\u003e\u003cp\u003eGiven that the dependent variables consisted of three unordered categories, the MNL model was used to estimate the probability of workers selecting \u003cem\u003eincrease\u003c/em\u003e or \u003cem\u003edecrease\u003c/em\u003e relative to the reference outcome (\u003cem\u003eno change\u003c/em\u003e). Model estimation was performed using maximum likelihood methods implemented in the \u003cem\u003emultinom\u003c/em\u003e function of the R package \u003cem\u003ennet\u003c/em\u003e. To address potential multicollinearity among independent variables, we examined pairwise correlation coefficients and visualized them using the R package \u003cem\u003ecorrplot\u003c/em\u003e. Variables with correlation coefficients greater than 0.7 were not simultaneously included in the models. The variables heat-prevention training, heat warnings, and heat guidelines were highly correlated (r\u0026thinsp;\u0026gt;\u0026thinsp;0.7); thus, only heat-prevention training was retained for the final models. The coefficients from the MNL models represent the log odds of selecting a particular outcome relative to the reference category (\u003cem\u003eno change\u003c/em\u003e). The results were reported as odds ratios (ORs) with 95% confidence intervals (CIs). An OR greater than 1 indicates a higher likelihood of reporting either \u003cem\u003eincrease\u003c/em\u003e or \u003cem\u003edecrease\u003c/em\u003e in a behavior relative to \u003cem\u003eno change\u003c/em\u003e, whereas an OR less than 1 indicates a lower likelihood, holding all other variables constant.\u003c/p\u003e\u003c/div\u003e"},{"header":"3. Results","content":"\u003cdiv id=\"Sec8\" class=\"Section2\"\u003e\u003ch2\u003e3.1. Characteristics of respondents\u003c/h2\u003e\u003cp\u003eTable\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e summarizes the demographic and working characteristics of the study participants. The study included 320 workers, predominantly male (99.1%), with no significant gender difference between construction and welding workers. More than half (56.3%) were aged 18\u0026ndash;30 years, with a slightly higher proportion of younger workers in construction (57.8%) than welding (54.1%), though this difference was not statistically significant. Education levels varied, with most having at least a secondary education (41.6%), while 13.1% had no formal education; construction workers were more likely to have no formal education, whereas welding workers had a higher proportion of respondents with secondary education, though the difference between the two groups was once again not statistically significant. Most workers (66.3%) earned between 10,001\u0026ndash;20,000 BDT, with construction workers more likely to fall within this range (71.4%) than welding workers (59.3%), while welding workers had a higher proportion (25.9%) earning more than 20,000 BDT. Once again, the income difference between the two groups was not statistically significant. Nearly half of all respondents (46.6%) had 5\u0026ndash;9 years of work experience. A statistically significant difference was observed between the two respondent groups in the number of daily working hours: 48.1% of all workers exceeded 8 hours, with welding workers (68.1%) working longer hours than construction workers (33.5%). Outdoor exposure in hot weather also varied statistically significantly between the two groups, with 87.5% of all workers spending more than 3 hours outdoors, but construction workers (94.6%) had greater outdoor exposure than welding workers (77.8%). The significant difference was in the workplace environment, with 96.8% of construction workers working entirely outdoors compared to 50.4% of welding workers. Despite most (93.8%) workers being exposed to heat, no significant difference was observed between the two groups, though welding workers were slightly more likely to report working near heat sources \"often\" or \"always.\"\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\u003eCharacteristics of study respondents (n\u0026thinsp;=\u0026thinsp;320).\u003c/p\u003e\u003c/div\u003e\u003c/caption\u003e\u003ccolgroup cols=\"5\"\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e\u003cthead\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cem\u003eDescriptive Statistics\u003c/em\u003e\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c2\"\u003e\u003cp\u003e\u003cem\u003eTotal\u003c/em\u003e\u003c/p\u003e\u003cp\u003e\u003cem\u003e(n\u0026thinsp;=\u0026thinsp;320)\u003c/em\u003e\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c3\"\u003e\u003cp\u003e\u003cem\u003eConstruction\u003c/em\u003e\u003c/p\u003e\u003cp\u003e\u003cem\u003e(n\u0026thinsp;=\u0026thinsp;185)\u003c/em\u003e\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c4\"\u003e\u003cp\u003e\u003cem\u003eWelding\u003c/em\u003e\u003c/p\u003e\u003cp\u003e\u003cem\u003e(n\u0026thinsp;=\u0026thinsp;135)\u003c/em\u003e\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c5\"\u003e\u003cp\u003e\u003cem\u003eχ2 (p)\u003c/em\u003e\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003eGender\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\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e0.09 (0.755)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eMale\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e317 (99.1%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e183 (98.9%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e134 (99.3%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eFemale\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e3 (0.99%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e2 (1.1%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e1 (0.7%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003eAge\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\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e0.45 (0.503)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e18\u0026ndash;30 years\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e180 (56.3%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e107 (57.8%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e73 (54.1%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u0026gt;\u0026thinsp;30 years\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e140 (43.8%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e78 (42.2%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e62 (45.9%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003eEducation\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\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e6.11 (0.106)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eNo formal education\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e42 (13.1%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e29 (15.7%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e13 (9.6%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003ePrimary school level\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e101 (31.6%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e57 (30.8%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e44 (32.6%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eSecondary school level\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e133 (41.6%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e69 (37.3%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e64 (47.4%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eCollege or higher\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e44 (13.8%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e30 (16.2%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e14 (10.4%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003eIncome\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\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e5.22 (0.073)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e0-10000 BDT\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e41 (12.8%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e21 (11.4%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e20 (14.8%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e10001\u0026ndash;20000 BDT\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e212 (66.3%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e132 (71.4%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e80 (59.3%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u0026gt;\u0026thinsp;20000 BDT\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e67 (20.9%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e32 (17.3%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e35 (25.9%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003eYears of working\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\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e1.35 (0.510)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u0026lt;\u0026thinsp;5 years\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e84 (26.3%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e45 (24.3%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e39 (28.9%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e5\u0026ndash;9 years\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e149 (46.6%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e91 (49.2%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e58 (43.0%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e9+\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e87 (27.2%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e49 (26.5%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e38 (28.1%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003eDaily working hours\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\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e52.55 (0.000)***\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u0026lt;\u0026thinsp;8h\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e13 (4.1%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e3 (1.6%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e10 (7.4%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e8h\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e153 (47.8%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e120 (64.9%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e33 (24.4%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u0026gt;\u0026thinsp;8h\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e110 (48.1%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e62 (33.5%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e92 (68.1%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colspan=\"4\" nameend=\"c4\" namest=\"c1\"\u003e\u003cp\u003e\u003cb\u003eOutdoor times during hot weather\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e20.31 (0.000)***\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u0026lt;\u0026thinsp;1h\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e10 (3.1%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e3 (1.6%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e7 (5.2%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e1-3h\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e30 (9.4%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e7 (3.8%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e23 (17.0%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e3-5h\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e280 (87.5%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e175 (94.6%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e105 (77.8%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003eWorkplace environment\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\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e100.07 (0.000)***\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eCompletely outdoor\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e91 (28.4%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e74 (40.0%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e17 (12.6%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eMainly outdoor\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e156 (48.8%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e105 (56.8%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e51 (37.8%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eCompletely indoor\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e18 (5.6%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e2 (1.1%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e16 (11.9%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eMainly indoor\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e55 (17.2%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e4 (2.2%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e51 (37.8%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003eHeat source exposure\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\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e0.07 (0.793)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eYes\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e300 (93.8%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e11 (5.9%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e9 (6.7%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eNo\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e20 (6.3%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e174 (94.1%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e126 (93.3%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colspan=\"4\" nameend=\"c4\" namest=\"c1\"\u003e\u003cp\u003e\u003cb\u003eFrequency of working around heat source\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e6.74 (0.150)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eNever\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e3 (0.9%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e3 (1.6%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e8 (5.9%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eRarely\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e16 (5.0%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e8 (4.3%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e16 (11.9%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eSometimes\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e42 (13.1%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e26 (14.1%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e16 (11.9%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eOften\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e167 (52.2%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e88 (47.8%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e79 (58.5%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eAlways\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e92 (28.7%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e60 (32.6%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e32 (23.7%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003c/tbody\u003e\u003c/colgroup\u003e\u003ctfoot\u003e\u003ctr\u003e\u003ctd colspan=\"5\"\u003e***p\u0026thinsp;\u0026lt;\u0026thinsp;0.001 significant at 1% level\u003c/td\u003e\u003c/tr\u003e\u003c/tfoot\u003e\u003c/table\u003e\u003c/div\u003e\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec9\" class=\"Section2\"\u003e\u003ch2\u003e3.2. Climate change risk perceptions\u003c/h2\u003e\u003cp\u003eTable\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e summarizes workers' awareness and concerns regarding climate change. The majority (75.6%) of workers were aware of climate change, with no significant difference (p\u0026thinsp;=\u0026thinsp;0.615) between construction (74.6%) and welding workers (77%). Perceived signs of climate change varied significantly (p\u0026thinsp;\u0026lt;\u0026thinsp;0.001) between workers. The most reported signs were increased temperature (71.3%) and irregular rainfall (67.2%), with welding workers more likely to note both (83.7% and 74.8%) compared to construction workers (62.2% and 61.6%). Most workers (92.5%) believed climate change affects heat-related stress, with no difference between groups (p\u0026thinsp;=\u0026thinsp;0.707). However, significant differences existed in environmental factors influencing heat exposure (p\u0026thinsp;=\u0026thinsp;0.003), with welding workers more likely to report hot air (77.0%) and high humidity (60.0%), while construction workers cited direct sunlight exposure (78.4%) more often.\u003c/p\u003e\u003cp\u003eSignificant differences were found in work-related heat exposure factors (p\u0026thinsp;\u0026lt;\u0026thinsp;0.001). The majority of workers mentioned physical workload (95.3%), working hours (91.3%), duration of rest hours (71.9%) and access to cooling condition (54.1%) contributed to heat stress, with welding workers reporting longer working hours (97.8% vs. 86.5%) but less rest hours (69.6% vs 73.5%) and access to cooling (42.2% vs. 62.7%) (p\u0026thinsp;\u0026lt;\u0026thinsp;0.001). Concerns about the impact of climate change on workplace heat stress also varied (p\u0026thinsp;=\u0026thinsp;0.004), where 74.6% were very or extremely concerned, with welding workers more likely to be extremely concerned (39.3%) compared to construction workers (21.1%).\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\u003eAwareness and concern about climate change among workers.\u003c/p\u003e\u003c/div\u003e\u003c/caption\u003e\u003ccolgroup cols=\"5\"\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e\u003cthead\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cem\u003eDescriptive Statistics\u003c/em\u003e\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c2\"\u003e\u003cp\u003e\u003cem\u003eTotal\u003c/em\u003e\u003c/p\u003e\u003cp\u003e\u003cem\u003e(n\u0026thinsp;=\u0026thinsp;320)\u003c/em\u003e\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c3\"\u003e\u003cp\u003e\u003cem\u003eConstruction\u003c/em\u003e\u003c/p\u003e\u003cp\u003e\u003cem\u003e(n\u0026thinsp;=\u0026thinsp;185)\u003c/em\u003e\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c4\"\u003e\u003cp\u003e\u003cem\u003eWelding\u003c/em\u003e\u003c/p\u003e\u003cp\u003e\u003cem\u003e(n\u0026thinsp;=\u0026thinsp;135)\u003c/em\u003e\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c5\"\u003e\u003cp\u003e\u003cem\u003eχ2 (p)\u003c/em\u003e\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colspan=\"4\" nameend=\"c4\" namest=\"c1\"\u003e\u003cp\u003e\u003cb\u003eAwareness of climate change\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e0.25 (0.615)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eYes\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e242 (75.6%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e138 (74.6%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e104 (77%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eNo\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e78 (24.4%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e47 (25.4%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e31 (23%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colspan=\"4\" nameend=\"c4\" namest=\"c1\"\u003e\u003cp\u003e\u003cb\u003ePerceived signs of climate change\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e17.68 (0.000)***\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eIncrease in temperature and hot weather\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e228 (71.3%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e115 (62.2%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e113 (83.7%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eIrregular rainfall pattern\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e215 (67.2%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e114 (61.6%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e101 (74.8%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eIncreased frequency of cyclones and storms\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e158 (49.4%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e89 (48.1%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e69 (51.1%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eFrequent floods\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e115 (35.9%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e77 (41.6%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e38 (28.1%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eProlong drought\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e96 (30.0%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e60 (32.4%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e36 (26.7%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eRising sea level\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e54 (16.9%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e41 (22.2%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e13 (9.6%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eLower water level\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e120 (37.5%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e73 (39.5%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e47 (34.8%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eSaline water\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e71 (22.2%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e44 (23.8%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e27 (20.0%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eNo response\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e8 (2.5%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e4 (2.2%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e4 (3.0%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colspan=\"4\" nameend=\"c4\" namest=\"c1\"\u003e\u003cp\u003e\u003cb\u003eBelief that climate change could affect the frequency or severity of heat-related stress in the workplace\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e0.14 (0.707)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eYes\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e296 (92.5%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e172 (93.0%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e124 (91.9%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eNo\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e24 (7.5%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e13 (7.0%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e11 (8.1%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colspan=\"4\" nameend=\"c4\" namest=\"c1\"\u003e\u003cp\u003e\u003cb\u003eEnvironmental factors influencing workplace heat exposure\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e8.54 (0.003)**\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eHot air around the workplace\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e218 (68.1%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e114 (61.6%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e104 (77.0%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eHigh humidity in the workplace\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e158 (49.4%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e77 (41.6%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e81 (60.0%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eAir flow around the workplace\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e153 (47.8%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e80 (43.2%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e73 (54.1%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eExposure to direct sunlight or other sources of radiant heat\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e217 (67.8%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e145 (78.4%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e72 (53.7%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colspan=\"4\" nameend=\"c4\" namest=\"c1\"\u003e\u003cp\u003e\u003cb\u003eWork-related factors influencing heat exposure\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e13.12 (0.000)***\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eType of physical workload\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e305 (95.3%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e174 (94.1%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e131 (97.0%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eDuration of working hours\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e292 (91.3%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e160 (86.5%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e132 (97.8%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eType of protective clothing\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e133 (41.6%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e86 (46.5%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e47 (34.8%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eAccess to cooling systems (e.g., air conditions \u0026amp; fans)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e173 (54.1%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e116 (62.7%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e57 (42.2%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eDuration of break/rest hours\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e230 (71.9%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e136 (73.5%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e94 (69.6%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eAccess to shade\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e147 (45.9%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e114 (61.6%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e33 (24.4%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eAccess to drinking water\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e83 (25.9%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e53 (28.6%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e30 (22.2%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eType of clothing\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e90 (28.1%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e61 (33.0%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e29 (21.5%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colspan=\"4\" nameend=\"c4\" namest=\"c1\"\u003e\u003cp\u003e\u003cb\u003eLevel of concern about the impact of climate change on workplace heat stress\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e15.52 (0.004)**\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eNot at all concerned\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e25 (7.8%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e13 (7.0%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e12 (8.9%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eSlightly concerned\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e22 (6.9%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e15 (8.1%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e7 (5.2%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eModerately concerned\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e34 (10.6%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e25 (13.5%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e9 (6.7%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eHighly concerned\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e147 (45.9%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e93 (50.3%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e54 (40.0%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eExtremely concerned\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e92 (28.7%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e39 (21.1%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e53 (39.3%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003c/tbody\u003e\u003c/colgroup\u003e\u003ctfoot\u003e\u003ctr\u003e\u003ctd colspan=\"5\"\u003e*p\u0026thinsp;\u0026lt;\u0026thinsp;0.05; **p\u0026thinsp;\u0026lt;\u0026thinsp;0.01; ***p\u0026thinsp;\u0026lt;\u0026thinsp;0.001;\u003c/td\u003e\u003c/tr\u003e\u003c/tfoot\u003e\u003c/table\u003e\u003c/div\u003e\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec10\" class=\"Section2\"\u003e\u003ch2\u003e3.3. Workplace heat risk perceptions\u003c/h2\u003e\u003cp\u003eTable\u0026nbsp;\u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e3\u003c/span\u003e presents workers\u0026rsquo; concerns and preparedness regarding heat exposure and heat-related injuries in the workplace. Most workers (80.6%) were concerned about heat exposure, with no significant difference between construction (78.4%) and welding (83.7%) workers (p\u0026thinsp;=\u0026thinsp;0.234). However, concerns about heat illness risk at work varied (p\u0026thinsp;=\u0026thinsp;0.047), with welding workers (31.6%) being more extremely concerned than construction workers (21.7%). Regarding heat-related injuries, 72.5% expressed concern, though differences between groups were not significant (p\u0026thinsp;=\u0026thinsp;0.066). Among injury concerns, most workers cited risks of hitting objects, fear of burns, and worry about falls, trips, and slips. However, there were no significant differences between groups (p\u0026thinsp;=\u0026thinsp;0.693). Burns were more frequently reported by welding workers (67.7%) than construction workers (26.2%), while falls (41.1%) and hitting objects (52.5%) were more common concerns among construction workers. Significant disparities were noted in workplace heat guidelines (p\u0026thinsp;\u0026lt;\u0026thinsp;0.001), with more (42.7%) construction workers reporting their existence compared to welding workers (20.7%). Similarly, construction workers (42.7%) were more likely to receive heatwave warnings than welding workers (16.3%, p\u0026thinsp;\u0026lt;\u0026thinsp;0.001). Training on heat-related injury prevention was also more common among construction workers (40.0%) than welding workers (10.4%, p\u0026thinsp;\u0026lt;\u0026thinsp;0.001).\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\u003eOccupational heat risk perception among workers.\u003c/p\u003e\u003c/div\u003e\u003c/caption\u003e\u003ccolgroup cols=\"5\"\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e\u003cthead\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cem\u003eDescriptive Statistics\u003c/em\u003e\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c2\"\u003e\u003cp\u003e\u003cem\u003eTotal\u003c/em\u003e\u003c/p\u003e\u003cp\u003e\u003cem\u003e(n\u0026thinsp;=\u0026thinsp;320)\u003c/em\u003e\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c3\"\u003e\u003cp\u003e\u003cem\u003eConstruction\u003c/em\u003e\u003c/p\u003e\u003cp\u003e\u003cem\u003e(n\u0026thinsp;=\u0026thinsp;185)\u003c/em\u003e\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c4\"\u003e\u003cp\u003e\u003cem\u003eWelding\u003c/em\u003e\u003c/p\u003e\u003cp\u003e\u003cem\u003e(n\u0026thinsp;=\u0026thinsp;135)\u003c/em\u003e\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c5\"\u003e\u003cp\u003e\u003cem\u003eχ2 (p)\u003c/em\u003e\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colspan=\"4\" nameend=\"c4\" namest=\"c1\"\u003e\u003cp\u003e\u003cb\u003eConcerns about heat exposure in the workplace\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e1.41 (0.234)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eYes\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e258 (80.6%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e145 (78.4%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e113 (83.7%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eNo\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e62 (19.4%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e40 (21.6%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e22 (16.3%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colspan=\"4\" nameend=\"c4\" namest=\"c1\"\u003e\u003cp\u003e\u003cb\u003eConcern about heat illness risk in the workplace\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e9.61 (0.047)*\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eNot at all concerned\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e34 (10.6%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e20 (10.9%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e14 (10.5%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eSlightly concerned\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e28 (8.8%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e16 (8.7%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e12 (9.0%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eModerately concerned\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e44 (13.8%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e34 (18.5%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e10 (7.5%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eHighly concerned\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e129 (40.3%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e74 (40.2%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e55 (41.4%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eExtremely concerned\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e82 (25.6%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e40 (21.7%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e42 (31.6%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colspan=\"4\" nameend=\"c4\" namest=\"c1\"\u003e\u003cp\u003e\u003cb\u003eHeat-related injury concerns\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e5.44 (0.066)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eYes\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e232 (72.5%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e42 (22.7%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e42 (31.1%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eNo\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e84 (26.3%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e139 (75.1%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e93 (68.9%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eDon\u0026rsquo;t know/ Not sure\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e4 (1.3%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e4 (2.2%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e0 (0%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colspan=\"4\" nameend=\"c4\" namest=\"c1\"\u003e\u003cp\u003e\u003cb\u003eInjury experienced\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e5.44 (0.066)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eFalls, trips and slips\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e93 (29.1%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e58 (41.1%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e35 (37.6%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eHitting objects\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e122 (38.1%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e74 (52.5%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e48 (51.6%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eBeing hit by moving objects\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e58 (18.1%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e36 (25.5%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e22 (23.7%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eBurn\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e100 (31.3%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e37 (26.2%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e63 (67.7%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eLoss of grip and control due to sweaty hands\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e82 (25.6%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e48 (34.0%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e34 (36.6%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colspan=\"4\" nameend=\"c4\" namest=\"c1\"\u003e\u003cp\u003e\u003cb\u003eWorking guidelines in the workplace during hot weather\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e24.40 (0.000)***\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eYes\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e107 (33.4%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e79 (42.7%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e28 (20.7%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eNo\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e206 (64.4%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e99 (53.5%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e107 (79.3%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eDon\u0026rsquo;t know/Not sure\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e9 (2.8%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e7 (3.8%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e0 (0%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colspan=\"4\" nameend=\"c4\" namest=\"c1\"\u003e\u003cp\u003e\u003cb\u003eInformation or warnings from authorities or health organizations about safety during heatwaves\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e35.44 (0.000)***\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eYes\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e101 (31.6%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e79 (42.7%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e22 (16.3%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eNo\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e210 (65.6%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e97 (52.4%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e113 (83.7%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eDon\u0026rsquo;t know/Not sure\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e9 (2.8%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e9 (4.9%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e0 (0%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colspan=\"4\" nameend=\"c4\" namest=\"c1\"\u003e\u003cp\u003e\u003cb\u003eWorkers training on the prevention of heat-related injuries\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e46.02 (0.000)***\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eYes\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e88 (27.5%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e74 (40.0%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e14 (10.4%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eNo\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e222 (69.4%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e101 (54.6%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e121 (89.6%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eDon\u0026rsquo;t know/Not sure\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e10 (3.1%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e10 (5.4%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e0 (0%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003c/tbody\u003e\u003c/colgroup\u003e\u003ctfoot\u003e\u003ctr\u003e\u003ctd colspan=\"5\"\u003e*p\u0026thinsp;\u0026lt;\u0026thinsp;0.05; **p\u0026thinsp;\u0026lt;\u0026thinsp;0.01; ***p\u0026thinsp;\u0026lt;\u0026thinsp;0.001;\u003c/td\u003e\u003c/tr\u003e\u003c/tfoot\u003e\u003c/table\u003e\u003c/div\u003e\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec11\" class=\"Section2\"\u003e\u003ch2\u003e3.4. Heat-related illness symptoms\u003c/h2\u003e\u003cp\u003eFigure \u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e \u0026amp; Table S1 summarizes the self-reported physical illness symptoms among the workers during hot weather. The most commonly reported symptoms included excessive sweating, frequent thirst, tiredness or weakness, and headaches. Significant differences were observed in heat-related physical illness symptoms (p\u0026thinsp;\u0026lt;\u0026thinsp;0.05), with excessive sweating being more prevalent among welding workers (70.7%) than construction workers (51.3%). Frequent thirst was also higher among welding workers (57.8%) compared to construction workers (45.5%). Muscle cramps were reported more frequently by welding workers (27.0%) than by construction workers (14.3%). Nausea or vomiting was more common among construction workers (7.2%) than welding workers (2.6%). Fainting was significantly less frequent among welding workers (93.0%) than construction workers (70.9%, p\u0026thinsp;\u0026lt;\u0026thinsp;0.001). No significant differences were found for tiredness or weakness, headache, or dizziness.\u003c/p\u003e\u003cp\u003eRegarding specific psychological illnesses, emotional irritability (63.7%) and difficulty controlling temper (66.9%) were the most commonly reported issues. However, no significant differences were observed in mental health symptoms between groups. Emotional irritability (74.1%) and difficulty controlling temper (80.7%) were more common among welding workers than construction workers (56.2% and 56.8%, respectively). Low mood was reported at similar rates (43.7% vs. 37.8%). Insomnia was more frequent among construction workers (53.0%) than welding workers (40.7%). No substantial differences were noted in memory decline, concentration issues, lack of interest in activities, or poor appetite, though welding workers (35.6%) had slightly higher reports of poor appetite than construction workers (25.4%) (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003e \u0026amp; Table S1).\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec12\" class=\"Section2\"\u003e\u003ch2\u003e3.5. Behavioral adaptations during hot weather\u003c/h2\u003e\u003cp\u003eMost workers reported an increase in adaptive behaviors to mitigate heat exposure. The most commonly increased behaviors included drinking cool water before feeling thirsty (80%), taking regular breaks in shaded or cooler areas (69%), wearing loose and light-colored clothing (58%), slowing down the work rate to accommodate hot weather conditions (54%), and planning outdoor work during cooler times of the day (52%). However, a considerable proportion of workers indicated that they had not previously engaged in such adaptive behaviors, including participation in heat safety training programs (68%) and the use of PPE (60%) (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003e).\u003c/p\u003e\u003cp\u003eSignificant differences were observed in the adaptive behaviors between occupational groups. A greater proportion of welding workers (71%) reported an increased practice of taking regular breaks in shaded or cooler areas compared to construction workers (68%, p\u0026thinsp;=\u0026thinsp;0.004). The increased practice of planning outdoor work during cooler times was also more common among welding workers (73%) than construction workers (44%, p\u0026thinsp;=\u0026thinsp;0.004). In contrast, participating in heat safety training programs was significantly higher among construction workers (25%) compared to welding workers (11%, p\u0026thinsp;\u0026lt;\u0026thinsp;0.001). Similarly, the increased practice of using personal protective equipment during hot weather was more frequently reported among construction workers (27%) than welding workers (13%, p\u0026thinsp;\u0026lt;\u0026thinsp;0.001). No significant differences were observed between the groups regarding the increased practice of following weather forecasts, drinking water before feeling thirsty, wearing light-colored clothing, slowing down the work rate, or using electric fans (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003e \u0026amp; Table S2).\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec13\" class=\"Section2\"\u003e\u003ch2\u003e3.6. Factors influencing the changes in heat adaptation behavior in workplace\u003c/h2\u003e\u003cdiv id=\"Sec14\" class=\"Section3\"\u003e\u003ch2\u003e3.6.1. Demographic and occupational differences in adaptation behavior\u003c/h2\u003e\u003cp\u003eTable\u0026nbsp;\u003cspan refid=\"Tab4\" class=\"InternalRef\"\u003e4\u003c/span\u003e summarizes the factors influencing the behavioral adaptation by workers with odds ratios (ORs) and their 95% confidence intervals (CIs). The results revealed that workers with a college or higher level of education were less likely to increase their participation in heat\u0026thinsp;\u0026minus;\u0026thinsp;related safety training at their workplace (OR\u0026thinsp;=\u0026thinsp;0.22, CI\u0026thinsp;=\u0026thinsp;0.05\u0026thinsp;\u0026minus;\u0026thinsp;0.93). Construction workers, compared to welding workers, were nine times more likely to increase taking regular breaks during hot weather (OR\u0026thinsp;=\u0026thinsp;9.49, CI\u0026thinsp;=\u0026thinsp;2.45\u0026thinsp;\u0026minus;\u0026thinsp;36.74), four times more likely to increase wearing loose clothing (OR\u0026thinsp;=\u0026thinsp;4.26, CI\u0026thinsp;=\u0026thinsp;1.14\u0026thinsp;\u0026minus;\u0026thinsp;15.90), and nearly three times more likely to increase using electric fans to cool down (OR\u0026thinsp;=\u0026thinsp;2.84, CI\u0026thinsp;=\u0026thinsp;1.12\u0026thinsp;\u0026minus;\u0026thinsp;7.22). However, construction workers were four times less likely to plan to work during cooler periods of the day (OR\u0026thinsp;=\u0026thinsp;4.81, CI\u0026thinsp;=\u0026thinsp;2.22\u0026thinsp;\u0026minus;\u0026thinsp;46.80) and 14 times less likely to slow down their work rate as an adaptation to extreme heat (OR\u0026thinsp;=\u0026thinsp;14.20, CI\u0026thinsp;=\u0026thinsp;2.03\u0026thinsp;\u0026minus;\u0026thinsp;99.21) than welding workers. Workers with greater work experience (9 years or more) were seven times more likely to increase the use of cooling options, such as electric fans, (OR\u0026thinsp;=\u0026thinsp;6.97, CI\u0026thinsp;=\u0026thinsp;1.97\u0026thinsp;\u0026minus;\u0026thinsp;24.68) and nearly four times more likely to follow weather forecasts regularly (OR\u0026thinsp;=\u0026thinsp;3.81, CI\u0026thinsp;=\u0026thinsp;1.01\u0026thinsp;\u0026minus;\u0026thinsp;14.37), although they were nearly seven times less likely to adopt the behavior of slowing down their work rate (OR\u0026thinsp;=\u0026thinsp;6.96, CI\u0026thinsp;=\u0026thinsp;1.31\u0026thinsp;\u0026minus;\u0026thinsp;9.45) than those having lower work experience. Those working more than eight hours per day showed six times more increased tendency to drink water more frequently before feeling thirsty (OR\u0026thinsp;=\u0026thinsp;6.41, CI\u0026thinsp;=\u0026thinsp;1.45\u0026thinsp;\u0026minus;\u0026thinsp;28.35) and nearly ten times more willingness to follow weather forecasts to manage heat exposure (OR\u0026thinsp;=\u0026thinsp;9.76, CI\u0026thinsp;=\u0026thinsp;1.39\u0026thinsp;\u0026minus;\u0026thinsp;68.59) than their counterparts. In contrast, workers primarily engaged in outdoor activities were less likely to take regular breaks during hot weather, while workers engaged in indoor settings were less likely to wear loose clothing as an adaptive strategy.\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec15\" class=\"Section3\"\u003e\u003ch2\u003e3.6.2. Occupational risk perceptions and behavioral adaptation\u003c/h2\u003e\u003cp\u003ePerceptions of occupational heat risk significantly influenced adaptive behaviors. Workers who expressed concern about heat exposure at the workplace were less likely to increase the practice of wearing loose clothing. Workers who were slightly concerned about heat\u0026thinsp;\u0026minus;\u0026thinsp;illness risks were more likely to increase drinking water before feeling thirsty and to enhance the use of cooling options, such as electric fans. In contrast, workers who were moderately concerned were less likely to slow down their work rate. Workers who were very concerned about heat risks were more likely to increase behaviors such as following weather forecasts and slowing down their work rate, although they were less likely to increase the behavior of wearing loose clothing to adapt to extreme heat. Workers who were extremely concerned about heat risks were more likely to increase behaviors such as slowing down their work rate (Table\u0026nbsp;\u003cspan refid=\"Tab4\" class=\"InternalRef\"\u003e4\u003c/span\u003e).\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec16\" class=\"Section3\"\u003e\u003ch2\u003e3.6.3. Physical injuries, heat\u0026thinsp;\u0026minus;\u0026thinsp;stress symptoms and behavioral adaptation\u003c/h2\u003e\u003cp\u003eWorkers who experienced injuries from hitting stationary objects in their workplace were 3.49 times more likely to increase the practice of taking regular breaks, while workers injured by moving objects were 7.90 times more likely to use cooling options (e.g., electric fans). Similarly, workers who suffered burns were 6.55 times more likely to plan their tasks during cooler hours of the day. Participate in heat\u0026thinsp;\u0026minus;\u0026thinsp;related training was also associated with a 6.50\u0026thinsp;\u0026minus;\u0026thinsp;fold increase in the likelihood of adjusting work schedules to cooler periods.\u003c/p\u003e\u003cp\u003eWorkers reporting excessive sweating and tiredness or weakness were 6.35 and 3.19 times more likely to increase water intake, respectively, to mitigate heat stress. Experiencing muscle cramps or fainting was associated with a 2.42 and 2.64 times higher likelihood of wearing loose clothing, respectively. Additionally, those with muscle cramps were 1.95 times more likely to regularly follow weather forecasts. Workers who experienced mental health symptoms during hot weather at their workplace also showed changes in their adaptive behaviors. Workers who reported a decline in memory were 11.72 times more likely to increasingly use electric fans and 4.2 times more likely to increase the slowing down their work rate to cope with the heat. Workers who experienced insomnia were 8.67 times more likely to adopt the behavior of drinking water more frequently before feeling thirsty. Furthermore, those who reported having little interest or pleasure in doing things were 9.90\u0026thinsp;\u0026minus;\u0026thinsp;fold more likely to shift their work to cooler times of the day (Table\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\u003eFactors affecting the behavioral adaptation by workers with red colours indicating a negative and green a positive effect at different levels of significance.\u003c/p\u003e\u003c/div\u003e\u003c/caption\u003e\u003ccolgroup cols=\"19\"\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\u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c8\" colnum=\"8\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c9\" colnum=\"9\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c10\" colnum=\"10\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c11\" colnum=\"11\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c12\" colnum=\"12\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c13\" colnum=\"13\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c14\" colnum=\"14\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c15\" colnum=\"15\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c16\" colnum=\"16\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c17\" colnum=\"17\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c18\" colnum=\"18\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c19\" colnum=\"19\"\u003e\u003c/div\u003e\u003cthead\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e\u0026nbsp;\u003c/th\u003e\u003cth align=\"left\" colspan=\"2\" nameend=\"c3\" namest=\"c2\"\u003e\u003cp\u003eDrink water before thirsty\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colspan=\"2\" nameend=\"c5\" namest=\"c4\"\u003e\u003cp\u003eTake regular break\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colspan=\"2\" nameend=\"c7\" namest=\"c6\"\u003e\u003cp\u003eWear loose clothing\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colspan=\"2\" nameend=\"c9\" namest=\"c8\"\u003e\u003cp\u003eWork in cooler hours\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colspan=\"2\" nameend=\"c11\" namest=\"c10\"\u003e\u003cp\u003eUse cooling option (e.g., electric fans)\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colspan=\"2\" nameend=\"c13\" namest=\"c12\"\u003e\u003cp\u003eUse PPE\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colspan=\"2\" nameend=\"c15\" namest=\"c14\"\u003e\u003cp\u003eFollow weather forecast\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colspan=\"2\" nameend=\"c17\" namest=\"c16\"\u003e\u003cp\u003eSlow down work rate\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colspan=\"2\" nameend=\"c19\" namest=\"c18\"\u003e\u003cp\u003eTake heat safety training\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c2\"\u003e\u003cp\u003eDecrease\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c3\"\u003e\u003cp\u003eIncrease\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c4\"\u003e\u003cp\u003eDecrease\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c5\"\u003e\u003cp\u003eIncrease\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c6\"\u003e\u003cp\u003eDecrease\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c7\"\u003e\u003cp\u003eIncrease\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c8\"\u003e\u003cp\u003eDecrease\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c9\"\u003e\u003cp\u003eIncrease\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c10\"\u003e\u003cp\u003eDecrease\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c11\"\u003e\u003cp\u003eIncrease\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c12\"\u003e\u003cp\u003eDecrease\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c13\"\u003e\u003cp\u003eIncrease\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c14\"\u003e\u003cp\u003eDecrease\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c15\"\u003e\u003cp\u003eIncrease\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c16\"\u003e\u003cp\u003eDecrease\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c17\"\u003e\u003cp\u003eIncrease\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c18\"\u003e\u003cp\u003eDecrease\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c19\"\u003e\u003cp\u003eIncrease\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003eDemographics\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\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c10\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c11\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c12\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c13\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c14\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c15\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c16\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c17\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c18\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c19\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003eGender\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\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c10\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c11\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c12\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c13\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c14\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c15\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c16\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c17\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c18\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c19\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eFemale\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\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c10\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c11\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c12\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c13\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c14\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c15\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c16\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c17\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c18\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c19\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003eAge\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\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c10\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c11\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c12\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c13\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c14\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c15\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c16\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c17\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c18\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c19\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u0026gt;\u0026thinsp;30 years\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\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"char\" char=\"\u0026minus;\" colname=\"c8\"\u003e\u003cp\u003e0.07 (0.01\u0026thinsp;\u0026minus;\u0026thinsp;0.81)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c10\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c11\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c12\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c13\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c14\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c15\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c16\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c17\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c18\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c19\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003eEducation\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\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c10\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c11\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c12\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c13\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c14\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c15\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c16\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c17\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c18\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c19\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003ePrimary school level\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\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c10\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c11\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c12\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c13\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c14\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c15\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c16\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c17\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c18\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c19\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eSecondary school level\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\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c10\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c11\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c12\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c13\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c14\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c15\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c16\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c17\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c18\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c19\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eCollege or higher\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\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c10\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c11\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c12\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c13\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c14\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c15\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c16\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c17\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"char\" char=\"\u0026minus;\" colname=\"c18\"\u003e\u003cp\u003e0.08 (0.01\u0026thinsp;\u0026minus;\u0026thinsp;0.94)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\"\u0026minus;\" colname=\"c19\"\u003e\u003cp\u003e0.22 (0.05\u0026thinsp;\u0026minus;\u0026thinsp;0.93)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003eIncome\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\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c10\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c11\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c12\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c13\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c14\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c15\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c16\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c17\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c18\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c19\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e10001\u0026thinsp;\u0026minus;\u0026thinsp;20000 BDT\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\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c10\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c11\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c12\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c13\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c14\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c15\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c16\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c17\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c18\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c19\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eMore than 20000 BDT\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\u003ctd align=\"char\" char=\"\u0026minus;\" colname=\"c4\"\u003e\u003cp\u003e0.03 (0.00\u0026thinsp;\u0026minus;\u0026thinsp;0.77)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c10\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c11\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c12\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c13\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c14\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c15\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c16\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c17\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c18\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c19\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003eWorking sectors\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\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c10\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c11\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c12\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c13\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c14\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c15\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c16\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c17\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c18\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c19\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eConstruction Site\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\u003ctd align=\"char\" char=\"\u0026minus;\" colname=\"c4\"\u003e\u003cp\u003e9.17 (1.29\u0026thinsp;\u0026minus;\u0026thinsp;64.96)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\"\u0026minus;\" colname=\"c5\"\u003e\u003cp\u003e9.49 (2.45\u0026thinsp;\u0026minus;\u0026thinsp;36.74)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"char\" char=\"\u0026minus;\" colname=\"c7\"\u003e\u003cp\u003e4.26 (1.14\u0026thinsp;\u0026minus;\u0026thinsp;15.90)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\"\u0026minus;\" colname=\"c8\"\u003e\u003cp\u003e34.81 (2.22\u0026thinsp;\u0026minus;\u0026thinsp;46.80)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c10\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"char\" char=\"\u0026minus;\" colname=\"c11\"\u003e\u003cp\u003e2.84 (1.12\u0026thinsp;\u0026minus;\u0026thinsp;7.22)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c12\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c13\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c14\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c15\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"char\" char=\"\u0026minus;\" colname=\"c16\"\u003e\u003cp\u003e14.20 (2.03\u0026thinsp;\u0026minus;\u0026thinsp;99.21)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c17\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c18\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c19\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003eYears of working\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\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c10\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c11\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c12\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c13\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c14\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c15\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c16\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c17\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c18\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c19\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e5\u0026thinsp;\u0026minus;\u0026thinsp;9 years\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\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c10\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"char\" char=\"\u0026minus;\" colname=\"c11\"\u003e\u003cp\u003e3.19 (1.13\u0026thinsp;\u0026minus;\u0026thinsp;8.99)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c12\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c13\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c14\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c15\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c16\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c17\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c18\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c19\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e9+\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\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c10\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"char\" char=\"\u0026minus;\" colname=\"c11\"\u003e\u003cp\u003e6.97 (1.97\u0026thinsp;\u0026minus;\u0026thinsp;24.68)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c12\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c13\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c14\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"char\" char=\"\u0026minus;\" colname=\"c15\"\u003e\u003cp\u003e3.81 (1.01\u0026thinsp;\u0026minus;\u0026thinsp;14.37)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\"\u0026minus;\" colname=\"c16\"\u003e\u003cp\u003e6.96 (1.31\u0026thinsp;\u0026minus;\u0026thinsp;9.45)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c17\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c18\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c19\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003eDaily working hours\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\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c10\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c11\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c12\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c13\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c14\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c15\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c16\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c17\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c18\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c19\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e8h\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\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c10\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c11\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c12\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c13\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c14\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c15\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c16\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c17\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c18\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c19\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e8h+\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"char\" char=\"\u0026minus;\" colname=\"c3\"\u003e\u003cp\u003e6.41 (1.45\u0026thinsp;\u0026minus;\u0026thinsp;28.35)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c10\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c11\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c12\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c13\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c14\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"char\" char=\"\u0026minus;\" colname=\"c15\"\u003e\u003cp\u003e9.76 (1.39\u0026thinsp;\u0026minus;\u0026thinsp;68.59)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c16\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c17\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c18\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c19\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003eOutdoor times during hot weather\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\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c10\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c11\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c12\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c13\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c14\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c15\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c16\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c17\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c18\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c19\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e1\u0026thinsp;\u0026minus;\u0026thinsp;3h\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\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c10\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c11\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c12\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c13\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c14\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c15\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c16\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c17\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c18\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c19\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e3\u0026thinsp;\u0026minus;\u0026thinsp;5h\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\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"char\" char=\"\u0026minus;\" colname=\"c6\"\u003e\u003cp\u003e0.01 (0.00\u0026thinsp;\u0026minus;\u0026thinsp;0.56)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c10\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c11\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c12\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c13\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c14\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c15\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c16\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c17\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c18\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c19\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003eWorkplace environment\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\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c10\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c11\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c12\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c13\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c14\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c15\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c16\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c17\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c18\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c19\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eMainly outdoor\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\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"char\" char=\"\u0026minus;\" colname=\"c5\"\u003e\u003cp\u003e0.21 (0.06\u0026thinsp;\u0026minus;\u0026thinsp;0.69)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c10\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c11\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c12\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c13\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c14\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c15\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c16\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c17\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c18\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c19\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eCompletely indoor\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\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"char\" char=\"\u0026minus;\" colname=\"c7\"\u003e\u003cp\u003e0.08 (0.01\u0026thinsp;\u0026minus;\u0026thinsp;0.69)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c10\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c11\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c12\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c13\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c14\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c15\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c16\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c17\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c18\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c19\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eMainly indoor\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\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"char\" char=\"\u0026minus;\" colname=\"c7\"\u003e\u003cp\u003e0.05 (0.01\u0026thinsp;\u0026minus;\u0026thinsp;0.26)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c10\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c11\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c12\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c13\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c14\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c15\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c16\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c17\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c18\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c19\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003eHeat Source\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\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c10\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c11\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c12\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c13\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c14\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c15\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c16\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c17\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c18\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c19\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eYes\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\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c10\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c11\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c12\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c13\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c14\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c15\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c16\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c17\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c18\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c19\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003eFrequency of your work around the heat source\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\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c10\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c11\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c12\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c13\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c14\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c15\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c16\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c17\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c18\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c19\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eRarely\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\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c10\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c11\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c12\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c13\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c14\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c15\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c16\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c17\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c18\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c19\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eSometimes\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\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c10\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c11\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c12\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c13\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c14\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c15\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c16\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c17\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c18\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c19\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eOften\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\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c10\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c11\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c12\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c13\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c14\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c15\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c16\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c17\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c18\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c19\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eAlways\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\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c10\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c11\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c12\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c13\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c14\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c15\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c16\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c17\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c18\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c19\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003eConcern about heat\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\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c10\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c11\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c12\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c13\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c14\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c15\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c16\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c17\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c18\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c19\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eYes\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\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"char\" char=\"\u0026minus;\" colname=\"c7\"\u003e\u003cp\u003e0.11 (0.02\u0026thinsp;\u0026minus;\u0026thinsp;0.74)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c10\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c11\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c12\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c13\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c14\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c15\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c16\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c17\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c18\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c19\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003eConcern about heat\u0026thinsp;\u0026minus;\u0026thinsp;illness risk\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\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c10\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c11\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c12\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c13\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c14\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c15\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c16\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c17\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c18\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c19\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eSlightly concerned\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"char\" char=\"\u0026minus;\" colname=\"c3\"\u003e\u003cp\u003e31.85 (1.28\u0026thinsp;\u0026minus;\u0026thinsp;793.83)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c10\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"char\" char=\"\u0026minus;\" colname=\"c11\"\u003e\u003cp\u003e7.14 (1.05\u0026thinsp;\u0026minus;\u0026thinsp;48.47)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c12\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c13\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c14\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c15\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c16\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c17\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c18\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c19\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eModerately concerned\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\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c10\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c11\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c12\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c13\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c14\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c15\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c16\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"char\" char=\"\u0026minus;\" colname=\"c17\"\u003e\u003cp\u003e0.20 (0.04\u0026thinsp;\u0026minus;\u0026thinsp;0.93)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c18\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c19\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eVery concerned\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\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"char\" char=\"\u0026minus;\" colname=\"c7\"\u003e\u003cp\u003e0.06 (0.01\u0026thinsp;\u0026minus;\u0026thinsp;0.34)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c10\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c11\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c12\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c13\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c14\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"char\" char=\"\u0026minus;\" colname=\"c15\"\u003e\u003cp\u003e5.21 (1.20\u0026thinsp;\u0026minus;\u0026thinsp;22.61)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c16\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c17\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c18\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c19\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eExtremely concerned\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\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c10\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c11\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c12\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c13\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c14\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c15\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c16\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"char\" char=\"\u0026minus;\" colname=\"c17\"\u003e\u003cp\u003e6.73 (1.12\u0026thinsp;\u0026minus;\u0026thinsp;40.49)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c18\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c19\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003eHeat\u0026thinsp;\u0026minus;\u0026thinsp;related injury concern\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\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c10\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c11\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c12\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c13\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c14\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c15\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c16\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c17\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c18\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c19\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eYes\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\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c10\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c11\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c12\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c13\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c14\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c15\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c16\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c17\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c18\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c19\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003eInjury experienced\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\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c10\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c11\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c12\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c13\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c14\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c15\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c16\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c17\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c18\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c19\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eFalls, trips and slips\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\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c10\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c11\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c12\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c13\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c14\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c15\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c16\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c17\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c18\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c19\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eHitting objects\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\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"char\" char=\"\u0026minus;\" colname=\"c5\"\u003e\u003cp\u003e3.49 (1.04\u0026thinsp;\u0026minus;\u0026thinsp;11.77)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c10\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c11\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c12\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c13\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c14\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c15\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c16\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c17\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c18\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c19\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eBeing hit by moving objects\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\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c10\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"char\" char=\"\u0026minus;\" colname=\"c11\"\u003e\u003cp\u003e7.90 (1.81\u0026thinsp;\u0026minus;\u0026thinsp;34.56)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c12\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c13\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c14\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c15\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c16\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c17\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c18\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c19\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eBurn\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\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"char\" char=\"\u0026minus;\" colname=\"c9\"\u003e\u003cp\u003e6.55 (1.17\u0026thinsp;\u0026minus;\u0026thinsp;36.74)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c10\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c11\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c12\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c13\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c14\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c15\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c16\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c17\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c18\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c19\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eLoss of grip and controls due to sweaty hands\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\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c10\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c11\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c12\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c13\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c14\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c15\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c16\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c17\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c18\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c19\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003eHeat\u0026thinsp;\u0026minus;\u0026thinsp;related training\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\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c10\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c11\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c12\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c13\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c14\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c15\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c16\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c17\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c18\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c19\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eYes\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\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"char\" char=\"\u0026minus;\" colname=\"c9\"\u003e\u003cp\u003e6.50 (1.00\u0026thinsp;\u0026minus;\u0026thinsp;42.21)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c10\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c11\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c12\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c13\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c14\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c15\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c16\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c17\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c18\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c19\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003ePerceived physical illness\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\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c10\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c11\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c12\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c13\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c14\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c15\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c16\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c17\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c18\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c19\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eExcessive sweating\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"char\" char=\"\u0026minus;\" colname=\"c3\"\u003e\u003cp\u003e6.35 (1.67\u0026thinsp;\u0026minus;\u0026thinsp;24.14)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c10\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c11\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c12\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c13\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c14\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c15\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c16\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c17\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c18\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c19\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eFeeling thirsty\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\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c10\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c11\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c12\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c13\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c14\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c15\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c16\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c17\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c18\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c19\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eMuscle cramp\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"char\" char=\"\u0026minus;\" colname=\"c3\"\u003e\u003cp\u003e0.17 (0.05\u0026thinsp;\u0026minus;\u0026thinsp;0.53)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"char\" char=\"\u0026minus;\" colname=\"c7\"\u003e\u003cp\u003e2.42 (1.20\u0026thinsp;\u0026minus;\u0026thinsp;4.87)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c10\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c11\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c12\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c13\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c14\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"char\" char=\"\u0026minus;\" colname=\"c15\"\u003e\u003cp\u003e1.95 (1.09\u0026thinsp;\u0026minus;\u0026thinsp;3.47)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c16\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c17\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c18\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c19\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eTiredness or weakness\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"char\" char=\"\u0026minus;\" colname=\"c3\"\u003e\u003cp\u003e3.19 (1.22\u0026thinsp;\u0026minus;\u0026thinsp;8.35)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"char\" char=\"\u0026minus;\" colname=\"c7\"\u003e\u003cp\u003e0.47 (0.23\u0026thinsp;\u0026minus;\u0026thinsp;0.95)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c10\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c11\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c12\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c13\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c14\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c15\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c16\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c17\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c18\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c19\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eHeadache\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\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c10\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c11\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c12\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c13\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c14\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c15\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c16\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c17\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c18\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c19\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eDizziness\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\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c10\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c11\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c12\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c13\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c14\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c15\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c16\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c17\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c18\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c19\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eNausea or vomiting\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\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c10\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c11\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c12\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c13\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c14\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c15\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c16\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c17\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c18\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c19\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eFainting\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\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"char\" char=\"\u0026minus;\" colname=\"c7\"\u003e\u003cp\u003e2.64 (1.07\u0026thinsp;\u0026minus;\u0026thinsp;6.51)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c10\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c11\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c12\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c13\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c14\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c15\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c16\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c17\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c18\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c19\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003ePerceived mental health symptoms\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\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c10\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c11\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c12\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c13\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c14\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c15\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c16\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c17\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c18\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c19\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eEmotional irritability\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\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c10\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c11\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c12\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c13\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c14\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c15\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c16\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c17\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c18\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c19\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eDifficulty to control temper\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\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c10\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c11\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c12\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c13\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c14\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c15\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c16\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c17\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c18\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c19\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eLow mood\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\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c10\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c11\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c12\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c13\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c14\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c15\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c16\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c17\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c18\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c19\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eDecline of memory\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\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c10\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"char\" char=\"\u0026minus;\" colname=\"c11\"\u003e\u003cp\u003e11.72 (2.04\u0026thinsp;\u0026minus;\u0026thinsp;67.38)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c12\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c13\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c14\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c15\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c16\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"char\" char=\"\u0026minus;\" colname=\"c17\"\u003e\u003cp\u003e4.28 (1.01\u0026thinsp;\u0026minus;\u0026thinsp;18.14)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c18\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c19\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eInsomnia\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"char\" char=\"\u0026minus;\" colname=\"c3\"\u003e\u003cp\u003e8.67 (1.30\u0026thinsp;\u0026minus;\u0026thinsp;57.77)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c10\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c11\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c12\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c13\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c14\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c15\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c16\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c17\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c18\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c19\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eTrouble on concentration\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\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c10\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c11\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c12\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c13\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c14\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c15\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c16\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c17\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c18\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c19\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eLittle interest on things\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\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"char\" char=\"\u0026minus;\" colname=\"c9\"\u003e\u003cp\u003e9.90 (1.60\u0026thinsp;\u0026minus;\u0026thinsp;61.29)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c10\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c11\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c12\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c13\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c14\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c15\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c16\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c17\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c18\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c19\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003ePoor appetite\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\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c10\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c11\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c12\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c13\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c14\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c15\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c16\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c17\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c18\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c19\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003c/tbody\u003e\u003c/colgroup\u003e\u003ctfoot\u003e\u003ctr\u003e\u003ctd colspan=\"19\"\u003e\u003cb\u003eNote\u003c/b\u003e: The darkness of the colors corresponds to the level of significance. Dark red and green indicate a 1% significance level, light hues a 5% level; Reference: no change; Results reported as Odds Ratio (OR) with 95% confidence interval; PPE, Personal Protective Equipment.\u003c/td\u003e\u003c/tr\u003e\u003c/tfoot\u003e\u003c/table\u003e\u003c/div\u003e\u003c/p\u003e\u003c/div\u003e\u003c/div\u003e"},{"header":"4. Discussion","content":"\u003cdiv id=\"Sec18\" class=\"Section2\"\u003e\u003ch2\u003e4.1. Climate change risk perceptions\u003c/h2\u003e\u003cp\u003eIn our study of construction and welding workers in Bangladesh, we found that these heat\u0026thinsp;\u0026minus;\u0026thinsp;stressed workers showed reasonably high levels of awareness of climate change, consistent with previous studies reporting strong recognition of climate risks among outdoor workers in diverse settings \u003csup\u003e\u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e33\u003c/span\u003e,\u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e34\u003c/span\u003e,\u003cspan citationid=\"CR68\" class=\"CitationRef\"\u003e68\u003c/span\u003e\u003c/sup\u003e. Such awareness was likely reinforced by their occupational exposure to changing weather conditions. However, variations in perceived signs of climate change indicated the influence of job\u0026thinsp;\u0026minus;\u0026thinsp;specific environments. For instance, welding workers were more likely to report increased temperature and irregular rainfall, possibly due to combined exposure to ambient and process\u0026thinsp;\u0026minus;\u0026thinsp;generated heat, which may heighten their sensitivity to environmental change. This finding supported evidence that climate change perceptions often reflect lived occupational and environmental experiences \u003csup\u003e\u003cspan citationid=\"CR69\" class=\"CitationRef\"\u003e69\u003c/span\u003e,\u003cspan citationid=\"CR70\" class=\"CitationRef\"\u003e70\u003c/span\u003e\u003c/sup\u003e. Workers widely recognized the impact of climate change on heat\u0026thinsp;\u0026minus;\u0026thinsp;related stress, consistent with climatological trends of rising temperature, irregular rainfall, and extreme weather in the region \u003csup\u003e\u003cspan citationid=\"CR71\" class=\"CitationRef\"\u003e71\u003c/span\u003e\u003c/sup\u003e. Yet significant differences were observed in their identification of environmental heat factors. Welding workers emphasized hot air and humidity, while construction workers cited direct sunlight exposure, reflecting how task environments shape risk perceptions \u003csup\u003e\u003cspan citationid=\"CR72\" class=\"CitationRef\"\u003e72\u003c/span\u003e\u003c/sup\u003e. These variations are critical for policy considerations, as they point to differentiated vulnerabilities across occupational groups. Perceptions of work\u0026thinsp;\u0026minus;\u0026thinsp;related factors further revealed welding workers\u0026rsquo; elevated risk: they more frequently reported longer working hours, fewer rest breaks, and limited access to cooling compared to construction workers. Such conditions explain their greater concern about workplace heat stress. Prior studies highlight rest regimes, shade, cooling systems, and hydration as essential for adaptation \u003csup\u003e\u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e33\u003c/span\u003e,\u003cspan citationid=\"CR72\" class=\"CitationRef\"\u003e72\u003c/span\u003e\u003c/sup\u003e.\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec19\" class=\"Section2\"\u003e\u003ch2\u003e4.2. Occupational risk perceptions\u003c/h2\u003e\u003cp\u003eThe majority of workers expressed concern about workplace heat exposure, aligning with prior studies \u003csup\u003e\u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e33\u003c/span\u003e,\u003cspan citationid=\"CR73\" class=\"CitationRef\"\u003e73\u003c/span\u003e\u003c/sup\u003e. While overall concern did not differ significantly between construction and welding workers, welding workers were more likely to be extremely concerned about heat illness. This may reflect their more continuous exposure to process\u0026thinsp;\u0026minus;\u0026thinsp;generated heat, which amplifies vulnerability perceptions, echoing findings from other heat\u0026thinsp;\u0026minus;\u0026thinsp;intensive occupations \u003csup\u003e\u003cspan citationid=\"CR66\" class=\"CitationRef\"\u003e66\u003c/span\u003e,\u003cspan citationid=\"CR73\" class=\"CitationRef\"\u003e73\u003c/span\u003e\u003c/sup\u003e. Workers\u0026rsquo; concerns about heat\u0026thinsp;\u0026minus;\u0026thinsp;related injuries were consistent with patterns reported elsewhere (Nunfam et al., 2019b; Stoecklin\u0026thinsp;\u0026minus;\u0026thinsp;Marois et al., 2013). Although group differences were not statistically significant, welding workers more frequently reported burns, reflecting dual risks of radiant heat and direct contact with hot surfaces, whereas construction workers mentioned falls, slips, and being struck by objects, often exacerbated by fatigue or dizziness. These task\u0026thinsp;\u0026minus;\u0026thinsp;specific differences parallel findings among mining and outdoor industrial workers, where exposure shaped diverse morbidity profiles \u003csup\u003e\u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e34\u003c/span\u003e,\u003cspan citationid=\"CR66\" class=\"CitationRef\"\u003e66\u003c/span\u003e\u003c/sup\u003e. An important disparity emerged in access to workplace heat guidelines, early warnings, and training, with construction workers significantly more likely to report such provisions. This suggests structural inequities in institutional support, echoing evidence that informal or small\u0026thinsp;\u0026minus;\u0026thinsp;enterprise workers often lack occupational health programs \u003csup\u003e\u003cspan citationid=\"CR75\" class=\"CitationRef\"\u003e75\u003c/span\u003e\u003c/sup\u003e. Prior research emphasizes that guidelines, training, and warning systems are critical for reducing heat stress and injuries \u003csup\u003e\u003cspan citationid=\"CR72\" class=\"CitationRef\"\u003e72\u003c/span\u003e,\u003cspan citationid=\"CR76\" class=\"CitationRef\"\u003e76\u003c/span\u003e\u003c/sup\u003e.\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec20\" class=\"Section2\"\u003e\u003ch2\u003e4.3. Perceived heat\u0026thinsp;\u0026minus;\u0026thinsp;related illness symptoms\u003c/h2\u003e\u003cp\u003ePhysical symptoms such as excessive sweating, frequent thirst, and muscle cramps were commonly reported, with welding workers experiencing higher rates than construction workers, aligning with prior studies reported in other similar working settings \u003csup\u003e\u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e31\u003c/span\u003e,\u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e33\u003c/span\u003e,\u003cspan citationid=\"CR73\" class=\"CitationRef\"\u003e73\u003c/span\u003e\u003c/sup\u003e. This may result from intense thermal exposure, heavy physical exertion, and the use of protective clothing, which reduces sweat evaporation, traps heat, and elevates body temperature even under moderate conditions \u003csup\u003e\u003cspan citationid=\"CR73\" class=\"CitationRef\"\u003e73\u003c/span\u003e,\u003cspan additionalcitationids=\"CR78\" citationid=\"CR77\" class=\"CitationRef\"\u003e77\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR79\" class=\"CitationRef\"\u003e79\u003c/span\u003e\u003c/sup\u003e. Symptoms such as headaches and dizziness did not significantly differ between groups, indicating general heat exposure effects.\u003c/p\u003e\u003cp\u003ePsychological symptoms were also observed with no differences between welding workers and construction workers. However, welding workers reported higher irritability, potentially linked to both heat exposure and occupational manganese exposure, which has been associated with cognitive and mood disturbances \u003csup\u003e\u003cspan citationid=\"CR80\" class=\"CitationRef\"\u003e80\u003c/span\u003e,\u003cspan citationid=\"CR81\" class=\"CitationRef\"\u003e81\u003c/span\u003e\u003c/sup\u003e. Construction workers reported more insomnia, possibly related to irregular working hours or stress from outdoor work \u003csup\u003e\u003cspan citationid=\"CR82\" class=\"CitationRef\"\u003e82\u003c/span\u003e,\u003cspan citationid=\"CR83\" class=\"CitationRef\"\u003e83\u003c/span\u003e\u003c/sup\u003e. Welding workers experienced slightly more cases of poor appetite, likely due to dehydration, physical exhaustion, and prolonged exposure to high temperatures \u003csup\u003e\u003cspan citationid=\"CR84\" class=\"CitationRef\"\u003e84\u003c/span\u003e\u003c/sup\u003e.\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec21\" class=\"Section2\"\u003e\u003ch2\u003e4.4. Factors explaining differences in behavioral adaptation\u003c/h2\u003e\u003cdiv id=\"Sec22\" class=\"Section3\"\u003e\u003ch2\u003e4.4.1. Changes in hydration behavior\u003c/h2\u003e\u003cp\u003eExperienced workers were more likely to engage in proactive hydration, such as drinking water before feeling thirsty, consistent with previous studies in diverse occupational settings (Baby et al., 2021; Butani, 1988; Trillo\u0026thinsp;\u0026minus;\u0026thinsp;Cabello et al., 2021). Repeated exposure to heat, personal experience with dehydration, and witnessing workplace incidents may enhance internalization of self\u0026thinsp;\u0026minus;\u0026thinsp;protective practices. Experienced workers also serve as informal safety leaders, reinforcing hydration norms through peer influence \u003csup\u003e\u003cspan citationid=\"CR88\" class=\"CitationRef\"\u003e88\u003c/span\u003e\u003c/sup\u003e. Workers reporting excessive sweating, fatigue, or weakness were more likely to adopt anticipatory hydration. Studies from other occupational settings reported that exposure to extreme heat encourages self\u0026thinsp;\u0026minus;\u0026thinsp;regulatory behaviors, including proactive hydration, to prevent performance decline or illness (Al\u0026thinsp;\u0026minus;\u0026thinsp;Bouwarthan et al., 2020; Montazer et al., 2013). Sweating is the primary thermoregulatory mechanism during strenuous outdoor work, but heavy fluid loss can impair cardiovascular and muscular function (Ahasani et al., 1999; Al\u0026thinsp;\u0026minus;\u0026thinsp;Bouwarthan et al., 2019; Gagnon and Crandall, 2018; Krishnamurthy et al., 2017). Early\u0026thinsp;\u0026minus;\u0026thinsp;onset fatigue, often a precursor to heat exhaustion (Cunningham et al., 2022), has been frequently observed among outdoor workers exposed to prolonged solar radiation and physically strenuous labor \u003csup\u003e\u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e31\u003c/span\u003e,\u003cspan citationid=\"CR92\" class=\"CitationRef\"\u003e92\u003c/span\u003e\u003c/sup\u003e. Workers with insomnia were also more inclined to hydrate, possibly due to dysregulation of thermoregulatory and hormonal systems induced by poor \u003csup\u003e\u003cspan citationid=\"CR93\" class=\"CitationRef\"\u003e93\u003c/span\u003e,\u003cspan citationid=\"CR94\" class=\"CitationRef\"\u003e94\u003c/span\u003e\u003c/sup\u003e, which aligns with evidence linking sleep deprivation to higher perceived heat stress \u003csup\u003e\u003cspan citationid=\"CR95\" class=\"CitationRef\"\u003e95\u003c/span\u003e\u003c/sup\u003e.\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec23\" class=\"Section3\"\u003e\u003ch2\u003e4.4.2. Changes in working schedule\u003c/h2\u003e\u003cp\u003eConstruction workers were more likely to take regular breaks during hot weather compared to welding workers, likely due to the physically demanding nature of their tasks and awareness of heat\u0026thinsp;\u0026minus;\u0026thinsp;related risks \u003csup\u003e\u003cspan additionalcitationids=\"CR97\" citationid=\"CR96\" class=\"CitationRef\"\u003e96\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR98\" class=\"CitationRef\"\u003e98\u003c/span\u003e\u003c/sup\u003e. Work break and rest regimens were commonly employed to prevent heat stress \u003csup\u003e\u003cspan additionalcitationids=\"CR34\" citationid=\"CR33\" class=\"CitationRef\"\u003e33\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e35\u003c/span\u003e\u003c/sup\u003e, and globally, similar practices have been formalized, such as mandatory ten\u0026thinsp;\u0026minus;\u0026thinsp;minute breaks every four hours in Austin \u003csup\u003e\u003cspan citationid=\"CR99\" class=\"CitationRef\"\u003e99\u003c/span\u003e\u003c/sup\u003e. In Bangladesh, construction sites are typically exposed to the full intensity of the tropical sun \u003csup\u003e\u003cspan citationid=\"CR100\" class=\"CitationRef\"\u003e100\u003c/span\u003e\u003c/sup\u003e, making breaks an essential physiological coping mechanism, consistent with patterns observed in other tropical climates \u003csup\u003e\u003cspan citationid=\"CR101\" class=\"CitationRef\"\u003e101\u003c/span\u003e\u003c/sup\u003e. Despite this, construction workers were reported to be less likely to plan work during cooler hours or slow their work pace compared to welding workers in this study, due to high\u0026thinsp;\u0026minus;\u0026thinsp;pressure, output\u0026thinsp;\u0026minus;\u0026thinsp;driven environments, strict timelines, contractual obligations, and client expectations, which limit flexibility \u003csup\u003e\u003cspan additionalcitationids=\"CR103\" citationid=\"CR102\" class=\"CitationRef\"\u003e102\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR104\" class=\"CitationRef\"\u003e104\u003c/span\u003e\u003c/sup\u003e. Economic pressures, especially in settings with informal labor arrangements and piece\u0026thinsp;\u0026minus;\u0026thinsp;rate payments, further discourage adjustments to work schedules, as reduced pace or breaks directly affect wages \u003csup\u003e\u003cspan additionalcitationids=\"CR106\" citationid=\"CR105\" class=\"CitationRef\"\u003e105\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR107\" class=\"CitationRef\"\u003e107\u003c/span\u003e\u003c/sup\u003e. Similar patterns have been reported in mining industries and other low\u0026thinsp;\u0026minus;\u0026thinsp;income country contexts, highlighting how economic vulnerability can override heat safety considerations \u003csup\u003e\u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e35\u003c/span\u003e,\u003cspan citationid=\"CR108\" class=\"CitationRef\"\u003e108\u003c/span\u003e\u003c/sup\u003e.\u003c/p\u003e\u003cp\u003ePrior experience of workplace injuries influenced scheduling behaviors, such as workers who had burns or injuries were more likely to take breaks or plan work during cooler hours. Similar observations were reported among construction workers in China \u003csup\u003e\u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e31\u003c/span\u003e\u003c/sup\u003e. Burns, particularly common among welding workers due to intense radiant heat and sparks, are a severe and often traumatic form of injury \u003csup\u003e\u003cspan citationid=\"CR109\" class=\"CitationRef\"\u003e109\u003c/span\u003e,\u003cspan citationid=\"CR110\" class=\"CitationRef\"\u003e110\u003c/span\u003e\u003c/sup\u003e. Increased heat stress results in reduced job productivity and leads to occupational illnesses and injuries if enough breaks have not been maintained during work activities \u003csup\u003e\u003cspan citationid=\"CR111\" class=\"CitationRef\"\u003e111\u003c/span\u003e\u003c/sup\u003e. A direct and painful experience with severe heat can foster a deep concern for thermal dangers (e.g., burn), prompting workers to implement further preventive measures \u003csup\u003e\u003cspan citationid=\"CR112\" class=\"CitationRef\"\u003e112\u003c/span\u003e\u003c/sup\u003e, such as smart work scheduling.\u003c/p\u003e\u003cp\u003eWorkers who reported extreme concern about heat illness were more likely to slow their work pace, indicating that high perceived vulnerability serves as a strong motivator for adaptive behavior, consistent with previous occupational health studies \u003csup\u003e\u003cspan citationid=\"CR113\" class=\"CitationRef\"\u003e113\u003c/span\u003e\u003c/sup\u003e. Similarly, workers who received heat\u0026thinsp;\u0026minus;\u0026thinsp;related training were more likely to adjust their schedules, as training enhances understanding of heat risks, symptom recognition, and the rationale for adaptive practices such as shifting work hours \u003csup\u003e\u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e31\u003c/span\u003e,\u003cspan additionalcitationids=\"CR115\" citationid=\"CR114\" class=\"CitationRef\"\u003e114\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR116\" class=\"CitationRef\"\u003e116\u003c/span\u003e\u003c/sup\u003e. In contrast, workers with greater work experience (\u0026ge;\u0026thinsp;9 years) were less likely to reduce their pace, possibly due to physiological acclimatization, psychological desensitization \u003csup\u003e\u003cspan citationid=\"CR51\" class=\"CitationRef\"\u003e51\u003c/span\u003e\u003c/sup\u003e, or a strong sense of duty and resilience compelling them to maintain productivity \u003csup\u003e\u003cspan citationid=\"CR117\" class=\"CitationRef\"\u003e117\u003c/span\u003e\u003c/sup\u003e. Likewise, workers with only moderate concern about heat\u0026thinsp;\u0026minus;\u0026thinsp;related illness tended not to slow their work, aligning with the Health Belief Model \u003csup\u003e\u003cspan citationid=\"CR118\" class=\"CitationRef\"\u003e118\u003c/span\u003e\u003c/sup\u003e, as they may rely on other preventive strategies, such as hydration or rest breaks, while perceiving they can manage risk without compromising output.\u003c/p\u003e\u003cp\u003ePsychological factors are also related to workplace heat adaptation, with workers reporting reduced motivation or memory decline being more likely to adjust work schedules and slow their work pace Heat stress is well\u0026thinsp;\u0026minus;\u0026thinsp;documented to impair attention, concentration, and short \u0026minus;\u0026thinsp;term memory, and workers experiencing such cognitive effects may consciously or subconsciously slow their work to prevent errors, accidents, or performance decline \u003csup\u003e\u003cspan additionalcitationids=\"CR120\" citationid=\"CR119\" class=\"CitationRef\"\u003e119\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR121\" class=\"CitationRef\"\u003e121\u003c/span\u003e\u003c/sup\u003e. Evidence indicated that elevated temperatures exacerbate pre\u0026thinsp;\u0026minus;\u0026thinsp;existing mental health challenges, increasing irritability, fatigue, and impairing coping capacity \u003csup\u003e\u003cspan citationid=\"CR122\" class=\"CitationRef\"\u003e122\u003c/span\u003e,\u003cspan citationid=\"CR123\" class=\"CitationRef\"\u003e123\u003c/span\u003e\u003c/sup\u003e. Consequently, these workers proactively modify their schedules to cooler periods as a form of self\u0026thinsp;\u0026minus;\u0026thinsp;preservation. These findings underscore the importance of recognizing cognitive impairment as an early indicator of heat stress and integrating mental health considerations into occupational safety strategies, particularly in heat\u0026thinsp;\u0026minus;\u0026thinsp;exposed settings like Bangladesh, to support both physical and psychological well\u0026thinsp;\u0026minus;\u0026thinsp;being \u003csup\u003e\u003cspan citationid=\"CR124\" class=\"CitationRef\"\u003e124\u003c/span\u003e\u003c/sup\u003e.\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec24\" class=\"Section3\"\u003e\u003ch2\u003e4.4.3. Changes in personal comfort adaptation\u003c/h2\u003e\u003cp\u003e\u003cspan type=\"SmallCaps\" class=\"SmallCaps\" name=\"Emphasis\"\u003eConstruction workers commonly adopt adaptive clothing and cooling strategies to cope with extreme heat, with loose\u0026thinsp;\u0026minus;\u0026thinsp;fitting garments being the most prevalent. Loose clothing facilitates heat dissipation, reduces thermal discomfort, and lowers the risk of heat\u0026thinsp;\u0026minus;\u0026thinsp;related illness, a practice widely observed among physically demanding outdoor workers in tropical and subtropical climates\u003c/span\u003e \u003csup\u003e\u003cspan type=\"SmallCaps\" class=\"SmallCaps\" name=\"Emphasis\"\u003e\u003cspan citationid=\"CR125\" class=\"CitationRef\"\u003e125\u003c/span\u003e,\u003cspan citationid=\"CR126\" class=\"CitationRef\"\u003e126\u003c/span\u003e\u003c/span\u003e\u003c/sup\u003e. \u003cspan type=\"SmallCaps\" class=\"SmallCaps\" name=\"Emphasis\"\u003eIn contrast, workers primarily indoors exhibited little adjustment in clothing may be linked to indoor employees tend to neglect the possibility of overheating, even when ventilation or climate control is inadequate\u003c/span\u003e \u003csup\u003e\u003cspan type=\"SmallCaps\" class=\"SmallCaps\" name=\"Emphasis\"\u003e\u003cspan citationid=\"CR127\" class=\"CitationRef\"\u003e127\u003c/span\u003e,\u003cspan citationid=\"CR128\" class=\"CitationRef\"\u003e128\u003c/span\u003e\u003c/span\u003e\u003c/sup\u003e, \u003cspan type=\"SmallCaps\" class=\"SmallCaps\" name=\"Emphasis\"\u003edespite evidence linking elevated indoor temperatures to reduced cognitive and physical performance, fatigue, and heat morbidity\u003c/span\u003e \u003csup\u003e\u003cspan type=\"SmallCaps\" class=\"SmallCaps\" name=\"Emphasis\"\u003e\u003cspan citationid=\"CR129\" class=\"CitationRef\"\u003e129\u003c/span\u003e\u003c/span\u003e\u003c/sup\u003e.\u003c/p\u003e\u003cp\u003ePersonal cooling methods, particularly electric fans, were frequently reported among construction workers exposed to high solar radiation. Fans improve thermal comfort and mitigate heat stress when used alongside hydration and breaks, reflecting growing awareness of occupational heat risks \u003csup\u003e\u003cspan additionalcitationids=\"CR131 CR132\" citationid=\"CR130\" class=\"CitationRef\"\u003e130\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR133\" class=\"CitationRef\"\u003e133\u003c/span\u003e\u003c/sup\u003e. Adoption of these practices correlated with work experience; employees with over five years of experience reported actively following adaptive measures, while those exceeding nine years often treated them as routine. Similarly, earlier studies found that workers with more years of experience demonstrated more consistent use of cooling strategies, including electric fans and rest breaks \u003csup\u003e\u003cspan citationid=\"CR134\" class=\"CitationRef\"\u003e134\u003c/span\u003e\u003c/sup\u003e.\u003c/p\u003e\u003cp\u003ePerceived vulnerability was also related to personal adaptive behavior. Workers expressing even slight concern about heat\u0026thinsp;\u0026minus;\u0026thinsp;related illness were more likely to adopt cooling strategies, including shade seeking and adjusting work pace, supporting evidence that moderate risk perception promotes preventive actions \u003csup\u003e\u003cspan citationid=\"CR51\" class=\"CitationRef\"\u003e51\u003c/span\u003e,\u003cspan citationid=\"CR135\" class=\"CitationRef\"\u003e135\u003c/span\u003e\u003c/sup\u003e. Similarly, workers with a history of occupational injuries demonstrated higher engagement in heat mitigation, likely due to heightened risk awareness and sensitivity to environmental hazards \u003csup\u003e\u003cspan citationid=\"CR36\" class=\"CitationRef\"\u003e36\u003c/span\u003e,\u003cspan citationid=\"CR133\" class=\"CitationRef\"\u003e133\u003c/span\u003e\u003c/sup\u003e\u003c/p\u003e\u003cp\u003ePsychological factors were further related to personal thermal adaptation. Outdoor workers reporting memory decline or reduced attention were more likely to implement cooling measures, reflecting a behavioral response to the cognitive strain imposed by heat stress. Elevated temperatures were known to impair attention, working memory, and executive function, and workers perceiving these effects appear to proactively adopt strategies to mitigate physical and cognitive risks \u003csup\u003e\u003cspan citationid=\"CR119\" class=\"CitationRef\"\u003e119\u003c/span\u003e,\u003cspan citationid=\"CR122\" class=\"CitationRef\"\u003e122\u003c/span\u003e,\u003cspan citationid=\"CR136\" class=\"CitationRef\"\u003e136\u003c/span\u003e\u003c/sup\u003e.\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec25\" class=\"Section3\"\u003e\u003ch2\u003e4.4.4. Environmental awareness and preparedness\u003c/h2\u003e\u003cp\u003eExperienced construction workers demonstrated greater attentiveness to weather forecasts than younger, less experienced colleagues. Previous research supports this pattern, showing that age and work experience positively influence safety attitudes and behaviors, whereas early\u0026thinsp;\u0026minus;\u0026thinsp;career workers tend to be more risk\u0026thinsp;\u0026minus;\u0026thinsp;taking and less cautious regarding occupational hazards \u003csup\u003e\u003cspan citationid=\"CR87\" class=\"CitationRef\"\u003e87\u003c/span\u003e,\u003cspan citationid=\"CR137\" class=\"CitationRef\"\u003e137\u003c/span\u003e,\u003cspan citationid=\"CR138\" class=\"CitationRef\"\u003e138\u003c/span\u003e\u003c/sup\u003e. Similarly, those working more than nine hours daily were more likely to monitor weather conditions, consistent with studies indicating that prolonged outdoor exposure fosters recognition of heat risks and motivates preventive behaviors \u003csup\u003e\u003cspan citationid=\"CR66\" class=\"CitationRef\"\u003e66\u003c/span\u003e\u003c/sup\u003e. Workers who experienced heat\u0026thinsp;\u0026minus;\u0026thinsp;related illnesses (e.g., muscle cramps) were also more inclined to follow weather forecasts. Such experiences reinforce the importance of proactive measures, including adjusting work hours, hydrating adequately, and seeking shade during peak heat \u003csup\u003e\u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e31\u003c/span\u003e,\u003cspan citationid=\"CR98\" class=\"CitationRef\"\u003e98\u003c/span\u003e,\u003cspan citationid=\"CR139\" class=\"CitationRef\"\u003e139\u003c/span\u003e\u003c/sup\u003e. Interestingly, workers with college or higher education were less likely to participate in heat\u0026thinsp;\u0026minus;\u0026thinsp;related training, diverging from prior studies showing greater engagement among educated employees \u003csup\u003e\u003cspan citationid=\"CR66\" class=\"CitationRef\"\u003e66\u003c/span\u003e,\u003cspan citationid=\"CR140\" class=\"CitationRef\"\u003e140\u003c/span\u003e\u003c/sup\u003e. Locally, this may reflect prioritization of career\u0026thinsp;\u0026minus;\u0026thinsp;focused training or financial incentives over occupational health programs, suggesting that perceived practical value strongly influences participation in preventive initiatives.\u003c/p\u003e\u003c/div\u003e\u003c/div\u003e\u003cdiv id=\"Sec26\" class=\"Section2\"\u003e\u003ch2\u003e4.5. Policy and practice implications\u003c/h2\u003e\u003cp\u003eOur study suggests that effective heat adaptation among Bangladeshi outdoor workers requires behavioral, educational, and structural interventions. Policies should ensure regular work breaks, shaded rest areas, and access to cooling tools such as electric fans, particularly at high\u0026thinsp;\u0026minus;\u0026thinsp;exposure outdoor sites. Targeted training is needed for younger and less experienced workers to improve recognition of heat stress, adoption of safe work practices, and practical adaptation strategies. Workplace interventions should consider informal labor arrangements and economic pressures that prevent workers from slowing their pace or attending safety training. Integrating heat awareness into routine occupational health programs, with incentives, may improve engagement among educated workers who prioritize career\u0026thinsp;\u0026minus;\u0026thinsp;oriented training. Heat stress prevention must be included in workplace risk assessments and occupational health systems, with direct worker input. Guidelines should address both outdoor (construction) and indoor/high\u0026thinsp;\u0026minus;\u0026thinsp;heat (welding) environments, reflecting sector\u0026thinsp;\u0026minus;\u0026thinsp;specific challenges. Low participation in heat safety training highlights the need for accessible and practical programs. Policies should empower workers to self\u0026thinsp;\u0026minus;\u0026thinsp;pace and take breaks without fear of penalty. Monitoring systems tracking environmental conditions and worker health, combined with proactive scheduling based on weather forecasts, can reduce risks. Multi\u0026thinsp;\u0026minus;\u0026thinsp;sector collaboration among government, employers, labor organizations, and public health authorities is essential for the effective implementation and evaluation of interventions.\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec27\" class=\"Section2\"\u003e\u003ch2\u003e4.6. Strengths and limitations\u003c/h2\u003e\u003cp\u003eThis study was one of the few in Bangladesh to examine outdoor workers\u0026rsquo; perceptions and adaptations to heat exposure, providing important insights for policy. However, several limitations should be noted. The sample included only male workers, as construction and welding remain male\u0026thinsp;\u0026minus;\u0026thinsp;dominated sectors in Bangladesh, which limits the inclusion of female perspectives. Heat\u0026thinsp;\u0026minus;\u0026thinsp;related symptoms were self\u0026thinsp;\u0026minus;\u0026thinsp;reported and not objectively verified, and workplace temperatures or additional sources of heat from machinery and direct sunlight were not measured. Finally, the study focused on two occupational groups in selected cities, which may not represent all outdoor workers across different climatic zones of Bangladesh.\u003c/p\u003e\u003c/div\u003e"},{"header":"5. Conclusions","content":"\u003cp\u003eThis study showed that Bangladeshi construction and welding workers were generally aware of climate change and its impact on heat stress at work, but their ability to adapt varied. Most workers recognized factors like high temperature, humidity, and heavy workload as contributors to heat exposure. However, access to protective measures such as shade, cooling devices, and heat\u0026thinsp;\u0026minus;\u0026thinsp;related training was limited, especially among welding workers. Workers\u0026rsquo; adaptive behaviors, such as drinking more water, taking breaks, using fans, wearing loose clothing, or adjusting work schedules, were influenced by previous heat\u0026thinsp;\u0026minus;\u0026thinsp;related symptoms, injuries, work experience, and their level of concern about heat risks. More experienced workers and those working longer hours tended to take more preventive actions, while younger or indoor workers adapted less. Furthermore, changes in working schedule and personal comfort had also been initiated to cope with the rising heat events. These outcomes highlight the urgent need for targeted policy interventions, occupational heat standards, and context\u0026thinsp;\u0026minus;\u0026thinsp;specific awareness programs to address urban heat exposure among outdoor workers in Bangladesh. The study also emphasizes the importance of integrating heat risk management into labor and urban planning policies, particularly for outdoor workers who are often excluded from mainstream protection frameworks.\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eData Availability\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eData can be made available on request to corresponding author.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eHuman and Animal Rights and Informed Consent\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eAll participants provided their consent before taking the survey and were given the option to stop the survey at any time. The survey did not require the disclosure of personal information such as names or email addresses. The study was approved by the research ethical clearance committee of Khulna University, Bangladesh (KUECC\u0026minus;2023/09/51).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConsent for publication\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eAll authors consent to publish this article in \u003cem\u003eScientific Reports.\u003c/em\u003e\u003cem\u003e\u0026nbsp;\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eDeclaration of Competing Interest\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFunding\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe study did not receive any funds, grants, or other support.\u003c/p\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n\u003cli\u003eKlingelh\u0026ouml;fer D, Braun M, Br\u0026uuml;ggmann D, Groneberg DA. 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Perceptions of employees with a low and medium level of education towards workplace health promotion programmes: a mixed-methods study. \u003cem\u003eBMC Public Health\u003c/em\u003e 2022; \u003cstrong\u003e22\u003c/strong\u003e: 1617.\u003c/li\u003e\n\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":true,"hideJournal":true,"highlight":"","institution":"Environment and Sustainability Research Initiative","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":"Occupational Heat Stress, Heat-Related Illness, Heatwave Adaptation, Climate Change, LMICs","lastPublishedDoi":"10.21203/rs.3.rs-8123494/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-8123494/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003eThe increasing frequency and intensity of extreme heat events pose severe health risks to outdoor workers. Despite growing global recognition of occupational heat illness, evidence from low- and middle-income countries (LMICs) remains limited. This cross-sectional study surveyed 320 construction and welding workers to assess perceived heat-related health risk and behavioral adaptation in Bangladesh. Multinomial logistic regression examined factors associated with adaptive behaviors. Over 80% of workers perceived themselves as vulnerable, commonly reporting excessive sweating, thirst, cramps, irritability, and emotional instability. Construction workers were more likely than welding workers to take regular breaks (OR\u0026thinsp;=\u0026thinsp;9.49, 95%CI: 2.45\u0026ndash;36.74), wear loose clothing (OR\u0026thinsp;=\u0026thinsp;4.26, 95%CI: 1.14\u0026ndash;15.90), and use electric fans (OR\u0026thinsp;=\u0026thinsp;2.84, 95%CI: 1.12\u0026ndash;7.22). Conversely, welding workers more often slowed work pace (OR\u0026thinsp;=\u0026thinsp;14.20, 95%CI: 2.03\u0026ndash;99.21) or scheduled tasks during cooler hours (OR\u0026thinsp;=\u0026thinsp;4.81, 95%CI: 2.22\u0026ndash;46.80). Long work experience was associated with using cooling options (OR\u0026thinsp;=\u0026thinsp;6.97, 95%CI: 1.97\u0026ndash;24.68) and following weather forecasts (OR\u0026thinsp;=\u0026thinsp;3.81, 95%CI: 1.01\u0026ndash;14.37). Workers who experienced burns or memory decline adopted specific protective measures. Surprisingly, higher education was linked to lower participation in heat-safety training. These findings highlight the urgent need for occupation-specific heat standards, awareness campaigns, and targeted interventions to safeguard vulnerable outdoor workers in Bangladesh.\u003c/p\u003e","manuscriptTitle":"Occupational Heat Risk Perceptions and Behavioral Adaptation Strategies Among Construction and Welding Workers in Bangladesh","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2025-11-20 06:03:07","doi":"10.21203/rs.3.rs-8123494/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":"0a5a2ed5-2f65-416e-8d93-75170c5f9990","owner":[],"postedDate":"November 20th, 2025","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[{"id":58212201,"name":"Environmental Policy"},{"id":58212202,"name":"Occupational Medicine"},{"id":58212203,"name":"Climatology"},{"id":58212204,"name":"Health Policy"}],"tags":[],"updatedAt":"2025-11-20T06:17:33+00:00","versionOfRecord":[],"versionCreatedAt":"2025-11-20 06:03:07","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-8123494","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-8123494","identity":"rs-8123494","version":["v1"]},"buildId":"8U1c8b4HqxoKbykW_rLl7","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}