BACKGROUND:Individual components of the ambient environment, such as temperature and air pollution, exist as part of a complex mixture and have been associated with suicide; however, their interactive effects remain poorly understood. This study examined the independent and interactive effects of wet bulb globe temperature (WBGT), nitrogen dioxide (NO2), and fine particulate matter (PM2.5) on suicide mortality. METHODS:We identified 7,551 suicide cases in Utah, USA, from 2000 to 2016 and assigned exposure to daily maximum WBGT (sourced from the European Center for Medium-Range Weather Forecasts) and PM2.5 and NO2 concentrations (sourced from a national spatiotemporal ensemble model) using decedent's residential address at the time of death. A case-crossover design with conditional logistic regression was used to estimate the independent and interactive effects of WBGTmax, PM2.5, and NO2 on suicide. For exposure windows, we considered single days preceding suicide (lag 0 to 6) and their averages across preceding days (lag 0-1, 0-3, and 0-6). Analyses were stratified by season. RESULTS:We identified a significant association between WBGTmax and suicide across all seasons (odds ratio [OR] = 1.05, 95% confidence interval [CI]: 1.01, 1.10; per 5 °C increase on lag 0-3 days). The associations were stronger in the warm season (March 22 to September 21), with ORs and 95% CIs ranging from 1.08 (1.02, 1.15) to 1.20 (1.10, 1.30) per 5 °C increase depending on the lag periods. We observed synergistic interactions between WBGTmax and PM2.5 and NO2 in the warm season, associated with higher odds of suicide. The associations of WBGTmax with suicide were most pronounced at high NO2 levels. CONCLUSIONS:We found evidence of synergistic interactions between WBGTmax and PM2.5 and NO2 on suicide in the warm season, emphasizing the need for considering the combined effects of heat stress and air pollution in suicide prevention strategies.

Background: Particulate air pollution and residential greenness are associated with sleep quality in the general population; however, their influence on maternal sleep quality during pregnancy has not been assessed. Objective: This cross-sectional study investigated the individual and interactive effects of exposure to particulate matter (PM) air pollution and residential greenness on sleep quality in pregnant women. Methods: Pregnant women (n = 4933) enrolled in the Korean Children's Environmental Health Study with sleep quality information and residential address were included. Sleep quality was assessed using the Pittsburgh Sleep Quality Index (PSQI). The average concentrations of PM (PM2.5 and PM10) during pregnancy were estimated through land use regression, and residential greenness in a 1000 m buffer area around participants' residences was estimated using the Normalized Difference Vegetation Index (NDVI1000-m). Modified Poisson regression models were used to estimate the associations between PM and NDVI and poor sleep quality (PSQI >5) after controlling for a range of covariates. A four-way mediation analysis was conducted to examine the mediating effects of PM. Results: After adjusting for confounders, each 10 μg/m3 increase in PM2.5 and PM10 exposure was associated with a higher risk of poor sleep quality (relative risk [RR]: 1.06; 95% confidence interval [CI]: 1.01, 1.11; and RR: 1.09; 95% CI: 1.06, 1.13, respectively), and each 0.1-unit increase in NDVI1000-m was associated with a lower risk of poor sleep quality (RR: 0.97; 95% CI: 0.95, 0.99). Mediation analysis showed that PM mediated approximately 37%–56% of the association between residential greenness and poor sleep quality. Conclusions: This study identified a positive association between residential greenness and sleep quality. Furthermore, these associations are mediated by a reduction in exposure to particulate air pollution and highlight the link between green areas, air pollution control, and human health.

BACKGROUND:Although web-based intervention programs are effective in changing health behavior, evidence of their effectiveness in relation to air pollution and respiratory health in children is lacking. We assessed the effects of web-based behavioral intervention on exposure to fine particulate matter (PM ≤ 2.5 μm in diameter [PM2.5]), lung function, and airway inflammation in children. METHODS:We randomized 80 mother-child pairs into intervention or control groups (two arms, 1:1 allocation). Personal and indoor PM2.5 concentrations over a sampling period of 24 h up to four occasions during the study period were measured in participants' homes. We used linear mixed models to assess the intervention effects on PM2.5 concentration, lung function parameters including forced vital capacity (FVC), forced-expiratory volume in 1 s (FEV1), FEV1/FVC, and forced-expiratory flow at 25-75 % (FEF25 %-75 %), and the airway inflammation marker, fractional exhaled nitric oxide (FeNO), as well as the association of PM2.5 with lung function and airway inflammation. Quantile regression was also used to examine the effects of PM2.5 exposure at different quantiles of the outcome distribution. RESULTS:In comparison with the control group, the intervention group showed reduction in indoor and personal PM2.5 concentrations by 20.5 % (95 % confidence interval [CI]: -30.7, -8.9) and 12.9 % (95 % CI: -20.1, -5.1), respectively. Lung function parameters such as FVC, FEV1, and FEF25 %-75 % were higher in the intervention group, with greater benefits observed for children at the lower end of these parameters. Higher levels of outdoor and personal PM2.5 (≥90th percentile) were negatively associated with these lung function parameters at the lower quantiles, whereas the higher level of outdoor PM2.5 concentration was positively associated with FeNO at the lower quantile. CONCLUSIONS:The behavioral intervention reduced PM2.5 concentration in the homes, which was linked to markers of lung function and airway inflammation in children, particularly at the lower quantiles.

Background: Exposure to particulate matter <2.5 mu m (PM2.5) is linked to chronic obstructive pulmonary disease (COPD), but most studies lack individual PM2.5 measurements. Seasonal variation and their impact on clinical outcomes remain understudied. Objective: This study investigated the impact of PM2.5 concentrations on COPD-related clinical outcomes and their seasonal changes. Methods: A multicentre panel study enrolled 105 COPD patients (age range: 46-82) from July 2019 to August 2020. Their mean forced expiratory volume in 1 second after bronchodilation was 53.9%. Individual PM2.5 levels were monitored continuously with indoor measurements at residences and outdoor data from the National Ambient Air Quality Monitoring Information System. Clinical parameters, including pulmonary function tests, symptom questionnaires (CAT and SGRQ-C), and impulse oscillometry (IOS), were assessed every three months over the course of one year. Statistical analysis was conducted using a linear mixed-effect model to account for repeated measurements and control for confounding variables, including age, sex, smoking status and socioeconomic status. Results: The mean indoor and outdoor PM2.5 concentrations were 16.2 +/- 8.4 mu g m(-3) and 17.2 +/- 5.0 mu g m(-3), respectively. Winter had the highest PM2.5 concentrations (indoor, 18.8 +/- 11.7 mu g m(3); outdoor, 22.5 +/- 5.0 mu g m(-3)). Higher PM2.5 concentrations significantly correlated with poorer St. George's Respiratory Questionnaire for COPD (SGRQ-C) scores and increased acute exacerbations, particularly in winter. Patients of lower socioeconomic status were more vulnerable. Increased PM2.5 concentrations were also associated with amplified small airway resistance (R5-R20). Conclusions: PM2.5 concentration changes are positively correlated with poorer SGRQ-C scores and increased acute exacerbations in COPD patients with significant seasonal variations, especially in winter.

Prenatal exposure to climate factors, air pollution, and green space has been linked to respiratory diseases in infants. However, the role of the combined effects of exposure to these factors on respiratory ailments remains unclear. Here we investigate the association of combined exposure to traffic-related air pollution (TRAP), climate factors, and green space during the prenatal period with respiratory diseases in infants. We enrolled 454 participants from the ongoing prospective birth cohort known as the Mothers and Children's Environmental Health study. Data on infant respiratory diseases were collected from parents or guardians. Average exposure values of TRAP, climate factors, and green spaces for the study population were calculated based on geocoded residential addresses. Multiple logistic regression and quantile-based g-calculation models were utilized to examine the association of exposure to environmental factors and green space with respiratory diseases. The combined exposure to climate factors and TRAP during the first trimester of pregnancy was associated with an increased risk of respiratory diseases in infants. High levels of particulate matter with a diameter less than 2.5 μm (PM2.5) and temperature increased the risk of respiratory diseases (adjusted odds ratio (AOR): 1.615, 95% confidence interval (CI): 1.001, 2.658). Additionally, the risk of respiratory diseases from exposure to air pollution and temperature was associated with lower tertiles of residential green spaces. The AOR was 1.064 (95% CI: 1.001, 1.133) per 1 µg/m3 increase in PM2.5, 1.057 (95% CI: 1.001, 1.116) per 1 ppb increase in NO2, and 1.108 (95% CI: 1.001, 1.176) per 1 ℃ increase in temperature. Incorporating green space into the analysis of joint exposure to climate factors and air pollution reduced the risk of respiratory disease. This study proposes that combined exposures to climate factors, TRAP, and green spaces during pregnancy are associated with infant respiratory diseases. Fewer residential green spaces could enhance the association of climate factors and air pollution with respiratory diseases.

[This corrects the article DOI: 10.1016/j.heliyon.2024.e26742.].

Background: Evidence linking environmental toxicants to sleep quality is growing; however, these associations during pregnancy remain unclear. We examined the associations of repeated measures of urinary phthalates in early and late pregnancy with multiple markers of sleep quality among pregnant women. Methods: The study population included 2324 pregnant women from the Korean Children's Environmental Health Study. We analyzed spot urine samples collected at two time points during pregnancy for exposure biomarkers of eight phthalate metabolites. We investigated associations between four summary phthalates (all phthalates: & sum;Phthalates; di-(2-ethylhexyl) phthalate: & sum;DEHP; phthalates from plastic sources: & sum;Plastic; and antiandrogenic phthalates: & sum;AA) and eight individual phthalates and self-reported sleep measures using generalized ordinal logistic regression and generalized estimating equations models that accounted for repeated exposure measurements. The models were adjusted for age, body mass index, education, gestational age, income, physical activity, smoking, occupation, chronic diseases, depression, and urinary cotinine levels. Results: Multiple individual phthalates and summary measures of phthalate mixtures, including & sum;Plastic, & sum;DEHP, & sum;AA, and & sum;Phthalates, were associated with lower sleep efficiency. To illustrate, every 1-unit log increase in & sum;AA was associated with a reduction of sleep efficiency by 1.37 % (95% confidence interval [CI] = -2.41, -0.32). & sum;AA and & sum;Phthalates were also associated with shorter sleep duration and longer sleep latency. Associations between summary phthalate measures and sleep efficiency differed by urinary cotinine levels (P for subgroup difference < 0.05). Conclusions: Findings suggest that higher phthalate exposure may be related to lower sleep efficiency, shorter sleep duration, and prolonged sleep latency during pregnancy.

BACKGROUND AND AIM: Evidence linking environmental toxicants to sleep quality is growing, but these associations during pregnancy remain unclear. In the present study, we examined association between phthalate exposure and sleep quality among pregnant women using repeated exposure measurements. METHOD: Spot urine samples collected from a nationwide sample of 2,324 pregnant women at two time points during pregnancy were analyzed for exposure biomarkers of eight phthalate metabolites. We investigated associations between summary and individual phthalate metabolites and self-reported sleep measures using generalized ordinal logistic regression and generalized estimating equations models adjusted for age, body mass index, education, gestational age, income, physical activity, smoking, occupation, chronic health condition, depression, and urinary cotinine level. RESULTS: Multiple individual phthalates and summary measures of phthalate mixtures, including the phthalates from plastic sources (∑Plastic), di-(2-ethyhexyl) phthalate (∑DEHP), anti-androgenic phthalates (∑AA), and all phthalate metabolites (∑Phthalates), were associated with lower sleep efficiency. To illustrate, every 1-unit log increase in ∑AA was associated with a reduction of sleep efficiency by 1.26% (95% confidence interval [CI]: –2.30, –0.21; q 0.05). ∑AA and ∑Phthalates were associated with shorter sleep duration and longer sleep latency. Associations between ∑DEHP and ∑Plastic and sleep efficiency differed by urinary cotinine level (p-interaction 0.01). CONCLUSIONS: Results indicate that higher phthalate exposure may be related to low sleep efficiency, short sleep duration, and prolonged sleep latency during pregnancy.

The recent global pandemic of the novel coronavirus disease 2019 (COVID-19) is affecting the entire population of Nepal, and the outcome of the epidemic varies from place to place. A district-level analysis was conducted to identify socio-demographic risk factors that drive the large variations in COVID-19 mortality and related health outcomes, as of 22 January 2021. Data on COVID-19 extracted from relevant reports and websites of the Ministry of Health and Population of Nepal, and the National Population and Housing Census and the Nepal Demographic and Health Survey were the main data sources for the district-level socio-demographic characteristics. We calculated the COVID-19 incidence, recovered cases, and deaths per 100,000 population, then estimated the associations with the risk factors using regression models. COVID-19 outcomes were positively associated with population density. A higher incidence of COVID-19 was associated with districts with a higher percentage of overcrowded households and without access to handwashing facilities. Adult literacy rate was negatively associated with the COVID-19 incidence. Increased mortality was significantly associated with a higher obesity prevalence in women and a higher smoking prevalence in men. Access to health care facilities reduced mortality. Population density was the most important driver behind the large variations in COVID-19 outcomes. This study identifies critical risk factors of COVID-19 outcomes, including population density, crowding, education, and hand hygiene, and these factors should be considered to address inequities in the burden of COVID-19 across districts.

BACKGROUND:Air pollution is associated with depressive and anxiety symptoms in the general population. However, this relationship among pregnant women remains largely unknown.OBJECTIVE:To evaluate the association between pregnancy air pollution exposure and maternal depressive and anxiety symptoms during the third trimester assessed using the Center for Epidemiologic Studies-Depression and State-Trait Anxiety Inventory scales, respectively.METHODS:We analyzed 1481 pregnant women from a cohort study in Seoul. Maternal exposure to particulate matter with an aerodynamic diameter <2.5 μm (PM2.5) and <10 μm (PM10), as well as to nitrogen dioxide (NO2) and ozone (O3) for each trimester and the entire pregnancy was assessed at participant's residential address by land use regression models. We estimated the relative risk (RR) and corresponding confidence interval (CI) of the depressive and anxiety symptoms associated with an interquartile range (IQR) increase in PM2.5, PM10, NO2, and O3 using modified Poisson regression.RESULTS:In single-pollutant models, an IQR increase in PM2.5, PM10, and NO2 during the second trimester was associated with an increased risk of depressive symptoms (PM2.5 RR = 1.15, 95% CI: 1.04, 1.27; PM10 RR = 1.13, 95% CI: 1.04, 1.23; NO2 RR = 1.15, 95% CI: 1.03, 1.29) after adjusting for relevant covariates. Similarly, an IQR increase in O3 during the third trimester was associated with an increased risk of depressive symptoms (RR = 1.09, 95% CI: 1.01, 1.18), while the IQR increase in O3 during the first trimester was associated with a decreased risk (RR = 0.89, 95% CI: 0.82, 0.96). Exposure to PM2.5, PM10, and NO2 during the second trimester was significantly associated with anxiety symptoms. The associations with PM2.5 and O3 in single-and multi-pollutant models were consistent.CONCLUSIONS:Our findings indicate that increased levels of particulate matter, NO2, and O3 during pregnancy may elevate the risk of depression or anxiety in pregnant women.

Air pollution may influence prenatal maternal stress, but research evidence is scarce. Using data from a prospective cohort study conducted on pregnant women (n = 2153), we explored the association between air pollution and perceived stress, which was assessed using the 14-item Perceived Stress Scale (PSS), among pregnant women. Average exposures to particulate matter with an aerodynamic diameter of < 2.5 µm (PM 2.5 ) or < 10 µm (PM 10 ), nitrogen dioxide (NO 2 ), and ozone (O 3 ) for each trimester and the entire pregnancy were estimated at maternal residential addresses using land-use regression models. Linear regression models were applied to estimate associations between PSS scores and exposures to each air pollutant. After adjustment for potential confounders, interquartile-range (IQR) increases in whole pregnancy exposures to PM 2.5 , PM 10 , and O 3 in the third trimester were associated with 0.37 (95% confidence interval [CI] 0.01, 0.74), 0.54 (95% CI 0.11, 0.97), and 0.30 (95% CI 0.07, 0.54) point increases in prenatal PSS scores, respectively. Furthermore, these associations were more evident in women with child-bearing age and a lower level of education. Also, the association between PSS scores and PM 10 was stronger in the spring. Our findings support the relationship between air pollution and prenatal maternal stress.

Background: Air pollution is associated with perceived stress in the general population, but its influence on maternal perceived stress during pregnancy has not been investigated.We aimed to investigate the relationship between air pollution and non-specific perceived stress among pregnant women. Methods: Our analysis included2162 pregnant women who had participated in the cohort for childhood origin of asthma and allergic disease study between 2008 and 2015. Maternal exposures to particulate matter with an aerodynamic diameter < 2.5 µm (PM 2.5 ) and < 10 µm (PM 10 ), as well as to nitrogen dioxide (NO 2 ) and ozone (O 3 ) for each trimesterand the entire pregnancy were determined using land-use regression models. Maternal perceived stress during the third trimester was assessed using the 14-item Perceived Stress Scale (PSS): scores ranged from 0-56 with higher scores indicating increased stress. Linear regression models were applied to estimate associations between PSS scores and each air pollutant, after adjusting for socio-demographic and behavioral covariates. Results: In single-pollutant models,after adjustment, an IQR increase in the whole pregnancy exposure to PM 2.5 and PM 10 and O 3 in the third trimester was related to 0.37 (95% confidence interval [CI]: 0.01, 0.74) and 0.55 (95% CI: 0.12, 0.98) and 0.29 (95% CI: 0.05, 0.52) points increase in the PSS score, respectively.This association was more evident in women with child-bearing age and lower levelofeducation, and the association of PM 10 was stronger in thespring season.In multi-pollutant models, exposures to PM 10 and O 3 were associated with higher perceived stress. Conclusion: Our findings suggest that pregnancy exposure to PM 2.5 , PM 10 and O 3 is positively associated with maternal PSS score during the third trimester.

Background/AimSeveral studies have demonstrated associations between household air pollution (HAP) and child undernutrition, but the extent to which this relationship varies across the outcome distribution and according to socioeconomic status (SES) is unknown. We aimed to address this using data from Nepal Demographic and Health Survey (NDHS).MethodsWe used child anthropometry data for 9,914 children aged 0-59 months from the 2006, 2011, and 2016 NDHS. Sex-stratified quantile regression (QR) analysis was performed to identify the relationship between the markers of HAP and child nutritional status, which is indicated by z scores for height-for-age (HAZ), weight-for-age (WAZ), and weight-for-height (WHZ). The SES was based on the composite of education, household wealth, and occupation. We used QR plots to visually examine the effect of HAP across the entire outcome distribution for each SES group.ResultsIn the adjusted model, the negative association between HAP and HAZ was stronger at the lower end of HAZ distribution in both sexes. For example, the estimate for female children at the 10th quantile was −0.39 (95% confidence interval (CI) = −0.65, −0.13), decreasing to −0.26 (95% CI = −0.52, 0.01) at the 90th quantile. The QR plots showed a pattern of stronger association in low SES group and at the lower end of HAZ distribution, particularly among female children. For example, female children from low SES group, HAP was associated with a 0.81unit decrease (95% CI = 1.51, 0.11) in HAZ at the 10th quantile, whereas it was associated with a 0.49 unit decrease (95% CI = 0.69, 0.28) for high SES group in the same quantile. The strength of evidence for socioeconomic inequalities for WAZ and WHZ was weak.ConclusionsWe observed evidence for a pattern of stronger effect of HAP in lower SES group, particularly among female children and at the lower end of the HAZ.

BACKGROUND:An association between maternal exposure to air pollution and the birth weight distribution has been reported, but the extent to which this relationship varies according to socioeconomic status (SES) is unknown. This study examined the relationship using the data from a Korean birth cohort. METHODS:Data for singleton births in Seoul from 2007 to 2017 (n = 1739) were analyzed. Maternal exposures to particulate matter with an aerodynamic diameter <10 µm (PM10) and <2.5 µm (PM2.5), as well as to nitrogen dioxide (NO2) and ozone (O3) for each trimester and the entire pregnancy were estimated using residential address, gestational age, and the birth date. The associations between the interquartile range (IQR) increases in pollutant concentrations and the changes in birth weight were examined using linear regression and quantile regression models. The socioeconomic disparities in the associations were investigated using a derived SES variable based on the composite of parental education and occupation. This SES variable was then interacted with the air pollutant. RESULTS:In the gestational age-adjusted models, particulate air pollutants (PM10 and PM2.5) and O3 were associated with birth weight decreases for the lower birth weight percentiles. For example, the decrease in mean birthweight per IQR increase in PM2.5 during second trimester was -21.1 g (95% confidence interval (CI) = -41.8, -0.4), whereas the quantile-specific associations were: 10th percentile -27.0 g (95% CI = -46.6, -7.3); 50th percentile -22.2 g (95% CI = -39.6, -4.8); and 90th percentile -22.9 g (95% CI = -45.5, -0.2). Particulate air pollutants and O3 showed a pattern of socioeconomic inequalities; the reduced birth weight was of greater magnitude for children from a low SES group. CONCLUSIONS:Negative associations between particulate air pollutants and O3 and birth weight were consistently greater at the lower quantiles of the birth weight distribution, especially in lower SES group.

This study investigated whether the association between household air pollution (HAP) and nutritional status (stunting, underweight, or wasting) among children differ by caste/ethnicity. Child anthropometry data for 9,914 children aged 0-59 months were analyzed linearly as Z scores and as dichotomous categories. Exposure to HAP was significantly associated with a decrease in child height-for-age and child weight-for-age, as well as with stunting and underweight. Children in low caste (Dalits) had higher prevalence of stunting (odds ratio [OR] = 1.21; 95% confidence intervals [CI] = 1.01, 1.44), underweight (OR = 1.47; 95% CI = 1.24, 1.75), and wasting (OR = 1.53; 95% CI = 1.21, 1.92) than those children in upper caste group. This association was modestly attenuated with adjustment for HAP. Exposure to HAP partly explained the caste-ethnic difference in undernutrition among children in Nepal.

TPS 742: Adverse birth outcomes 1, Exhibition Hall, Ground floor, August 27, 2019, 3:00 PM - 4:30 PM Background/Aim: Previous studies have examined associations between air pollution and pregnancy outcomes, but most have reported inconsistent results. We aimed to investigate the association between maternal exposure to particulate air pollution and low birth weight (LBW) and preterm birth (PTB) using a representative data from South Korea. Methods: We analyzed a representative sample of 2,072 delivered live births between April and July, 2008, using data from the Panel Study on Korean Children (PSKC). During each trimester of gestation and entire pregnancy, the effect of NO2, PM10, and PM2.5 exposure on PTB and LBW was explored. The exposures were assessed by Land Use Regression (LUR). We extracted odds ratio (OR) and 95% confidence intervals (CIs) using logistic regression analyses. Results: In fully adjusted model, a significantly increased risk of PTB (per 10 μg/m3) increase in PM10 (OR=1.031; 95% CI 1.001, 1.063) and PM2.5 (OR=1.037; 95% CI 1.001, 1.074) exposure during entire pregnancy was observed. Highest ORs were observed during trimester 1 (1.043; 1.010-1.077). Exposures to PM2.5 during trimester 1, trimester 2, and the whole pregnancy were associated with increased risk of LBW increase in PM2.5 [OR with 10 μg/m3 and 95% CIs: 1.044 (1.011, 1.078), 1.034 (1.004, 1.064), and 1.039 (1.003, 1.076), respectively]. Conclusions: This study, based on a representative data from South Korea, provides further evidence linking particulate matter and adverse pregnancy outcomes. Acknowledgement: This work was supported by a grant from the National Research Foundation of Korea (NRF-2017R1D1A1B03035917) and the National Institute of Environmental Research (NIER) funded by the Ministry of Environment (MOE) of the Republic of Korea.

Background In Korea, several household humidifier disinfectants (HDs) were clinically confirmed to cause HD-associated lung injury (HDLI). Polyhexamethylene guanidine (PHMG) phosphate is the main ingredient of the HDs found to be associated with lung disease. However, the association of HDs with other interstitial lung disease including idiopathic interstitial pneumonia (IIP) is not clear. We examined the relationship between HD exposure and IIP in a family-based study. Methods This case-control study included 244 IIP cases and 244 family controls who lived with the IIP patients. The IIP cases were divided into two groups, HDLI and other IIP, and were matched to family controls based on age and gender. Information on exposure to HDs was obtained from a structured questionnaire and field investigations. Conditional logistic regression was used to estimate odds ratio (ORs) and their corresponding 95% confidence interval (CI), investigating the association of HD-related exposure characteristics with IIP risk. Results The risks of IIP increased two-fold or more in the highest compared with the lowest quartile of several HD use characteristics, including average total use hours per day, cumulative sleep hours, use of HD during sleep, and cumulative exposure level. In analyses separated by HDLI and other IIP, the risks of HDLI were associated with airborne HD concentrations (adjusted OR = 3.01, 95% CI = 1.34-6.76; Q4 versus Q1) and cumulative exposure level (adjusted OR = 3.57, 95% CI = 1.59-8.01; Q4 versus Q1), but this relationship was not significant in the patients with other IIP. In comparison between HDLI and other IIP, the odds ratios of average total use hours, cumulative use hours, and cumulative sleeps hours was higher for other IIP. Conclusion The use of household HDs is associated not only with HDLI but also with other IIP.

PDS 72: Environmental health issues in LMIC, Exhibition Hall (PDS), Ground floor, August 28, 2019, 10:30 AM - 12:00 PM Background/Aim: Recent studies suggest ethnic inequalities in air pollution and health. Very few studies have investigated the role of air pollution on ethnic differences in child health. This study aimed to examine whether the association between being exposed to household air pollution from burning solid fuels and child health (stunting, wasting, or underweight) varied by ethnicity. Methods: The study used child data from the recent Nepal Demographic and Health Survey (NDHS) 2016. Outcome variables were based on growth and weight anthropometry data, which were analyzed linearly as z scores and as dichotomous categories. We analyzed the NDHS data for children aged 0-59 months (n = 2373) using the ordinary least squares (OLS) and instrumental variable (IV) models accounting for the complex survey design. Results: We found strong evidence that exposure to solid fuel smoke increases the probability of being stunted, as well as reduces the height-for-age (HAZ) measure. The difference in means between the HAZ score of children exposed to solid fuels and those not exposed to it was 0.61. The OLS model estimated that up to 42.6% (β = 0.26, p = 0.010) of this difference is due to exposure to solid fuel, after controlling for potential risk factors, while the IV model estimated about 67.2% (β = 0.41, p = 0.003) of the difference. The stratified IV models showed lower HAZ score and stunting among indigenous people compared to the upper caste people. Further stratified analyses indicated that the impact of solid fuel smoke is stronger among indigenous people with low household wealth, but did not explain the wealth differences in the impact of solid fuels among the upper caste people. Conclusions: Children from indigenous communities are likely to be more susceptible to the health effects of solid fuel smoke.