Health assessment of future PM2.5 exposures from indoor, outdoor, and secondhand tobacco smoke concentrations under alternative policy pathways in Ulaanbaatar, Mongolia

Utilizing Low-Cost Sensors to Monitor Indoor Air Quality in Mongolian Gers

Air quality has important climate and health effects. There is a need, therefore, to monitor air quality both indoors and outdoors. Methods of measuring air quality should be cost-effective if they are to be used widely, and one such method is low-cost sensors (LCS). This study reports on the use of LCSs in Ulaanbataar, Mongolia to measure PM2.5 concentrations inside yurts or "gers". Some of these gers were part of a non-government agency (NGO) initiative to improve insulating properties of these housing structures. The goal of the NGO was to decrease particulate emissions inside the gers; a secondary result was to lower the use of coal and other biomass material. LCSs were installed in gers heated primarily by coal, and interior air quality was measured. Gers that were modified by increasing their insulating capacities showed a 17.5% reduction in PM2.5 concentrations, but this is still higher than recommended by health organizations. Gers that were insulated and used a combination of both coal and electricity showed a 19.1% reduction in PM2.5 concentrations. Insulated gers that used electricity for both heating and cooking showed a 48% reduction in PM2.5 but still had higher concentrations of PM2.5 that were 6.4 times higher than recommended by the World Health Organization (WHO). Nighttime and daytime trends followed similar patterns and trends in PM2.5 concentrations with slight variations. It was found that at nighttime the outside PM2.5 concentrations were generally higher than the inside concentrations of the gers in this study, meaning that PM2.5 would flow into the ger whenever the doors were opened, causing spikes in PM2.5 concentrations.

Portable HEPA filter air cleaner use during pregnancy and children's autistic behaviors at four years of age: The UGAAR randomized controlled trial

BACKGROUND

Developmental exposure to airborne particulate matter (PM) may increase children's risk of developing autism spectrum disorder. We quantified the impact of reducing PM exposure during pregnancy on the development of autistic traits in children. We also assessed associations between indoor fine PM (PM2.5) concentrations during pregnancy and autistic traits.

METHODS

In this parallel-group randomized controlled trial, we randomized 540 non-smoking pregnant women to receive HEPA filter air cleaners or to a control group, which did not receive air cleaners. We administered the Social Responsiveness Scale (SRS-2) to caregivers when children were a median of 48 months (range: 48 to 51 months). Our primary outcome was the SRS-2 total T-score. We imputed missing data using multiple imputation with chained equations and our primary analysis was by intention to treat. In secondary analyses, we estimated associations between full pregnancy and trimester-specific indoor PM2.5 concentrations and T-scores.

RESULTS

We enrolled participants at a median of 11 weeks' gestation. Our analysis included 478 children (233 control, 245 intervention). The intervention reduced average indoor PM2.5 concentrations by 29 % (95 % CI: 21, 37 %). The mean SRS-2 total T-score was 0.5 units lower (95 % CI: -2.5, 1.5) among intervention participants, with evidence of larger benefits for children at the high end of the T-score distribution. An interquartile range (9.6 µg/m3) increase in indoor PM2.5 during pregnancy was associated with 1.8-unit (95 % CI: 0.3, 3.2) increase in mean SRS-2 total T-score. Effect estimates for PM2.5 concentrations by trimester were smaller and confidence intervals spanned no effect.

CONCLUSION

Reducing indoor PM during pregnancy had little impact on mean autism-related behavior scores in children. However, indoor PM2.5 concentrations during pregnancy were associated with higher scores. Exposure to particulate matter during pregnancy may influence the development of autistic traits in childhood.

TRIAL REGISTRATION

ClinicalTrials.gov: NCT01741051.

Characteristics of particle-bound polycyclic aromatic hydrocarbons (PAHs) in indoor PM2.5 of households in the Southwest part of Ulaanbaatar capital, Mongolia

Air pollution, including PM_2.5 concentration in Ulaanbaatar (capital of Mongolia) is a serious matter of concern. As the majority of households use coal in large areas of the city, indoor air quality is also posing a serious risk to human health. This study investigated the concentration of polycyclic aromatic compounds (PAHs) in indoor particulate matter (PM_2.5) in 10 non-smoker households. Sampling was conducted in winter of 2018, between 27 January and 09 February. Concentrations of PM_2.5 in the indoor air of households ranged between 62.8 and 324.8 µg m^-3. Total concentration of PAHs also varied in a relatively wide range, between 46.2 and 175.7 ng m^-3. Five-ring PAHs represented a considerably high fraction of total PAHs between 25 and 53%, benzo[b]fluoranthene (BbF) and benzo[a]pyrene (BaP) were the two predominant compounds within five-ring PAHs. Significant correlation was found between indoor and outdoor particulate matter levels in wintertime. Considering individual characteristic PAHs, heavier PAHs homologues (4- to 5-ring and 6-ring PAHs) were detected in all households, which suggested the influence of coal combustion and traffic exhaust. Health risk of children attributed to PAHs inhalation was assessed by taking into account the lifetime-average daily dose (LADD) and corresponding lifetime cancer risk. Lifetime average daily dose for children in only one household were slightly higher than health-based guideline level (1.0 × 10^-5), defined by WHO, whereas LADD for adults and children of other households were within acceptable limit. The cancer risks from the exposure of children to air pollutants in all households except HH-3 were found high. In the Vibrio fischeri bioluminescence inhibition assay, according to the toxic unit (TU) values of indoor PM_2.5 from ten households, all samples were classified as toxic.

Assessing the Environmental-Health-Economic Co-Benefits from Solar Electricity and Thermal Heating in Ulaanbaatar, Mongolia

This article quantifies the environmental, health, and economic co-benefits from the use of solar electricity and heat generation in the Ger area (a sub-district of traditional residences and private houses) in Ulaanbaatar (UB), Mongolia. The quantification of the featured co-benefits is based on calculating emissions reductions from the installation of the solar photovoltaic (PV) and solar water heaters. A user-friendly spreadsheet tool is developed to shed much-needed light on the steps involved in estimating these co-benefits. The tool simulates the hourly electricity and thermal energy generation, taking into account local meteorological conditions, local geographical data, and technical specifications of the solar power and heat generation systems. The tool is then employed to evaluate two intervention scenarios: (1) Installing 100 MW solar electricity, including both rooftop PV and community grids, to reduce the peak-load burden on the grid; (2) Providing solar thermal heaters for 20,000 households to replace the heating load demand from the existing heat only boilers (HOBs) in UB. The modelling results reveal a significant reduction in GHG emissions and fine particulate matter (PM_2.5) (PM that is 2.5 microns or less in diameter) by 311,000 tons and 767 tons, respectively, as well as nearly 6500 disability-adjusted life years (DALYs) and an annual saving of USD 7.7 million for the local economy. The article concludes that the mainstreaming spreadsheet-based estimation tools like the one used in this article into decision-making processes can fill important research gaps (e.g., usability of assessment tools) and help translate co-benefits analyses into action in Mongolia and beyond.

Portable HEPA Filter Air Cleaner Use during Pregnancy and Children's Cognitive Performance at Four Years of Age: The UGAAR Randomized Controlled Trial

BACKGROUND

Developmental exposure to air pollution is associated with diminished cognitive abilities in observational studies, but no randomized controlled trial has examined the effect of reducing air pollution on cognition in children.

OBJECTIVES

We sought to quantify the impact of reducing exposure to particulate matter (PM) during pregnancy on children's cognitive performance at 4 y of age.

METHODS

In this single-blind, parallel-group, randomized controlled trial in Ulaanbaatar, Mongolia, we randomly assigned 540 nonsmoking pregnant women (268 intervention and 272 control) to receive 1-2 portable high-efficiency particulate air (HEPA) filter air cleaners or no air cleaners. The air cleaners were used from a median of 11 wk gestation until the end of pregnancy. The primary outcome was full-scale intelligence quotient (FSIQ) assessed using the Wechsler Preschool and Primary Scale of Intelligence, Fourth Edition (WPPSI-IV) when children were a median of 48 months old. We imputed missing outcome data using multiple imputation with chained equations, and our primary analysis was by intention to treat.

RESULTS

After excluding known miscarriages, stillbirths, neonatal deaths, and medical conditions that impeded cognitive testing and imputation, 475 (233 control and 242 intervention) children were included in our analyses. In an unadjusted analysis, the mean FSIQ of children who were randomly assigned to the intervention group was 2.5 points [95% confidence interval (CI): -0.4, 5.4 points] higher than that of children in the control group. After adjustment to account for an imbalance in preterm birth between groups, the effect estimate increased to 2.8 points (95% CI: -0.1, 5.7).

CONCLUSIONS

Reducing PM air pollution during pregnancy may improve cognitive performance in childhood. https://doi.org/10.1289/EHP10302.

Synergistic Health Benefits of Household Stove Upgrading and Energy Switching in Rural China

Rural residential energy switching from solid fuels to electricity and natural gas has resulted in substantial health benefits in China. Here, we quantitatively estimated the environmental and health benefits of stove upgrading, energy switching, and the interaction of stove upgrading and energy switching in rural mainland China during the period of 1980-2014. Driven by government intervention, technical progress, and socioeconomic development, domestic stoves have been upgraded from a domination of open-fire and traditional stoves to energy-saving, clean stoves, and gas range/electric stoves. Furthermore, stove upgrading significantly contributed to the overall reductions in PM_2.5 emissions (25%), ambient and indoor PM_2.5 concentrations (49 and 28%), population exposure (31%), and premature deaths (37%) attributable to residential emissions. The interaction between stove upgrading and energy switching resulted in an additional 15% reduction in premature deaths. The influences of the residential sector and the beneficial effects of stove upgrading and energy switching are magnified along the causal path from emissions to health impacts. The overall benefit of the transition in residential energy would be substantially underestimated without considering stove upgrading.

Portable HEPA filter air cleaner use during pregnancy and children's body mass index at two years of age: The UGAAR randomized controlled trial

IMPORTANCE

Gestational exposure to particulate matter (PM) air pollution may increase the risk of childhood obesity, but the impact of reducing air pollution during pregnancy on obesity-related outcomes in childhood has not been examined.

OBJECTIVE

To assess the impact of reducing gestational PM exposure on body mass index (BMI) at two years of age.

METHODS

In this single-blind, parallel group randomized controlled trial in Ulaanbaatar Mongolia, we randomly assigned 540 pregnant women to receive 1-2 portable high efficiency particulate air (HEPA) filter air cleaners or no air cleaners. We measured height and weight when children were a mean age of 23.8 months. Our primary outcome was age- and sex-specific BMI z-score based on the World Health Organization 2007 Growth Charts. Secondary outcomes included age- and sex-specific weight z score, overweight/obesity (defined as BMI z-score > 2.00), and catch-up growth (defined using various cut-offs to identify children with relatively low birth weight for sex and gestational age and relatively high age- and sex-specific weight in childhood). We imputed missing outcome data using multiple imputation with chained equations and our primary analysis was by intention to treat (ITT). We estimated intervention effects on continuous and binary outcomes using linear and logistic regression, respectively.

RESULTS

After excluding known miscarriages, still births, and neonatal deaths our analysis included 480 children (235 control and 245 intervention). The mean (SD) child BMI z score was 0.79 (1.0); 9.8% of children were overweight or obese. The mean BMI z score of children who were randomly assigned to the intervention group was 0.16-units lower (95% CI: -0.35, 0.04) than children in the control group. The intervention was also associated with reductions in overweight/obesity (odds ratio = 0.59; 95% CI: 0.31, 1.12). Catch-up growth occurred less frequently in the intervention group, but effect estimates varied depending on the specific definition of catch-up growth and confidence intervals consistently spanned no effect.

CONCLUSIONS

We found that the use of portable air cleaners during pregnancy was associated with improvements in obesity-related outcomes, although some effect estimates lacked precision. Reducing PM exposure during pregnancy may lead to improvements in cardiometabolic health in childhood.

Portable HEPA filter air cleaner use during pregnancy and children's behavior problem scores: a secondary analysis of the UGAAR randomized controlled trial

BACKGROUND

Developmental exposure to particulate matter (PM) air pollution may impair children's behaviors. Our objectives were to quantify the impact of reducing indoor PM using portable HEPA filter air cleaners during pregnancy on behavioral problems in children and to assess associations between indoor fine PM (PM_2.5) concentrations during pregnancy and children's behavior.

METHODS

This is a secondary analysis of a single-blind parallel-group randomized controlled trial in which we randomly assigned 540 non-smoking pregnant women to receive 1 or 2 HEPA filter air cleaners or no air cleaners. We administered the Behavior Assessment System for Children (BASC-3) to caregivers when children were a mean age of 23 months, and again at a mean age of 48 months. Primary outcomes were the four BASC-3 composite scales: externalizing problems, internalizing problems, adaptive skills, and the behavioral symptoms index. We imputed missing data using multiple imputation with chained equations. The primary analysis was by intention-to-treat. In a secondary analysis, we evaluated associations between BASC-3 composite indices and modeled trimester-specific PM_2.5 concentrations inside residences.

RESULTS

We enrolled participants at a median of 11 weeks gestation. After excluding miscarriages, still births and neonatal deaths, our analysis included 478 children (233 control and 245 intervention). We observed no differences in the mean BASC-3 scores between treatment groups. An interquartile increase (20.1 µg/m³) in first trimester PM_2.5 concentration was associated with higher externalizing problem scores (2.4 units, 95% CI: 0.7, 4.1), higher internalizing problem scores (2.4 units, 95% CI: 0.7, 4.0), lower adaptive skills scores (-1.5 units, 95% CI: -3.0, 0.0), and higher behavior symptoms index scores (2.3 units, 95% CI: 0.7, 3.9). Third trimester PM_2.5 concentrations were also associated with some behavioral indices at age 4, but effect estimates were smaller. No significant associations were observed with PM_2.5 concentrations during the second trimester or for any of the BASC indices when children were 2 years old.

CONCLUSION

We found no benefit of reducing indoor particulate air pollution during pregnancy on parent-reported behaviors in children. Associations between indoor PM_2.5 concentrations in the first trimester and behavioral scores among 4-year old children suggest that it may be necessary to intervene early in pregnancy to protect children, but these exploratory findings should be interpreted cautiously.

TRIAL REGISTRATION

ClinicalTrials.gov: NCT01741051.

Association between household solid fuel use and tuberculosis: cross-sectional data from the Mongolian National Tuberculosis Prevalence Survey

BACKGROUND

Tuberculosis (TB) and indoor air pollution (IAP) are equally critical public health issues in the developing world. Mongolia is experiencing the double burden of TB and IAP due to solid fuel combustion. However, no study has assessed the relationship between household solid fuel use and TB in Mongolia. The present study aimed to assess the association between household solid fuel use and TB based on data from the Mongolian National Tuberculosis Prevalence Survey (MNTP Survey).

METHOD

The MNTP Survey was a nationally representative population-based cross-sectional survey targeting households in Mongolia from 2014 to 2015, with the aim of evaluating the prevalence of TB. The survey adopted a multistage cluster sampling design in accordance with the World Health Organization prevalence survey guidelines. Clusters with at least 500 residents were selected by random sampling. A sample size of 98 clusters with 54,100 participants was estimated to be required for the survey, and 41,450 participants were included in the final analysis of the present study. A structured questionnaire was used to collect information on environmental and individual factors related to TB. Physical examination, chest X-ray, and sputum examinations were also performed to diagnose TB.

RESULTS

The use of solid fuels for heating (adjusted odds ratio (aOR): 1.5; 95% confidence interval (CI): 1.1-2.1), male gender (aOR: 2.2; 95% CI: 1.6-3.2), divorced or widowed (aOR: 2.6; 95% CI: 1.7-3.8), daily smoker (aOR: 1.8; 95% CI: 1.3-2.5), contact with an active TB case (aOR: 1.7; 95% CI: 1.2-2.3), being underweight (aOR: 3.7; 95% CI: 2.4-5.7), and previous history of TB (aOR: 4.3; 95% CI: 3.0-6.1) were significantly associated with bacteriologically confirmed TB after adjusting for confounding variables.

CONCLUSION

The use of solid fuels for heating was significantly associated with active TB in Mongolian adults. Increased public awareness is needed on the use of household solid fuels, a source of IAP.

Exceedances and trends of particulate matter (PM2.5) in five Indian megacities

Fine particulate matter (PM_2.5) is the leading environmental risk factor that requires regular monitoring and analysis for effective air quality management. This work presents the variability, trend, and exceedance analysis of PM_2.5 measured at US Embassy and Consulate in five Indian megacities (Chennai, Kolkata, Hyderabad, Mumbai, and New Delhi) for six years (2014-2019). Among all cities, Delhi is found to be the most polluted city followed by Kolkata, Mumbai, Hyderabad, and Chennai. The trend analysis for six years for five megacities suggests a statistically significant decreasing trend ranging from 1.5 to 4.19 μg/m³ (2%-8%) per year. Distinct diurnal, seasonal, and monthly variations are observed in the five cities due to the different site locations and local meteorology. All cities show the highest and lowest concentrations in the winter and monsoon months respectively except for Chennai which observed the lowest levels in April. All the cities consistently show morning peaks (~08: 00-10:00 h) and the lowest level in late afternoon hours (~15:00-16:00 h). We found that the PM_2.5 levels in the cities exceed WHO standards and Indian NAAQS for 50% and 33% of days in a year except for Chennai. Delhi is found to have more than 200 days of exceedances in a year and experiences an average 15 number of episodes per year when the level exceeds the Indian NAAQS. The trends in the exceedance with a varying threshold (20-380 μg/m³) suggest that not only is the annual mean PM_2.5 decreasing in Delhi but also the number of exceedances is decreasing. This decrease can be attributed to the recent policies and regulations implemented in Delhi and other cities for the abatement of air pollution. However, stricter compliance of the National Clean Air Program (NCAP) policies can further accelerate the reduction of the pollution levels.

Individual- and Household-Level Interventions to Reduce Air Pollution Exposures and Health Risks: a Review of the Recent Literature

PURPOSE OF REVIEW

We reviewed recent peer-reviewed literature on three categories of individual- and household-level interventions against air pollution: air purifiers, facemasks, and behavior change.

RECENT FINDINGS

High-efficiency particulate air/arresting (HEPA) filter air purifier use over days to weeks can substantially reduce fine particulate matter (PM2.5) concentrations indoors and improve subclinical cardiopulmonary health. Modeling studies suggest that the population-level benefits of HEPA filter air purification would often exceed costs. Well-fitting N95 and equivalent respirators can reduce PM2.5 exposure, with several randomized crossover studies also reporting improvements in subclinical cardiovascular health. The health benefits of other types of face coverings have not been tested and their effectiveness in reducing exposure is highly variable, depends largely on fit, and is unrelated to cost. Behavior modifications may reduce exposure, but there has been little research on health impacts. There is now substantial evidence that HEPA filter air purifiers reduce indoor PM2.5 concentrations and improve subclinical health indicators. As a result, their use is being recommended by a growing number of government and public health organizations. Several studies have also reported subclinical cardiovascular health benefits from well-fitting respirators, while evidence of health benefits from other types of facemasks and behavior changes remains very limited. In situations when emissions cannot be controlled at the source, such as during forest fires, individual- or household-level interventions may be the primary option. In most cases, however, such interventions should be supplemental to emission reduction efforts that benefit entire communities.

Estimating the potential impact of behavioral public health interventions nationally while maintaining agreement with global patterns on relative risks

Objective

This paper introduces a novel method to evaluate the local impact of behavioral scenarios on disease prevalence and burden with representative individual level data while ensuring that the model is in agreement with the qualitative patterns of global relative risk (RR) estimates. The method is used to estimate the impact of behavioral scenarios on the burden of disease due to ischemic heart disease (IHD) and diabetes in the Turkish adult population.

Methods

Disease specific Hierarchical Bayes (HB) models estimate the individual disease probability as a function of behaviors, demographics, socio-economics and other controls, where constraints are specified based on the global RR estimates. The simulator combines the counterfactual disease probability estimates with disability adjusted life year (DALY)-per-prevalent-case estimates and rolls up to the targeted population level, thus reflecting the local joint distribution of exposures. The Global Burden of Disease (GBD) 2016 study meta-analysis results guide the analysis of the Turkish National Health Surveys (2008 to 2016) that contain more than 90 thousand observations.

Findings

The proposed Qualitative Informative HB models do not sacrifice predictive accuracy versus benchmarks (logistic regression and HB models with non-informative and numerical informative priors) while agreeing with the global patterns. In the Turkish adult population, Increasing Physical Activity reduces the DALYs substantially for both IHD by 8.6% (6.4% 11.2%), and Diabetes by 8.1% (5.8% 10.6%), (90% uncertainty intervals). Eliminating Smoking and Second-hand Smoke predominantly decreases the IHD burden 13.1% (10.4% 15.8%) versus Diabetes 2.8% (1.1% 4.6%). Increasing Fruit and Vegetable Consumption, on the other hand, reduces IHD DALYs by 4.1% (2.8% 5.4%) while not improving the Diabetes burden 0.1% (0% 0.1%).

Conclusion

While the national RR estimates are in qualitative agreement with the global patterns, the scenario impact estimates are markedly different than the attributable risk estimates from the GBD analysis and allow evaluation of practical scenarios with multiple behaviors.

Coal smoke, gestational cadmium exposure, and fetal growth

BACKGROUND

Gestational cadmium exposure may impair fetal growth. Coal smoke has largely been unexplored as a source of cadmium exposure. We investigated the relationship between gestational cadmium exposure and fetal growth, and assessed coal smoke as a potential source of airborne cadmium, among non-smoking pregnant women in Ulaanbaatar, Mongolia, where coal combustion in home heating stoves is a major source of outdoor and indoor air pollution.

METHODS

This observational study was nested within the Ulaanbaatar Gestation and Air Pollution Research (UGAAR) study, a randomized controlled trial of portable high efficiency particulate air (HEPA) filter air cleaner use during pregnancy, fetal growth, and early childhood development. We measured third trimester blood cadmium concentrations in 374 out of 465 participants who had a live birth. We used multiple linear and logistic regression to assess the relationships between log₂-transformed maternal blood cadmium concentrations and birth weight, length, head circumference, ponderal index, low birth weight, small for gestational age, and preterm birth in crude and adjusted models. We also evaluated the relationships between log₂-transformed blood cadmium concentrations and the density of coal-burning stoves within 5000 m of each participant's apartment as a proxy of coal smoke emissions from home heating stoves.

RESULTS

The median (25th,75th percentile) blood cadmium concentration was 0.20 (0.15, 0.29) μg/L. A doubling of blood cadmium was associated with a 95 g (95% CI: 34, 155 g) reduction in birth weight in adjusted models. An interquartile range increase in coal stove density (from 3.4 to 4.9 gers/hectare) surrounding participants' apartments was associated with a 12.2% (95% CI: 0.3, 25.6%) increase in blood cadmium concentrations.

CONCLUSIONS

Gestational cadmium exposure was associated with reduced birth weight. In settings where coal is a widely used fuel, cadmium may play a role in the putative association between air pollution and impaired fetal growth.

A Review of the Potential Benefits of Increasing Vitamin D Status in Mongolian Adults through Food Fortification and Vitamin D Supplementation

Serum 25-hydroxyvitamin D (25(OH)D) concentrations are low in Mongolia, averaging 22 ng/mL in summer and only 8 ng/mL in winter. Mongolians have high incidence and/or prevalence of several diseases linked to low 25(OH)D concentrations, including ischemic heart disease, malignant neoplasms, cirrhosis of the liver, ischemic stroke, lower respiratory tract infections, preterm birth complications, and diabetes mellitus. Fortifying regularly consumed foods such as flour, milk, and edible oils with vitamin D₃ could raise 25(OH)D concentrations by about 10 ng/mL. However, to achieve 25(OH)D concentrations of 30–40 ng/mL in adults, vitamin D intakes of 1000 to 4000 IU/day would be required, making personal supplement use necessary. On the basis of prospective observational studies and clinical trials of disease incidence or known mortality rates and adverse pregnancy and birth outcomes, raising mean serum 25(OH)D concentrations to 40 ng/mL would likely reduce incidence and mortality rates for those and other diseases, reduce the rate of adverse pregnancy and birth outcomes, and increase mean life expectancy by one year or more.

Advanced household heat pumps for air pollution control: A pilot field study in Ulaanbaatar, the coldest capital city in the world

Ulaanbaatar - the coldest capital in the world - is home to half of Mongolia's population, much of which uses coal for household heating, contributing to high wintertime air pollution. We piloted two-stage air-to-air heat pumps in 2017, when temperatures dropped to -39 °C. These heat pumps were reliable and efficient, with an average coefficient of performance of 1.86 on the coldest days. Heat pumps' recurrent costs were similar to those of coal stoves and lower than those of resistive heaters.

Machine-learned modeling of PM2.5 exposures in rural Lao PDR

This study presents a machine-learning-enhanced method of modeling PM_2.5 personal exposures in a data-scarce, rural, solid fuel use context. Data collected during a cookstove (Africa Clean Energy (ACE)-1 solar-battery-powered stove) intervention program in rural Lao PDR are presented and leveraged to explore advanced techniques for predicting personal exposures to particulate matter with aerodynamic diameter smaller than 2.5 μm (PM_2.5). Mean 48-h PM_2.5 exposure concentrations for female cooks were measured for the pre- and post-intervention periods (the "Before" and "After" periods, respectively) as 123 μg/m³ and 81 μg/m³. Mean 48-h PM_2.5 kitchen air pollution ("KAP") concentrations were measured at 462 μg/m³ Before and 124 μg/m³ After. Application of machine learning and ensemble modeling demonstrated cross-validated personal exposure predictions that were modest at the individual level but reasonably strong at the group level, with the best models producing an observed vs. predicted r² between 0.26 and 0.31 (r² = 0.49 when using a smaller, un-imputed dataset) and mean Before estimates of 119-120 μg/m³ and After estimates of 86-88 μg/m³. This offered improvement over one typical method of predicting exposure - using a kitchen exposure factor (the ratio of exposure to KAP)- which demonstrated an r² ~ 0.03 and poorly estimated group average values. The results of these analyses highlight areas of methodological improvement for future exposure assessments of household air pollution and provide evidence for researchers to explore the advantages of further incorporating machine learning methods into similar research across wider geographic and cultural contexts.

Systematic Literature Review of Health Impact Assessments in Low and Middle-Income Countries

Health Impact Assessments (HIAs) motivate effective measures for safeguarding public health. There is consensus that HIAs in low and middle-income countries (LMICs) are lacking, but no study systematically focuses on those that have been successfully conducted across all regions of the world, nor do they highlight factors that may enable or hinder their implementation. Our objectives are to (1) systematically review, geographically map, and characterize HIA activity in LMICs; and (2) apply a process evaluation method to identify factors which are important to improve HIA implementation in LMICs. A systematic review of peer-reviewed HIAs in 156 LMICs was performed in Scopus, Medline, Web of Science, Sociological abstracts, and LILACs (Latin American and Caribbean Health Sciences) databases. The search used PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) guidelines and covered HIAs across all type of interventions, topics, and health outcomes. HIAs were included if they reported a clear intervention and health outcome to be assessed. No time restriction was applied, and grey literature was not included. The eligible studies were subjected to six process evaluation criteria. The search yielded 3178 hits and 57 studies were retained. HIAs were conducted in 26 out of 156 countries. There was an unequal distribution of HIAs across regions and within LMICs countries. The leading topics of HIA in LMICs were air pollution, development projects, and urban transport planning. Most of the HIAs reported quantitative approaches (72%), focused on air pollution (46%), appraised policies (60%), and were conducted at the city level (36%). The process evaluation showed important variations in the way HIAs have been conducted and low uniformity in the reporting of six criteria. No study reported the time, money, and staff used to perform HIAs. Only 12% of HIAs were based on participatory approaches; 92% of HIAs considered multiple outcomes; and 61% of HIAs provided recommendations and fostered cross-national collaboration. The limited transparency in process, weak participation, and inconsistent delivery of recommendations were potential limitations to HIA implementation in low and middle-income countries. Scaling and improving HIA implementation in low and middle-income countries in the upcoming years will depend on expanding geographically by increasing HIA governance, adapting models and tools in quantitative methods, and adopting better reporting practices.

Evaluation of random forest regression and multiple linear regression for predicting indoor fine particulate matter concentrations in a highly polluted city

BACKGROUND

Indoor and outdoor fine particulate matter (PM_2.5) are both leading risk factors for death and disease, but making indoor measurements is often infeasible for large study populations.

METHODS

We developed models to predict indoor PM_2.5 concentrations for pregnant women who were part of a randomized controlled trial of portable air cleaners in Ulaanbaatar, Mongolia. We used multiple linear regression (MLR) and random forest regression (RFR) to model indoor PM_2.5 concentrations with 447 independent 7-day PM_2.5 measurements and 87 potential predictor variables obtained from outdoor monitoring data, questionnaires, home assessments, and geographic data sets. We also developed blended models that combined the MLR and RFR approaches. All models were evaluated in a 10-fold cross-validation.

RESULTS

The predictors in the MLR model were season, outdoor PM_2.5 concentration, the number of air cleaners deployed, and the density of gers (traditional felt-lined yurts) surrounding the apartments. MLR and RFR had similar performance in cross-validation (R² = 50.2%, R² = 48.9% respectively). The blended MLR model that included RFR predictions had the best performance (cross validation R² = 81.5%). Intervention status alone explained only 6.0% of the variation in indoor PM_2.5 concentrations.

CONCLUSIONS

We predicted a moderate amount of variation in indoor PM_2.5 concentrations using easily obtained predictor variables and the models explained substantially more variation than intervention status alone. While RFR shows promise for modelling indoor concentrations, our results highlight the importance of out-of-sample validation when evaluating model performance. We also demonstrate the improved performance of blended MLR/RFR models in predicting indoor air pollution.

Characteristics of Indoor PM2.5 Concentration in Gers Using Coal Stoves in Ulaanbaatar, Mongolia

Coal combustion in ger areas is the main source of ambient air pollution in Ulaanbaatar (Mongolia). This study determined the characteristics of indoor PM_2.5 concentrations in gers using coal stoves during winter. The study population consisted of 60 gers in the Chingeltei district of Ulaanbaatar. The indoor particle number concentration (PNC) in each ger was measured using a Dylos DC1700 particle counter for 24 h in January and February 2016. The PNC by Dylos was converted into the mass concentration using a calibration equation developed using a collocated real-time light scattering monitor adjusted by gravimetric measurement. The average 24 h PM_2.5 concentration was 203.9 ± 195.1 μg/m³ in gers with traditional stoves (n = 29) and 257.5 ± 204.4 μg/m³ in those with improved stoves (n = 31). In the daily profile, concentrations were lower at night, increased in the early morning, and peaked up to noon. The temperature in gers was slightly higher than that recommended in winter. Many development-assistance programs have supported the installation of improved energy-efficient stoves. Better control measures are needed to improve the indoor air quality of gers.

Population-weighted exposure to PM2.5 pollution in China: An integrated approach

Fine particulate matter air pollution (PM_2.5) is a major risk factor for premature death globally. Studies of the PM_2.5 health burden usually treat exposure to ambient air pollution (AAP) and household air pollution from solid fuels (HAP) as separate risk factors. AAP and HAP can, however, be closely interrelated. Taking as the starting point that the total exposure to PM_2.5 is what matters for health, and recognizing the curvilinear form of exposure-response functions for important health effects, we develop a method for estimating the total annual mean population-weighted personal exposure, denoted integrated population-weighted exposure (IPWE). To establish the IPWE in China, we used recent emission inventories, Chemical Transport Models, China Census data on population and residential fuel use, and estimates of the PM_2.5 exposure among solid fuel users. We found an IPWE of 151 [123-179] μg/m³, of which 62-74% was attributable to residential solid fuels through HAP exposure and the residential sector emissions' contribution to AAP. We found large disparities in the PM_2.5 exposure burden, with an estimated IPWE in rural populations nearly twice the level in urban populations. Using the IPWE metric, we estimated that 1.15 [1.09-1.19] million premature deaths were attributable to PM_2.5 exposure annually in the period 2010-2013. Using the same data set, but calculating premature deaths from AAP and HAP in isolation, the estimated number was nearly 50% higher. The IPWE metric enables integration across AAP and HAP in policy analyses and could mitigate the concern of a potential double counting of the health burden that may arise from treating AAP and HAP as separate health risk factors.