Global estimation of exposure to fine particulate matter (PM2.5) from household air pollution

Assessing personal PM2.5 exposure using a novel neck-mounted monitoring device in rural Rwanda

There is growing global concern regarding the detrimental health impacts of PM2.5 emissions from traditional stoves that utilize polluting fuels. Conventional methods for estimating daily personal PM2.5 exposure involve personal air samplers and measuring devices placed in a waist pouch, but these instruments are cumbersome and inconvenient. To address this issue, we developed a novel neck-mounted PM2.5 monitoring device (Pocket PM2.5 Logger) that is compact, lightweight, and can operate continuously for 1 week without recharging. Twelve participants who utilized charcoal, firewood, or propane gas for cooking in rural regions of Rwanda wore the Pocket PM2.5 Logger continuously for 1 week, and time-series variations in personal PM2.5 exposure were recorded at 5-min intervals. Individual daily exposure concentrations during cooking differed significantly among users of the different fuel types, and PM2.5 exposure was at least 2.6 and 3.4 times higher for charcoal and firewood users, respectively, than for propane gas users. Therefore, switching from biomass fuels to propane gas would reduce daily individual exposure by at least one-third. An analysis of cooking times showed that the median cooking time per meal was 30 min; however, half the participants cooked for 1.5 h per meal, and one-third cooked for over 4.5 h per meal. Reducing these extremely long cooking times would reduce exposure with all fuel types. The Pocket PM2.5 Logger facilitates the comprehensive assessment of personal PM2.5 exposure dynamics and is beneficial for the development of intervention strategies targeting household air pollution.

Global Burden of Lung Cancer Attributable to Household Fine Particulate Matter Pollution in 204 Countries and Territories, 1990 to 2019

INTRODUCTION

Household particulate matter (PM) air pollution is substantially associated with lung cancer. Nevertheless, the global burden of lung cancer attributable to household PM2.5 is still uncertain.

METHODS

In this study, data from the Global Burden and Disease Study 2019 are used to thoroughly assess the burden of lung cancer associated with household PM2.5.

RESULTS

The number of deaths and disability-adjusted life-years (DALYs) attributable to household PM2.5 was found to be 0.08 million and 1.94 million, respectively in 2019. Nevertheless, the burden of lung cancer attributable to household PM2.5 decreased from 1990 to 2019. At the sociodemographic index (SDI) district level, the middle SDI region had the most number of lung cancer deaths and DALYs attributable to household PM2.5. Moreover, the burden of lung cancer was mainly distributed in low-SDI regions, such as Sub-Saharan Africa. Conversely, in high-SDI regions, the age-standardized mortality rate and age-standardized DALY rate of lung cancer attributable to household PM2.5 exhibit the most rapid declines. The burden of lung cancer attributable to household PM2.5 is heavier for men than for women. The sex difference is more obvious in the elderly.

CONCLUSIONS

The prevalence of lung cancer attributable to household PM2.5 has exhibited a declining trend from 1990 to 2019 owing to a concurrent decline in household PM2.5 exposure.

Economic Growth Facilitates Household Fuel Use Transition to Reduce PM2.5-Related Deaths in China

Exposure to ambient and indoor particle matter (PM2.5) leads to millions of premature deaths in China. In recent years, indoor air pollution and premature deaths associated with polluting fuel cooking demonstrate an abrupt decline. However, the driving forces behind the mortality change are still unclear due to the uncertainty in household fuel use prediction. Here, we propose an integrated approach to estimate the fuel use fractions and PM2.5-related deaths from outdoor and indoor sources during 2000-2020 across China. Our model estimated 1.67 and 1.21 million premature deaths attributable to PM2.5 exposure in 2000 and 2020, respectively. We find that the residential energy transition is associated with a substantial reduction in premature deaths from indoor sources, with 100,000 (95% CI: 76,000-122,000) for urban and 265,000 (228,000-300,000) for rural populations during 2000-2020. Economic growth is the dominant driver of fuel use transition and avoids 21% related deaths (357,000, 315,000-402,000) from polluting fuel cooking since 2000, which offsets the adverse impact of ambient emissions contributed by economic growth. Our findings give an insight into the coupled impact of socioeconomic factors in reshaping health burden in exposure pathways.

Urban-rural disparity in global estimation of PM2·5 household air pollution and its attributable health burden

BACKGROUND

Polluting fuels and inefficient stove technologies are still a leading cause of premature deaths worldwide, particularly in low-income and middle-income countries. Previous studies of global household air pollution (HAP) have neither considered the estimation of PM2·5 at national level nor the corresponding attributable mortality burden. Additionally, the effects of climate and ambient air pollution on the global estimation of HAP-PM2·5 exposure for different urban and rural settings remain largely unknown. In this study, we include climatic effects to estimate the HAP-PM2·5 exposure from different fuel types and stove technologies in rural and urban settings separately and the related attributable global mortality burden.

METHODS

Bayesian hierarchical models were developed to estimate an annual average HAP-PM2·5 personal exposure and HAP-PM2·5 indoor concentration (including both outdoor and indoor sources). Model variables were selected from sample data in 282 peer-reviewed studies drawn and updated from the WHO Global HAP dataset. The PM2·5 exposure coefficients from the developed model were applied to the external datasets to predict the HAP-PM2·5 exposure globally (personal exposure in 62 countries and indoor concentration in 69 countries). Attributable mortality rate was estimated using a comparative risk assessment approach. Using weighted averages, the national level 24 h average HAP-PM2·5 exposure due to polluting and clean fuels and related death rate per 100 000 population were estimated.

FINDINGS

In 2020, household use of polluting solid fuels for cooking and heating led to a national-level average personal exposure of 151 μg/m3 (95% CI 133-169), with rural households having an average of 171 μg/m3 (153-189) and urban households an average of 92 μg/m3 (77-106). Use of clean fuels gave rise to a national-level average personal exposure of 69 μg/m3 (62-76), with a rural average of 76 μg/m3 (69-83) and an urban average of 49 μg/m3 (46-53). Personal exposure-attributable premature mortality (per 100 000 population) from the use of polluting solid fuels at national level was on average 78 (95% CI 69-87), with a rural average of 82 (73-90) and an urban average of 66 (57-75). The average attributable premature mortality (per 100 000 population) from the use of clean fuels at the national level is 62 (54-70), with a rural average of 66 (58-74) and an urban average of 52 (47-57). The estimated HAP-PM2·5 indoor concentration shows that the use of polluting solid fuels resulted in a national-level average of 412 μg/m3 (95% CI 353-471), with a rural average of 514 μg/m3 (446-582) and an urban average of 149 μg/m3 (126-173). The use of clean fuels (gas and electricity) led to an average PM2·5 indoor concentration of 135 μg/m3 (117-153), with a rural average of 174 μg/m3 (154-195) and an urban average of 71 μg/m3 (63-80). Using time-weighted HAP-PM2·5 indoor concentrations, the attributable premature death rate (per 100 000 population) from the use of polluting solid fuels at the national level is on average 78 (95% CI 72-84), the rural average being 84 (78-91) and the urban average 60 (54-66). From the use of clean fuels, the average attributable premature death rate (per 100 000 population) at the national level is 59 (53-64), the rural average being 68 (62-74) and the urban average 45 (41-50).

INTERPRETATION

A shift from polluting to clean fuels can reduce the average PM2·5 personal exposure by 53% and thereby lower the death rate. For all fuel types, the estimated average HAP-PM2·5 personal exposure and indoor concentrations exceed the WHO's Interim Target-1 average annual threshold. Policy interventions are urgently needed to greatly increase the use of clean fuels and stove technologies by 2030 to achieve the goal of affordable clean energy access, as set by the UN in 2015, and address health inequities in urban-rural settings.

FUNDING

Wellcome Trust, The Lancet Countdown, the Engineering and Physical Sciences Research Council, and the Natural Environment Research Council.

Source Contributions to Fine Particulate Matter and Attributable Mortality in India and the Surrounding Region

Fine particulate matter (PM_2.5) exposure is a leading mortality risk factor in India and the surrounding region of South Asia. This study evaluates the contribution of emission sectors and fuels to PM_2.5 mass for 29 states in India and 6 surrounding countries (Pakistan, Bangladesh, Nepal, Bhutan, Sri Lanka, and Myanmar) by combining source-specific emission estimates, stretched grid simulations from a chemical transport model, high resolution hybrid PM_2.5, and disease-specific mortality estimates. We find that 1.02 (95% Confidence Interval (CI): 0.78-1.26) million deaths in South Asia attributable to ambient PM_2.5 in 2019 were primarily from three leading sectors: residential combustion (28%), industry (15%), and power generation (12%). Solid biofuel is the leading combustible fuel contributing to the PM_2.5-attributable mortality (31%), followed by coal (17%), and oil and gas (14%). State-level analyses reveal higher residential combustion contributions (35%-39%) in states (Delhi, Uttar-Pradesh, Haryana) with high ambient PM_2.5 (>95 μg/m³). The combined mortality burden associated with residential combustion (ambient) and household air pollution (HAP) in India is 0.72 million (95% CI:0.54-0.89) (68% attributable to HAP, 32% attributable to residential combustion). Our results illustrate the potential to reduce PM_2.5 mass and improve population health by reducing emissions from traditional energy sources across multiple sectors in South Asia.

Kitchen Characteristics and Practices Associated with Increased PM2.5 Concentration Levels in Zimbabwean Rural Households

Household air pollution (HAP) from biomass fuels significantly contributes to cardio-respiratory morbidity and premature mortality globally. Particulate matter (PM), one of the pollutants generated, remains the most accurate indicator of household air pollution. Determining indoor air concentration levels and factors influencing these levels at the household level is of prime importance, as it objectively guides efforts to reduce household air pollution. This paper describes household factors associated with increased PM_2.5 levels in Zimbabwean rural household kitchens. Our HAP and lung health in women study enrolled 790 women in rural and urban households in Zimbabwe between March 2018 and December 2019. Here, we report data from 148 rural households using solid fuel as the primary source of fuel for cooking and heating and where indoor air samples were collected. Data on kitchen characteristics and practices were collected cross-sectionally using an indoor walk-through survey and a modified interviewer-administered questionnaire. An Air metrics miniVol Sampler was utilized to collect PM_2.5 samples from the 148 kitchens over a 24 h period. To identify the kitchen features and practices that would likely influence PM_2.5 concentration levels, we applied a multiple linear regression model. The measured PM_2.5 ranged from 1.35 μg/m³ to 1940 μg/m³ (IQR: 52.1-472). The PM_2.5 concentration levels in traditional kitchens significantly varied from the townhouse type kitchens, with the median for each kitchen being 291.7 μg/m³ (IQR: 97.2-472.2) and 1.35 μg/m³ (IQR: 1.3-97.2), respectively. The use of wood mixed with other forms of biomass was found to have a statistically significant association (p < 0.001) with increased levels of PM_2.5 concentration. In addition, cooking indoors was strongly associated with higher PM_2.5 concentrations (p = 0.012). Presence of smoke deposits on walls and roofs of the kitchens was significantly associated with increased PM_2.5 concentration levels (p = 0.044). The study found that kitchen type, energy type, cooking place, and smoke deposits were significant predictors of increased PM₂.₅ concentrations in the rural households. Concentrations of PM_2.5 were high as compared to WHO recommended exposure limits for PM_2.5. Our findings highlight the importance of addressing kitchen characteristics and practices associated with elevated PM_2.5 concentrations in settings where resources are limited and switching to cleaner fuels may not be an immediate feasible option.

Worldwide Correlations Support COVID-19 Seasonal Behavior and Impact of Global Change

Many viral diseases exhibit seasonal behavior and can be affected by environmental stressors. Using time-series correlation charts extrapolated from worldwide data, we provide strong support for the seasonal development of COVID-19 regardless of the immunity of the population, behavioral changes, and the periodic appearance of new variants with higher rates of infectivity and transmissibility. Statistically significant latitudinal gradients were also observed with indicators of global change. Using the Environmental Protection Index (EPI) and State of Global Air (SoGA) metrics, a bilateral analysis of environmental health and ecosystem vitality effects showed associations with COVID-19 transmission. Air quality, pollution emissions, and other indicators showed strong correlations with COVID-19 incidence and mortality. Remarkably, EPI category and performance indicators also correlated with latitude, suggesting cultural and psychological diversity in human populations not only impact wealth and happiness but also planetary health at latitudinal level. Looking forward, we conclude there will be a need to disentangle the seasonal and global change effects of COVID-19 noting that countries that go against the health of the planet affect health in general.

Baseline associations between household air pollution exposure and blood pressure among pregnant women in the Household Air Pollution Intervention Network (HAPIN) multi-country randomized controlled trial

Cooking and heating using solid fuels can result in dangerous levels of exposure to household air pollution (HAP). HAPIN is an ongoing randomized controlled trial assessing the impact of a liquified petroleum gas stove and fuel intervention on HAP exposure and health in Guatemala, India, Peru, and Rwanda among households that rely primarily on solid cooking fuels. Given the potential impacts of HAP exposure on cardiovascular outcomes during pregnancy, we seek to characterize the relationship between personal exposures to HAP and blood pressure among pregnant women at baseline (prior to intervention) in the study. We assessed associations between PM2.5 (particulate matter with an aerodynamic diameter ≤2.5 μm), BC (black carbon), and CO (carbon monoxide) exposures and blood pressure at baseline, prior to intervention, among 3195 pregnant women between 9 and 19 weeks of gestation. We measured 24-hour personal exposure to PM2.5/BC/CO and gestational blood pressure. Multivariable linear regression models were used to evaluate associations between personal exposures to three air pollutants and blood pressure parameters. Trial-wide, we found moderate increases in systolic blood pressure (SBP) and decreases in diastolic blood pressure (DBP) as exposure to PM2.5, BC, and CO increased. None of these associations, however, were significant at the 0.05 level. HAP exposure and blood pressure associations were inconsistent in direction and magnitude within each country. We observed effect modification by body mass index (BMI) in India and Peru. Compared to women with normal weights, obese women in India and Peru (but not in Rwanda or Guatemala) had higher SBP per unit increase in log transformed PM2.5 and BC exposures. We did not find a cross-sectional association between HAP exposure and blood pressure in pregnant women; however, HAP may be associated with higher blood pressure in pregnant women who are obese, but this increase was not consistent across settings.

Association of household air pollution with glucose homeostasis markers in Chinese rural women: Effect modification of socioeconomic status

BACKGROUND

Socioeconomic status (SES) was a crucial influencing factor of household air pollution (HAP). However, few studies have explored the potential effect modification of SES on the associations of HAP with type 2 diabetes mellitus (T2DM) and glucose homeostasis.

METHODS

A total of 20900 participants were obtained from the Henan Rural Cohort. HAP reflected by cooking fuel type and cooking duration was assessed via questionnaire. SES was evaluated by two dimensions: educational level and average monthly income. Associations of cooking fuel type, cooking duration with T2DM and glucose homeostasis indices (insulin, fasting plasma glucose (FPG), and HOMA-β) were assessed by the generalized linear model. Analyses were also conducted in different SES groups to explore the potential effect modification.

RESULTS

Significant negative association of cooking fuel type and cooking duration with T2DM, FPG, and HOMA-β was not observed. However, cooking with solid fuel and long-duration cooking were associated with decreased insulin level in women, and the adjusted coefficients were - 0.35 (95% confidence interval (95% CI): - 0.53, - 0.17) and - 0.36 (95% CI: -0.50, -0.21), respectively. Results from stratified analyses showed that these associations were more prominent in women with low average monthly income, with corresponding coefficient of - 0.57 (95% CI: -0.77, -0.37) for cooking with solid fuel and - 0.34 (95% CI: -0.52, -0.16) for long-duration cooking. Among women with low average monthly income, the largest decreased insulin level was observed in those who cooked with solid fuel, long-duration and poor kitchen ventilation, while the negative association of cooking fuel type and cooking duration with insulin level was slightly alleviated in the good kitchen ventilation group.

CONCLUSIONS

Low average monthly income aggravated the negative association of HAP and insulin level among rural women, while improving kitchen ventilation may be a practical intervention.

TRAIL REGISTRATION

The Henan Rural Cohort Study has been registered at Chinese Clinical Trial Register (Registration number: ChiCTR-OOC-15006699). Date of registration: 06 July, 2015. http://www.chictr.org.cn/showproj.aspx?proj=11375.

Effects of Daily Peat Smoke Exposure on Present and Next Generations

This study aimed to follow the neurotoxic effect of peat smoke on adult outbred rats and its influence on central nervous system (CNS) parameters in first-generation offspring. Under experimental conditions, exposure to peat smoke was carried out on adult male Wistar rats for 24 h. After the end of the exposure, an open field test (OFT), electroencephalography (EEG), and histological analysis of the testes and brains of smoke-exposed males were performed, after which they were mated with intact females to obtain F1 offspring. Stillbirth, neonatal mortality, and body weight at 4, 7, 14, and 21 postnatal days, as well as behavior in the OFT and EEG parameters during puberty (3 months), were assessed. The results of the examination of F0 males showed a significant increase in motor activity and anxiety in the open field test and a violation of EEG parameters. Histopathologically, peat smoke caused a sharp increase in shadow cells (homogeneous cells with pale-stained cytoplasm, in which the cell and nuclear membranes are not visualized) and degeneratively altered neurons in the brain; we found no changes in the testicles. Peat smoke exposure during preconception did not affect neonatal mortality and weight gain in F1 offspring. Adult females born to peat-smoke-exposed males showed an increase in locomotor activity, and the behavior of adult F1 males did not differ from the control. In F1 males, a statistically significant increase in slow-wave activity indices in the delta band was observed.

The Effect of Kitchen Ventilation Modification on Independent and Combined Associations of Cooking Fuel Type and Cooking Duration with Suicidal Ideation: A Cross-Sectional Study

Although household air pollution (HAP) is associated with an increased risk of mental disorders, evidence remains scarce for the relationship between HAP and suicidal ideation. A total of 21,381 qualified participants were enrolled on the Henan Rural Cohort Study. HAP information including cooking fuel type, cooking duration and kitchen ventilation was collected by questionnaires. Suicidal ideation was evaluated by item nine of the Patient Health Questionnaire-9 (PHQ-9). Independent and combined associations of cooking fuel type and cooking duration with suicidal ideation were explored by logistic regression models. Analyses were conducted in different kitchen ventilation groups to detect the potential effect modification. The adjusted odds ratio (OR) and 95% confidence interval (95% CI) of solid fuel users versus clean fuel users for suicidal ideation was 1.37 (1.16, 1.62), and the risk of suicidal ideation increased by 15% (95% CI: 5%, 26%) for each additional hour of the cooking duration. Participants cooking with solid fuel for long durations were related to the highest risk of suicidal ideation (OR (95% CI): 1.51 (1.22, 1.87)). However, all these associations were not observed in those cooking with mechanical ventilation. Mechanical ventilation ameliorated relationships between solid fuel use and long-duration cooking with suicidal ideation.

Deaths Attributable to Indoor PM2.5 in Urban China When Outdoor Air Meets 2021 WHO Air Quality Guidelines

The World Health Organization reduced the recommended level of annual mean PM_2.5 concentrations to 5 μg/m³ in 2021. Previously, the guideline was geared toward ambient air pollution, and now it explicitly applies to indoor air pollution. However, the disease burden attributed to different indoor emission sources has been overlooked, particularly in urban areas. Our objective was to estimate the mortality attributable to indoor PM_2.5 in urban areas in China. Our model estimated 711 thousand (584-823) deaths and 2.75 trillion (2.26-3.19) CNY economic losses attributable to PM_2.5 in urban China in 2019, in which indoor sources contributed 394 thousand (323-457) deaths and 1.53 trillion (1.25-1.77) CNY losses. There would still be 536 thousand (427-638) PM_2.5-attributable deaths and 2.07 trillion (1.65-2.47) CNY losses each year when the outdoor PM_2.5 is 5 μg/m³, of which 485 thousand (386-578) deaths and 1.87 trillion (1.49-2.23) CNY are attributable to indoor sources. Despite cleaner outdoor air and no solid fuels being used, considerable health hazards and economic losses are attributable to indoor PM_2.5. Measures to reduce PM_2.5 exposure in humans from both indoor and outdoor sources are required to achieve a substantial reduction in deaths.

Characterization of fine particulate matter from indoor cooking with solid biomass fuels

Household burning of solid biomass fuels emits pollution particles that are a huge health risk factor, especially in low-income countries (LICs) such as those in Sub-Saharan Africa. In epidemiological studies, indoor exposure is often more challenging to assess than outdoor exposure. Laboratory studies of solid biomass fuels, performed under real-life conditions, are an important path toward improved exposure assessments. Using on- and offline measurement techniques, particulate matter (PM) from the most commonly used solid biomass fuels (charcoal, wood, dung, and crops residue) was characterized in laboratory settings using a way of burning the fuels and an air exchange rate that is representative of real-world settings in low-income countries. All the fuels generated emissions that resulted in concentrations which by far exceed both the annual and the 24-hour-average WHO guidelines for healthy air. Fuels with lower energy density, such as dung, emitted orders of magnitude more than, for example, charcoal. The vast majority of the emitted particles were smaller than 300 nm, indicating high deposition in the alveoli tract. The chemical composition of the indoor pollution changes over time, with organic particle emissions often peaking early in the stove operation. The chemical composition of the emitted PM is different for different biomass fuels, which is important to consider both in toxicological studies and in source apportionment efforts. For example, dung and wood yield higher organic aerosol emissions, and for dung, nitrogen content in the organic PM fraction is higher than for the other fuels. We show that aerosol mass spectrometry can be used to differentiate stove-related emissions from fuel, accelerant, and incense. We argue that further emission studies, targeting, for example, vehicles relevant for LICs and trash burning, coupled with field observations of chemical composition, would advance our understanding of air pollution in LIC. We believe this to be a necessary step for improved air quality policy.

Mapping development and health effects of cooking with solid fuels in low-income and middle-income countries, 2000-18: a geospatial modelling study

BACKGROUND

More than 3 billion people do not have access to clean energy and primarily use solid fuels to cook. Use of solid fuels generates household air pollution, which was associated with more than 2 million deaths in 2019. Although local patterns in cooking vary systematically, subnational trends in use of solid fuels have yet to be comprehensively analysed. We estimated the prevalence of solid-fuel use with high spatial resolution to explore subnational inequalities, assess local progress, and assess the effects on health in low-income and middle-income countries (LMICs) without universal access to clean fuels.

METHODS

We did a geospatial modelling study to map the prevalence of solid-fuel use for cooking at a 5 km × 5 km resolution in 98 LMICs based on 2·1 million household observations of the primary cooking fuel used from 663 population-based household surveys over the years 2000 to 2018. We use observed temporal patterns to forecast household air pollution in 2030 and to assess the probability of attaining the Sustainable Development Goal (SDG) target indicator for clean cooking. We aligned our estimates of household air pollution to geospatial estimates of ambient air pollution to establish the risk transition occurring in LMICs. Finally, we quantified the effect of residual primary solid-fuel use for cooking on child health by doing a counterfactual risk assessment to estimate the proportion of deaths from lower respiratory tract infections in children younger than 5 years that could be associated with household air pollution.

FINDINGS

Although primary reliance on solid-fuel use for cooking has declined globally, it remains widespread. 593 million people live in districts where the prevalence of solid-fuel use for cooking exceeds 95%. 66% of people in LMICs live in districts that are not on track to meet the SDG target for universal access to clean energy by 2030. Household air pollution continues to be a major contributor to particulate exposure in LMICs, and rising ambient air pollution is undermining potential gains from reductions in the prevalence of solid-fuel use for cooking in many countries. We estimated that, in 2018, 205 000 (95% uncertainty interval 147 000-257 000) children younger than 5 years died from lower respiratory tract infections that could be attributed to household air pollution.

INTERPRETATION

Efforts to accelerate the adoption of clean cooking fuels need to be substantially increased and recalibrated to account for subnational inequalities, because there are substantial opportunities to improve air quality and avert child mortality associated with household air pollution.

FUNDING

Bill & Melinda Gates Foundation.

Estimating the burden of disease attributable to household air pollution from cooking with solid fuels in South Africa for 2000, 2006 and 2012

Background. Household air pollution (HAP) due to the use of solid fuels for cooking is a global problem with significant impacts on human health, especially in low- and middle-income countries. HAP remains problematic in South Africa (SA). While electrification rates have improved over the past two decades, many people still use solid fuels for cooking owing to energy poverty.Objectives. To estimate the disease burden attributable to HAP for cooking in SA over three time points: 2000, 2006 and 2012. Methods. Comparative risk assessment methodology was used. The proportion of South Africans exposed to HAP was assessed and assigned the estimated concentration of particulate matter with a diameter <2.5 μg/m3(PM2.5) associated with HAP exposure. Health outcomes and relative risks associated with HAP exposure were identified. Population-attributable fractions and the attributable burden of disease due to HAP exposure (deaths, years of life lost, years lived with disability and disability-adjusted life years (DALYs)) for SA were calculated. Attributable burden was estimated for 2000, 2006 and 2012. For the year 2012, we estimated the attributable burden at provincial level.Results. An estimated 17.6% of the SA population was exposed to HAP in 2012. In 2012, HAP exposure was estimated to have caused 8 862 deaths (95% uncertainty interval (UI) 8 413 - 9 251) and 1.7% (95% UI 1.6% - 1.8%) of all deaths in SA, respectively. Loss of healthy life years comprised 208 816 DALYs (95% UI 195 648 - 221 007) and 1.0% of all DALYs (95% UI 0.95% - 1.0%) in 2012, respectively. Lower respiratory infections and cardiovascular disease contributed to the largest proportion of deaths and DALYs. HAP exposure due to cooking varied across provinces, and was highest in Limpopo (50.0%), Mpumalanga (27.4%) and KwaZulu-Natal (26.4%) provinces in 2012. Age standardised burden measures showed that these three provinces had the highest rates of death and DALY burden attributable to HAP.Conclusion. The burden of disease from HAP due to cooking in SA is of significant concern. Effective interventions supported by legislation and policy, together with awareness campaigns, are needed to ensure access to clean household fuels and improved cook stoves. Continued and enhanced efforts in this regard are required to ensure the burden of disease from HAP is curbed in SA.

Personal and household PM2.5 and black carbon exposure measures and respiratory symptoms in 8 low- and middle-income countries

BACKGROUND

Household air pollution (HAP) from cooking with solid fuels has been associated with adverse respiratory effects, but most studies use surveys of fuel use to define HAP exposure, rather than on actual air pollution exposure measurements.

OBJECTIVE

To examine associations between household and personal fine particulate matter (PM_2.5) and black carbon (BC) measures and respiratory symptoms.

METHODS

As part of the Prospective Urban and Rural Epidemiology Air Pollution study, we analyzed 48-h household and personal PM_2.5 and BC measurements for 870 individuals using different cooking fuels from 62 communities in 8 countries (Bangladesh, Chile, China, Colombia, India, Pakistan, Tanzania, and Zimbabwe). Self-reported respiratory symptoms were collected after monitoring. Associations between PM_2.5 and BC exposures and respiratory symptoms were examined using logistic regression models, controlling for individual, household, and community covariates.

RESULTS

The median (interquartile range) of household and personal PM_2.5 was 73.5 (119.1) and 65.3 (91.5) μg/m³, and for household and personal BC was 3.4 (8.3) and 2.5 (4.9) x10^-5 m^-1, respectively. We observed associations between household PM_2.5 and wheeze (OR: 1.25; 95%CI: 1.07, 1.46), cough (OR: 1.22; 95%CI: 1.06, 1.39), and sputum (OR: 1.26; 95%CI: 1.10, 1.44), as well as exposure to household BC and wheeze (OR: 1.20; 95%CI: 1.03, 1.39) and sputum (OR: 1.20; 95%CI: 1.05, 1.36), per IQR increase. We observed associations between personal PM_2.5 and wheeze (OR: 1.23; 95%CI: 1.00, 1.50) and sputum (OR: 1.19; 95%CI: 1.00, 1.41). For household PM_2.5 and BC, associations were generally stronger for females compared to males. Models using an indicator variable of solid versus clean fuels resulted in larger OR estimates with less precision.

CONCLUSIONS

We used measurements of household and personal air pollution for individuals using different cooking fuels and documented strong associations with respiratory symptoms.

Association between the Use of Biomass as Fuel for Cooking and Acute Respiratory Infections in Children under 5 Years of Age in Peru: An Analysis of a Population-Based Survey, 2019

Background

Acute respiratory infections (ARIs) are the most frequent respiratory diseases associated with the use of biomass as fuel within the home. ARIs are the main cause of mortality in children under 5 years of age. We aimed to evaluate the association between the use of biomass as cooking fuel and ARI in children under 5 years of age in Peru in 2019.

Methods

A secondary data analysis of the 2019 Peru Demographic and Family Health Survey (ENDES) has been performed. The outcome variable was a history of ARI. The exposure variable was the use of biomass as fuel for cooking food. To evaluate the association of interest, generalized linear models from the Poisson family with logarithmic link function considering complex sampling to estimate crude prevalence ratio (cPR) and adjusted prevalence ratio (aPR) with their respective 95% confidence intervals have been performed. P values <0.05 were considered statistically significant.

Results

A total of 16,043 children were included in the analysis. Of the total, biomass was used as fuel to cook food in the homes of 3,479 (20.0%) children. Likewise, 2,185 (14.3%) of the children had a history of ARI. In the adjusted model, it was found that children living in homes in which biomass was used as cooking fuel had a greater probability of presenting ARI (aPR = 1.13; 95% CI: 1.01–1.28).

Conclusions

It has been found that biomass was used to cook food in two of every 10 households. Likewise, almost one-seventh of children under 5 years old presented an ARI. The use of biomass as a source of energy for cooking in the home was associated with a higher probability of presenting ARIs.

Global burden of chronic obstructive pulmonary disease attributable to ambient particulate matter pollution and household air pollution from solid fuels from 1990 to 2019

We aimed to estimate the spatiotemporal trends in the global burden of chronic obstructive pulmonary disease (COPD) attributable to both household air pollution from solid fuels (HAP) and ambient particulate matter (APM) from 1990 to 2019 and compared the possible differences between the burdens attributable to APM and HAP. The number of deaths, disability-adjusted life-years (DALYs), and years of life lost (YLLs) of COPD attributable to HAP from solid fuels and APM during 1990-2019 were extracted from the Global Burden of Diseases Study 2019. The proportion of YLLs in DALYs and average YLLs per COPD death were also calculated. Subgroup analyses by sex, age, and socio-demographic index (SDI) were conducted. The estimated annual percentage change (EAPC) was used to assess the temporal trend of age-standardized rate of mortality (ASMR) and DALYs (ASDR). Over the past 30 years, we observed a clear downward trend in COPD deaths attributable to HAP and an upward trend by 97.61% in COPD deaths attributable to APM. The global COPD burden attributable to APM in 2019 was higher than those due to HAP, except in low-SDI regions. For both HAP and APM, YLLs continued to predominate in DALYs of COPD, with an average YLLs per death of more than 10 years in different regions. The ASMR was higher in males and lower in high-SDI regions. The ASMR and ASDR attributable to HAP decreased globally in all age groups during 1990-2019, while those attributable to APM increased among people older than 80 years and in regions with lower SDI. Our study reveals an increasing trend in APM-attributable COPD burden over the past three decades. Comparatively, the global burden due to HAP decreased markedly, but it was still pronounced in low-SDI regions. Continued efforts on PM mitigation are needed for COPD prevention.

Measuring and predicting personal and household Black Carbon levels from 88 communities in eight countries

Black Carbon (BC) is an important component of household air pollution (HAP) in low- and middle- income countries (LMICs), but levels and drivers of exposure are poorly understood. As part of the Prospective Urban and Rural Epidemiological (PURE) study, we analyzed 48-hour BC measurements for 1187 individual and 2242 household samples from 88 communities in 8 LMICs (Bangladesh, Chile, China, Colombia, India, Pakistan, Tanzania, and Zimbabwe). Light absorbance (10^-5 m^-1) of collected PM_2.5 filters, a proxy for BC concentrations, was calculated via an image-based reflectance method. Surveys of household/personal characteristics and behaviors were collected after monitoring. The geometric mean (GM) of personal and household BC measures was 2.4 (3.3) and 3.5 (3.9)·10^-5 m^-1, respectively. The correlation between BC and PM_2.5 was r = 0.76 for personal and r = 0.82 for household measures. A gradient of increasing BC concentrations was observed for cooking fuels: BC increased 53% (95%CI: 30, 79) for coal, 142% (95%CI: 117, 169) for wood, and 190% (95%CI: 149, 238) for other biomass, compared to gas. Each hour of cooking was associated with an increase in household (5%, 95%CI: 3, 7) and personal (5%, 95%CI: 2, 8) BC; having a window in the kitchen was associated with a decrease in household (-38%, 95%CI: -45, -30) and personal (-31%, 95%CI: -44, -15) BC; and cooking on a mud stove, compared to a clean stove, was associated with an increase in household (125%, 95%CI: 96, 160) and personal (117%, 95%CI: 71, 117) BC. Male participants only had slightly lower personal BC (-0.6%, 95%CI: -1, 0.0) compared to females. In multivariate models, we were able to explain 46-60% of household BC variation and 33-54% of personal BC variation. These data and models provide new information on exposure to BC in LMICs, which can be incorporated into future exposure assessments, health research, and policy surrounding HAP and BC.

Indoor solid fuel use and renal function among middle-aged and older adults: A national study in rural China

Solid fuel use is the main source of indoor air pollution, especially in rural areas of developing countries. Nevertheless, the evidence linking indoor solid fuel use and renal function is very limited. Therefore, we investigated the association between indoor solid fuel use and renal function among middle-aged and older adults in rural China. Cystatin C (CysC) concentration of each participant was used to calculate the estimated glomerular filtration rate (eGFR). We used the baseline data to investigate the associations between solid fuel use for cooking and heating and eGFR through a linear-mixed effects model. Then, we applied the generalized linear-mixed effects model with binary distribution to examine the relationship between renal function decline and cooking fuel switching from 2011 to 2015. A total of 4959 participants were included at baseline, and 3536 participants were included in the follow-up analysis. Compared to participants who used clean fuel for both cooking and heating, the eGFR was significantly lower among participants who cooked with solid fuel and heated with clean fuel (β: -2.81; 95% CI: -5.53, -0.09). In the follow-up analysis, the risks of renal function decline for participants using solid fuel for cooking were significantly higher in males (OR: 2.74; 95% CI: 1.68, 4.49), smokers (OR: 5.70; 95% CI: 2.82, 11.55), and drinkers (OR: 7.11; 95% CI: 3.15, 16.02) compared to females, non-smokers, and non-drinkers. Moreover, 45-65 years aged participants (OR: 0.54; 95% CI: 0.33, 0.89) and non-drinkers (OR: 0.61; 95% CI: 0.41, 0.92) who switched from solid to clean cooking fuel had a lower risk of renal function decline. In conclusion, our findings show that household solid fuel use is likely to be an important risk factor for renal function decline in rural China. And switching to cleaner fuel may provide significant public health benefits.

Estimation of Ground PM2.5 Concentrations in Pakistan Using Convolutional Neural Network and Multi-Pollutant Satellite Images

During the last few decades, worsening air quality has been diagnosed in many cities around the world. The accurately prediction of air pollutants, particularly, particulate matter 2.5 (PM2.5) is extremely important for environmental management. A Convolutional Neural Network (CNN) P-CNN model is presented in this paper, which uses seven different pollutant satellite images, such as Aerosol index (AER AI), Methane (CH4), Carbon monoxide (CO), Formaldehyde (HCHO), Nitrogen dioxide (NO2), Ozone (O3) and Sulfur dioxide (SO2), as auxiliary variables to estimate daily average PM2.5 concentrations. This study estimates daily average of PM2.5 concentrations in various cities of Pakistan (Islamabad, Lahore, Peshawar and Karachi) by using satellite images. The dataset contains a total of 2562 images from May-2019 to April-2020. We compare and analyze AlexNet, VGG16, ResNet50 and P-CNN model on every dataset. The accuracy of machine learning models was checked with Mean Absolute Error (MAE), Root Mean Square Error (RMSE) and Mean Absolute Percentage Error (MAPE). The results show that P-CNN is more accurate than other approaches in estimating PM2.5 concentrations from satellite images. This study presents robust model using satellite images, useful for estimating PM2.5 concentrations.

In-kitchen aerosol exposure in twelve cities across the globe

Poor ventilation and polluting cooking fuels in low-income homes cause high exposure, yet relevant global studies are limited. We assessed exposure to in-kitchen particulate matter (PM_2.5 and PM₁₀) employing similar instrumentation in 60 low-income homes across 12 cities: Dhaka (Bangladesh); Chennai (India); Nanjing (China); Medellín (Colombia); São Paulo (Brazil); Cairo (Egypt); Sulaymaniyah (Iraq); Addis Ababa (Ethiopia); Akure (Nigeria); Blantyre (Malawi); Dar-es-Salaam (Tanzania) and Nairobi (Kenya). Exposure profiles of kitchen occupants showed that fuel, kitchen volume, cooking type and ventilation were the most prominent factors affecting in-kitchen exposure. Different cuisines resulted in varying cooking durations and disproportional exposures. Occupants in Dhaka, Nanjing, Dar-es-Salaam and Nairobi spent > 40% of their cooking time frying (the highest particle emitting cooking activity) compared with ∼ 68% of time spent boiling/stewing in Cairo, Sulaymaniyah and Akure. The highest average PM_2.5 (PM₁₀) concentrations were in Dhaka 185 ± 48 (220 ± 58) μg m^-3 owing to small kitchen volume, extensive frying and prolonged cooking compared with the lowest in Medellín 10 ± 3 (14 ± 2) μg m^-3. Dual ventilation (mechanical and natural) in Chennai, Cairo and Sulaymaniyah reduced average in-kitchen PM_2.5 and PM₁₀ by 2.3- and 1.8-times compared with natural ventilation (open doors) in Addis Ababa, Dar-es-Salam and Nairobi. Using charcoal during cooking (Addis Ababa, Blantyre and Nairobi) increased PM_2.5 levels by 1.3- and 3.1-times compared with using natural gas (Nanjing, Medellin and Cairo) and LPG (Chennai, Sao Paulo and Sulaymaniyah), respectively. Smaller-volume kitchens (<15 m³; Dhaka and Nanjing) increased cooking exposure compared with their larger-volume counterparts (Medellin, Cairo and Sulaymaniyah). Potential exposure doses were highest for Asian, followed by African, Middle-eastern and South American homes. We recommend increased cooking exhaust extraction, cleaner fuels, awareness on improved cooking practices and minimising passive occupancy in kitchens to mitigate harmful cooking emissions.

Multinational prediction of household and personal exposure to fine particulate matter (PM2.5) in the PURE cohort study

INTRODUCTION

Use of polluting cooking fuels generates household air pollution (HAP) containing health-damaging levels of fine particulate matter (PM_2.5). Many global epidemiological studies rely on categorical HAP exposure indicators, which are poor surrogates of measured PM_2.5 levels. To quantitatively characterize HAP levels on a large scale, a multinational measurement campaign was leveraged to develop household and personal PM_2.5 exposure models.

METHODS

The Prospective Urban and Rural Epidemiology (PURE)-AIR study included 48-hour monitoring of PM_2.5 kitchen concentrations (n = 2,365) and male and/or female PM_2.5 exposure monitoring (n = 910) in a subset of households in Bangladesh, Chile, China, Colombia, India, Pakistan, Tanzania and Zimbabwe. PURE-AIR measurements were combined with survey data on cooking environment characteristics in hierarchical Bayesian log-linear regression models. Model performance was evaluated using leave-one-out cross validation. Predictive models were applied to survey data from the larger PURE cohort (22,480 households; 33,554 individuals) to quantitatively estimate PM_2.5 exposures.

RESULTS

The final models explained half (R² = 54%) of the variation in kitchen PM_2.5 measurements (root mean square error (RMSE) (log scale):2.22) and personal measurements (R² = 48%; RMSE (log scale):2.08). Primary cooking fuel type, heating fuel type, country and season were highly predictive of PM_2.5 kitchen concentrations. Average national PM_2.5 kitchen concentrations varied nearly 3-fold among households primarily cooking with gas (20 μg/m³ (Chile); 55 μg/m³ (China)) and 12-fold among households primarily cooking with wood (36 μg/m³ (Chile)); 427 μg/m³ (Pakistan)). Average PM_2.5 kitchen concentration, heating fuel type, season and secondhand smoke exposure were significant predictors of personal exposures. Modeled average PM_2.5 female exposures were lower than male exposures in upper-middle/high-income countries (India, China, Colombia, Chile).

CONCLUSION

Using survey data to estimate PM_2.5 exposures on a multinational scale can cost-effectively scale up quantitative HAP measurements for disease burden assessments. The modeled PM_2.5 exposures can be used in future epidemiological studies and inform policies targeting HAP reduction.

Air Quality in Africa: Public Health Implications

This review highlights the importance of air quality in the African urban development process. We address connections between air pollution and (a) rapid urbanization, (b) social problems, (c) health impacts, (d) climate change, (e) policies, and (f) new innovations. We acknowledge that air pollution levels in Africa can be extremely high and a serious health threat. The toxic content of the pollution could relate to region-specific sources such as low standards for vehicles and fuels, cooking with solid fuels, and burning household waste. We implore the pursuit of interdisciplinary research to create new approaches with relevant stakeholders. Moreover, successful air pollution research must regard conflicts, tensions, and synergies inherent to development processes in African municipalities, regions, and countries. This includes global relationships regarding climate change, trade, urban planning, and transportation. Incorporating aspects of local political situations (e.g., democracy) can also enhance greater political accountability and awareness about air pollution.

LPG stove and fuel intervention among pregnant women reduce fine particle air pollution exposures in three countries: Pilot results from the HAPIN trial

The Household Air Pollution Intervention Network trial is a multi-country study on the effects of a liquefied petroleum gas (LPG) stove and fuel distribution intervention on women's and children's health. There is limited data on exposure reductions achieved by switching from solid to clean cooking fuels in rural settings across multiple countries. As formative research in 2017, we recruited pregnant women and characterized the impact of the intervention on personal exposures and kitchen levels of fine particulate matter (PM2.5) in Guatemala, India, and Rwanda. Forty pregnant women were enrolled in each site. We measured cooking area concentrations of and personal exposures to PM2.5 for 24 or 48 h using gravimetric-based PM2.5 samplers at baseline and two follow-ups over two months after delivery of an LPG cookstove and free fuel supply. Mixed models were used to estimate PM2.5 reductions. Median kitchen PM2.5 concentrations were 296 μg/m3 at baseline (interquartile range, IQR: 158-507), 24 μg/m3 at first follow-up (IQR: 18-37), and 23 μg/m3 at second follow-up (IQR: 14-37). Median personal exposures to PM2.5 were 134 μg/m3 at baseline (IQR: 71-224), 35 μg/m3 at first follow-up (IQR: 23-51), and 32 μg/m3 at second follow-up (IQR: 23-47). Overall, the LPG intervention was associated with a 92% (95% confidence interval (CI): 90-94%) reduction in kitchen PM2.5 concentrations and a 74% (95% CI: 70-79%) reduction in personal PM2.5 exposures. Results were similar for each site. CONCLUSIONS: The intervention was associated with substantial reductions in kitchen and personal PM2.5 overall and in all sites. Results suggest LPG interventions in these rural settings may lower exposures to the WHO annual interim target-1 of 35 μg/m3. The range of exposure contrasts falls on steep sections of estimated exposure-response curves for birthweight, blood pressure, and acute lower respiratory infections, implying potentially important health benefits when transitioning from solid fuels to LPG.

Association of heating fuel types with mortality and cardiovascular events among non-smokers in China

Only a few prospective studies have investigated the relationship between solid fuel use and cardiovascular disease (CVD) and mortality, and they have reported inconsistent conclusions. This study aimed to investigate the effect of solid fuel heating on the risk of CVD events and all-cause mortality among non-smokers. Data of this sub-study were obtained from the China Hypertension Survey (CHS), and 13,528 non-smoking participants aged 35 or above without self-reported medical history of CVD were enrolled between October 2012 and December 2015. CVD events and all-cause mortality were followed up in 2018 and 2019. The type of primary heating fuel was categorized as clean fuel (natural gas and electricity) and solid fuel (coal, wood, and straw). Cox regression was applied to evaluate the relationship between solid fuel use and CVD events and all-cause mortality. Of the 13,528 non-smoking participants, the mean age was 55.4 ± 13.1 years. During the median follow-up of 4.93 years, 424 participants developed fatal or nonfatal CVD (stroke, 273; coronary heart disease, 119; and other cardiovascular events, 32) and 288 died from all causes. The cumulative incidence of fatal and nonfatal CVD and all-cause mortality were 6.78 and 4.62 per 1000 person-years, respectively. Solid fuel heating was independently associated with an increased risk of fatal or nonfatal stroke and all-cause mortality compared with the use of clean fuels, the fully adjusted hazard ratios (HRs), and 95% confidence intervals (CI) were 1.44 (1.00-2.08) and 1.55 (1.10-2.17), respectively. The relationship between solid fuel heating and fatal and nonfatal CVD events was non-significant (HR = 1.19; 95% CI: 0.89-1.59). Solid fuel heating is longitudinally associated with a higher risk of stroke and all-cause mortality in non-smoking Chinese. Switching to cleaner energy sources for heating may be important for reducing the risk of CVD and mortality.

Solid cooking fuel use and cognitive decline among older Mexican adults

Studies of air pollution and cognition often rely on measures from outdoor environments. Many individuals in low- and middle-income countries are exposed to indoor air pollution from combustion of solid cooking fuels. Little is known about how solid cooking fuel use affects cognitive decline over time. This study uses data from the 2012, 2015, and 2018 Mexican Health and Aging Study (n = 14 245, age 50+) to assess how use of wood or coal for cooking fuel affects cognition of older adults relative to use of gas. It uses latent change score modeling to determine how using solid cooking fuel affected performance in Verbal Learning, Verbal Recall, Visual Scanning, and Verbal Fluency. Solid cooking fuel was used by 17% of the full sample but was more common in rural areas. Solid fuel users also had lower socioeconomic status. Compared to those using gas, solid fuel users had lower baseline scores and faster decline in Verbal Learning (β = -0.18, p < 0.05), Visual Scanning (β = -1.00, p < 0.001), and Verbal Fluency (β = -0.33, p < 0.001). Indoor air pollution from solid cooking fuels may represent a modifiable risk factor for cognitive decline. Policy should focus on facilitating access to clean cooking fuels.

Modeling approaches and performance for estimating personal exposure to household air pollution: A case study in Kenya

This study assessed the performance of modeling approaches to estimate personal exposure in Kenyan homes where cooking fuel combustion contributes substantially to household air pollution (HAP). We measured emissions (PM_2.5 , black carbon, CO); household air pollution (PM_2.5 , CO); personal exposure (PM_2.5 , CO); stove use; and behavioral, socioeconomic, and household environmental characteristics (eg, ventilation and kitchen volume). We then applied various modeling approaches: a single-zone model; indirect exposure models, which combine person-location and area-level measurements; and predictive statistical models, including standard linear regression and ensemble machine learning approaches based on a set of predictors such as fuel type, room volume, and others. The single-zone model was reasonably well-correlated with measured kitchen concentrations of PM_2.5 (R²  = 0.45) and CO (R²  = 0.45), but lacked precision. The best performing regression model used a combination of survey-based data and physical measurements (R²  = 0.76) and a root mean-squared error of 85 µg/m³ , and the survey-only-based regression model was able to predict PM2.5 exposures with an R² of 0.51. Of the machine learning algorithms evaluated, extreme gradient boosting performed best, with an R² of 0.57 and RMSE of 98 µg/m³ .

Ambient and household PM2.5 pollution and adverse perinatal outcomes: A meta-regression and analysis of attributable global burden for 204 countries and territories

BACKGROUND

Particulate matter <2.5 micrometer (PM2.5) is associated with adverse perinatal outcomes, but the impact on disease burden mediated by this pathway has not previously been included in the Global Burden of Disease (GBD), Mortality, Injuries, and Risk Factors studies. We estimated the global burden of low birth weight (LBW) and preterm birth (PTB) and impacts on reduced birth weight and gestational age (GA), attributable to ambient and household PM2.5 pollution in 2019.

METHODS AND FINDINGS

We searched PubMed, Embase, and Web of Science for peer-reviewed articles in English. Study quality was assessed using 2 tools: (1) Agency for Healthcare Research and Quality checklist; and (2) National Institute of Environmental Health Sciences (NIEHS) risk of bias questions. We conducted a meta-regression (MR) to quantify the risk of PM2.5 on birth weight and GA. The MR, based on a systematic review (SR) of articles published through April 4, 2021, and resulting uncertainty intervals (UIs) accounted for unexplained between-study heterogeneity. Separate nonlinear relationships relating exposure to risk were generated for each outcome and applied in the burden estimation. The MR included 44, 40, and 40 birth weight, LBW, and PTB studies, respectively. Majority of the studies were of retrospective cohort design and primarily from North America, Europe, and Australia. A few recent studies were from China, India, sub-Saharan Africa, and South America. Pooled estimates indicated 22 grams (95% UI: 12, 32) lower birth weight, 11% greater risk of LBW (1.11, 95% UI: 1.07, 1.16), and 12% greater risk of PTB (1.12, 95% UI: 1.06, 1.19), per 10 μg/m3 increment in ambient PM2.5. We estimated a global population-weighted mean lowering of 89 grams (95% UI: 88, 89) of birth weight and 3.4 weeks (95% UI: 3.4, 3.4) of GA in 2019, attributable to total PM2.5. Globally, an estimated 15.6% (95% UI: 15.6, 15.7) of all LBW and 35.7% (95% UI: 35.6, 35.9) of all PTB infants were attributable to total PM2.5, equivalent to 2,761,720 (95% UI: 2,746,713 to 2,776,722) and 5,870,103 (95% UI: 5,848,046 to 5,892,166) infants in 2019, respectively. About one-third of the total PM2.5 burden for LBW and PTB could be attributable to ambient exposure, with household air pollution (HAP) dominating in low-income countries. The findings should be viewed in light of some limitations such as heterogeneity between studies including size, exposure levels, exposure assessment method, and adjustment for confounding. Furthermore, studies did not separate the direct effect of PM2.5 on birth weight from that mediated through GA. As a consequence, the pooled risk estimates in the MR and likewise the global burden may have been underestimated.

CONCLUSIONS

Ambient and household PM2.5 were associated with reduced birth weight and GA, which are, in turn, associated with neonatal and infant mortality, particularly in low- and middle-income countries.

Global PM2.5-attributable health burden from 1990 to 2017: Estimates from the Global Burden of disease study 2017

BACKGROUND

Long-term exposure to ambient and household particulate matter (PM2.5) causes death and health loss, and both are the leading risk factor to global disease burden. We assessed spatiotemporal trends of ambient and household PM2.5 attributable burdens across various diseases at the global, regional, and national levels from 1990 to 2017.

METHODS

Data on PM2.5-attributable disease burdens were extracted from the Global Burden of Disease (GBD) study 2017. Numbers and age-standardized rates (ASRs) of deaths, disability-adjusted life years (DALYs) and corresponding estimated annual percentage change (EAPC) were estimated by disease, age, sex, Socio-demographic Index (SDI), locations.

RESULTS

Exposure to PM2.5 contributed to 4.58 million deaths and 142.52 million DALYs globally in 2017, among which ambient PM2.5 contributed to 64.2% deaths and 58.3% DALYs. ASRs of deaths and DALYs in 2017 decreased to 59.62/10⁵ persons with an EAPC of -2.15 (95% CI: 2.21 to -2.09) and 1856.61/10⁵ persons with an EAPC of -2.58 (95% CI: 2.64 to -2.51), respectively compared to those in 1990. Ambient PM2.5-attributable Non-communicable diseases (NCDs) have dominated major concern in middle and low SDI countries especially in South Asia and East Asia, while household PM2.5-attributable lower respiratory infections (LRIs) still caused the largest burden in low SDI countries in Africa and Asia. Those under 5 and over 70 years old had the largest burdens in PM2.5 attributable LRI and NCDs, respectively.

CONCLUSION

In conclusion, ambient PM2.5-attributable NCDs have threatened public health in middle and low SDI countries, while household PM2.5-attributable LRI still caused the largest burden in low SDI countries. More positive strategies should be tailored to reduce PM2.5-attributable burdens considering specific settings globally.

Simulation and Analysis of Indoor Air Quality in Florida Using Time Series Regression (TSR) and Artificial Neural Networks (ANN) Models

Exposures to air pollutants have been associated with various acute respiratory diseases and detrimental human health. Analysis and further interpretation of air pollutant patterns are correspondingly important as monitoring them. In the present study, the 24-h and four-month indoor and outdoor PM2.5, PM10, NO2, relative humidity, and temperature were measured simultaneously for a laboratory in Gainesville city, Florida. The indoor PM2.5, PM10, and NO2 concentrations were predicted using multiple linear regression (MLR), time series regression (TSR), and artificial neural networks (ANN) models. The modeling conducted in this study aims to perform a cross comparison study between these models in a symmetric environment. The value of root-mean-square error was improved by 18.33% in comparison with the MLR model. In addition, the value of the coefficient of determination was improved by 24.68%. The ANN model had the best performance and could predict the target air pollutants at 10-min intervals of the studied building with 90% accuracy levels. The TSR model showed slightly better performance compared to the MLR model. These results can be accordingly referred for studies analyzing indoor air quality in similar building types and climate zones.

Regional and seasonal variations in household and personal exposures to air pollution in one urban and two rural Chinese communities: A pilot study to collect time-resolved data using static and wearable devices

BACKGROUND

Previous studies of the health impact of ambient and household air pollution (AAP/HAP) have chiefly relied on self-reported and/or address-based exposure modelling data. We assessed the feasibility of collecting and integrating detailed personal exposure data in different settings and seasons.

METHODS/DESIGN

We recruited 477 participants (mean age 58 years, 72% women) from three (two rural [Gansu/Henan] and one urban [Suzhou]) study areas in the China Kadoorie Biobank, based on their previously reported fuel use patterns. A time-resolved monitor (PATS+CO) was used to measure continuously for 120-hour the concentration of fine particulate matter (PM2.5) at personal and household (kitchen and living room) levels in warm (May-September 2017) and cool (November 2017-January 2018) seasons, along with questionnaires on participants' characteristics (e.g. socio-demographic, and fuel use) and time-activity (48-hour). Parallel local ambient monitoring of particulate matter (PM1, PM2.5 and PM10) and gaseous pollutants (CO, ozone, nitrogen oxides) was conducted using regularly-calibrated devices. The air pollution exposure data were compared by study sites and seasons.

FINDINGS

Overall 76% reported cooking at least weekly (regular-cooks), and 48% (urban 1%, rural 65%) used solid fuels (wood/coal) for cooking. Winter heating was more common in rural sites than in urban site (74-91% vs 17% daily), and mainly involved solid fuels. Mixed use of clean and solid fuels was common for cooking in rural areas (38%) but not for heating (0%). Overall, the measured mean PM2.5 levels were 2-3 fold higher in the cool than warm season, and in rural (e.g. kitchen: Gansuwarm_season = 142.3 µg/m3; Gansucool_season = 508.1 µg/m3; Henanwarm_season = 77.5 µg/m3; Henancool_season = 222.3 µg/m3) than urban sites (Suzhouwarm_season = 41.6 µg/m3; Suzhoucool_season = 81.6 µg/m3). The levels recorded tended to be the highest in kitchens, followed by personal, living room and outdoor. Time-resolved data show prominent peaks consistently recorded in the kitchen at typical cooking times, and sustained elevated PM2.5 levels (> 100 µg/m3) were observed in rural areas where use of solid fuels for heating was common.

DISCUSSION

Personal air pollution exposure can be readily assessed using a low-cost time-resolved monitor in different settings, which, in combination with other personal and health outcome data, will enable reliable assessment of the long-term health effects of HAP/AAP exposures in general populations.

Air pollution and indoor settings

Indoor environments contribute significantly to total human exposure to air pollutants, as people spend most of their time indoors. Household air pollution (HAP) resulting from cooking with polluting ("dirty") fuels, which include coal, kerosene, and biomass (wood, charcoal, crop residues, and animal manure) is a global environmental health problem. Indoor pollutants are gases, particulates, toxins, and microorganisms among others, that can have an impact especially on the health of children and adults through a combination of different mechanisms on oxidative stress and gene activation, epigenetic, cellular, and immunological systems. Air pollution is a major risk factor and contributor to morbidity and mortality from major chronic diseases. Children are significantly affected by the impact of the environment due to biological immaturity, prenatal and postnatal lung development. Poor air quality has been related to an increased prevalence of clinical manifestations of allergic asthma and rhinitis. Health professionals should increase their role in managing the exposure of children and adults to air pollution with better methods of care, prevention, and collective action. Interventions to reduce household pollutants may promote health and can be achieved with education, community, and health professional involvement.

Prenatal exposure to fine particles, premature rupture of membranes and gestational age: A prospective cohort study

BACKGROUND

The associations between maternal exposure to fine particles with aerodynamic diameter ≤ 2.5 μm (PM_2.5) and gestational age as well as premature rupture of membranes (PROM) remain unclear. Few studies have focused on preconception exposure and components of fine particles in China.

METHODS

A total of 1715 pregnant women were enrolled at hospitals affiliated with Nanjing Medical University from 2014 to 2015. Personal exposure to PM_2.5 was estimated from preconception to the first trimester. Gestational age and PROM were investigated to explore their associations with PM_2.5 and its components.

RESULTS

From 12 weeks before conception to the end of the first trimester, the gestational age was reduced by 0.89 days (95% CI: -1.37, -0.40) per 10 μg/m³ increment in PM_2.5 exposure. After the exposure period was separated into two groups, PM_2.5 exposure reduced the gestational age by 0.35 days (95% CI: -0.59, -0.11) in the 12 weeks before pregnancy. With maternal exposure to PM_2.5 early in the first trimester, gestational age was reduced by 0.62 days (95% CI: -1.09, -0.14). After mediation analysis, we found that PROM mediated the association between PM_2.5 and gestational age from preconception to the first trimester. Components analysis indicated that exposure to black carbon, organic matter, and nitrate increased the risk of PROM and decreased gestational age.

CONCLUSION

Exposure to PM_2.5 as well as some components of PM_2.5 before and during early pregnancy was associated with PROM and gestational age. PROM might be a potential mediator in associations between PM_2.5 as well as various components and gestational age.

Household air pollution exposure and associations with household characteristics among biomass cookstove users in Puno, Peru

BACKGROUND

Household air pollution (HAP) from combustion of biomass fuel, such as wood and animal dung, is among the leading environmental risk factors for preventable disease. Close to half of the world's population relies on biomass cookstoves for their daily cooking needs. Understanding factors that affect HAP can inform measures to maximize the effectiveness of cookstove interventions in a cost-effective manner. However, the impact of kitchen and household characteristics, as well as the presence of secondary stoves, on HAP concentrations is poorly understood in Puno, Peru.

OBJECTIVE

To explore how household characteristics explain variability of kitchen area concentrations and personal exposures to CO, PM2.5 and BC from biomass cookstoves among women in rural Peru.

METHODS

Household characteristics (including kitchen materials and layout, wealth, and cooking behaviors) and HAP measurements were collected from 180 households in Puno, Peru, from baseline measurements of a randomized trial. Kitchen area concentrations and personal exposures to carbon monoxide (CO), fine particulate matter (PM2.5) and black carbon (BC) were sampled for 48 h. We implemented simple and multivariable linear regression models to determine the associations between household characteristics and both kitchen area concentration and personal exposure to each pollutant.

RESULTS

Mean daily kitchen area concentrations and personal exposures to HAP were, on average, 48 times above World Health Organization indoor guidelines for PM2.5. We found that roof type explained the most variability in HAP and was strongly associated with both kitchen area concentrations and personal exposures for all pollutants after adjusting for other household variables. Personal exposures were 27%-36% lower for PM2.5, CO and BC, in households with corrugated metal roofs, compared to roofs made of natural materials (straw, totora or reed) after adjusting for other factors. Higher kitchen area concentrations were also associated with less wealth, owning more animals, or sampling during the dry season in multivariable models. Having a liquefied petroleum gas (LPG) stove and having a chimney were associated with lower personal exposures, but were not associated with kitchen area concentrations. Personal exposures were lower by 21% for PM2.5 and 28% for CO and BC concentrations among participants who had both LPG and biomass stoves compared to those with only biomass cookstoves adjusting for other household factors.

CONCLUSIONS

Characterizing HAP within different settings can help identify effective and culturally-relevant solutions to reduce HAP exposures. We found that housing roof type is strongly related to kitchen area concentrations and personal exposures to HAP, perhaps because of greater ventilation in kitchens with metal roofs compared to those with thatch roofs. Although HAP concentrations remained above guidelines for all households, promoting use of metal roof materials and LPG stoves may be actionable interventions that can help reduce exposures to HAP in high-altitude rural Peru and similar settings.

Adverse health effects associated with household air pollution: a systematic review, meta-analysis, and burden estimation study

BACKGROUND

3 billion people worldwide rely on polluting fuels and technologies for domestic cooking and heating. We estimate the global, regional, and national health burden associated with exposure to household air pollution.

METHODS

For the systematic review and meta-analysis, we systematically searched four databases for studies published from database inception to April 2, 2020, that evaluated the risk of adverse cardiorespiratory, paediatric, and maternal outcomes from exposure to household air pollution, compared with no exposure. We used a random-effects model to calculate disease-specific relative risk (RR) meta-estimates. Household air pollution exposure was defined as use of polluting fuels (coal, wood, charcoal, agricultural wastes, animal dung, or kerosene) for household cooking or heating. Temporal trends in mortality and disease burden associated with household air pollution, as measured by disability-adjusted life-years (DALYs), were estimated from 2000 to 2017 using exposure prevalence data from 183 of 193 UN member states. 95% CIs were estimated by propagating uncertainty from the RR meta-estimates, prevalence of household air pollution exposure, and disease-specific mortality and burden estimates using a simulation-based approach. This study is registered with PROSPERO, CRD42019125060.

FINDINGS

476 studies (15·5 million participants) from 123 nations (99 [80%] of which were classified as low-income and middle-income) met the inclusion criteria. Household air pollution was positively associated with asthma (RR 1·23, 95% CI 1·11-1·36), acute respiratory infection in both adults (1·53, 1·22-1·93) and children (1·39, 1·29-1·49), chronic obstructive pulmonary disease (1·70, 1·47-1·97), lung cancer (1·69, 1·44-1·98), and tuberculosis (1·26, 1·08-1·48); cerebrovascular disease (1·09, 1·04-1·14) and ischaemic heart disease (1·10, 1·09-1·11); and low birthweight (1·36, 1·19-1·55) and stillbirth (1·22, 1·06-1·41); as well as with under-5 (1·25, 1·18-1·33), respiratory (1·19, 1·18-1·20), and cardiovascular (1·07, 1·04-1·11) mortality. Household air pollution was associated with 1·8 million (95% CI 1·1-2·7) deaths and 60·9 million (34·6-93·3) DALYs in 2017, with the burden overwhelmingly experienced in low-income and middle-income countries (LMICs; 60·8 million [34·6-92·9] DALYs) compared with high-income countries (0·09 million [0·01-0·40] DALYs). From 2000, mortality associated with household air pollution had reduced by 36% (95% CI 29-43) and disease burden by 30% (25-36), with the greatest reductions observed in higher-income nations.

INTERPRETATION

The burden of cardiorespiratory, paediatric, and maternal diseases associated with household air pollution has declined worldwide but remains high in the world's poorest regions. Urgent integrated health and energy strategies are needed to reduce the adverse health impact of household air pollution, especially in LMICs.

FUNDING

British Heart Foundation, Wellcome Trust.

Household and personal air pollution exposure measurements from 120 communities in eight countries: results from the PURE-AIR study

BACKGROUND

Approximately 2·8 billion people are exposed to household air pollution from cooking with polluting fuels. Few monitoring studies have systematically measured health-damaging air pollutant (ie, fine particulate matter [PM2·5] and black carbon) concentrations from a wide range of cooking fuels across diverse populations. This multinational study aimed to assess the magnitude of kitchen concentrations and personal exposures to PM2·5 and black carbon in rural communities with a wide range of cooking environments.

METHODS

As part of the Prospective Urban and Rural Epidemiological (PURE) cohort, the PURE-AIR study was done in 120 rural communities in eight countries (Bangladesh, Chile, China, Colombia, India, Pakistan, Tanzania, and Zimbabwe). Data were collected from 2541 households and from 998 individuals (442 men and 556 women). Gravimetric (or filter-based) 48 h kitchen and personal PM2·5 measurements were collected. Light absorbance (10-5m-1) of the PM2·5 filters, a proxy for black carbon concentrations, was calculated via an image-based reflectance method. Surveys of household characteristics and cooking patterns were collected before and after the 48 h monitoring period.

FINDINGS

Monitoring of household air pollution for the PURE-AIR study was done from June, 2017, to September, 2019. A mean PM2·5 kitchen concentration gradient emerged across primary cooking fuels: gas (45 μg/m3 [95% CI 43-48]), electricity (53 μg/m3 [47-60]), coal (68 μg/m3 [61-77]), charcoal (92 μg/m3 [58-146]), agricultural or crop waste (106 μg/m3 [91-125]), wood (109 μg/m3 [102-118]), animal dung (224 μg/m3 [197-254]), and shrubs or grass (276 μg/m3 [223-342]). Among households cooking primarily with wood, average PM2·5 concentrations varied ten-fold (range: 40-380 μg/m3). Fuel stacking was prevalent (981 [39%] of 2541 households); using wood as a primary cooking fuel with clean secondary cooking fuels (eg, gas) was associated with 50% lower PM2·5 and black carbon concentrations than using only wood as a primary cooking fuel. Similar average PM2·5 personal exposures between women (67 μg/m3 [95% CI 62-72]) and men (62 [58-67]) were observed. Nearly equivalent average personal exposure to kitchen exposure ratios were observed for PM2·5 (0·79 [95% 0·71-0·88] for men and 0·82 [0·74-0·91] for women) and black carbon (0·64 [0·45-0·92] for men and 0·68 [0·46-1·02] for women).

INTERPRETATION

Using clean primary fuels substantially lowers kitchen PM2·5 concentrations. Importantly, average kitchen and personal PM2·5 measurements for all primary fuel types exceeded WHO's Interim Target-1 (35 μg/m3 annual average), highlighting the need for comprehensive pollution mitigation strategies.

FUNDING

Canadian Institutes for Health Research, National Institutes of Health.

Long-term effects of ambient PM2.5 on hypertension in multi-ethnic population from Sichuan province, China: a study based on 2013 and 2018 health service surveys

Hypertension, a major risk factor of many severe chronic diseases and leading cause of global disease burden, is reported to be associated with long-term exposure to PM_2.5. China's high PM_2.5 pollution level has become a major public health issue. However, existing studies from China have got inconsistent results with very limited investigation into the multi-ethnic peoples. This study adds multi-ethnic evidence from Sichuan Province, southwestern China, and assesses ethnic differences of PM_2.5 exposure effect on hypertension. We pooled large cross-sectional data from two surveys conducted in 2013 and 2018 to examine the association of long-term exposure to PM_2.5 on prevalence of hypertension in adults aged 30 years old and above. Community-specified annual PM_2.5 concentration was estimated using satellite data. Thirty-one thousand four hundred sixty-two participants with average exposure concentration of 32.8 μg/m³ were included. The proportions of the Han, the Tibetan, the Yi, and other ethnic people were 89.2%, 7.3%, 3.2%, and 0.3%, respectively. The adjusted odds ratio (OR) was 1.08 (95% CI, 1.04-1.12) for a 10 μg/m³ PM_2.5 concentration increment. The adjusted ORs for the Han, the Tibetan, and the Yi were 1.08 (95% CI, 1.04-1.12), 0.03 (95% CI, 0.00-0.27), and 1.75 (95% CI, 1.28-2.38) for a 10 μg/m³ PM_2.5 concentration increment, respectively. Stratification analysis found stronger associations in participants with chronic diseases and Yi minority population. The results showed that long-term exposure to PM_2.5 may increase the risk of hypertension prevalence in Chinese multi-ethnic adults. The associations were different among ethnicities.

Lung Health in Children in Sub-Saharan Africa: Addressing the Need for Cleaner Air

Air pollution is increasingly recognized as a global health emergency with its impacts being wide ranging, more so for low- and middle-income countries where both indoor and outdoor pollution levels are high. In Africa, more than 80% of children live in households which use unclean sources of energy. The effects of both indoor and outdoor pollution on lung health on children who are the most vulnerable to their effects range from acute lower respiratory tract infections to long-term chronic health effects. We reviewed the literature on the effects of air pollution in children in Sub-Saharan Africa from prenatal exposure, infancy and school-going children. Data from Sub-Saharan Africa on quantification of exposures both indoor and outdoor mainly utilizes modelling or self-reporting. Exposures to biomass not only increases the risk of acute respiratory tract infections in young children but also increases the risk of carriage of pathogenic bacteria in the upper respiratory tract. Although there is limited evidence of association between asthma and pollution in African children, airway hyper-responsiveness and lower lung function has been demonstrated in children with higher risk of exposure. Interventions at a policy level to both quantify the exposure levels at a population level are urgently needed to address the possible interventions to limit exposure and improve lung health in children in Sub-Saharan Africa.

Air pollutant emission factors of solid fuel stoves and estimated emission amounts in rural Beijing

Solid fuels used for heating and cooking in rural households cause a large amount of pollutant emissions. Actions are being taken to replace these solid fuels with cleaner energy carriers. However, the pollutant emission amounts from solid fuels over large areas have rarely been evaluated. In this study, we tested eight common heating stoves consuming bituminous coal chunk, anthracite coal chunk, and anthracite coal briquette; three honeycomb briquette stoves; and three traditional cookstoves consuming corn straw and wood in rural Beijing. Emission factors of particulate matter with aerodynamic diameters ≤2.5 μm (PM_2.5), carbon monoxide (CO), nitrogen oxide (NO_x), and sulfur dioxide (SO₂), were measured as 0.08-13.74 g/kg, 10.80-148.5 g/kg, 0.52-8.44 g/kg, and 0-0.85 g/kg, respectively, for coal heating stoves; 0.35-1.11 g/kg, 16.10-109.43 g/kg, 0.51-0.75 g/kg, and 0-1.98 g/kg, respectively, for honeycomb briquette cookstoves; and 5.90-11.79 g/kg, 28.96-50.23 g/kg, 1.52-2.46 g/kg, and 0-0.05 g/kg, respectively, for traditional biomass cookstoves. Combining emission performance and solid fuel consumption, the estimated annual PM_2.5, CO, NO_x, and SO₂ emission amounts were 26.18 Gg, 394.07 Gg, 14.56 Gg, and 1.53 Gg, respectively. The results present useful information regarding the emission inventory of common solid fuels in rural Beijing on a city-scale. This study provides an example for future intervention projects and environment evaluation in the rural areas of other cities.

Health and Climate Impacts of Scaling Adoption of Liquefied Petroleum Gas (LPG) for Clean Household Cooking in Cameroon: A Modeling Study

BACKGROUND

The Cameroon government has set a target that, by 2030, 58% of the population will be using Liquefied Petroleum Gas (LPG) as a cooking fuel, in comparison with less than 20% in 2014. The National LPG Master Plan (Master Plan) was developed for scaling up the LPG sector to achieve this target.

OBJECTIVES

This study aimed to estimate the potential impacts of this planned LPG expansion (the Master Plan) on population health and climate change mitigation, assuming primary, sustained use of LPG for daily cooking.

METHODS

We applied existing and developed new mathematical models to calculate the health and climate impacts of expanding LPG primary adoption for household cooking in Cameroon over two periods: a) short-term (2017-2030): Comparing the Master Plan 58% target with a counterfactual LPG adoption of 32% in 2030, in line with current trends; and b) long-term (2031-2100, climate modeling only), assuming Cameroon will become a mature and saturated LPG market by 2100 (73% adoption, based on Latin American countries). We compared this with a counterfactual adoption of 41% by 2100, in line with current trends.

RESULTS

By 2030, successful implementation of the Master Plan was estimated to avert about 28,000 (minimum = 22,000 , maximum = 35,000 ) deaths and 770,000 (minimum = 580,000 maximum = 1   million ) disability-adjusted life years. For the same period, we estimated reductions in pollutant emissions of more than a third in comparison with the counterfactual, leading to a global cooling of - 0.1   milli   ° C in 2030. For 2100, a cooling impact from the Master Plan leading to market saturation (73%) was estimated to be - 0.70   milli   ° C in comparison with to the counterfactual, with a range of - 0.64 to - 0.93   milli   ° C based on different fractions of nonrenewable biomass.

DISCUSSION

Successful implementation of the Master Plan could have significant positive impacts on population health in Cameroon with no adverse impacts on climate. https://doi.org/10.1289/EHP4899.

Women exposure to household air pollution after an improved cookstove program in rural San Luis Potosi, Mexico

The state government of San Luis Potosí (SLP), Mexico implemented an improved cookstove (ICS) program in rural areas. As part of the comprehensive program evaluation, we compared fine particulate material (PM_2.5) concentrations in kitchens and patios in treated (TH), and non-treated households (NTH), and analyzed pollutant levels according to patterns of fuels and devices use reported by the women. A panel study was conducted in 728 households (357 TH and 371 NTH) in three regions of SLP including two sampling rounds in 2015-16. Data on exposure determinants, ICS conditions and cooking practices were collected. Daily PM_2.5 in kitchen and patio was measured in a subsample. The average treatment effect was estimated using the double difference method. We constructed a mixed linear model to estimate PM_2.5 levels for the entire study sample and obtained personal exposure according to time-activity logs. NTH had lower socioeconomic status compared to TH. The average daily PM_2.5 concentrations in NTH compared to TH were 155.2 and 92.6 μg/m³ for kitchen and 35.4 and 39.8 μg/m³ for patio, respectively. PM_2.5 levels showed significant regional differences but no significant treatment effect. In many cases, the ICS was added to previous open fire and LPG use (stacking). The household size, kitchen ventilation, relative humidity, temperature and the ratio of indoor/outdoor PM_2.5 concentration were significant predictors of kitchen PM_2.5 levels. The daily PM_2.5 personal exposure was significantly reduced using ICS in good conditions or LPG (57 μg/m³) compared to the traditional open fire (86 μg/m³). This study strengthens the evidence on the potential daily PM_2.5 exposure reduction for women using an ICS in good conditions or LPG, displacing the polluting open fire. Comprehensive strategies tailored to the sociocultural context of the communities are needed to implement clean energy programs that achieve adoption and sustained use of ICS or LPG.

A follow-up study after an improved cookstove intervention in rural Mexico: Estimation of household energy use and chronic PM2.5 exposure

The benefits of improved biomass cookstoves (ICS) depends on their adoption and sustained use. Few studies have documented if and how they are used more than five years after being introduced. We conducted a 9-year prospective cohort study among young rural women in the highlands of Michoacan, Mexico. Participants had received a Patsari ICS during a community trial either in 2005 or 2006. With retrospective information collected in 2012-13, we studied the households' energy use, ICS survival, and cooking practices during the follow-up period. Using an exposure model constructed with personal PM_2.5 measurements in a subsample of homes at the time of the initial trial in 2005, we estimated the exposure associated with different energy use patterns during the follow-up period. The ICS had a mean lifespan of 4 years, after which more than half of the stoves were not in use; therefore, the use of open fire increased, particularly among the indigenous communities. ICS use peak was achieved two years after the initial trial, either exclusively or combined with open fire. Yearly household energy use and other variables were used to estimate chronic air pollution exposure. Mean PM_2.5 exposure during the follow-up period ranged from 51 to 319 μg/m³; the median was 102 and 146 μg/m³ for mainly ICS and mainly open fire use, respectively. The ICS has a useful period after which it needs maintenance, repair, or replacement. Unfortunately, many programs have not afforded a follow-up component. Exposure to biomass smoke air pollutants can be reduced by using an ICS instead of the traditional open fire. Household energy strategies should ensure equitable access to clean energy options adapted to local needs and preferences with culturally appropriate technology implemented on a sustainable perspective.

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.

The association of PM2.5 with airway innate antimicrobial activities of salivary agglutinin and surfactant protein D

Fine particulate matter ≤2.5 μm (PM_2.5) is a prominent global public health risk factor that can cause respiratory infection by downregulating the amounts of antimicrobial proteins and peptides (AMPs). Both salivary agglutinin (SAG) and surfactant protein D (SPD) are important AMPs in respiratory mucosal fluid, providing protection against airway pathogen invasion and infection by inducing microbial aggregation and enhancing pathogen clearance. However, the relationship between PM_2.5 and these AMPs is unclear. To better understand the relationship between PM_2.5 and airway innate immune defenses, we review the respiratory antimicrobial activities of SAG and SPD, as well as the adverse effects of PM_2.5 on airway innate antimicrobial defense. We speculate there exists a dual effect between PM_2.5 and respiratory antimicrobial activity, which means that PM_2.5 suppresses respiratory antimicrobial activity through downregulating airway AMPs, while airway AMPs accelerate PM_2.5 clearance by inducing PM_2.5 microbial aggregation. We propose further research on the relationship between PM_2.5 and these AMPs.

Nagaland health assessment: High mortality rates and difficulty accessing essential health services in Lahe Township, Republic of the Union of Myanmar

INTRODUCTION

Lahe Township belongs to Myanmar`s Naga Self-administered Zone, which is one of the most remote and mountainous areas in Myanmar. However, the limited health data available for the region suggests that there could be neglected health needs that require attention. The purpose of this study was to assess the health status of the population of Lahe Township.

METHODS

A cross-sectional study design incorporating a two-stage cluster sampling methodology recommended by the WHO was used to conduct a household level survey. In the first stage, 30 village clusters were selected from all villages situated in the Lahe Township through systematic sampling with probability of selection proportional to the population size of each village based on the 2014 Myanmar census. In the second stage, a GPS-based sampling method was used to select 30 households within a village cluster. The head of the household completed the survey for all members of the household. Questionnaires inquired about maternal health, mortality, morbidities, childhood nutritional status, access to health care, and water & sanitation. The resulting data was stratified by urban/rural status.

RESULTS

Data was collected on 5,929 individuals living in 879 households, of which 993 individuals (16.7%) were children 5 years old or younger. The median age was 18.0 (IQR 8.0-35.0). Children 15 years old or younger represented 44.7% of the population. 19.8% of households reported at least 1 household member sick during the previous 30 days. The crude mortality rate per 10,000 people per day was 0.58 (95% CI: 0.48-0.69). The under 5 mortality per 10,000 people per day was 0.74 (95% CI: 0.50-1.06). Only 46.7% of households could access a hospital if there was a need.

CONCLUSION

Our results demonstrate a high rate of mortality and the inability to access healthcare in Lahe Township, which should be addressed to prevent further deterioration of health.