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

Factors Determining Black Carbon Exposures among Pregnant Women Enrolled in the HAPIN Trial

Residential biomass burning is an important source of black carbon (BC) exposure among rural communities in low- and middle-income countries. We collected 7165 personal BC samples and individual/household level information from 3103 pregnant women enrolled in the Household Air Pollution Intervention Network trial. Women in the intervention arm received free liquefied petroleum gas stoves and fuel throughout pregnancy; women in the control arm continued the use of biomass stoves. Median (IQR) postintervention BC exposures were 9.6 μg/m3 (5.2-14.0) for controls and 2.8 μg/m3 (1.6-4.8) for the intervention group. Using mixed models, we characterized predictors of BC exposure and assessed how exposure contrasts differed between arms by select predictors. Primary stove type was the strongest predictor (R2 = 0.42); the models including kerosene use, kitchen location, education, occupation, or stove use hours also provided additional explanatory power from the base model adjusted only for the study site. Our full, trial-wide, model explained 48% of the variation in BC exposures. We found evidence that the BC exposure contrast between arms differed by study site, adherence to the assigned study stove, and whether the participant cooked. Our findings highlight factors that may be addressed before and during studies to implement more impactful cookstove intervention trials.

In praise of fossil fuel subsidies (for cooking)

Households that burn biomass in inefficient open fires - a practice that results in $1.6 trillion in global damages from health impacts and climate-altering emissions yearly - are often unable to access cleaner alternatives, like gas, which is widely available but unaffordable, or electricity, which is unattainable for many due to insufficient supply and reliability of electricity services. Governments are often reluctant to make gas affordable. We argue that condemnation of all fossil fuel subsidies is short-sighted and does not adequately consider subsidizing gas for cooking as a potential strategy to improve public health and reduce greenhouse gas emissions.

Household concentrations and female and child exposures to air pollution in peri-urban sub-Saharan Africa: measurements from the CLEAN-Air(Africa) study

BACKGROUND

Relatively clean cooking fuels such as liquefied petroleum gas (LPG) emit less fine particulate matter (PM2·5) and carbon monoxide (CO) than polluting fuels (eg, wood, charcoal). Yet, some clean cooking interventions have not achieved substantial exposure reductions. This study evaluates determinants of between-community variability in exposures to household air pollution (HAP) across sub-Saharan Africa.

METHODS

In this measurement study, we recruited households cooking primarily with LPG or exclusively with wood or charcoal in peri-urban Cameroon, Ghana, and Kenya from previously surveyed households. In 2019-20, we conducted monitoring of 24 h PM2·5 and CO kitchen concentrations (n=256) and female cook (n=248) and child (n=124) exposures. PM2·5 measurements used gravimetric and light scattering methods. Stove use monitoring and surveys on cooking characteristics and ambient air pollution exposure (eg, walking time to main road) were also administered.

FINDINGS

The mean PM2·5 kitchen concentration was five times higher among households cooking with charcoal than those using LPG in the Kenyan community (297 μg/m3, 95% CI 216-406, vs 61 μg/m3, 49-76), but only 4 μg/m3 higher in the Ghanaian community (56 μg/m3, 45-70, vs 52 μg/m3, 40-68). The mean CO kitchen concentration in charcoal-using households was double the WHO guideline (6·11 parts per million [ppm]) in the Kenyan community (15·81 ppm, 95% CI 8·71-28·72), but below the guideline in the Ghanaian setting (1·77 ppm, 1·04-2·99). In all communities, mean PM2·5 cook exposures only met the WHO interim-1 target (35 μg/m3) among LPG users staying indoors and living more than 10 min walk from a road.

INTERPRETATION

Community-level variation in the relative difference in HAP exposures between LPG and polluting cooking fuel users in peri-urban sub-Saharan Africa might be attributed to differences in ambient air pollution levels. Thus, mitigation of indoor and outdoor PM2·5 sources will probably be critical for obtaining significant exposure reductions in rapidly urbanising settings of sub-Saharan Africa.

FUNDING

UK National Institute for Health and Care Research.

Ecological study on household air pollution exposure and prevalent chronic disease in the elderly

Older people spend most of their time indoors. Limited evidence demonstrates that exposure to indoor air pollutants might be related to chronic complications. This study aimed to estimate the correlation between household air pollution (HAP)'s long-term exposure and the prevalence of elevated hypertension, diabetes mellitus (DM), obesity, and low-density lipoprotein (LDL) cholesterol. From the Global Burden disease dataset, we extracted HAP, hypertension, DM, body mass index, and LDL cholesterol data from Iran from 1990 to 2019 to males and females in people over 50 years. We present APC and AAPC and their confidence intervals using Joinpoint Software statistical software. R software examined the correlation between HAP and hypertension, DM2, Obesity, and high LDL cholesterol. Our finding showed a significant and positive correlation between HAP exposure and prevalence of high low-density lipoprotein cholesterol (p ≤ 0.001, r = 0.70), high systolic blood pressure (p ≤ 0.001, r = 0.63), and high body mass index (p ≤ 0.001, r = 0.57), and DM2 (p ≤ 0.001, r = 0.38). The analysis results also illustrated a positive correlation between indoor air pollution and smoking (p ≤ 0.001, r = 0.92). HAP exposure might be a risk factor for elevated blood pressure, DM, obesity, and LDL cholesterol and, consequently, more serious health problems. According to our results, smoking is one of the sources of HAP. However, ecological studies cannot fully support causal relationships, and this article deals only with Iran. Our findings should be corroborated in personal exposure and biomonitoring approach studies.

Using time-resolved monitor wearing data to study the effect of clean cooking interventions on personal air pollution exposures

BACKGROUND

Personal monitoring can estimate individuals' exposures to environmental pollutants; however, accuracy depends on consistent monitor wearing, which is under evaluated.

OBJECTIVE

To study the association between device wearing and personal air pollution exposure.

METHODS

Using personal device accelerometry data collected in the context of a randomized cooking intervention in Ghana with three study arms (control, improved biomass, and liquified petroleum gas (LPG) arms; N = 1414), we account for device wearing to infer parameters of PM2.5 and CO exposure.

RESULTS

Device wearing was positively associated with exposure in the control and improved biomass arms, but weakly in the LPG arm. Inferred community-level air pollution was similar across study arms (~45 μg/m3). The estimated direct contribution of individuals' cooking to PM2.5 exposure was 64 μg/m3 for the control arm, 74 μg/m3 for improved biomass, and 6 μg/m3 for LPG. Arm-specific average PM2.5 exposure at near-maximum wearing was significantly lower in the LPG arm as compared to the improved biomass and control arms. Analysis of personal CO exposure mirrored PM2.5 results.

CONCLUSIONS

Personal monitor wearing was positively associated with average air pollution exposure, emphasizing the importance of high device wearing during monitoring periods and directly assessing device wearing for each deployment.

SIGNIFICANCE

We demonstrate that personal monitor wearing data can be used to refine exposure estimates and infer unobserved parameters related to the timing and source of environmental exposures.

IMPACT STATEMENTS

In a cookstove trial among pregnant women, time-resolved personal air pollution device wearing data were used to refine exposure estimates and infer unobserved exposure parameters, including community-level air pollution, the direct contribution of cooking to personal exposure, and the effect of clean cooking interventions on personal exposure. For example, in the control arm, while average 48 h personal PM2.5 exposure was 77 μg/m3, average predicted exposure at near-maximum daytime device wearing was 108 μg/m3 and 48 μg/m3 at zero daytime device wearing. Wearing-corrected average 48 h personal PM2.5 exposures were 50% lower in the LPG arm than the control and improved biomass and inferred direct cooking contributions to personal PM2.5 from LPG were 90% lower than the other arms. Our recommendation is that studies assessing personal exposures should examine the direct association between device wearing and estimated mean personal exposure.

Effects of household and participant characteristics on personal exposure and kitchen concentration of fine particulate matter and black carbon in rural Honduras

Traditional cooking with solid fuels (biomass, animal dung, charcoals, coal) creates household air pollution that leads to millions of premature deaths and disability worldwide each year. Exposure to household air pollution is highest in low- and middle-income countries. Using data from a stepped-wedge randomized controlled trial of a cookstove intervention among 230 households in Honduras, we analyzed the impact of household and personal variables on repeated 24-h measurements of fine particulate matter (PM2.5) and black carbon (BC) exposure. Six measurements were collected approximately six-months apart over the course of the three-year study. Multivariable mixed models explained 37% of variation in personal PM2.5 exposure and 49% of variation in kitchen PM2.5 concentrations. Additionally, multivariable models explained 37% and 47% of variation in personal and kitchen BC concentrations, respectively. Stove type, season, presence of electricity, primary stove location, kitchen enclosure type, stove use time, and presence of kerosene for lighting were all associated with differences in geometric mean exposures. Stove type explained the most variability of the included variables. In future studies of household air pollution, tracking the cooking behaviors and daily activities of participants, including outdoor exposures, may explain exposure variation beyond the household and personal variables considered here.

Exposure Contrasts of Pregnant Women during the Household Air Pollution Intervention Network Randomized Controlled Trial

BACKGROUND

Exposure to PM 2.5 arising from solid fuel combustion is estimated to result in ∼ 2.3 million premature deaths and 91 million lost disability-adjusted life years annually. Interventions attempting to mitigate this burden have had limited success in reducing exposures to levels thought to provide substantive health benefits.

OBJECTIVES

This paper reports exposure reductions achieved by a liquified petroleum gas (LPG) stove and fuel intervention for pregnant mothers in the Household Air Pollution Intervention Network (HAPIN) randomized controlled trial.

METHODS

The HAPIN trial included 3,195 households primarily using biomass for cooking in Guatemala, India, Peru, and Rwanda. Twenty-four-hour exposures to PM 2.5 , carbon monoxide (CO), and black carbon (BC) were measured for pregnant women once before randomization into control (n = 1,605 ) and LPG (n = 1,590 ) arms and twice thereafter (aligned with trimester). Changes in exposure were estimated by directly comparing exposures between intervention and control arms and by using linear mixed-effect models to estimate the impact of the intervention on exposure levels.

RESULTS

Median postrandomization exposures of particulate matter (PM) with aerodynamic diameter ≤ 2.5 μ m (PM 2.5 ) in the intervention arm were lower by 66% at the first (71.5 vs. 24.1   μ g / m 3 ), and second follow-up visits (69.5 vs. 23.7   μ g / m 3 ) compared to controls. BC exposures were lower in the intervention arm by 72% (9.7 vs. 2.7   μ g / m 3 ) and 70% (9.6 vs. 2.8   μ g / m 3 ) at the first and second follow-up visits, respectively, and carbon monoxide exposure was 82% lower at both visits (1.1 vs. 0.2  ppm ) in comparison with controls. Exposure reductions were consistent over time and were similar across research locations.

DISCUSSION

Postintervention PM 2.5 exposures in the intervention arm were at the lower end of what has been reported for LPG and other clean fuel interventions, with 69% of PM 2.5 samples falling below the World Health Organization Annual Interim Target 1 of 35   μ g / m 3 . This study indicates that an LPG intervention can reduce PM 2.5 exposures to levels at or below WHO targets. https://doi.org/10.1289/EHP10295.

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.