Multinational prediction of household and personal exposure to fine particulate matter (PM2.5) in the PURE cohort study
The research developed household and personal exposure models for fine particulate matter (PM2.5) using data from the PURE-AIR study across multiple countries. The models explained a significant portion of the variation in PM2.5 measurements and identified key predictors such as cooking fuel type and season. These findings can enhance quantitative assessments of household air pollution and inform public health policies.
College of Health researcher(s)
Abstract
Introduction
Use of polluting cooking fuels generates household air pollution (HAP) containing health-damaging levels of fine particulate matter (PM2.5). Many global epidemiological studies rely on categorical HAP exposure indicators, which are poor surrogates of measured PM2.5 levels. To quantitatively characterize HAP levels on a large scale, a multinational measurement campaign was leveraged to develop household and personal PM2.5 exposure models.
Methods
The Prospective Urban and Rural Epidemiology (PURE)-AIR study included 48-hour monitoring of PM2.5 kitchen concentrations (n = 2,365) and male and/or female PM2.5 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 PM2.5 exposures.
Results
The final models explained half (R2 = 54%) of the variation in kitchen PM2.5 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 PM2.5 kitchen concentrations. Average national PM2.5 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 PM2.5 kitchen concentration, heating fuel type, season and secondhand smoke exposure were significant predictors of personal exposures. Modeled average PM2.5 female exposures were lower than male exposures in upper-middle/high-income countries (India, China, Colombia, Chile).
Conclusion
Using survey data to estimate PM2.5 exposures on a multinational scale can cost-effectively scale up quantitative HAP measurements for disease burden assessments. The modeled PM2.5 exposures can be used in future epidemiological studies and inform policies targeting HAP reduction.
Household Air Pollution FAQ
What is household air pollution (HAP)?
Household air pollution (HAP) refers to the presence of harmful pollutants within a home, primarily caused by the incomplete combustion of polluting fuels, such as wood, charcoal, animal dung, and coal, often used in inefficient stoves.
Why is HAP a concern?
HAP is linked to several adverse health and environmental effects. The pollutants, especially fine particulate matter (PM2.5), contribute to respiratory infections in children, lung cancer, COPD, cataracts, pregnancy complications, hypertension, and cardiovascular diseases. Furthermore, HAP contributes significantly to global black carbon emissions, a major contributor to climate change and ambient air pollution.
What are the key factors influencing HAP levels?
The study found that aside from the type of primary cooking fuel used, other crucial factors affecting HAP levels include:
- Stove type: Improved stoves with chimneys generally produce less pollution than traditional open fires or mud stoves.
- Heating fuel type: Using polluting fuels for heating, like wood or coal, significantly adds to PM2.5 concentrations.
- Presence of a chimney: Kitchens equipped with a chimney have lower PM2.5 concentrations as they help vent out smoke.
- Country and Region: Location-specific factors like housing structure, ventilation practices, fuel quality, and ambient air pollution levels greatly influence indoor PM2.5 levels.
Are there seasonal variations in HAP levels?
Yes, HAP levels tend to be higher during winter months (dry season) due to increased use of polluting fuels for heating and reduced ventilation. However, elevated winter concentrations were observed even in households not using heating fuels, suggesting other seasonal factors influence indoor PM2.5 levels.
How do HAP exposures differ between men and women?
Traditionally, women are considered more exposed to HAP due to their cooking roles. However, the study found varying differences between male and female exposures across different countries. Notably:
- Similar or Higher Male Exposures: In some countries with higher ambient air pollution, male exposures were similar or even greater than female exposures. This may be due to occupational exposures and time spent outdoors.
- Higher Female Exposures: In countries with lower ambient pollution and where wood is the dominant cooking fuel, female exposures were significantly higher than male exposures, likely due to prolonged time spent in the cooking area.
Does switching to clean cooking fuels solve the issue entirely?
While switching to clean cooking fuels like gas or electricity drastically reduces PM2.5 concentrations, it may not entirely eliminate the problem. In rapidly developing countries with high ambient air pollution levels, reaching the WHO-recommended PM2.5 levels will likely require additional measures beyond fuel transition.
How does ambient air pollution affect HAP exposures?
Regional differences in ambient air pollution significantly impact indoor PM2.5 levels, especially in countries with high outdoor pollution levels. The study found a strong correlation between average annual outdoor PM2.5 concentrations and indoor PM2.5 levels in households using clean fuels, highlighting the infiltration of outdoor pollution indoors.
What are the implications of these findings for policies and future research?
The study emphasizes the need for:
- Collecting detailed data: Future global health surveys should prioritize collecting information about cooking fuel type, stove type, heating fuel, presence of a chimney, and ambient air pollution levels to better assess HAP exposures.
- Considering contextual factors: HAP interventions and policies should account for regional differences in cooking practices, fuel availability, socioeconomic conditions, and ambient air pollution levels to ensure effective and equitable solutions.
- Monitoring male exposures: Future HAP measurement studies should include monitoring of male exposures to improve the accuracy of risk assessments and understand the full impact of HAP on both sexes.