University of Georgia, Athens, Georgia 30602, United States.
Benchmark Risk Group, Chicago, Illinois 60601, United States.
Environ Sci Technol. 2024 Jun 11;58(23):10162-10174. doi: 10.1021/acs.est.3c09991. Epub 2024 May 29.
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/m (5.2-14.0) for controls and 2.8 μg/m (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 ( = 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.
住宅生物质燃烧是中低收入国家农村社区接触黑碳(BC)的一个重要来源。我们从参与家庭空气污染干预网络试验的 3103 名孕妇中收集了 7165 份个人 BC 样本和个人/家庭层面的信息。干预组的女性在整个孕期获得免费的液化石油气炉和燃料;对照组的女性继续使用生物质炉灶。干预组和对照组的干预后 BC 暴露的中位数(IQR)分别为 9.6 μg/m(5.2-14.0)和 2.8 μg/m(1.6-4.8)。使用混合模型,我们描述了 BC 暴露的预测因素,并根据选定的预测因素评估了暴露对比在两个组之间的差异。主要炉灶类型是最强的预测因素( = 0.42);纳入煤油使用、厨房位置、教育、职业或炉灶使用时间的模型,与仅根据研究地点调整的基础模型相比,还提供了额外的解释能力。我们的全模型,即整个试验范围的模型,解释了 BC 暴露变化的 48%。我们发现有证据表明,组间 BC 暴露的差异与研究地点、对指定研究炉灶的依从性以及参与者是否做饭有关。我们的研究结果强调了在研究之前和期间可能需要解决的因素,以实施更有影响力的炉灶干预试验。