Medgyesi Danielle N, Mujtaba Mohammed Nuhu, Yang Qiang, Abubakari Sulemana Watara, Lee Alison G, Porter Jeremy, Chillrud Steven N, Kaali Seyram, Jack Darby W, Asante Kwaku Poku
Department of Environmental Health Sciences, Mailman School of Public Health, Columbia University, New York, NY, USA.
Kintampo Health Research Centre, Research and Development Division, Ghana Health Service, Kintampo, North Municipality, Ghana.
J Expo Sci Environ Epidemiol. 2024 Sep;34(5):802-813. doi: 10.1038/s41370-023-00606-1. Epub 2023 Oct 5.
Personal exposure to fine particulate matter (PM) from household air pollution is well-documented in sub-Saharan Africa, but spatiotemporal patterns of exposure are poorly characterized.
We used paired GPS and personal PM data to evaluate changes in exposure across location-time environments (e.g., household and community, during cooking and non-cooking hours), building density and proximity to roadways.
Our study included 259 sessions of geolocated, gravimetrically-calibrated one-minute personal PM measurements from participants in the GRAPHS Child Lung Function Study. The household vicinity was defined using a 50-meter buffer around participants' homes. Community boundaries were developed using a spatial clustering algorithm applied to an open-source dataset of building footprints in Africa. For each GPS location, we estimated building density (500 m buffer) and proximity to roadways (100 m buffer). We estimated changes in PM exposure by location (household, community), time of day (morning/evening cooking hours, night), building density, and proximity to roadways using linear mixed effect models.
Relative to nighttime household exposure, PM exposure during evening cooking hours was 2.84 (95%CI = 2.70-2.98) and 1.80 (95%CI = 1.54-2.10) times higher in the household and community, respectively. Exposures were elevated in areas with the highest versus lowest quartile of building density (Factor = 1.60, 95%CI = 1.42-1.80). The effect of building density was strongest during evening cooking hours, and influenced levels in both the household and community (31% and 65% relative increase from Q1 to Q4, respectively). Being proximal to a trunk, tertiary or track roadway increased exposure by a factor of 1.16 (95%CI = 1.07-1.25), 1.68 (95%CI = 1.45-1.95) and 1.27 (95%CI = 1.06-1.53), respectively.
Household air pollution from cooking with solid fuels in sub-Saharan Africa is a major environmental concern for maternal and child health. Our study advances previous knowledge by quantifying the impact of household cooking activities on air pollution levels in the community, and identifying two geographic features, building density and roadways, that contribute to maternal and child daily exposure. Household cooking contributes to higher air pollution levels in the community especially in areas with greater building density. Findings underscore the need for equitable clean household energy transitions that reach entire communities to reduce health risks from household and outdoor air pollution.
在撒哈拉以南非洲，个人暴露于家庭空气污染产生的细颗粒物（PM）已有充分记录，但暴露的时空模式特征尚不明确。
我们使用配对的全球定位系统（GPS）和个人PM数据，评估跨位置 - 时间环境（如家庭和社区、烹饪和非烹饪时间）、建筑密度以及与道路的接近程度的暴露变化。
我们的研究包括来自GRAPHS儿童肺功能研究参与者的259次地理定位、重量校准的一分钟个人PM测量。家庭附近区域定义为围绕参与者房屋的50米缓冲区。社区边界使用应用于非洲建筑足迹开源数据集的空间聚类算法确定。对于每个GPS位置，我们估计建筑密度（500米缓冲区）和与道路的接近程度（100米缓冲区）。我们使用线性混合效应模型估计按位置（家庭、社区）、一天中的时间（早晚烹饪时间、夜间）、建筑密度和与道路的接近程度划分的PM暴露变化。
相对于夜间家庭暴露，晚上烹饪时间在家庭和社区的PM暴露分别是夜间的2.84倍（95%置信区间 = 2.70 - 2.98）和1.80倍（95%置信区间 = 1.54 - 2.10）。建筑密度最高四分位数区域的暴露比最低四分位数区域高（系数 = 1.60，95%置信区间 = 1.42 - 1.80）。建筑密度的影响在晚上烹饪时间最强，对家庭和社区的水平都有影响（从第一四分位数到第四四分位数分别相对增加31%和65%）。靠近主干道、三级道路或小道会使暴露分别增加1.16倍（95%置信区间 = 1.07 - 1.25）、1.68倍（95%置信区间 = 1.45 - 1.95）和1.27倍（95%置信区间 = 1.06 - 1.53）。
撒哈拉以南非洲使用固体燃料烹饪造成的家庭空气污染是母婴健康面临的主要环境问题。我们的研究通过量化家庭烹饪活动对社区空气污染水平的影响，并确定建筑密度和道路这两个导致母婴日常暴露的地理特征，推进了先前的知识。家庭烹饪导致社区空气污染水平升高，尤其是在建筑密度较大的地区。研究结果强调需要实现公平的清洁家庭能源转型，覆盖整个社区，以降低家庭和室外空气污染带来的健康风险。
