Arku Raphael E, Dionisio Kathie L, Hughes Allison F, Vallarino Jose, Spengler John D, Castro Marcia C, Agyei-Mensah Samuel, Ezzati Majid
Department of Environmental Health, Harvard School of Public Health, Boston, Massachusetts, USA.
Department of Global Health and Population, Harvard School of Public Health, Boston, Massachusetts, USA.
J Expo Sci Environ Epidemiol. 2015 Nov-Dec;25(6):557-66. doi: 10.1038/jes.2014.56. Epub 2014 Aug 27.
Air pollution exposure and places where the exposures occur may differ in cities in the developing world compared with high-income countries. Our aim was to measure personal fine particulate matter (PM2.5) exposure of students in neighborhoods of varying socioeconomic status in Accra, Ghana, and to quantify the main predictors of exposure. We measured 24-hour PM2.5 exposure of 56 students from eight schools in four neighborhoods. PM2.5 was measured both gravimetrically and continuously, with time-matched global positioning system coordinates. We collected data on determinants of exposure, such as distances of homes and schools from main roads and fuel used for cooking at their home or in the area of residence/school. The association of PM2.5 exposure with sources was estimated using linear mixed-effects models. Personal PM2.5 exposures ranged from less than 10 μg/m(3) to more than 150 μg/m(3) (mean 56 μg/m(3)). Girls had higher exposure than boys (67 vs 44 μg/m(3); P-value=0.001). Exposure was inversely associated with distance of home or school to main roads, but the associations were not statistically significant in the multivariate model. Use of biomass fuels in the area where the school was located was also associated with higher exposure, as was household's own biomass use. Paved schoolyard surface was associated with lower exposure. School locations in relation to major roads, materials of school ground surfaces, and biomass use in the area around schools may be important determinants of air pollution exposure.
与高收入国家相比,发展中世界城市的空气污染暴露情况以及暴露发生的地点可能有所不同。我们的目标是测量加纳阿克拉不同社会经济地位社区学生的个人细颗粒物(PM2.5)暴露情况,并量化暴露的主要预测因素。我们测量了来自四个社区八所学校的56名学生的24小时PM2.5暴露情况。通过重量法和连续监测法测量PM2.5,并结合时间匹配的全球定位系统坐标。我们收集了暴露决定因素的数据,如家庭和学校与主要道路的距离以及家庭或居住/学校区域烹饪所用的燃料。使用线性混合效应模型估计PM2.5暴露与污染源之间的关联。个人PM2.5暴露范围从小于10μg/m³到超过150μg/m³(平均56μg/m³)。女孩的暴露水平高于男孩(67μg/m³对44μg/m³;P值 = 0.001)。暴露与家庭或学校到主要道路的距离呈负相关,但在多变量模型中这些关联无统计学意义。学校所在区域使用生物质燃料以及家庭自身使用生物质燃料也与较高的暴露相关。铺设的校园地面与较低的暴露相关。学校相对于主要道路的位置、校园地面材料以及学校周边区域的生物质燃料使用可能是空气污染暴露的重要决定因素。