Air pollution is the second largest risk to health in Africa, and children with asthma are particularly susceptible to its effects. Yet, there is a scarcity of air pollution exposure data from cities in sub-Saharan Africa. We aimed to identify potential exposure reduction strategies for school children with asthma living in urban areas in sub-Saharan Africa. This personal exposure study was part of the Achieving Control of Asthma in Children in Africa (ACACIA) project. Personal exposure to particulate matter (PM) was monitored in school children in six cities in sub-Saharan Africa (Blantyre, Malawi; Durban, South Africa; Harare, Zimbabwe; Kumasi, Ghana; Lagos, Nigeria; and Moshi, Tanzania). Participants were selected if they were aged 12-16 years and had symptoms of asthma. Monitoring was conducted between June 21, and Nov 26, 2021, from Monday morning (approximately 1000 h) to Friday morning (approximately 1000 h), by use of a bespoke backpack with a small air pollution monitoring unit with an inbuilt Global Positioning System (GPS) data logger. Children filled in a questionnaire detailing potential sources of air pollution during monitoring and exposures were tagged into three different microenvironments (school, commute, and home) with GPS coordinates. Mixed-effects models were used to identify the most important determinants of children's PM2·5 (PM <2·5 μm in diameter) exposure. 330 children were recruited across 43 schools; of these, 297 had valid monitoring data, and 1109 days of valid data were analysed. Only 227 (20%) of 1109 days monitored were lower than the current WHO 24 h PM2·5 exposure health guideline of 15 μg/m3. Children in Blantyre had the highest PM2·5 exposure (median 41·8 μg/m3), whereas children in Durban (16·0 μg/m3) and Kumasi (17·9 μg/m3) recorded the lowest exposures. Children had significantly higher PM2·5 exposures at school than at home in Kumasi (median 19·6 μg/m3vs 14·2 μg/m3), Lagos (32·0 μg/m3vs 18·0 μg/m3), and Moshi (33·1 μg/m3vs 23·6 μg/m3), while children in the other three cities monitored had significantly higher PM2·5 exposures at home and while commuting than at school (median 48·0 μg/m3 and 43·2 μg/m3vs 32·3 μg/m3 in Blantyre, 20·9 μg/m3 and 16·3 μg/m3vs 11·9 μg/m3 in Durban, and 22·7 μg/m3 and 25·4 μg/m3vs 16·4 μg/m3 in Harare). The mixed-effects model highlighted the following determinants for higher PM2·5 exposure: presence of smokers at home (23·0% higher exposure, 95% CI 10·8-36·4), use of coal or wood for cooking (27·1%, 3·9-56·3), and kerosene lamps for lighting (30·2%, 9·1-55·2). By contrast, 37·2% (95% CI 22·9-48·2) lower PM2·5 exposures were found for children who went to schools with paved grounds compared with those whose school grounds were covered with loose dirt. Our study suggests that the most effective changes to reduce PM2·5 exposures in these cities would be to provide paving in school grounds, increase the use of clean fuel for cooking and light in homes, and discourage smoking within homes. The most efficient way to improve air quality in these cities would require tailored interventions to prioritise different exposure-reduction policies in different cities. UK National Institute for Health and Care Research.
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