Abiotic and socioenvironmental factors of PM2.5 pollution associated with asthma in a dense urban road network environment in Kinshasa, D.R. Congo: a cross-sectional study

Fine particulate matter (PM_2.5) air pollution, a major invisible threat to public health, poses a particular risk to individuals with asthma. A significant research gap exists regarding the specific links between PM_2.5 air quality and asthma in the DRC, particularly in Kinshasa's dense urban environments, despite proven pollution. This cross-sectional analytical study aims to identify the links between air quality and bronchial asthma in the Binza Météo health zone, which is characterized by intense traffic and a high prevalence of respiratory diseases. The study was conducted from August 1 to September 30, 2024, and included 424 households across 36 sites within 6 randomly selected health areas. Atmospheric data were collected via PurpleAir PA-II-FLEX sensors and corrected via a specific model developed for the aerosol properties of Kinshasa. Health data were obtained via an adapted ISAAC questionnaire and confirmed by clinical examination. The mean prevalence of asthma was 15.8%. Our results revealed a significant association between asthma incidence and high PM_2.5 concentrations (adjusted OR = 1.210; p < 0.000), a daily outdoor exposure time of more than 12 h (adjusted OR = 5.111; p = 0.007), and the occupation of the asthmatic household head, notably for teachers (adjusted OR = 1.671, p = 0.048), unemployed individuals (adjusted OR = 1.304, p = 0.019), and those in the "other" category (adjusted OR = 1.613, p = 0.003), which are often linked to low socioeconomic status. In contrast, no association was found with proximity to a major road (adjusted OR = 0.939, p = 0.069), suggesting that in a dense urban road network environment, traffic-related-air pollution is nearly homogeneous throughout the urban network, even away from main roads. This finding challenges the assumption that air pollution is primarily concentrated around major traffic routes. The results also revealed significant temporal variability in the PM_2.5 concentration, which was particularly high at the beginning of the study (291.20 µg/m³), with a progressive decrease linked to the rainy season onset. This highlights that to fully understand urban pollution phenomena, a comprehensive approach to the urban network is necessary. Future atmospheric dispersion models should therefore account for the complexity of these systems for better air quality management.