• Environmental sciences

• Wenming Shi
• Department of Environmental Health, School of Public Health, Fudan University, Shanghai 200032, China
• Cong Liu
• Department of Environmental Health, School of Public Health, Fudan University, Shanghai 200032, China
• Isabella Annesi-Maesano
• Epidemiology of Allergic and Respiratory Diseases Department, IPLESP, Sorbonne Université and INSERM, Medical School Saint-Antoine, F75012 Paris, France
• Dan Norback
• Department of Medical Sciences, Uppsala University, Uppsala SE-751, Sweden
• Qihong Deng
• School of Energy Science and Engineering, Central South University, Changsha 410083, China
• Chen Huang
• School of Environment and Architecture, University of Shanghai for Science and Technology, Shanghai 200093, China
• Hua Qian
• School of Energy & Environment, Southeast University, Nanjing 210096, China
• Xin Zhang
• Research Center for Environmental Science and Engineering, Shanxi University, Taiyuan 030006, China
• Yuexia Sun
• Tianjin Key Lab of Indoor Air Environmental Quality Control, Tianjin University, Tianjin 300072, China
• Tingting Wang
• School of Nursing & Health Management, Shanghai University of Medicine & Health Sciences, Shanghai 201318, China
• Aaron van Donkelaar
• Department of Physics and Atmospheric Science, Dalhousie University, B3H 4R2 Halifax, Nova Scotia, Canada; Department of Energy, Environmental and Chemical Engineering, Washington University in St. Louis, St. Louis, MO, USA
• Randall V. Martin
• Department of Physics and Atmospheric Science, Dalhousie University, B3H 4R2 Halifax, Nova Scotia, Canada; Department of Energy, Environmental and Chemical Engineering, Washington University in St. Louis, St. Louis, MO, USA; Atomic and Molecular Physics Division, Harvard-Smithsonian Center for Astrophysics, 60 Garden St, Cambridge, MA 02138, USA
• Yinping Zhang
• Department of Building Science, Tsinghua University, Beijing 100084, China
• Baizhan Li
• Key Laboratory of Three Gorges Reservoir Region's Eco-Environment, Chongqing University, Chongqing 400030, China
• Haidong Kan
• Department of Environmental Health, School of Public Health, Fudan University, Shanghai 200032, China; Key Laboratory of Public Health Safety of the Ministry of Education, NHC Key Laboratory of Health Technology Assessment (Fudan University), Shanghai Typhoon Institute/CMA, Shanghai Key Laboratory of Meteorology and Health, Shanghai 200030, China; Corresponding authors at: Room 331, Building 8, 130 Dong-an Road, Xuhui District, Shanghai 200032, China (Z. Zhao). Room 333, Building 8, 130 Dong-an Road, Xuhui District, Shanghai 200032, China (H. Kan).
• Zhuohui Zhao
• Department of Environmental Health, School of Public Health, Fudan University, Shanghai 200032, China; Key Laboratory of Public Health Safety of the Ministry of Education, NHC Key Laboratory of Health Technology Assessment (Fudan University), Shanghai Typhoon Institute/CMA, Shanghai Key Laboratory of Meteorology and Health, Shanghai 200030, China; Corresponding authors at: Room 331, Building 8, 130 Dong-an Road, Xuhui District, Shanghai 200032, China (Z. Zhao). Room 333, Building 8, 130 Dong-an Road, Xuhui District, Shanghai 200032, China (H. Kan).

Abstract

The long-term effects of ambient PM2.5 and chemical constituents on childhood pneumonia were still unknown. A cross-sectional study was conducted in 30,315 children in the China Children, Homes, Health (CCHH) project, involving 205 preschools in six cities in China, to investigate the long-term effects of PM2.5 constituents on lifetime-ever diagnosed pneumonia. Information on the lifetime-ever pneumonia and demographics were collected by validated questionnaires. The lifetime annual average ambient PM2.5, ozone and five main PM2.5 constituents, including SO42−, NO3−, NH4+, organic matter (OM) and black carbon (BC), were estimated according to preschool addresses by a combination of satellite remote sensing, chemical transport modeling and ground-based monitors. The prevalence of lifetime-ever diagnosed pneumonia was 34.5% across six cities and differed significantly among cities (p = 0.004). The two-level logistic regression models showed that the adjusted odds ratio for PM2.5 (per 10 µg/m3) and its constituents (per 1 µg/m3)-SO42−, NO3−, NH4+, and OM were 1.12 (95% CI:1.07–1.18), 1.02 (1.00–1.04), 1.06 (1.04–1.09), 1.05 (1.03–1.07) and 1.09 (1.06–1.12), respectively. Children in urban area, aged < 5 years and breastfeeding time < 6 months enhanced the risks of pneumonia. Our study provided robust results that long-term levels of ambient PM2.5 and its constituents increased the risk of childhood pneumonia, especially NH4+, NO3− and OM.

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