Yabin Hu1, Jian Cheng2, Fan Jiang3, Shijian Liu1, Shenghui Li4, Jianguo Tan5, Yong Yin6, Shilu Tong7. 1. Department of Clinical Epidemiology and Biostatistics, Shanghai Children's Medical Center, Shanghai Jiaotong University School of Medicine, Shanghai, China. 2. School of Public Health and Social Work, Institute of Health and Biomedical Innovation, Queensland University of Technology, Brisbane, Australia. 3. Department of Developmental and Behavioral Pediatrics, Pediatric Translational Medicine Institution, Shanghai Children's Medical Center, Shanghai Jiaotong University School of Medicine, Shanghai, China. 4. School of Public Health, Shanghai Jiaotong University, Shanghai, China. 5. Shanghai Key Laboratory of Meteorology and Health (Shanghai Meteorological Service), Shanghai, China. 6. Department of Respiratory Medicine, Shanghai Children's Medical Center, Shanghai Jiaotong University School of Medicine, Shanghai, China. Electronic address: yinyong@scmc.com.cn. 7. Department of Clinical Epidemiology and Biostatistics, Shanghai Children's Medical Center, Shanghai Jiaotong University School of Medicine, Shanghai, China; School of Public Health and Social Work, Institute of Health and Biomedical Innovation, Queensland University of Technology, Brisbane, Australia; School of Public Health, Institute of Environment and Population Health, Anhui Medical University, Hefei, China; Center for Global Health, School of Public Health, Nanjing Medical University, Nanjing, China. Electronic address: tongshilu@scmc.com.cn.
Abstract
OBJECTIVES: There has been increasing interest in identifying the adverse effects of ambient environmental factors on asthma exacerbations (AE), but season-stratified effects of meteorological factors on childhood asthma remain unclear. We explored the season-stratified effects of meteorological factors on childhood AE in Shanghai, China. METHODS: Poisson generalized linear regression model combined with a distributed lag nonlinear model was used to examine the lagged and nonlinear effects of meteorological factors on childhood AE after adjustment for putative confounders. We also performed a season-stratified analysis to determine whether the season modified the relationship between meteorological factors and childhood AE. RESULTS: There were 23,103 emergency department visits (EDVs) for childhood AE, including 15,466 boys and 7637 girls during 2008-2017. Most meteorological factors (e.g., temperature, diurnal temperature range (DTR), relative humidity (RH) and wind speed (WS)) were significantly associated with EDVs for childhood AE, even after adjustment for the confounding effects of air pollutants. In the whole year, extreme cold, moderate heat, higher DTR, lower RH and WS increased the relative risk (RR) for childhood AE. In the cold season, lower RH and wind speed increased the risks of childhood AE (RRlag0-28 for the 5th percentile (p5) of RH: 9.744, 95% CI: 3.567, 26.616; RRlag0-28 for the p5 of wind speed: 10.671, 95% CI: 1.096, 103.879). In the warm season, higher temperature and DTR, lower RH and WS increased the RR for childhood AE (RRlag0-5 for the p95 of temperature: 1.871, 95% CI: 1.246, 2.810; RRlag0-2 for the p95 of DTR: 1.146, 95% CI: 1.010, 1.300; RRlag0-5 for the p5 of RH: 1.931, 95% CI: 1.191, 3.128; RRlag0-2 for the p5 of WS: 1.311, 95% CI: 1.005, 1.709). CONCLUSIONS: Extreme meteorological factors appeared to be triggers of EDVs for childhood AE in Shanghai and the effects modified by season. These findings provide evidence for developing season-specific and tailored strategies to prevent and control childhood AE.
OBJECTIVES: There has been increasing interest in identifying the adverse effects of ambient environmental factors on asthma exacerbations (AE), but season-stratified effects of meteorological factors on childhood asthma remain unclear. We explored the season-stratified effects of meteorological factors on childhood AE in Shanghai, China. METHODS: Poisson generalized linear regression model combined with a distributed lag nonlinear model was used to examine the lagged and nonlinear effects of meteorological factors on childhood AE after adjustment for putative confounders. We also performed a season-stratified analysis to determine whether the season modified the relationship between meteorological factors and childhood AE. RESULTS: There were 23,103 emergency department visits (EDVs) for childhood AE, including 15,466 boys and 7637 girls during 2008-2017. Most meteorological factors (e.g., temperature, diurnal temperature range (DTR), relative humidity (RH) and wind speed (WS)) were significantly associated with EDVs for childhood AE, even after adjustment for the confounding effects of air pollutants. In the whole year, extreme cold, moderate heat, higher DTR, lower RH and WS increased the relative risk (RR) for childhood AE. In the cold season, lower RH and wind speed increased the risks of childhood AE (RRlag0-28 for the 5th percentile (p5) of RH: 9.744, 95% CI: 3.567, 26.616; RRlag0-28 for the p5 of wind speed: 10.671, 95% CI: 1.096, 103.879). In the warm season, higher temperature and DTR, lower RH and WS increased the RR for childhood AE (RRlag0-5 for the p95 of temperature: 1.871, 95% CI: 1.246, 2.810; RRlag0-2 for the p95 of DTR: 1.146, 95% CI: 1.010, 1.300; RRlag0-5 for the p5 of RH: 1.931, 95% CI: 1.191, 3.128; RRlag0-2 for the p5 of WS: 1.311, 95% CI: 1.005, 1.709). CONCLUSIONS: Extreme meteorological factors appeared to be triggers of EDVs for childhood AE in Shanghai and the effects modified by season. These findings provide evidence for developing season-specific and tailored strategies to prevent and control childhood AE.
Authors: Ji Zhou; Ruoyi Lei; Jianming Xu; Li Peng; Xiaofang Ye; Dandan Yang; Sixu Yang; Yong Yin; Renhe Zhang Journal: Int J Environ Res Public Health Date: 2022-09-09 Impact factor: 4.614