Huagui Guo1, Zheng Chang2, Jiansheng Wu3, Weifeng Li4. 1. Department of Urban Planning and Design, The University of Hong Kong, Hong Kong, SAR, PR China; Shenzhen Institute of Research and Innovation, The University of Hong Kong, Shenzhen 518057, PR China. Electronic address: huaguiguo@hku.hk. 2. Department of Architecture and Civil Engineering, City University of Hong Kong, Hong Kong, SAR, PR China. Electronic address: zchang@cityu.edu.hk. 3. Key Laboratory for Urban Habitat Environmental Science and Technology, Shenzhen Graduate School, Peking University, Shenzhen 518055, PR China; Key Laboratory for Earth Surface Processes, Ministry of Education, College of Urban and Environmental Sciences, Peking University, Beijing 100871, PR China. Electronic address: wujs@pkusz.edu.cn. 4. Department of Urban Planning and Design, The University of Hong Kong, Hong Kong, SAR, PR China; Shenzhen Institute of Research and Innovation, The University of Hong Kong, Shenzhen 518057, PR China. Electronic address: wfli@hku.hk.
Abstract
BACKGROUND: Whether socioeconomic indicators modify the relationship between air pollution exposure and health outcomes remains uncertain, especially in developing countries. OBJECTIVE: This work aims to examine modification effects of socioeconomic indicators on the association between PM2.5 and annual incidence rate of lung cancer for males in China. METHODS: We performed a nationwide analysis in 295 counties (districts) from 2006 to 2014. Using multivariable linear regression models controlling for weather conditions and socioeconomic indicators, we examined modification effects in the stratified and combined datasets according to the tertile and binary divisions of socioeconomic indicators. We also extensively investigated whether the roles of socioeconomic modifications were sensitive to the further adjustment of demographic factors, health and behaviour covariates, household solid fuel consumption, the different operationalization of socioeconomic indicators and PM2.5 exposure with single and moving average lags. RESULTS: We found a stronger relationship between PM2.5 and incidence rate of male lung cancer in urban areas, in the lower economic or lower education counties (districts). If PM2.5 changes by 10 μg/m3, then the shift in incidence rate relative to its mean was significantly higher by 3.97% (95% CI: 2.18%, 4.96%, p = 0.000) in urban than in rural areas. With regard to economic status, if PM2.5 changes by 10 μg/m3, then the change in incidence rate relative to its mean was significantly lower by 0.99% (95% CI: -2.18%, 0.20%, p = 0.071) and 1.39% (95% CI: -2.78%, 0.00%, p = 0.037) in the middle and high economic groups than in the low economic group, respectively. The change in incidence rate relative to its mean was significantly lower by 1.98% (95% CI: -3.18%, -0.79%, p = 0.001) and 2.78% (95% CI: -4.17%, -1.39%, p = 0.000) in the middle and high education groups compared with the low education group, respectively, if PM2.5 changes by 10 μg/m3. We found no robust modification effects of employment rate and urbanisation growth rate. CONCLUSION: Male residents in urban areas, in the lower economic or lower education counties are faced with a greater effect of PM2.5 on the incidence rate of lung cancer in China. The findings emphasize the need for public health intervention and urban planning initiatives targeting the urban-rural, educational or economic disparities in health associated with air pollution exposure. Future prediction on air pollution-induced health effects should consider such socioeconomic disparities, especially for the dominant urban-rural disparity in China.
BACKGROUND: Whether socioeconomic indicators modify the relationship between air pollution exposure and health outcomes remains uncertain, especially in developing countries. OBJECTIVE: This work aims to examine modification effects of socioeconomic indicators on the association between PM2.5 and annual incidence rate of lung cancer for males in China. METHODS: We performed a nationwide analysis in 295 counties (districts) from 2006 to 2014. Using multivariable linear regression models controlling for weather conditions and socioeconomic indicators, we examined modification effects in the stratified and combined datasets according to the tertile and binary divisions of socioeconomic indicators. We also extensively investigated whether the roles of socioeconomic modifications were sensitive to the further adjustment of demographic factors, health and behaviour covariates, household solid fuel consumption, the different operationalization of socioeconomic indicators and PM2.5 exposure with single and moving average lags. RESULTS: We found a stronger relationship between PM2.5 and incidence rate of male lung cancer in urban areas, in the lower economic or lower education counties (districts). If PM2.5 changes by 10 μg/m3, then the shift in incidence rate relative to its mean was significantly higher by 3.97% (95% CI: 2.18%, 4.96%, p = 0.000) in urban than in rural areas. With regard to economic status, if PM2.5 changes by 10 μg/m3, then the change in incidence rate relative to its mean was significantly lower by 0.99% (95% CI: -2.18%, 0.20%, p = 0.071) and 1.39% (95% CI: -2.78%, 0.00%, p = 0.037) in the middle and high economic groups than in the low economic group, respectively. The change in incidence rate relative to its mean was significantly lower by 1.98% (95% CI: -3.18%, -0.79%, p = 0.001) and 2.78% (95% CI: -4.17%, -1.39%, p = 0.000) in the middle and high education groups compared with the low education group, respectively, if PM2.5 changes by 10 μg/m3. We found no robust modification effects of employment rate and urbanisation growth rate. CONCLUSION: Male residents in urban areas, in the lower economic or lower education counties are faced with a greater effect of PM2.5 on the incidence rate of lung cancer in China. The findings emphasize the need for public health intervention and urban planning initiatives targeting the urban-rural, educational or economic disparities in health associated with air pollution exposure. Future prediction on air pollution-induced health effects should consider such socioeconomic disparities, especially for the dominant urban-rural disparity in China.