Association Between Nitrogen Dioxide Pollution and Cause-Specific Mortality in China: Cross-Sectional Time Series Study

• DOI: 10.2196/44648
• Publication Date: 2024-02-05T15:15:33Z
• Authors: Jie Zeng; Guozhen Lin; Hang Dong; Mengmeng Li; Honglian Ruan; Jun Yang
• Keywords: Nitrogen dioxide

Background Nitrogen dioxide (NO2) has been frequently linked to a range of diseases and associated with high rates mortality morbidity worldwide. However, there is limited evidence regarding the risk NO2 on spectrum causes mortality. Moreover, adjustment for potential confounders in analysis insufficient, spatial resolution exposure assessment limited. Objective This study aimed quantitatively assess relationship between short-term death from by adjusting Guangzhou, China, determine modifying effect gender age. Methods A time series was conducted 413,703 deaths that occurred Guangzhou during period 2010 2018. The were classified into 10 categories 26 subcategories. We utilized generalized additive model quasi-Poisson regression using natural cubic splines function lag structure 0 4 days estimate cause-specific estimated percentage change per μg/m3 increase levels. stratified meteorological factors such as temperature, humidity, wind speed, air pressure low levels median critical value analyzed effects various death-causing at those To further identify potentially vulnerable subpopulations, we groups Results significant association existed multiple causes. Each increment density increased risks all-cause 1.73% (95% CI 1.36%-2.09%) due nonaccidental causes, cardiovascular disease, respiratory endocrine neoplasms 1.75% 1.38%-2.12%), 2.06% 1.54%-2.59%), 2.32% 1.51%-3.13%), 2.40% 0.84%-3.98%), 1.18% 0.59%-1.78%), respectively. Among subcategories, 16, including intentional self-harm, hypertensive ischemic stroke disease. Relatively higher estimates relative than levels, except relatively present disease level. Most differences subgroups not statistically significant. similar gender. There age all Conclusions Short-term may especially populations. These findings be important predicting guidelines China.