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Accepted for/Published in: JMIR Public Health and Surveillance

Date Submitted: Nov 29, 2022
Date Accepted: Jan 7, 2024

The final, peer-reviewed published version of this preprint can be found here:

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

Zeng J, Lin G, Dong H, Li M, Ruan H, Yang J

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

JMIR Public Health Surveill 2024;10:e44648

DOI: 10.2196/44648

PMID: 38315528

PMCID: 10877496

Association between nitrogen dioxide pollution and cause-specific mortality in China: A cross-sectional time series study

  • Jie Zeng; 
  • Guozhen Lin; 
  • Hang Dong; 
  • Mengmeng Li; 
  • Honglian Ruan; 
  • Jun Yang

ABSTRACT

Background:

Nitrogen dioxide(NO2) has been frequently linked to a range of diseases. The effects of NO2 pollution on human health is associated with high rates of mortality and morbidity worldwide. However, there is limited evidence regarding the risk of NO2 on a spectrum of causes mortality. Moreover, the adjustment for potential confounders of NO2 analysis was insufficient and the spatial resolution of exposure assessment was limited.

Objective:

To quantitatively assess the relationship between short-term exposure to NO2 and death by adjusting potential confounders from a range of causes in Guangzhou, China, and determine the effect modification of gender and age.

Methods:

A time-series study was conducted on 413,703 deaths that occurred in Guangzhou during the period 2010-2018. The causes of death were classified into 10 categories and 26 subcategories. A generalized additive model with quasi-Poisson regression was applied using natural cubic splines function with lag 0-4 days structures to estimate the potential lag effect of NO2 on cause-specific mortality. We estimated percentage change increase (%) in mortality for per 10 μg/m3 increase in NO2 levels for cause-specific mortality. We stratified meteorological factors such as temperature, humidity, wind speed and air pressure into high and low levels with the median as the critical value, and analyzed the effects of NO2 on various death diseases at high and low levels respectively. To further identify the potential vulnerable subpopulations, groups stratified by gender and age were analyzed.

Results:

We found a significant association between NO2 exposure and deaths from multiple causes in Guangzhou. Each 10 μg/m3 increment in the density of NO2 at a lag of 0–4 days increased the risk of all-cause mortality by 1.73% (95%CI:1.36, 2.09%), and that due to non-accidental causes, cardiovascular diseases, respiratory diseases, endocrine diseases and neoplasms by 1.75% (95%CI: 1.38, 2.12%), 2.06% (95%CI:1.54, 2.59%), 2.32% (95%CI: 1.51, 3.13%), 2.40% (95%CI:0.84, 3.98%), and 1.18% (95%CI: 0.59, 1.78%), respectively. Among the 26 subcategories, the mortality risk associated with sixteen diseases, such as intentional self-harm, hypertensive disease, ischemic stroke disease, etc. We observed relatively higher effect estimates of NO2 on mortality among low levels of temperature, relative humidity, wind speed and air pressure than their counterparts, except that relatively higher effect estimate at high level of air pressure for endocrine diseases. But most of the difference between subgroups were not statistically significant. The effect estimates of NO2 were similar for both genders, while there were significant differences between the age groups for all-cause, non-accidental and cardiovascular disease-related mortality.

Conclusions:

Our study provided clear evidence of short-term exposure to NO2 may increase the risk of mortality due to a spectrum of causes, especially in some potential vulnerable populations. These findings may have important implications for predicting and modifying the guidelines of NO2 exposure in China.


 Citation

Please cite as:

Zeng J, Lin G, Dong H, Li M, Ruan H, Yang J

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

JMIR Public Health Surveill 2024;10:e44648

DOI: 10.2196/44648

PMID: 38315528

PMCID: 10877496

Per the author's request the PDF is not available.

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