Dataset Information

Estimating Short- and Long-Term Associations Between Air Quality Index and COVID-19 Transmission: Evidence From 257 Chinese Cities.

ABSTRACT: Objectives: To evaluate the long- and short-term effects of air pollution on COVID-19 transmission simultaneously, especially in high air pollution level countries. Methods: Quasi-Poisson regression was applied to estimate the association between exposure to air pollution and daily new confirmed cases of COVID-19, with mutual adjustment for long- and short-term air quality index (AQI). The independent effects were also estimated and compared. We further assessed the modification effect of within-city migration (WM) index to the associations. Results: We found a significant 1.61% (95%CI: 0.51%, 2.72%) and 0.35% (95%CI: 0.24%, 0.46%) increase in daily confirmed cases per 1 unit increase in long- and short-term AQI. Higher estimates were observed for long-term impact. The stratifying result showed that the association was significant when the within-city migration index was low. A 1.25% (95%CI: 0.0.04%, 2.47%) and 0.41% (95%CI: 0.30%, 0.52%) increase for long- and short-term effect respectively in low within-city migration index was observed. Conclusions: There existed positive associations between long- and short-term AQI and COVID-19 transmission, and within-city migration index modified the association. Our findings will be of strategic significance for long-run COVID-19 control.

SUBMITTER: Cao R

PROVIDER: S-EPMC8333027 | biostudies-literature | 2021

REPOSITORIES: biostudies-literature

ACCESS DATA

Publications

Estimating Short- and Long-Term Associations Between Air Quality Index and COVID-19 Transmission: Evidence From 257 Chinese Cities.

Cao Ru R Wang Yuxin Y Pan Xiaochuan X Jin Xiaobin X Huang Jing J Li Guoxing G

International journal of public health 20210721

<b>Objectives:</b> To evaluate the long- and short-term effects of air pollution on COVID-19 transmission simultaneously, especially in high air pollution level countries. <b>Methods:</b> Quasi-Poisson regression was applied to estimate the association between exposure to air pollution and daily new confirmed cases of COVID-19, with mutual adjustment for long- and short-term air quality index (AQI). The independent effects were also estimated and compared. We further assessed the modification ef ...[more]

PMID: 34366765

Similar Datasets

Project description:Ambient air pollution is a health concern in Latin America given its large urban population exposed to levels above recommended guidelines. Yet no studies have examined the mortality impact of air pollutants in the region across a wide range of cities. We assessed whether short-term levels of fine particulate matter (PM2.5) from modeled estimates, are associated with cardiovascular and respiratory mortality among adults in 337 cities from 9 Latin American countries. We compiled mortality, PM2.5 and temperature data for the period 2009-2015. For each city, we evaluated the association between monthly changes in PM2.5 and cardiovascular and respiratory mortality for sex and age subgroups using Poisson models, adjusted for seasonality, long-term trend, and temperature. To accommodate possibly different associations of mortality with PM2.5 by age, we included interaction terms between changes in PM2.5 and age in the models. We combined the city-specific estimates using a random effects meta-regression to obtain mortality relative risks for each sex and age group. We analyzed 3,026,861 and 1,222,623 cardiovascular and respiratory deaths, respectively, from a study population that represents 41 % of the total population of Latin America. We observed that a 10 μg/m3 increase in monthly PM2.5 is associated with an increase of 1.3 % (95 % confidence interval [CI], 0.4 to 2.2) in cardiovascular mortality and a 0.9 % increase (95 % CI -0.6 to 2.4) in respiratory mortality. Increases in mortality risk ranged between -0.5 % to 3.0 % across 6 sex-age groups, were larger in men, and demonstrated stronger associations with cardiovascular mortality as age increased. Socioeconomic, environmental and health contexts in Latin America are different than those present in higher income cities from which most evidence on air pollution impacts is drawn. Locally generated evidence constitutes a powerful instrument to engage civil society and help drive actions to mitigate and control ambient air pollution.

Project description:BackgroundCoarse particulate matter with aerodynamic diameter between 2.5 and [Formula: see text] ([Formula: see text]) air pollution is a severe environmental problem in developing countries, but its challenges to public health were rarely evaluated.ObjectiveWe aimed to investigate the associations between day-to-day changes in [Formula: see text] and cause-specific mortality in China.MethodsWe conducted a nationwide daily time-series analysis in 272 main Chinese cities from 2013 to 2015. The associations between [Formula: see text] concentrations and mortality were analyzed in each city using overdispersed generalized additive models. Two-stage Bayesian hierarchical models were used to estimate national and regional average associations, and random-effect models were used to pool city-specific concentration-response curves. Two-pollutant models were adjusted for fine particles with aerodynamic diameter [Formula: see text] ([Formula: see text]) or gaseous pollutants.ResultsOverall, we observed positive and approximately linear concentration-response associations between [Formula: see text] and daily mortality. A [Formula: see text] increase in [Formula: see text] was associated with higher mortality due to nonaccidental causes [0.23%; 95% posterior interval (PI): 0.13, 0.33], cardiovascular diseases (CVDs; 0.25%; 95% PI: 0.13, 0.37), coronary heart disease (CHD; 0.21%; 95% PI: 0.05, 0.36), stroke (0.21%; 95% PI: 0.08, 0.35), respiratory diseases (0.26%; 95% PI: 0.07, 0.46), and chronic obstructive pulmonary disease (COPD; 0.34%; 95% PI: 0.12, 0.57). Associations were stronger for cities in southern vs. northern China, with significant differences for total and cardiovascular mortality. Associations with [Formula: see text] were of similar magnitude to those for [Formula: see text] in both single- and two-pollutant models with mutual adjustment. Associations were robust to adjustment for gaseous pollutants other than nitrogen dioxide and sulfur dioxide. Meta-regression indicated that a larger positive correlation between [Formula: see text] and [Formula: see text] predicted stronger city-specific associations between [Formula: see text] and total mortality.ConclusionsThis analysis showed significant associations between short-term [Formula: see text] exposure and daily nonaccidental and cardiopulmonary mortality based on data from 272 cities located throughout China. Associations appeared to be independent of exposure to [Formula: see text], carbon monoxide, and ozone. https://doi.org/10.1289/EHP2711.

Dataset Information

Estimating Short- and Long-Term Associations Between Air Quality Index and COVID-19 Transmission: Evidence From 257 Chinese Cities.

Publications

Estimating Short- and Long-Term Associations Between Air Quality Index and COVID-19 Transmission: Evidence From 257 Chinese Cities.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets