Dataset Information

The association between ambient air pollution and scarlet fever in Qingdao, China, 2014-2018: a quantitative analysis.

ABSTRACT:

Background

We conducted a distributed lag non-linear time series analysis to quantify the association between air pollution and scarlet fever in Qingdao city during 2014-2018.

Methods

A distributed lag non-linear model (DLNM) combined with a generalized additive mixed model (GAMM) was applied to quantify the distributed lag effects of air pollutions on scarlet fever, with daily incidence of scarlet fever as the dependent variable and air pollutions as the independent variable adjusted for potential confounders.

Results

A total of 6316 cases of scarlet fever were notified, and there were 376 days occurring air pollution during the study period. Scarlet fever was significantly associated with air pollutions at a lag of 7 days with different relative risk (RR) of air pollution degrees [1.172, 95% confidence interval (CI): 1.038-1.323 in mild air pollution; 1.374, 95% CI 1.078-1.749 in moderate air pollution; 1.610, 95% CI 1.163-2.314 in severe air pollution; 1.887, 95% CI 1.163-3.061 in most severe air pollution].

Conclusions

Our findings show that air pollution is positively associated with scarlet fever in Qingdao, and the risk of scarlet fever could be increased along with the degrees of air pollution. It contributes to developing strategies to prevent and reduce health impact from scarlet fever and other non-vaccine-preventable respiratory infectious diseases in air polluted areas.

SUBMITTER: Jiang F

PROVIDER: S-EPMC8456591 | biostudies-literature |

REPOSITORIES: biostudies-literature

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Project description:BackgroundAir pollution disparities by socioeconomic status (SES) are well documented for the United States, with most literature indicating an inverse relationship (i.e., higher concentrations for lower-SES populations). Few studies exist for China, a country accounting for 26% of global premature deaths from ambient air pollution.ObjectiveOur objective was to test the relationship between ambient air pollution exposures and SES in China.MethodsWe combined estimated year 2015 annual-average ambient levels of nitrogen dioxide (NO2) and fine particulate matter [PM ≤2.5μm in aerodynamic diameter (PM2.5)] with national demographic information. Pollution estimates were derived from a national empirical model for China at 1-km spatial resolution; demographic estimates were derived from national gridded gross national product (GDP) per capita at 1-km resolution, and (separately) a national representative sample of 21,095 individuals from the China Health and Retirement Longitudinal Study (CHARLS) 2015 cohort. Our use of global data on population density and cohort data on where people live helped avoid the spatial imprecision found in publicly available census data for China. We quantified air pollution disparities among individual's rural-to-urban migration status; SES factors (education, occupation, and income); and minority status. We compared results using three approaches to SES measurement: individual SES score, community-averaged SES score, and gridded GDP per capita.ResultsAmbient NO2 and PM2.5 levels were higher for higher-SES populations than for lower-SES population, higher for long-standing urban residents than for rural-to-urban migrant populations, and higher for the majority ethnic group (Han) than for the average across nine minority groups. For the three SES measurements (individual SES score, community-averaged SES score, gridded GDP per capita), a 1-interquartile range higher SES corresponded to higher concentrations of 6-9 μg/m3 NO2 and 3-6 μg/m3 PM2.5; average concentrations for the highest and lowest 20th percentile of SES differed by 41-89% for NO2 and 12-25% for PM2.5. This pattern held in rural and urban locations, across geographic regions, across a wide range of spatial resolution, and for modeled vs. measured pollution concentrations.ConclusionsMultiple analyses here reveal that in China, ambient NO2 and PM2.5 concentrations are higher for high-SES than for low-SES individuals; these results are robust to multiple sensitivity analyses. Our findings are consistent with the idea that in China's current industrialization and urbanization stage, economic development is correlated with both SES and air pollution. To our knowledge, our study provides the most comprehensive picture to date of ambient air pollution disparities in China; the results differ dramatically from results and from theories to explain conditions in the United States. https://doi.org/10.1289/EHP9872.