Dataset Information

Relationship between fine particulate matter, weather condition and daily non-accidental mortality in Shanghai, China: A Bayesian approach.

ABSTRACT: There are concerns that the reported association of ambient fine particulate matter (PM2.5) with mortality might be a mixture of PM2.5 and weather conditions. We evaluated the effects of extreme weather conditions and weather types on mortality as well as their interactions with PM2.5 concentrations in a time series study. Daily non-accidental deaths, individual demographic information, daily average PM2.5 concentrations and meteorological data between 2012 and 2014 were obtained from Shanghai, China. Days with extreme weather conditions were identified. Six synoptic weather types (SWTs) were generated. The generalized additive model was set up to link the mortality with PM2.5 and weather conditions. Parameter estimation was based on Bayesian methods using both the Jeffreys' prior and an informative normal prior in a sensitivity analysis. We estimate the percent increase in non-accidental mortality per 10 ?g/m3 increase in PM2.5 concentration and constructed corresponding 95% credible interval (CrI). In total, 336,379 non-accidental deaths occurred during the study period. Average daily deaths were 307. The results indicated that per 10 ?g/m3 increase in daily average PM2.5 concentration alone corresponded to 0.26-0.35% increase in daily non-accidental mortality in Shanghai. Statistically significant positive associations between PM2.5 and mortality were found for favorable SWTs when considering the interaction between PM2.5 and SWTs. The greatest effect was found in hot dry SWT (percent increase = 1.28, 95% CrI: 0.72, 1.83), followed by warm humid SWT (percent increase = 0.64, 95% CrI: 0.15, 1.13). The effect of PM2.5 on non-accidental mortality differed under specific extreme weather conditions and SWTs. Environmental policies and actions should take into account the interrelationship between the two hazardous exposures.

SUBMITTER: Fang X

PROVIDER: S-EPMC5679525 | biostudies-literature | 2017

REPOSITORIES: biostudies-literature

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Relationship between fine particulate matter, weather condition and daily non-accidental mortality in Shanghai, China: A Bayesian approach.

Fang Xin X Fang Bo B Wang Chunfang C Xia Tian T Bottai Matteo M Fang Fang F Cao Yang Y

PloS one 20171109 11

There are concerns that the reported association of ambient fine particulate matter (PM2.5) with mortality might be a mixture of PM2.5 and weather conditions. We evaluated the effects of extreme weather conditions and weather types on mortality as well as their interactions with PM2.5 concentrations in a time series study. Daily non-accidental deaths, individual demographic information, daily average PM2.5 concentrations and meteorological data between 2012 and 2014 were obtained from Shanghai, ...[more]

PMID: 29121092

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Project description:Background: Exposures to both ambient fine particulate matter (PM2.5) and extreme weather conditions have been associated with cardiovascular disease (CVD) deaths in numerous epidemiologic studies. However, evidence on the associations with CVD deaths for interaction effects between PM2.5 and weather conditions is still limited. This study aimed to investigate associations of exposures to PM2.5 and weather conditions with cardiovascular mortality, and further to investigate the synergistic or antagonistic effects of ambient air pollutants and synoptic weather types (SWTs). Methods: Information on daily CVD deaths, air pollution, and meteorological conditions between 1 January 2012 and 31 December 2014 was obtained in Shanghai, China. Generalized additive models were used to assess the associations of daily PM2.5 concentrations and meteorological factors with CVD deaths. A 15-day lag analysis was conducted using a polynomial distributed lag model to access the lag patterns for associations with PM2.5. Results: During the study period, the total number of CVD deaths in Shanghai was 59,486, with a daily mean of 54.3 deaths. The average daily PM2.5 concentration was 55.0 µg/m3. Each 10 µg/m3 increase in PM2.5 concentration was associated with a 1.26% (95% confidence interval (CI): 0.40%, 2.12%) increase in CVD mortality. No SWT was statistically significantly associated with CVD deaths. For the interaction between PM2.5 and SWT, statistically significant interactions were found between PM2.5 and cold weather, with risk for PM2.5 in cold dry SWT decreasing by 1.47% (95% CI: 0.54%, 2.39%), and in cold humid SWT the risk decreased by 1.45% (95% CI: 0.52%, 2.36%). In the lag effect analysis, statistically significant positive associations were found for PM2.5 in the 1-3 lag days, while no statistically significant effects were found for other lag day periods. Conclusions: Exposure to PM2.5 was associated with short-term increased risk of cardiovascular deaths with some lag effects, while the cold weather may have an antagonistic effect with PM2.5. However, the ecological study design limited the possibility to identify a causal relationship, so prospective studies with individual level data are warranted.

Project description:BackgroundFetal growth restriction (FGR) is not only a major determinant of perinatal morbidity and mortality but also leads to adverse health effects in later life. Over the past decade, numerous studies have indicated that maternal exposure to ambient air pollution has been a risk factor for abnormal fetal growth in developed countries where PM2.5 levels are relatively low. However, studies in highly polluted regions, such as China, and studies that rely on assessments in utero are scarce.MethodsA total of 7965 women were selected from 11,441 women from the Shanghai Maternity and Infant Living Environment (SMILE) cohort who were pregnant between January 1, 2014, and April 30, 2015. From January 1, 2014, to April 30, 2015, weekly average PM2.5 values from 53 monitors were calculated and the inverse distance weighted (IDW) method was used to create a Shanghai pollution surface map according to the participants residential addresses. Individual exposure was the average PM2.5 value of every gestational week between the first gestational week and one week before the ultrasound measurement date (the range of measurements per participant was 1 to 10). Repeated fetal ultrasound measurements during gestational weeks 14~40 were selected. The estimated fetal weight (EFW) was calculated by biparietal diameter (BPD), abdominal circumference (AC), and femur length (FL) formulas. In total, 29,926 ultrasound measurements were analysed. Demographic variables, other pollutants (SO2, NO2, PM10 and O3) and relative humidity and temperature were controlled for potential confounding through generalized estimating equations (GEE).ResultsThe full model showed that with each 10 μg/m3 increase in PM2.5 exposure, the means (mm) of AC, BPD, FL decreased by 5.48 (- 9.06, - 1.91), 5.57 (- 6.66, - 4.47), and 5.47 (- 6.39, - 4.55), respectively; the mean EFW decreased by 14.49 (- 16.05, - 13.49) grams by Hadlock's third formula and 13.56 (- 14.71, - 12.50) grams by Shepard's formula with each 10 μg/m3 increase in PM2.5 exposure.ConclusionsA negative correlation existed between maternal PM2.5 exposure during pregnancy and fetal growth indicators, which may increase the risk of fetal growth restriction.

Project description:BACKGROUND AND OBJECTIVES:Fine particulate matter (PM2.5, particulate matter with an aerodynamic diameter less than or equal to 2.5 ?m) has multiple adverse effects on human health, especially on the respiratory and circulatory system. The purpose of this study was to evaluate the short-term effect of PM2.5 on the mortality risk of non-accidental and circulatory diseases, and to explore the potential effect modification by sex, education and death location. METHODS:We collected daily mortality counts of Changchun (China) residents, daily meteorology and air pollution data, from January 1, 2014, to January 1, 2017. We focused on the elderly (?65 years old) population who died from non-accidental causes and circulatory diseases, and stratified them by sex, education, and death location. A generalized additive Poisson regression model (GAM) was used to analyse the impact of air pollutants on mortality. We fit single pollutant models to examine PM2.5 effects with different lag structures of single-day (distributed lag:lag0-lag3) and multi-day (moving average lag: lag01-lag03). To test the sensitivity of the model, a multi-pollutant model was established when the PM2.5 effect was strongest. RESULTS:In the single pollutant models, an increment of PM2.5 by 10 ?g/m3 at lag0-3 was associated with a 0.385% (95% CI: 0.069% to 0.702%) increase in daily non-accidental mortality and a 0.442% (95% CI: 0.038% to 0.848%) increase in daily circulatory disease mortality. NO2 (lag1) and O3 (lag0, lag1, lag2, lag01,lag02, lag03) were associated with daily non-accidental death and NO2 (lag1, lag3, lag03) and O3 (lag0, lag1, lag01,lag02, lag03) were associated with daily circulatory disease mortality. In the co-pollutant models, the risk estimates for PM2.5 changed slightly. The excess mortality risk of non-accidental and circulatory diseases was higher for women, people with low education, and died outside hospital. CONCLUSIONS:We found that short-term exposure to PM2.5 increased the mortality risk of non-accidental and circulatory diseases among the elderly in Changchun. Women, people with low education and died outside hospital are more susceptible to PM2.5. NO2 and O3 were also associated with an increase in mortality from non-accidental and circulatory diseases and the O3 is a high effect.

Dataset Information

Relationship between fine particulate matter, weather condition and daily non-accidental mortality in Shanghai, China: A Bayesian approach.

Publications

Relationship between fine particulate matter, weather condition and daily non-accidental mortality in Shanghai, China: A Bayesian approach.

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