Mortality burden attributable to temperature variability in China

Impact of agricultural straw open-field burning on concentrations of six criteria air pollutants in China

Agricultural straw open-field burning (ASOB) is a major source of fine particles and carbonaceous aerosols, particularly in China, India, and Southeast Asia. However, the exposure-lag-response relationship between straw burning and urban air pollution in China remains insufficiently investigated. This study compiled satellite-based ASOB data along with daily meteorological and air pollution monitoring data for 156 Chinese cities from 2015 to 2020. The ASOB points detected by the Moderate Resolution Imaging Spectroradiometer (MODIS) were identified as exposure events, and their exposure-lag-response relationships with daily pollutant levels were elucidated using distributed lag nonlinear models. The nation-level estimate of the impact of ASOB points on urban air quality was obtained by a meta-analysis. The results revealed significant short-term elevation in the daily concentrations of six pollutants. Each increase of 10 straw burning points is associated with an increase of 8.89, 8.52, 8.17, 2.43, and 0.84 μg/m3 in PM10, O3, PM2.5, NO2, and SO2, respectively, and an increase of 0.048 mg/m3 in CO with a lag of 0-3 days. Regional and seasonal ASOB variations and their effects were observed, revealing a pronounced effect in East China, particularly from October to December. ASOB contributed 4.54 % of O3 and 2.72 % of PM2.5 concentrations in air pollution waves in the high-intensity ASOB burning seasons. This study highlights the adverse impact of open-field straw burning on air quality, even under China's strict ASOB ban, providing scientific evidence for future assessments of the cost-effectiveness of straw-burning bans and policy refinements.

Association between ambient temperature and years of life lost of external causes of death in 16 prefecture-level regions of Yunnan Province

BACKGROUND

Many injury deaths are related to the environment. This study examined the impact of ambient temperature on external causes of death in Yunnan Province.

METHODS

Data on external causes of death and meteorological information were collected from 2014 to 2020 across 129 counties and districts of Yunnan Province. We estimated associations of the years of life lost (YLL) and its attributable fraction (AF) with temperature using a distributed lag non-linear model in each city and then pooled them in a multivariate meta-regression.

RESULTS

This study included 191 115 external causes of death and daily YLL was 2338.1 years. The relationship between mean temperature and YLL was found to be U-shaped. The AF of the YLL was 12.65% (95% empirical CI (eCI) 7.80% to 16.45%), 18.54% (95% eCI 8.91% to 23.56%) and 15.79% (95% eCI 8.83% to 20.07%) for external causes of death, traffic accidents and other external causes, respectively. Most of the disease burden was attributed to heat temperature. In the disease burden caused by temperature, males, individuals under 75 years old and those of Han ethnicity were mainly affected by heat temperature; individuals over 75 years old and minority populations were mainly affected by cold temperatures. Non-farmers are more affected by temperature than farmers.

CONCLUSIONS

The findings suggest that ambient temperature impacts external causes of death, and the results vary by gender, age, ethnicity and occupation. The study shows the importance of implementing preventive measures targeting both the general population and vulnerable groups in order to address external causes of death in future adaptation policies.

Associations between various types of mortality and temperature variability distinguishing the intraday and interday effects in South Korea

BACKGROUND

The association between temperature variability (TV) and elevated mortality risks is widely known. Yet, few studies investigated the distinct effects of intraday and interday temperature fluctuations considering age-specific, gender-specific, and cause-specific mortality stratified by four seasons.

OBJECTIVES

We investigate the associations between total, intraday, and interday temperature variabilities and total, age-specific, gender-specific, cardiovascular, and respiratory mortality year-round and also stratified by four seasons.

METHODS

We collected district-level daily data for temperature and total, age-specific, gender-specific, cardiovascular, and respiratory mortality in South Korea from 2011 to 2021 (N = 3,113,425). TV indices (i.e., total TV, intraday TV, and interday TV) were computed as the standard deviations of daily minimum, maximum, and mean temperatures over a lag of one to seven days. The associations between TV and mortality were evaluated by a space-time-stratified case-crossover design with quasi-Poisson regression.

RESULTS

Mortality risks varied based on the type of TV index. The associations also differed depending on the mortality type and the season. Year-round associations showed interday TV was generally associated with elevated mortality risks (total mortality: 0.30% (95% CI: 0.07%, 0.52%), 65+ mortality: 0.32% (95% CI: 0.07%, 0.58%), female mortality: 0.49% (95% CI: 0.16%, 0.82%), CVD mortality: 0.47% (95% CI: 0.02%, 0.92%) on lag0-7) while intraday TV was not significantly associated with increased risk of mortality except for the male mortality, 0.68% (95% CI: 0.04%, 1.32%) on lag0-7. Season-stratified analysis revealed that TV-related mortality risks were high consistently in the spring season and generally in the summer season while the associations were generally negative in fall and insignificant in winter.

CONCLUSION

This study provided evidence on the season-stratified, independent impacts of intraday and interday temperature variabilities on total, age-specific, gender-specific, and cause-specific mortality risks in South Korea drawing attention to the need of targeted policies to alleviate the impacts on human health.

Seasonal Temperature Variability and Mortality in the Medicare Population

BACKGROUND

Seasonal temperature variability remains understudied and may be modified by climate change. Most temperature-mortality studies examine short-term exposures using time-series data. These studies are limited by regional adaptation, short-term mortality displacement, and an inability to observe longer-term relationships in temperature and mortality. Seasonal temperature and cohort analyses allow the long-term effects of regional climatic change on mortality to be analyzed.

OBJECTIVES

We aimed to carry out one of the first investigations of seasonal temperature variability and mortality across the contiguous United States. We also investigated factors that modify this association. Using adapted quasi-experimental methods, we hoped to account for unobserved confounding and to investigate regional adaptation and acclimatization at the ZIP code level.

METHODS

We examined the mean and standard deviation (SD) of daily temperature in the warm (April-September) and cold (October-March) season in the Medicare cohort from 2000 to 2016. This cohort comprised 622,427,230 y of person-time in all adults over the age of 65 y from 2000 to 2016. We used daily mean temperature obtained from gridMET to develop yearly seasonal temperature variables for each ZIP code. We used an adapted difference-in-difference approach model with a three-tiered clustering approach and meta-analysis to observe the relationship between temperature variability and mortality within ZIP codes. Effect modification was assessed with stratified analyses by race and population density.

RESULTS

For every 1°C increase in the SD of warm and cold season temperature, the mortality rate increased by 1.54% [95% confidence interval (CI): 0.73%, 2.15%] and 0.69% (95% CI: 0.22%, 1.15%) respectively. We did not see significant effects for seasonal mean temperatures. Participants who were classified by Medicare into an "other" race group had smaller effects than those classified as White for Cold and Cold SD and areas with lower population density had larger effects for Warm SD.

DISCUSSION

Warm and cold season temperature variability were significantly associated with increased mortality rates in U.S. individuals over the age of 65 y, even after controlling for seasonal temperature averages. Warm and cold season mean temperatures showed null effects on mortality. Cold SD had a larger effect size for those who were in the racial subgroup other, whereas Warm SD was more harmful for those living in lower population density areas. This study adds to the growing calls for urgent climate mitigation and environmental health adaptation and resiliency. https://doi.org/10.1289/EHP11588.