Projecting Future Heat-Related Mortality under Climate Change Scenarios: A Systematic Review

Background: Heat-related mortality is a matter of great public health concern, especially in the light of climate change. Although many studies have found associations between high temperatures and mortality, more research is needed to project the future impacts of climate change on heat-related mortality

Independent and Combined Effects of Heatwaves and PM2.5 on Preterm Birth in Guangzhou, China: A Survival Analysis.

BACKGROUND: Both extreme heat and air pollution exposure during pregnancy have been associated with preterm birth; however, their combined effects are unclear. OBJECTIVES: Our goal was to estimate the independent and joint effects of heatwaves and fine particulate matter [PM 0) for less extreme heatwaves (i.e., shorter or with relatively low temperature thresholds) but were less than additive (RERIs<0) for more intense heatwaves. CONCLUSIONS: Our research strengthens the evidence that exposure to heatwaves during the final gestational week can independently trigger preterm birth. Moderate heatwaves may also act synergistically with PM2.5 exposure to increase risk of preterm birth, which adds new evidence to the current understanding of combined effects of air pollution and meteorological variables on adverse birth outcomes. https://doi.org/10.1289/EHP5117

Geographical disparities in the impacts of heat on diabetes mortality and the protective role of greenness in Thailand: A nationwide case-crossover analysis.

Diabetes is a major public health problem globally, and heat exposure may be a potential risk factor for death among diabetes. This study examines the association between heat and diabetes mortality in different regions of Thailand and investigates whether heat effects are modified by regional greenness. Daily temperature and daily diabetes deaths data were obtained for 60 provinces of Thailand during 2000-2008. A case-crossover analysis was conducted to quantify the odds of heat-related death among diabetes. Meta-regression was then used to examine potential modification effects of regional greenness (as represented by the Normalized Difference Vegetation Index) on heat-related mortality. A strong association between heat and diabetes mortality was found in Thailand, with important regional variations. Nationally, the pooled odds ratio of diabetes mortality was 1.10 (95% confidence interval (CI): 1.06-1.14) for heat (90th percentile of temperature) and 1.20 (95% CI: 1.10-1.30) for extreme heat (99th percentile of temperature) compared with the minimum mortality temperature, across lag 0-1 days. Central and northeast Thailand were the most vulnerable regions. Regional greenness modified the effects of heat, with lower mortality impacts in areas of higher levels of greenness. In conclusion, heat exposure increases mortality risk in diabetes, with large geographical variations in risk suggesting the need for region-specific public health strategies. Increasing greenness levels may help to reduce the burden of heat on diabetes in Thailand against the backdrop of a warming climate

The burden of heatwave-related preterm births and associated human capital losses in China

Frequent heatwaves under global warming can increase the risk of preterm birth (PTB), which in turn will affect physical health and human potential over the life course. However, what remains unknown is the extent to which anthropogenic climate change has contributed to such burdens. We combine health impact and economic assessment methods to comprehensively evaluate the entire heatwave-related PTB burden in dimensions of health, human capital and economic costs. Here, we show that during 2010-2020, an average of 13,262 (95%CI 6,962-18,802) PTBs occurred annually due to heatwave exposure in China. In simulated scenarios, 25.8% (95%CI 17.1%-34.5%) of heatwave-related PTBs per year on average can be attributed to anthropogenic climate change, which further result in substantial human capital losses, estimated at over $1 billion costs. Our findings will provide additional impetus for introducing more stringent climate mitigation policies and also call for more sufficient adaptations to reduce heatwave detriments to newborn

The impact of the 2016 flood event in Anhui Province, China on infectious diarrhea disease: An interrupted time-series study.

Climate change may bring more frequent and severe floods which will heighten public health problems, including an increased risk of infectious diarrhea in susceptible populations. Affected by heavy rainfall and an El Niño event, a destructive flood occurred in Anhui province, China on 18th June 2016. This study investigates the impact of this severe flood on infectious diarrhea at both city-level and provincial level, and further to identify modifying factor. We obtained information on infectious diarrheal cases during 2013-2017 from the National Disease Surveillance System. An interrupted time-series design was used to estimate effects of the flood event on diarrhea in 16 cities. Then we applied a meta-analysis to estimate the area-level pooled effects of the flood in both flooded areas and non-flooded areas. Finally, a meta-regression was applied to determine whether proximity to flood was a predictor of city-level risks. Stratified analyses by gender and age group were also conducted for flooded areas. A significant increase in infectious diarrhea risk (RR = 1.11, 95% CI: 1.01, 1.23) after the flood event was found in flooded area with variation in risks across cities, while there was no increase in non-flooded areas. Diarrheal risks post-flood was progressively higher in cities with greater proximity to the Yangtze River. Children aged 5-14 were at highest risk of diarrhea post-flood in the flooded areas. Our study provides strong evidence that the 2016 severe flood significantly increased infectious diarrheal risk in exposed populations. Local public health agencies are advised to develop intervention programs to prevent and control infectious diarrhea risk when a major flood occurs, especially in areas close to water bodies and among vulnerable populations

A Large Change in Temperature between Neighbouring Days Increases the Risk of Mortality

Background: Previous studies have found high temperatures increase the risk of mortality in summer. However, little is known about whether a sharp decrease or increase in temperature between neighbouring days has any effect on mortality. Method: Poisson regression models were used to estimate the association between temperature change and mortality in summer in Brisbane, Australia during 1996–2004 and Los Angeles, United States during 1987–2000. The temperature change was calculated as the current day’s mean temperature minus the previous day’s mean. Results: In Brisbane, a drop of more than 3 °C in temperature between days was associated with relative risks (RRs) of 1.157 (95% confidence interval (CI): 1.024, 1.307) for total non external mortality (NEM), 1.186 (95%CI: 1.002, 1.405) for NEM in females, and 1.442 (95%CI: 1.099, 1.892) for people aged 65–74 years. An increase of more than 3 °C was associated with RRs of 1.353 (95%CI: 1.033, 1.772) for cardiovascular mortality and 1.667 (95%CI: 1.146, 2.425) for people aged < 65 years. In Los Angeles, only a drop of more than 3 °C was significantly associated with RRs of 1.133 (95%CI: 1.053, 1.219) for total NEM, 1.252 (95%CI: 1.131, 1.386) for cardiovascular mortality, and 1.254 (95%CI: 1.135, 1.385) for people aged ≥75 years. In both cities, there were joint effects of temperature change and mean temperature on NEM. Conclusion : A significant change in temperature of more than 3 °C, whether positive or negative, has an adverse impact on mortality even after controlling for the current temperature