Risk factors associated with heatwave mortality in Chinese adults over 65 years.

Aging populations are susceptible to heat-related mortality because of physiological factors and comorbidities. However, the understanding of individual vulnerabilities in the aging population is incomplete. In the Chinese Longitudinal Healthy Longevity Survey, we assessed daily heatwave exposure individually for 13,527 participants (median age = 89 years) and 3,249 summer mortalities during follow-up from 2008 to 2018. The mortality risk during heatwave days according to relative temperature is approximately doubled (hazard ratio (HR) range = 1.78-1.98). We found that heatwave mortality risks were increased for individuals with functional declines in mobility (HR range = 2.32-3.20), dependency in activities of daily living (HR range = 2.22-3.27), cognitive impairment (HR = 2.22) and social isolation reflected by having nobody to ask for help during difficulties (HR range = 2.14-10.21). Contrary to current understanding, older age was not predictive of heatwave mortality risk after accounting for individual functional declines; no statistical differences were detected according to sex. Beyond age as a risk factor, our findings emphasize that functional aging is an underlying factor in enhancing heatwave resilience. Assessment of functional decline and implementing care strategies are crucial for targeted prevention of mortality during heatwaves.

Global, regional and national estimates of influenza-attributable ischemic heart disease mortality.

Background: Influenza virus infection is associated with incident ischemic heart disease (IHD) events. Here, we estimate the global, regional, and national IHD mortality burden attributable to influenza. Methods: We used vital registration data from deaths in adults ≥50 years (13.2 million IHD deaths as underlying cause) to assess the relationship between influenza activity and IHD mortality in a non-linear meta-regression framework from 2010 to 2019. This derived relationship was then used to estimate the global influenza attributable IHD mortality. We estimated the population attributable fraction (PAF) of influenza for IHD deaths based on the relative risk associated with a given level of weekly influenza test positivity rate and multiplied PAFs by IHD mortality from the Global Burden of Disease study. Findings: Influenza activity was associated with increased risk of IHD mortality across all countries analyzed. The mean PAF of influenza for IHD mortality was 3.9% (95% uncertainty interval [UI] 2.5-5.3%), ranging from <1% to 10%, depending on country and year. Globally, 299,858 IHD deaths (95% UI 191,216-406,809) in adults ≥50 years could be attributed to influenza, with the highest rates per 100,000 population in the Central Europe, Eastern Europe and Central Asia Region (32.3; 95% UI 20.6-43.8), and in the North Africa and Middle East Region (26.7; 95% UI 17-36.2). Interpretation: Influenza may contribute substantially to the burden of IHD. Our results suggest that if there were no influenza, an average of 4% of IHD deaths globally would not occur. Funding: Collaborative study funded by Sanofi Vaccines.

NO2 and PM2.5 air pollution co-exposure and temperature effect modification on pre-mature mortality in advanced age: a longitudinal cohort study in China.

BACKGROUND: There is a discourse on whether air pollution mixture or air pollutant components are causally linked to increased mortality. In particular, there is uncertainty on whether the association of NO2 with mortality is independent of fine particulate matter (PM2.5). Furthermore, effect modification by temperature on air pollution-related mortality also needs more evidence. METHODS: We used the Chinese Longitudinal Healthy Longevity Study (CLHLS), a prospective cohort with geographical and socio-economic diversity in China. The participants were enrolled in 2008 or 2009 and followed up in 2011-2012, 2014, and 2017-2018. We used remote sensing and ground monitors to measure nitrogen dioxide (NO2), fine particulate matter (PM2.5) , and temperature. We used the Cox-proportional hazards model to examine the association between component and composite air pollution and all-cause mortality, adjusted for demographic characteristics, lifestyle, geographical attributes, and temperature. We used the restricted cubic spline to visualize the concentration-response curve. RESULTS: Our study included 11 835 individuals with an average age of 86.9 (SD: 11.4) at baseline. Over 55 606 person-years of follow-up, we observed 8 216 mortality events. The average NO2 exposure was 19.1 µg/m3 (SD: 14.1); the average PM2.5 exposure was 52.8 µg/m3 (SD: 15.9). In the single pollutant models, the mortality HRs (95% CI) for 10 µg/m3 increase in annual average NO2 or PM2.5 was 1.114 (1.085, 1.143) and 1.244 (1.221, 1.268), respectively. In the multi-pollutant model co-adjusting for NO2 and PM2.5, the HR for NO2 turned insignificant: 0.978 (0.950, 1.008), but HR for PM2.5 was not altered: 1.252 (1.227, 1.279). PM2.5 and higher mortality association was robust, regardless of NO2. When acccounting for particulate matter, NO2 exposure appeared to be harmful in places of colder climates and higher seasonal temperature variation. CONCLUSIONS: We see a robust relationship of PM2.5 exposure and premature mortality in advance aged individuals, however, NO2 exposure and mortality was only harmful in places of colder climate such as northeast China, indicating evidence of effect modification by temperature. Analysis of NO2 without accounting for its collinearity with PM2.5, may lead to overestimation.

Mortality burden attributable to high and low ambient temperatures in China and its provinces: Results from the Global Burden of Disease Study 2019.

Background: Non-optimal temperatures are associated with mortality risk, yet the heterogeneity of temperature-attributable mortality burden across subnational regions in a country was rarely investigated. We estimated the mortality burden related to non-optimal temperatures across all provinces in China in 2019. Methods: The global daily temperature data were obtained from the ERA5 reanalysis dataset. The daily mortality data and exposure-response curves between daily temperature and mortality for 176 individual causes of death were obtained from the Global Burden of Disease Study 2019 (GBD 2019). We estimated the population attributable fraction (PAF) based on the exposure-response curves, daily gridded temperature, and population. We calculated the cause- and province-specific mortality burden based on PAF and disease burden data from the GBD 2019. Findings: We estimated that 593·9 (95% UI:498·8, 704·6) thousand deaths were attributable to non-optimal temperatures in China in 2019 (PAF=5·58% [4·93%, 6·28%]), with 580·8 (485·7, 690·1) thousand cold-related deaths and 13·9 (7·7, 23·2) thousand heat-related deaths. The majority of temperature-related deaths were from cardiovascular diseases (399·7 [322·8, 490·4] thousand) and chronic respiratory diseases (177·4 [141·4, 222·3] thousand). The mortality burdens were observed significantly spatial heterogeneity for both high and low temperatures. For instance, the age-standardized death rates (per 100 000) attributable to low temperature were higher in Western China, with the highest in Tibet (113·7 [82·0, 155·5]), while for high temperature, they were greater in Xinjiang (1·8 [0·7, 3·3]) and Central-Southern China such as Hainan (2·5 [0·9, 5·4]). We also observed considerable geographical variation in the temperature-related mortality burden by causes of death at provincial level. Interpretation: A substantial mortality burden was attributable to non-optimal temperatures across China, and cold effects dominated the total mortality burden in all provinces. Both cold- and heat-related mortality burden showed significantly spatial variations across China. Funding: National Key Research and Development Program.

Estimating the cause-specific relative risks of non-optimal temperature on daily mortality: a two-part modelling approach applied to the Global Burden of Disease Study.

BACKGROUND: Associations between high and low temperatures and increases in mortality and morbidity have been previously reported, yet no comprehensive assessment of disease burden has been done. Therefore, we aimed to estimate the global and regional burden due to non-optimal temperature exposure. METHODS: In part 1 of this study, we linked deaths to daily temperature estimates from the ERA5 reanalysis dataset. We modelled the cause-specific relative risks for 176 individual causes of death along daily temperature and 23 mean temperature zones using a two-dimensional spline within a Bayesian meta-regression framework. We then calculated the cause-specific and total temperature-attributable burden for the countries for which daily mortality data were available. In part 2, we applied cause-specific relative risks from part 1 to all locations globally. We combined exposure-response curves with daily gridded temperature and calculated the cause-specific burden based on the underlying burden of disease from the Global Burden of Diseases, Injuries, and Risk Factors Study, for the years 1990-2019. Uncertainty from all components of the modelling chain, including risks, temperature exposure, and theoretical minimum risk exposure levels, defined as the temperature of minimum mortality across all included causes, was propagated using posterior simulation of 1000 draws. FINDINGS: We included 64·9 million individual International Classification of Diseases-coded deaths from nine different countries, occurring between Jan 1, 1980, and Dec 31, 2016. 17 causes of death met the inclusion criteria. Ischaemic heart disease, stroke, cardiomyopathy and myocarditis, hypertensive heart disease, diabetes, chronic kidney disease, lower respiratory infection, and chronic obstructive pulmonary disease showed J-shaped relationships with daily temperature, whereas the risk of external causes (eg, homicide, suicide, drowning, and related to disasters, mechanical, transport, and other unintentional injuries) increased monotonically with temperature. The theoretical minimum risk exposure levels varied by location and year as a function of the underlying cause of death composition. Estimates for non-optimal temperature ranged from 7·98 deaths (95% uncertainty interval 7·10-8·85) per 100 000 and a population attributable fraction (PAF) of 1·2% (1·1-1·4) in Brazil to 35·1 deaths (29·9-40·3) per 100 000 and a PAF of 4·7% (4·3-5·1) in China. In 2019, the average cold-attributable mortality exceeded heat-attributable mortality in all countries for which data were available. Cold effects were most pronounced in China with PAFs of 4·3% (3·9-4·7) and attributable rates of 32·0 deaths (27·2-36·8) per 100 000 and in New Zealand with 3·4% (2·9-3·9) and 26·4 deaths (22·1-30·2). Heat effects were most pronounced in China with PAFs of 0·4% (0·3-0·6) and attributable rates of 3·25 deaths (2·39-4·24) per 100 000 and in Brazil with 0·4% (0·3-0·5) and 2·71 deaths (2·15-3·37). When applying our framework to all countries globally, we estimated that 1·69 million (1·52-1·83) deaths were attributable to non-optimal temperature globally in 2019. The highest heat-attributable burdens were observed in south and southeast Asia, sub-Saharan Africa, and North Africa and the Middle East, and the highest cold-attributable burdens in eastern and central Europe, and central Asia. INTERPRETATION: Acute heat and cold exposure can increase or decrease the risk of mortality for a diverse set of causes of death. Although in most regions cold effects dominate, locations with high prevailing temperatures can exhibit substantial heat effects far exceeding cold-attributable burden. Particularly, a high burden of external causes of death contributed to strong heat impacts, but cardiorespiratory diseases and metabolic diseases could also be substantial contributors. Changes in both exposures and the composition of causes of death drove changes in risk over time. Steady increases in exposure to the risk of high temperature are of increasing concern for health. FUNDING: Bill & Melinda Gates Foundation.