Minimum Mortality Temperature Research Articles

Attributable risk of mortality associated with heat and heat waves: A time-series study in Kerman, Iran during 2005-2017.

The association between heat or heat waves and mortality should often be reported in a way that makes it sensible by health policymakers. In this study we aimed to assess the effect of heat and heat waves on mortality using attributable risks during 2005-2017. Nine heat waves were defined using a combination of severity and duration of mean daily temperature. Heat wave effects were assessed using added and main effects. Added effects were assessed as a binary variable and main effects were assessed by comparing the median temperature (in heat wave days) to Minimum Mortality Temperature (MMT). The effects of heat, mild heat and extreme heat on mortality were also assessed. Distributed Lag Non-linear Models were used to assess the relations in a bi-dimensional perspective in which the quadratic b-spline was chosen as the basis function for the dimension of the exposure and the natural cubic b-spline was chosen for lag dimension. The backward perspective was used to estimate the attributable risks. The total mortality attributed to non-optimal temperatures for all days was 1.91% (CI 95%: -6.36, 8.47). The attributable risks (AR) were 2.23%, 2.02% and 0.25% for heat, mild heat and extreme heat days, respectively. AR was more for females and the above 65 years old groups than other groups in heat, mild heat and extreme heat days. While the stronger heat waves defined based on temperature above the 95 and 98th percentile had a significant attributable risk for total mortality in the added effects; the weaker heat waves (defined based on temperature above of the 90th percentile (HW1, HW2, HW3) had higher attributable risks, significant for HW1 and HW2, in the main effects. Apparently weaker heat waves show more immediate effects, while stronger heat waves increase mortality over several days.

Evidence for Urban-Rural Disparity in Temperature-Mortality Relationships in Zhejiang Province, China.

Background:Temperature-related mortality risks have mostly been studied in urban areas, with limited evidence for urban–rural differences in the temperature impacts on health outcomes.Objectives:We investigated whether temperature–mortality relationships vary between urban and rural counties in China.Methods:We collected daily data on 1 km gridded temperature and mortality in 89 counties of Zhejiang Province, China, for 2009 and 2015. We first performed a two-stage analysis to estimate the temperature effects on mortality in urban and rural counties. Second, we performed meta-regression to investigate the modifying effect of the urbanization level. Stratified analyses were performed by all-cause, nonaccidental (stratified by age and sex), cardiopulmonary, cardiovascular, and respiratory mortality. We also calculated the fraction of mortality and number of deaths attributable to nonoptimum temperatures associated with both cold and heat components. The potential sources of the urban–rural differences were explored using meta-regression with county-level characteristics.Results:Increased mortality risks were associated with low and high temperatures in both rural and urban areas, but rural counties had higher relative risks (RRs), attributable fractions of mortality, and attributable death counts than urban counties. The urban–rural disparity was apparent for cold (first percentile relative to minimum mortality temperature), with an RR of 1.47 [95% confidence interval (CI): 1.32, 1.62] associated with all-cause mortality for urban counties, and 1.98 (95% CI: 1.87, 2.10) for rural counties. Among the potential sources of the urban–rural disparity are age structure, education, GDP, health care services, air conditioners, and occupation types.Conclusions:Rural residents are more sensitive to both cold and hot temperatures than urban residents in Zhejiang Province, China, particularly the elderly. The findings suggest past studies using exposure–response functions derived from urban areas may underestimate the mortality burden for the population as a whole. The public health agencies aimed at controlling temperature-related mortality should develop area-specific strategies, such as to reduce the urban–rural gaps in access to health care and awareness of risk prevention. Future projections on climate health impacts should consider the urban–rural disparity in mortality risks. https://doi.org/10.1289/EHP3556

Effects of extreme temperatures on cerebrovascular mortality in Lisbon: a distributed lag non-linear model.

Cerebrovascular diseases are the leading cause of mortality in Portugal, especially when related with extreme temperatures. This study highlights the impacts of the exposure-response relationship or lagged effect of low and high temperatures on cerebrovascular mortality, which can be important to reduce the health burden from cerebrovascular diseases. The purpose of this study was to assess the effects of weather on cerebrovascular mortality, measured by ambient temperature in the District of Lisbon, Portugal. A quasi-Poisson generalized additive model combined with a distributed lag non-linear model was applied to estimate the delayed effects of temperature on cerebrovascular mortality up to 30days. With reference to minimum mortality temperature threshold of 22°C, there was a severe risk (RR = 2.09, 95% CI 1.74, 2.51) of mortality for a 30-day-cumulative exposure to extreme cold temperatures of 7.3°C (1st percentile). Similarly, the cumulative effect of a 30-day exposure to an extreme hot temperature of 30°C (99th percentile) was 52% (RR = 1.65, 95% CI 1.37, 1.98) higher than same-day exposure. Over the 13years of study, non-linear effects of temperature on mortality were identified, and the probability of dying from cerebrovascular disease in Lisbon was 7% higher in the winter than in the summer. The findings of this study provide a baseline for future public health prevention programs on weather-related mortality.

A new method to estimate the temperature-CVD mortality relationship.

Few detailed, individual-focused studies have researched the added effect of temperature on cardiovascular disease (CVD), particularly in China. Moreover, no prior studies have explored the exposure-response relationship among all populations and different sub-sociodemographic groups. A distributed lag nonlinear model (DLNM) was applied to evaluate the adverse health effects of temperature on CVD mortality for all populations and different sub-sociodemographic groups (by age, sex, educational level, living arrangement, and occupation) in Beijing. Based on the exposure-response relationships, firstly, we proposed a new model (COCKTAIL, Code Of Climate Key To An Ill) for revealing the split-and-merge relationships of the temperature-CVD mortality curve. This method could be used to apply the CVD deaths in a studied area to forecast the exposure-response relationships in the same area in the future. Secondly, this is the most detailed study to analyze the relationship between temperature and CVD mortality for different subgroups among the existing researches for developed and developing countries. We found that the cold temperature (at - 14°C) was the risk factor for people with low socioeconomic status, especially for single people (including unmarried, divorced, and widowed), for indoor workers, and for people with low education, compared with the minimum mortality temperature, with a cumulative increase of 3.9 (80%CI, 2.9-5.4), 3.8 (80%CI, 2.8-5.1), and 4.5 (80%CI, 3.1-6.3) times respectively. Meanwhile, the hot temperature (at 35°C) was the risk factor for CVD death, with a cumulative increase of 2.6 (80%CI, 2.0-3.4) for females, and 3.1 (80%CI, 2.4-4.2) for single people. The varying CVD vulnerability in terms of CVD mortality among various groups may assist governments in preparing health resources and taking measures to prevent or reduce temperature-related deaths.

Variation of indoor minimum mortality temperature in different cities: Evidence of local adaptations

Epidemiological studies on the impact of outdoor temperature to human health have demonstrated the capability of humans to adapt to local climate. However, there is limited information on the association between indoor temperature and human health, despite people spending most of their time indoors. The problem stems from the lack of sufficient indoor temperature measurement in the population. To overcome this obstacle, this paper presents an indirect epidemiological approach to evaluate the impact of high indoor temperature on mortality. The relationships between indoor-outdoor temperatures in different climate zones identified in the literature were combined with the outdoor temperature-mortality curves of the same locations to obtain the local indoor minimum mortality temperatures (iMMT), the temperature at which mortality is lowest, which by implication is the temperature at which the population is most comfortable on average. We show that the iMMT varies and has a weak linear relationship with the distance to the equator, which provides evidence of human adaptation to local indoor temperatures. These findings reinforce the adaptive comfort theory, which states that people can adapt to local indoor environment and establish their thermal comfort. Recognising the human adaptability to local climate will direct flexible and optimized policy to protect public health against extreme temperature events. This will also help reduce energy consumption for regulating indoor temperature without compromising the occupants’ health.

Association between ambient temperature and mortality risk and burden: time series study in 272 main Chinese cities

ObjectivesTo examine the association between temperature and cause specific mortality, and to quantify the corresponding disease burden attributable to non-optimum ambient temperatures.DesignTime series analysis.Setting272 main cities in China.PopulationNon-accidental deaths in...

Heat waves in South Korea: differences of heat wave characteristics by thermal indices.

Heat wave warning systems and related research define heat waves using various indices and there exists no standard definition for a heat wave. Despite various weather forecast services for heat stress in South Korea, it is unclear how different thermal indices affect the designation of heat waves and health effect estimates. We aimed to analyze trends of heat wave characteristics and mortality associations using various criteria for the warm season (June-September) in 2011-5 for the most populated two cities in South Korea, Seoul and Busan. Hourly weather monitoring data and daily mortality data in each city were obtained. The following indices were estimated to define heat waves: air temperature, heat index (HI), humidex, apparent temperature (AT), effective temperature (ET), and wet-bulb globe temperature (WBGT). The thresholds of each index for heat wave definitions were obtained by statistical distribution (95th percentiles) and minimum mortality temperature (MMT). Thermal indices showed clustering of accumulation of excess heat above thresholds for northeast regions in the cities while air temperature showed it for central regions. Compared to 95th percentiles, the MMTs resulted 14 times longer heat wave days for thermal indices except for air temperature. When MMTs were used, nine times larger excess mortality from heat waves occurred for all indices compared to that from heat waves defined by the 95th percentiles. The thermal indices with the highest association between heat and mortality varied between the two cities: air temperature for Seoul and WBGT for Busan. Heat wave warnings should be based on a thorough comparison of how different heat wave criteria will affect the public health impact of heat wave warnings in terms of identifying a heat wave and degree of health impacts due to it.

Associations of Temperature Variation and Mortality in 47 Japanese Prefectures

Background / Aim: Few studies have investigated the mortality effects of temperature variation (TV) in Japan. In this study, we employed the newly proposed indicators of inter- and intra-day TVs computed separately using daily mean temperatures above or below the minimum mortality temperature to assess the TV-mortality associations and their relative contribution in comparison to daily mean temperature across Japan.Methods: We collected daily data on temperature and mortality during 1972-2012 from 47 Japanese prefectures. We performed a quasi-Poisson regression analysis incorporating a distributed-lag non-linear model to estimate associations of daily mean temperature, inter- and intra-day TVs with mortality in each prefecture.Results: Most prefectures showed a significant increase in mortality risk associated with daily mean temperature, with relative risks (RRs) reaching 1.236 (95% confidence interval (CI): 1.163, 1.313) for heat in Aomori, and 1.676 (95% CI: 1.313, 2.138) for cold in Wakayama. Inconsistent results for inter- / intra-day TVs were found, except for some protective associations between intra-day TV and mortality in Kochi (RR 0.979; 95% CI: 0.965, 0.993) and Gifu (RR 0.988; 95% CI: 0.98, 0.996) on cold days.Conclusion: We found that the association between mortality and TV was generally small compared with daily mean temperature in Japan.Acknowledgement: this research was supported by the Environmental Research and Technology Development Fund (S-10 & S-14) of the Ministry of the Environment, Japan.

Temperature-Related Mortality in Latin America: A Multi-City Multi-Country Study

BackgroundAttributable mortality risk for heat and cold has been investigated in Europe and North America. However, none so far has provided estimates for Latin American, with a whole temperature range in different climates. We aimed to estimate the mortality attributable to heat and cold in the Latin American countries participating in the Multi-City Multi-Country Collaborative Research Network, and study their heterogeneity of effects by climatic zones.MethodsWe collected data for 40 cities in Argentina, Brazil, Chile, Colombia and Mexico, between 1997-2015, totalling over 9 million deaths. We conducted a two-stage approach. Firstly, we estimated city-specific temperature-mortality associations using quasi-Poisson regression with distributed lag non-linear models with 21 days of lag. We calculated attributable deaths for heat and cold above and below the city-specific minimum mortality temperature using cutoffs at the 2.5th and 97.5th temperature percentiles. Next, we combined city-specific estimates using meta-regression including indicator variables for the country and climatic zone.ResultsMore temperature-attributable deaths were caused by cold (4.1%, 95%CI=[3.2 to 5.0%]) than by heat (0.7%, 95%CI=[0.4 to 0.9%]). This was observed consistently in all countries. Larger mortality was attributable to cold in dry and temperate than in tropical climates. While for heat, attributable mortality was larger in dry than in tropical and temperate climates.DiscussionMost of the temperature-related mortality burden in Latin American is attributable to the contribution of cold and mainly observed in dry climates. This could be of relevance to developing public-health interventions in the region to minimize the adverse health effects of temperatures.On behalf of the MCC Collaborative Research Network.

Heat and cold related-mortality in 18 French cities

ObjectivesUnderstanding the dynamics of the temperature-mortality relationship is an asset to support public health interventions. We investigated the lag structure of the mortality response to cold and warm temperatures in 18 French cities between 2000 and 2010. MethodsA distributed lag non-linear generalized model using a quasi-Poisson distribution and controlling for classical confounding factors was built in each city. A fitted meta-analytical model combined the city-specific models to derive the best linear unbiased prediction of the association, and a meta-regression explored the influence of background characteristics of the cities. The fraction of mortality attributable to cold and heat was estimated with reference to the minimum mortality temperature. ResultsBetween 2000 and 2010, 3.9% [CI 95% 3.2:4.6] of the total mortality was attributed to cold, and 1.2% [1.1:1.2] to heat. The immediate increase in mortality following high temperatures was partly compensated by a harvesting effect when temperatures were below the 99.2 percentiles of the mean temperature distributions. DiscussionCold represents a significant public health burden, mostly driven by moderate temperatures (between percentiles 2.5 and 25). The population is better adapted to warm temperatures, up to a certain intensity when heat becomes an acute environmental health emergency (above percentile 99). The rapid increase in mortality risk at very high temperatures percentiles calls for an active adaptation in a context of climate change.

Changing Susceptibility to Non-Optimum Temperatures in Japan, 1972-2012: The Role of Climate, Demographic, and Socioeconomic Factors.

Background:Previous studies have shown that population susceptibility to non-optimum temperatures has changed over time, but little is known about the related time-varying factors that underlie the changes.Objective:Our objective was to investigate the changing population susceptibility to non-optimum temperatures in 47 prefectures of Japan over four decades from 1972 to 2012, addressing three aspects: minimum mortality temperature (MMT) and heat- and cold-related mortality risks. In addition, we aimed to examine how these aspects of susceptibility were associated with climate, demographic, and socioeconomic variables.Methods:We first used a two-stage time-series design with a time-varying distributed lag nonlinear model and multivariate meta-analysis to estimate the time-varying MMT, heat- and cold-related mortality risks. We then applied linear mixed effects models to investigate the association between each of the three time-varying aspects of susceptibility and various time-varying factors.Results:MMT increased from 23.2 [95% confidence interval (CI): 23, 23.6] to 28.7 (27.0, 29.7) °C. Heat-related mortality risk [relative risk (RR) for the 99th percentile of temperature vs. the MMT] decreased from 1.18 (1.15, 1.21) to 1.01 (0.98, 1.04). Cold-related mortality risk (RR for the first percentile vs. the MMT) generally decreased from 1.48 (1.41, 1.54) to 1.35 (1.32, 1.40), with the exception of a few eastern prefectures that showed increased risk. The changing patterns in all three aspects differed by region, sex, and causes of death. Higher mean temperature was associated () with lower heat risk, whereas higher humidity was associated with higher cold risk. A higher percentage of elderly people was associated with a higher cold risk, whereas higher economic strength of the prefecture was related to lower cold risk.Conclusions:Population susceptibility to heat has decreased over the last four decades in Japan. Susceptibility to cold has decreased overall except for several eastern prefectures where it has either increased or remained unchanged. Certain climate, demographic, and socioeconomic factors explored in the current study might underlie this changing susceptibility. https://doi.org/10.1289/EHP2546

The temperature–mortality relationship: an analysis from 31 Chinese provincial capital cities

ABSTRACTWe aim to explore the Minimum Mortality Temperature (MMT) of different cities and regions, and that provides evidence for developing reasonable heat wave definition in China. The death data of 31 Chinese provincial capital cities from seven geographical regions during 2008–2013 was included in this study. In the first stage, a DLNM (Distributed Lag Non-linear Model) was used to estimate the association between mean temperature and mortality in a single city, then we pooled them with a multivariate meta-analysis to estimate the region-specific effects. The range of MMT was from 17.4 °C (Shijiazhuang) to 28.4 °C (Haikou), and the regional MMT increased as the original latitude decreased. Different cities and regions have their own specialized MMT due to geography and demographic characteristics. These findings indicate that the government deserves to adjust measures to local conditions to develop public health policies.

Regional Assessment of Temperature-Related Mortality in Finland.

The aim of this study was to assess regional differences in temperature–mortality relationships across 21 hospital districts in Finland. The temperature dependence of the daily number of all-cause, all-aged deaths during 2000–2014 was studied in each hospital district by using daily mean temperatures, spatially averaged across each hospital district, to describe exposure to heat stress and cold stress. The relationships were modelled using distributed lag non-linear models (DLNM). In a simple model version, no delayed impacts of heat and cold on mortality were taken into account, whereas a more complex version included delayed impacts up to 25 days. A meta-analysis with selected climatic and sociodemographic covariates was conducted to study differences in the relationships between hospital districts. A pooled mortality-temperature relationship was produced to describe the average relationship in Finland. The simple DLNM model version without lag gave U-shaped dependencies of mortality on temperature almost without exception. The outputs of the model version with a 25-day lag were also U-shaped in most hospital districts. According to the meta-analysis, the differences in the temperature-mortality relationships between hospital districts were not statistically significant on the absolute temperature scale, meaning that the pooled mortality–temperature relationship can be applied to the whole country. However, on a relative temperature scale, heterogeneity was found, and the meta-regression suggested that morbidity index and population in the hospital districts might explain some of this heterogeneity. The pooled estimate for the relative risk (RR) of mortality at a daily mean temperature of 24 °C was 1.16 (95% CI 1.12–1.20) with reference at 14 °C, which is the minimum mortality temperature (MMT) of the pooled relationship. On the cold side, the RR at a daily mean temperature of −20 °C was 1.14 (95% CI 1.12–1.16). On a relative scale of daily mean temperature, the MMT was found at the 79th percentile.

Adaptation to Heat and Cold in the Context of a Changing Climate: A Multi-Country Analysis

Background/Aim: The net impact of global warming will depend on the extent to which adaptation overcomes the effect of gradual changes in temperature. Disentangling the two processes is critical to provide accurate projections of future temperature-related impacts under climate change scenarios. We present evidence from a multi-country investigation that assessed temporal trends in mortality attributed to both heat and cold, and adaptation. Methods: We collected data from 305 locations in 10 countries between 1985 and 2012. Temporal trends in country-specific attributable mortality fractions (AF) for heat/cold (temperatures above/below minimum mortality temperature) were estimated using a two-stage time series design with time-varying distributed lag non-linear models and multivariate meta-analysis. To disentangle the contribution of adaptation from changes in attributable mortality due to gradual increases in temperature, we compared yearly AF with those predicted assuming either temperature distribution or exposure-response relationships as constant across the study period, respectively. Results: Heat-AF decreased in all countries except Australia and United Kingdom, from 0.45-1.39% in the first to 0.15-0.93% in the last 5-year periods, respectively. Different patterns were found for cold, with ranges from 5.56-15.43% to 2.17-8.54%, showing either decreasing (Japan, Spain, Australia, Ireland), increasing (US), or stable trends (Canada, South Korea, United Kingdom). We found inconsistent patterns in Brazil and Switzerland and a null heat-impact in Ireland. Long-term trends were mostly captured by temporal variation in exposure-response associations (interpreted as adaptation), while year-to-year fluctuations were driven by changes in temperature distribution. Conclusions: Our findings indicate that heat-mortality impacts decreased in most countries consistent with previous studies, whereas cold-mortality exhibited heterogeneous trends. In addition, the pace of adaptation has been faster than the observed warming, suggesting there is scope for the implementation of effective public health policies under climate change. Further investigations should focus on identification of the factors responsible for these adaptation trends.

A multi-country analysis on potential adaptive mechanisms to cold and heat in a changing climate

BackgroundTemporal variation of temperature-health associations depends on the combination of two pathways: pure adaptation to increasingly warmer temperatures due to climate change, and other attenuation mechanisms due to non-climate factors such as infrastructural changes and improved health care. Disentangling these pathways is critical for assessing climate change impacts and for planning public health and climate policies. We present evidence on this topic by assessing temporal trends in cold- and heat-attributable mortality risks in a multi-country investigation. MethodsTrends in country-specific attributable mortality fractions (AFs) for cold and heat (defined as below/above minimum mortality temperature, respectively) in 305 locations within 10 countries (1985–2012) were estimated using a two-stage time-series design with time-varying distributed lag non-linear models. To separate the contribution of pure adaptation to increasing temperatures and active changes in susceptibility (non-climate driven mechanisms) to heat and cold, we compared observed yearly-AFs with those predicted in two counterfactual scenarios: trends driven by either (1) changes in exposure-response function (assuming a constant temperature distribution), (2) or changes in temperature distribution (assuming constant exposure-response relationships). This comparison provides insights about the potential mechanisms and pace of adaptation in each population. ResultsHeat-related AFs decreased in all countries (ranging from 0.45–1.66% to 0.15–0.93%, in the first and last 5-year periods, respectively) except in Australia, Ireland and UK. Different patterns were found for cold (where AFs ranged from 5.57–15.43% to 2.16–8.91%), showing either decreasing (Brazil, Japan, Spain, Australia and Ireland), increasing (USA), or stable trends (Canada, South Korea and UK). Heat-AF trends were mostly driven by changes in exposure-response associations due to modified susceptibility to temperature, whereas no clear patterns were observed for cold. ConclusionsOur findings suggest a decrease in heat-mortality impacts over the past decades, well beyond those expected from a pure adaptation to changes in temperature due to the observed warming. This indicates that there is scope for the development of public health strategies to mitigate heat-related climate change impacts. In contrast, no clear conclusions were found for cold. Further investigations should focus on identification of factors defining these changes in susceptibility.

The association between ambient temperature and mortality in South Africa: A time-series analysis

BackgroundThere is an extensive literature describing temperature-mortality associations in developed regions, but research from developing countries, and Africa in particular, is limited. MethodsWe conducted a time-series analysis using daily temperature data and a national dataset of all 8.8 million recorded deaths in South Africa between 1997 and 2013. Mortality and temperature data were linked at the district municipality level and relationships were estimated with a distributed lag non-linear model with 21 days of lag, and pooled in a multivariate meta-analysis. ResultsWe found an association between daily maximum temperature and mortality. The relative risk for all-age all-cause mortality on very cold and hot days (1st and 99th percentile of the temperature distribution) was 1.14 (1.10,1.17) and 1.06 (1.03,1.09), respectively, when compared to the minimum mortality temperature. This “U” shaped relationship was evident for every age and cause group investigated, except among 25–44 year olds. The strongest associations were in the youngest (< 5) and oldest (> 64) age groups and for cardiorespiratory causes. Heat effects occurred immediately after exposure but diminished quickly whereas cold effects were delayed but persistent. Overall, 3.4% of deaths (~ 290,000) in South Africa were attributable to non-optimum temperatures over the study period. We also present results for the 52 district municipalities individually. ConclusionsAn assessment of the largest-ever dataset for analyzing temperature-mortality associations in (South) Africa indicates mortality burdens associated with cold and heat, and identifies the young and elderly as particularly vulnerable.

Study on influence of air temperature on daily chronic obstructive pulmonary disease mortality in Ningbo

Objective: To study the influence of daily air temperature on daily chronic obstructive pulmonary disease (COPD) mortality in residents in Ningbo. Methods: A time-series analysis using distributional lag non-linear model (DLNM) was conducted to estimate the attributable numbers and fraction of average air temperature on the daily COPD mortality in Ningbo from 2011 to 2016, by controlling the long-term time trend, day of week, air pollutants and other weather variables. Results: A reverse J-shape relationship was found between the average air temperature and COPD mortality, and the minimum-mortality temperature (MMT) was 25.5 ℃. The relative risks of extreme low and extreme high air temperature over lag 0-14 d were 2.767 (95%CI: 1.950-3.928) and 1.197 (95%CI: 1.021-1.404). In total, 31.62% (95%CI: 23.05%-38.89%) of COPD mortality (4 963 cases, 95%CI: 3 469-6 027) was attributable to non-MMT exposure, More attributable deaths were due to low air temperature, with a fraction of 30.41% corresponding to 4 772 deaths, compared with 1.22% and 192 deaths due to high air temperature. Low air temperature and high temperature were more likely to influence the mortality in females and those aged ≥65 years, but the influence was not significant in people aged <65 years. Conclusion: Both high and low air temperature were associated with an increased risk of COPD mortality in residents in Ningbo, especially during cold season, related measures on disease prevention should be taken to protect vulnerable population to reduce the risk of COPD mortality.

Longer-Term Impact of High and Low Temperature on Mortality: An International Study to Clarify Length of Mortality Displacement.

Background:In many places, daily mortality has been shown to increase after days with particularly high or low temperatures, but such daily time-series studies cannot identify whether such increases reflect substantial life shortening or short-term displacement of deaths (harvesting).Objectives:To clarify this issue, we estimated the association between annual mortality and annual summaries of heat and cold in 278 locations from 12 countries.Methods:Indices of annual heat and cold were used as predictors in regressions of annual mortality in each location, allowing for trends over time and clustering of annual count anomalies by country and pooling estimates using meta-regression. We used two indices of annual heat and cold based on preliminary standard daily analyses: a) mean annual degrees above/below minimum mortality temperature (MMT), and b) estimated fractions of deaths attributed to heat and cold. The first index was simpler and matched previous related research; the second was added because it allowed the interpretation that coefficients equal to 0 and 1 are consistent with none (0) or all (1) of the deaths attributable in daily analyses being displaced by at least 1 y.Results:On average, regression coefficients of annual mortality on heat and cold mean degrees were 1.7% [95% confidence interval (CI): 0.3, 3.1] and 1.1% (95% CI: 0.6, 1.6) per degree, respectively, and daily attributable fractions were 0.8 (95% CI: 0.2, 1.3) and 1.1 (95% CI: 0.9, 1.4). The proximity of the latter coefficients to 1.0 provides evidence that most deaths found attributable to heat and cold in daily analyses were brought forward by at least 1 y. Estimates were broadly robust to alternative model assumptions.Conclusions:These results provide strong evidence that most deaths associated in daily analyses with heat and cold are displaced by at least 1 y. https://doi.org/10.1289/EHP1756

Monte Carlo simulation-based estimation for the minimum mortality temperature in temperature-mortality association study

BackgroundRich literature has reported that there exists a nonlinear association between temperature and mortality. One important feature in the temperature-mortality association is the minimum mortality temperature (MMT). The commonly used approach for estimating the MMT is to determine the MMT as the temperature at which mortality is minimized in the estimated temperature-mortality association curve. Also, an approximate bootstrap approach was proposed to calculate the standard errors and the confidence interval for the MMT. However, the statistical properties of these methods were not fully studied.MethodsOur research assessed the statistical properties of the previously proposed methods in various types of the temperature-mortality association. We also suggested an alternative approach to provide a point and an interval estimates for the MMT, which improve upon the previous approach if some prior knowledge is available on the MMT. We compare the previous and alternative methods through a simulation study and an application. In addition, as the MMT is often used as a reference temperature to calculate the cold- and heat-related relative risk (RR), we examined how the uncertainty in the MMT affects the estimation of the RRs.ResultsThe previously proposed method of estimating the MMT as a point (indicated as Argmin2) may increase bias or mean squared error in some types of temperature-mortality association. The approximate bootstrap method to calculate the confidence interval (indicated as Empirical1) performs properly achieving near 95% coverage but the length can be unnecessarily extremely large in some types of the association. We showed that an alternative approach (indicated as Empirical2), which can be applied if some prior knowledge is available on the MMT, works better reducing the bias and the mean squared error in point estimation and achieving near 95% coverage while shortening the length of the interval estimates.ConclusionsThe Monte Carlo simulation-based approach to estimate the MMT either as a point or as an interval was shown to perform well particularly when some prior knowledge is incorporated to reduce the uncertainty. The MMT uncertainty also can affect the estimation for the MMT-referenced RR and ignoring the MMT uncertainty in the RR estimation may lead to invalid results with respect to the bias in point estimation and the coverage in interval estimation.

Seasonal variations of temperature-related mortality burden from cardiovascular disease and myocardial infarction in China

Incidence rate of cardiovascular disease (CVD) has significant seasonal trend, being higher in winter. However, the extent to which the seasonal variation of CVD deaths was caused by temperature remains unclear. We obtained daily data on temperature and CVD and myocardial infarction (MI) mortality from nine Chinese mega-cities during 2007–2013. Distributed lag non-linear models were applied to assess the city-specific temperature-related daily excess deaths across lag 0–21 days, using the minimum-mortality temperature as reference. Then, estimates of excess deaths in four seasons were separately aggregated from the daily series, and its ratio to the corresponding total deaths produced seasonal attributable fraction (AF). In total, 1,079,622 CVD and 201,897 MI deaths were recorded in the nine Chinese cities. Significant and non-linear associations between temperature and mortality were observed, with a total of 195,516 CVD and 50,658 MI deaths attributable to non-optimum temperatures. 103,439 (95% empirical CI: 54,475–141,537) CVD and 24,613 (5891–36,279) MI deaths related to non-optimum temperature occurred in winter, compared with 15,923 (1436–28,853) and 4946 (-325-9016) in summer. Temperature-related AFs were higher among MI than CVD, with AFs of 42% (9–62%) and 35% (19–48%) in winter, and 13% (-1-23%) and 8% (1–14%) in summer, respectively. This study may have important implications for developing effective targeted intervention measures on CVD events.