Brief Report: Investigating Uncertainty in the Minimum Mortality Temperature: Methods and Application to 52 Spanish Cities

Temporal trends in temperature-related mortality and evidence for maladaptation to heat and cold in the Eastern Mediterranean region

The eastern Mediterranean region is characterized by rising temperature trends exceeding the corresponding global averages and is considered a climate change hot-spot. Although previous studies have thoroughly investigated the impact of extreme heat and cold on human mortality and morbidity, both for the current and future climate change scenarios, the temporal trends in temperature-related mortality or the potential historical adaptation to heat and cold extremes has never been studied in this region. This study focuses on cardiovascular mortality and assesses the temporal evolution of the Minimum Mortality Temperature (MMT), as well as the disease-specific cold- and heat-attributable fraction of mortality in three typical eastern Mediterranean environments (Athens, Thessaloniki and Cyprus). Data on daily cardiovascular mortality (ICD-10 code: I00-I99) and meteorological parameters were available between 1999 and 2019 for Athens, 1999 to 2018 for Thessaloniki and 2004 to 2019 for Cyprus. Estimation of cardiovascular MMT and mortality fractions relied on time-series Poisson regressions with distributed lag nonlinear models (DLNM) controlling for seasonal and long-term trends, performed over a series of rolling sub-periods at each site. The results indicated that in Athens, the MMT decreased from 23 °C (67.5th percentile) in 1999-2007 to 21.8 °C (62nd percentile) in 2011-2019, while in Cyprus the MMT decreased from 26.3 °C (79th percentile) in 2004-2012 to 23.9 °C (66.5th percentile) in 2011-2019. In Thessaloniki, the decrease in MMT was rather negligible. In all regions under study, the fractions of mortality attributed to both cold and heat followed an upward trend throughout the years. In conclusion, the demonstrated increase in cold attributable fraction and the decreasing temporal trend of MMT across the examined sites are suggestive of maladaptation to extreme temperatures in regions with warm climate and highlight the need for relevant public health policies and interventions.

Spatial Bayesian distributed lag non-linear models (SB-DLNM) for small-area exposure-lag-response epidemiological modelling

BACKGROUND

Distributed lag non-linear models (DLNMs) are the reference framework for modelling lagged non-linear associations. They are usually used in large-scale multi-location studies. Attempts to study these associations in small areas either did not include the lagged non-linear effects, did not allow for geographically-varying risks or downscaled risks from larger spatial units through socioeconomic and physical meta-predictors when the estimation of the risks was not feasible due to low statistical power.

METHODS

Here we proposed spatial Bayesian DLNMs (SB-DLNMs) as a new framework for the estimation of reliable small-area lagged non-linear associations, and demonstrated the methodology for the case study of the temperature-mortality relationship in the 73 neighbourhoods of the city of Barcelona. We generalized location-independent DLNMs to the Bayesian framework (B-DLNMs), and extended them to SB-DLNMs by incorporating spatial models in a single-stage approach that accounts for the spatial dependence between risks.

RESULTS

The results of the case study highlighted the benefits of incorporating the spatial component for small-area analysis. Estimates obtained from independent B-DLNMs were unstable and unreliable, particularly in neighbourhoods with very low numbers of deaths. SB-DLNMs addressed these instabilities by incorporating spatial dependencies, resulting in more plausible and coherent estimates and revealing hidden spatial patterns. In addition, the Bayesian framework enriches the range of estimates and tests that can be used in both large- and small-area studies.

CONCLUSIONS

SB-DLNMs account for spatial structures in the risk associations across small areas. By modelling spatial differences, SB-DLNMs facilitate the direct estimation of non-linear exposure-response lagged associations at the small-area level, even in areas with as few as 19 deaths. The manuscript includes an illustrative code to reproduce the results, and to facilitate the implementation of other case studies by other researchers.

Short-term association between air temperature and mortality in seven cities in Norway: A time series analysis

BACKGROUND

The association between ambient air temperature and mortality has not been assessed in Norway. This study aimed to quantify for seven Norwegian cities (Oslo, Bergen, Stavanger, Drammen, Fredrikstad, Trondheim and Tromsø) the non-accidental, cardiovascular and respiratory diseases mortality burden due to non-optimal ambient temperatures.

METHODS

We used a historical daily dataset (1996-2018) to perform city-specific analyses with a distributed lag non-linear model with 14 days of lag, and pooled results in a multivariate meta-regression. We calculated attributable deaths for heat and cold, defined as days with temperatures above and below the city-specific optimum temperature. We further divided temperatures into moderate and extreme using cut-offs at the 1st and 99th percentiles.

RESULTS

We observed that 5.3% (95% confidence interval (CI) 2.0-8.3) of the non-accidental related deaths, 11.8% (95% CI 6.4-16.4) of the cardiovascular and 5.9% (95% CI -4.0 to 14.3) of the respiratory were attributable to non-optimal temperatures. Notable variations were found between cities and subgroups stratified by sex and age. The mortality burden related to cold dominated in all three health outcomes (5.1%, 2.0-8.1, 11.4%, 6.0-15.4, and 5.1%, -5.5 to 13.8 respectively). Heat had a more pronounced effect on the burden of respiratory deaths (0.9%, 0.2-1.0). Extreme cold accounted for 0.2% of non-accidental deaths and 0.3% of cardiovascular and respiratory deaths, while extreme heat contributed to 0.2% of non-accidental and to 0.3% of respiratory deaths.

CONCLUSIONS

Most of the burden could be attributed to the contribution of moderate cold. This evidence has significant implications for enhancing public-health policies to better address health consequences in the Norwegian setting.

Impact of population aging on future temperature-related mortality at different global warming levels

Older adults are generally amongst the most vulnerable to heat and cold. While temperature-related health impacts are projected to increase with global warming, the influence of population aging on these trends remains unclear. Here we show that at 1.5 °C, 2 °C, and 3 °C of global warming, heat-related mortality in 800 locations across 50 countries/areas will increase by 0.5%, 1.0%, and 2.5%, respectively; among which 1 in 5 to 1 in 4 heat-related deaths can be attributed to population aging. Despite a projected decrease in cold-related mortality due to progressive warming alone, population aging will mostly counteract this trend, leading to a net increase in cold-related mortality by 0.1%-0.4% at 1.5-3 °C global warming. Our findings indicate that population aging constitutes a crucial driver for future heat- and cold-related deaths, with increasing mortality burden for both heat and cold due to the aging population.

Heat-Related Mortality in the Extreme Summer of 2022

BACKGROUND

Estimating the excess mortality attributable to heat is a central element of the documentation of the consequences of climate change for human health. Until now, estimates of heatrelated deaths in Germany by the Robert Koch Institute (RKI) have been based on weekly mortality records.

METHODS

Our study is the first to use higher resolution data-i.e. daily all-cause mortality linked to daily mean temperatures-from each of the German federal states to assess the heat-related mortality from 2000 to 2023 in Germany, employing quasi-Poisson models and multivariate meta-regression analyses. We focus our analysis on the extreme summer of 2022.

RESULTS

Our analysis yielded an estimate of 9100 (95% CI: [7300; 10 700]) heat-related deaths in Germany for the summer of 2022, whereas previous studies of the RKI estimated the number of heatrelated deaths at 4500 [2100; 7000]. When we set a higher temperature threshold in the definition of the heat risk, we arrived at a figure of 6900 [5500; 8100] heat-related deaths in 2022. In other summers that-similarly to 2022-were characterized by large fluctuations in daily mean temperatures, we also robustly estimated higher numbers of heat-related deaths than the RKI did. The exclusion of reported deaths due to COVID-19 had only a minor effect on our estimates.

CONCLUSION

Our findings suggest that previous studies based on weekly mortality data have underestimated the full extent of heat-related mortality in Germany, particularly in the extreme summer of 2022. The monitoring of heat-related mortality should be systematic and as comprehensive as possible if it is to enable the development of effective heat-health action plans.

A Nationwide Comparative Analysis of Temperature-Related Mortality and Morbidity in Japan

BACKGROUND

The impact of temperature on morbidity remains largely unknown. Moreover, extensive evidence indicates contrasting patterns between temperature-mortality and temperature-morbidity associations. A nationwide comparison of the impact of temperature on mortality and morbidity in more specific subgroups is necessary to strengthen understanding and help explore underlying mechanisms by identifying susceptible populations.

OBJECTIVE

We performed this study to quantify and compare the impact of temperature on mortality and morbidity in 47 prefectures in Japan.

METHODS

We applied a two-stage time-series design with distributed lag nonlinear models and mixed-effect multivariate meta-analysis to assess the association of temperature with mortality and morbidity by causes (all-cause, circulatory, and respiratory) at prefecture and country levels between 2015 and 2019. Subgroup analysis was conducted by sex, age, and regions.

RESULTS

The patterns and magnitudes of temperature impacts on morbidity and mortality differed. For all-cause outcomes, cold exhibited larger effects on mortality, and heat showed larger effects on morbidity. At specific temperature percentiles, cold (first percentile) was associated with a higher relative risk (RR) of mortality [1.45; 95% confidence interval (CI): 1.39, 1.52] than morbidity (1.33; 95% CI: 1.26, 1.40), as compared to the minimum mortality/morbidity temperature. Heat (99th percentile) was associated with a higher risk of morbidity (1.30; 95% CI: 1.28, 1.33) than mortality (1.04; 95% CI: 1.02, 1.06). For cause-specific diseases, mortality due to circulatory diseases was more susceptible to heat and cold than morbidity. However, for respiratory diseases, both cold and heat showed higher risks for morbidity than mortality. Subgroup analyses suggested varied associations depending on specific outcomes.

DISCUSSION

Distinct patterns were observed for the association of temperature with mortality and morbidity, underlying different mechanisms of temperature on different end points, and the differences in population susceptibility are possible explanations. Future mitigation policies and preventive measures against nonoptimal temperatures should be specific to disease outcomes and targeted at susceptible populations. https://doi.org/10.1289/EHP12854.

Effects of air temperature on the risk of death from COPD in major microregions in Brazil: a time series study

OBJECTIVE

To evaluate the association between the risk of death from COPD and air temperature events in ten major Brazilian microregions.

METHODS

This was a time series analysis of daily COPD deaths and daily mean air temperatures between 1996 and 2017. Using distributed nonlinear lag models, we estimated the cumulative relative risks of COPD mortality for four temperature percentiles (representing moderate and extreme cold and heat events) in relation to a minimum mortality temperature, with a lag of 21 days, in each microregion.

RESULTS

Significant associations were found between extreme air temperature events and the risk of death from COPD in the southern and southeastern microregions in Brazil. There was an association of extreme cold and an increased mortality risk in the following microregions: 36% (95% CI, 1.12-1.65), in Porto Alegre; 27% (95% CI, 1.03-1.58), in Curitiba; and 34% (95% CI, 1.19-1.52), in São Paulo; whereas moderate cold was associated with an increased risk of 20% (95% CI, 1.01-1.41), 33% (95% CI, 1.09-1.62), and 24% (95% CI, 1.12-1.38) in the same microregions, respectively. There was an increased COPD mortality risk in the São Paulo and Rio de Janeiro microregions: 17% (95% CI, 1.05-1.31) and 12% (95% CI, 1,02-1,23), respectively, due to moderate heat, and 23% (95% CI, 1,09-1,38) and 32% (95% CI, 1,15-1,50) due to extreme heat.

CONCLUSIONS

Non-optimal air temperature events were associated with an increased risk of death from COPD in tropical and subtropical areas of Brazil.

High ambient temperatures associations with children and young adult injury emergency department visits in NYC

Injury is a significant health burden for children and young adult and may be an increasing concern in a warming climate. Research reveals many impacts to children's health associated with hot weather and heatwave events, including a growing literature on the association between high ambient temperature and injury, which may vary by intent such as injury resulting from violence. However, little is known about how this association varies across different types of injury and subgroups of young people. We examined relationships between warm season ambient temperature and intentional and unintentional injury among children and young adults in New York City (NYC). Within a case-crossover design, our study observed injury-related emergency department (ED) visits from the New York Statewide Planning and Research Cooperative System administrative dataset. Injuries were categorized as unintentional or intentional injuries during the warm season (May through September) in NYC from 2005 to 2011 among patients (0, 1-4, 5-9, 10-14, 15-19, 20-25 years old (y.o.)). Conditional logistic regression models with distributed lag non-linear functions were used to model the cumulative odds ratio (OR) injury-related ED visit over 0-5 lag days. Analyses were stratified by age group and sex to understand how associations vary across young people of different age and sex. There were a total of 572 535 injury-related ED visits. The largest effect of elevated temperature (daily minimum 77°F vs 48°F) was for unintentional injury among 5-9 y.o. (OR 1.32, 95% CI 1.23, 1.42) and for intentional injury among 20-25 y.o. (OR 1.54, 95% CI 1.28, 1.85). Further stratified analyses revealed that the highest risk of unintentional injury was among 5-9 y.o. males and 20-25 y.o. males for intentional injury. Our results suggest that high ambient temperatures are associated with higher odds of unintentional and intentional injuries among children. This work adds to a growing body of literature demonstrating the adverse impacts of heat on children, and suggests the need for messaging to parents and children about adopting adaptive strategies to prevent injuries when it is hot outside.

Urban heat island impacts on heat-related cardiovascular morbidity: A time series analysis of older adults in US metropolitan areas

Many United States (US) cities are experiencing urban heat islands (UHIs) and climate change-driven temperature increases. Extreme heat increases cardiovascular disease (CVD) risk, yet little is known about how this association varies with UHI intensity (UHII) within and between cities. We aimed to identify the urban populations most at-risk of and burdened by heat-related CVD morbidity in UHI-affected areas compared to unaffected areas. ZIP code-level daily counts of CVD hospitalizations among Medicare enrollees, aged 65-114, were obtained for 120 US metropolitan statistical areas (MSAs) between 2000 and 2017. Mean ambient temperature exposure was estimated by interpolating daily weather station observations. ZIP codes were classified as low and high UHII using the first and fourth quartiles of an existing surface UHII metric, weighted to each have 25% of all CVD hospitalizations. MSA-specific associations between ambient temperature and CVD hospitalization were estimated using quasi-Poisson regression with distributed lag non-linear models and pooled via multivariate meta-analyses. Across the US, extreme heat (MSA-specific 99th percentile, on average 28.6 °C) increased the risk of CVD hospitalization by 1.5% (95% CI: 0.4%, 2.6%), with considerable variation among MSAs. Extreme heat-related CVD hospitalization risk in high UHII areas (2.4% [95% CI: 0.4%, 4.3%]) exceeded that in low UHII areas (1.0% [95% CI: -0.8%, 2.8%]), with upwards of a 10% difference in some MSAs. During the 18-year study period, there were an estimated 37,028 (95% CI: 35,741, 37,988) heat-attributable CVD admissions. High UHII areas accounted for 35% of the total heat-related CVD burden, while low UHII areas accounted for 4%. High UHII disproportionately impacted already heat-vulnerable populations; females, individuals aged 75-114, and those with chronic conditions living in high UHII areas experienced the largest heat-related CVD impacts. Overall, extreme heat increased cardiovascular morbidity risk and burden in older urban populations, with UHIs exacerbating these impacts among those with existing vulnerabilities.

Gender inequalities in heat-related mortality in the Czech Republic

It is acknowledged that climate change exacerbates social inequalities, and women have been reported as more vulnerable to heat than men in many studies in Europe, including the Czech Republic. This study aimed at investigating the associations between daily temperature and mortality in the Czech Republic in the light of a sex and gender perspective, taking into account other factors such as age and marital status. Daily mean temperature and individual mortality data recorded during the five warmest months of the year (from May to September) over the period 1995-2019 were used to fit a quasi-Poisson regression model, which included a distributed lag non-linear model (DLNM) to account for the delayed and non-linear effects of temperature on mortality. The heat-related mortality risks obtained in each population group were expressed in terms of risk at the 99th percentile of summer temperature relative to the minimum mortality temperature. Women were found generally more at risk to die because of heat than men, and the difference was larger among people over 85 years old. Risks among married people were lower than risks among single, divorced, and widowed people, while risks in divorced women were significantly higher than in divorced men. This is a novel finding which highlights the potential role of gender inequalities in heat-related mortality. Our study underlines the relevance of including a sex and gender dimension in the analysis of the impacts of heat on the population and advocates the development of gender-based adaptation policies to extreme heat.

Atmospheric environment and severe acute respiratory infections in Nanjing, China, 2018-2019

The annual burden of severe acute respiratory infection (SARI) is enormous, and environmental factors may have a vital role in respiratory infections. This study aimed to investigate the potential effects of the atmospheric environment on SARI. A time-series analysis was performed on the relationship between atmospheric environment and 136,989 SARI cases by distributed lag non-linear model. Wind speed, PM₁₀, PM_2.5, O_3, and CO exhibited differential effects at a range of lag times or exposure ranges. Air pressure, temperature, and diurnal temperature range showed risk effects in the full range. The lag effect of high pollution was stronger, appeared earlier, and lasted longer than that of low pollution. Most environmental factors had a certain non-linear lag relationship with SARI. Low wind speed and high air pollution may be increasing risk factors for SARI.

Association of Ambient Temperature with Mortality in Resident and Multiethnic Transient Populations in a Desert Climate, 2006-2014

BACKGROUND

Although the association between ambient temperature and mortality in local populations is evident, this relationship remains unclear in transient populations (e.g., due to immigration, mass gatherings, or displacement). The holy city of Mecca annually shelters two populations comprising its residents and the transitory Hajj pilgrims (>2 million people from >180 countries). Both live side by side in a hot desert climate, rendering the development of evidence-based heat-protective measures challenging.

OBJECTIVES

We aimed to characterize the ambient temperature-mortality relationship and burden for the Mecca resident and Hajj transient populations, which have distinct levels of adaptation to ambient temperature.

METHODS

We analyzed daily air temperature and mortality data for Mecca residents and pilgrims over nine Hajj seasons between 2006 and 2014, using a fitted standard time-series Poisson model. We characterized the temperature-mortality relationship with a distributed lag nonlinear model with 10 d of lag. We determined the minimum mortality temperature (MMT) and attributable deaths for heat and cold for the two populations.

RESULTS

The median average daily temperature during the Hajj seasons was 30°C (19°C-37°C). There were 8,543 and 10,457 nonaccidental deaths reported during the study period among Mecca residents and pilgrims, respectively. The MMT was 2.5°C lower for pilgrims in comparison with the MMT for Mecca residents (23.5°C vs. 26.0°C). The temperature-mortality relationship shape varied from inverted J to U shape for the Mecca and pilgrim populations, respectively. Neither hot nor cold temperatures had a statistically significant association with mortality in Mecca residents. In contrast, for pilgrims, elevated temperatures were associated with significantly high attributable mortality of 70.8% [95% confidence interval (CI): 62.8, 76.0]. The effect of heat on pilgrims was immediate and sustained.

DISCUSSION

Our findings indicate that pilgrims and Mecca residents exposed to the same hot environmental conditions exhibited distinct health outcomes. This conclusion suggests that a precision public health approach may be warranted to protect against high environmental temperature during mass gatherings of diverse populations. https://doi.org/10.1289/EHP9838.

Changes in the temperature-mortality relationship in France: Limited evidence of adaptation to a new climate

CONTEXT

Documenting trends in the health impacts of ambient temperature is key to supporting adaptation strategies to climate change. This paper explores changes in the temperature-related mortality in 18 French urban centers between 1970 and 2015.

METHOD

A multicentric time-series design with time-varying distributed lag nonlinear models was adopted to model the shape of the relationship and assess temporal changes in risks and impacts.

RESULTS

The general shape of the temperature-mortality relationship did not change over time, except for an increasing risk at very low percentiles and a decreasing risk at very high percentiles. The relative risk at the 99.9^th percentile compared to the 50^th percentile of the 1970-2015 temperature distribution decreased from 2.33 [95% confidence interval (CI): 1.95:2.79] in 1975 to 1.33 [95% CI: 1.14:1.55] in 2015. Between 1970 and 2015, 302,456 [95% CI: 292,723:311,392] deaths were attributable to non-optimal temperatures, corresponding to 5.5% [95% CI: 5.3:5.6] of total mortality. This burden decreased progressively, representing 7.2% [95% CI: 6.7:7.7] of total mortality in the 1970s to 3.4% [95% CI: 3.2:3.6] in the 2000s. However, the contribution of hot temperatures to this burden (higher than the 90^th percentile) increased.

DISCUSSION

Despite the decreasing relative risk, the fraction of mortality attributable to extreme heat increased between 1970 and 2015, thus highlighting the need for proactive adaptation.

Analysis of the heat- and cold-related cardiovascular mortality in an urban mediterranean environment through various thermal indices

During the last decades the effects of thermal stress on public health have been a great concern worldwide. Thermal stress is determined by air temperature in combination with other meteorological parameters, such as relative humidity and wind speed. The present study is focused on the Mediterranean city of Thessaloniki, Greece and it aims to explore the association between thermal stress and mortality from cardiovascular diseases, using both air temperature and other thermal indices as indicators. For that, an over-dispersed Poisson regression function was used, in combination with distributed lag non-linear models, in order to capture the delayed and nonlinear effects of temperature. Our results revealed a reverse J-shaped exposure-response curve for the total population and females and a U-shaped association for males. In all cases examined, the minimum mortality temperature was identified around the 80th percentile of each distribution. It is noteworthy that despite the fact that the highest risks of cardiovascular mortality were estimated for exposure to extreme temperatures, moderate temperatures were found to cause the highest burden of mortality. On the whole, our estimations demonstrated that the population in Thessaloniki is more susceptible to cold effects and in regard with gender, females seem to be more vulnerable to ambient thermal conditions.

Trends in Temperature-associated Mortality in São Paulo (Brazil) between 2000 and 2018: an Example of Disparities in Adaptation to Cold and Heat

Exposure to non-optimal temperatures remains the single most deathful direct climate change impact to health. The risk varies based on the adaptation capacity of the exposed population which can be driven by climatic and/or non-climatic factors subject to fluctuations over time. We investigated temporal changes in the exposure-response relationship between daily mean temperature and mortality by cause of death, sex, age, and ethnicity in the megacity of São Paulo, Brazil (2000-2018). We fitted a quasi-Poisson regression model with time-varying distributed-lag non-linear model (tv-DLNM) to obtain annual estimates. We used two indicators of adaptation: trends in the annual minimum mortality temperature (MMT), i.e., temperature at which the mortality rate is the lowest, and in the cumulative relative risk (cRR) associated with extreme cold and heat. Finally, we evaluated their association with annual mean temperature and annual extreme cold and heat, respectively to assess the role of climatic and non-climatic drivers. In total, we investigated 4,471,000 deaths from non-external causes. We found significant temporal trends for both the MMT and cRR indicators. The former was decoupled from changes in AMT, whereas the latter showed some degree of alignment with extreme heat and cold, suggesting the role of both climatic and non-climatic adaptation drivers. Finally, changes in MMT and cRR varied substantially by sex, age, and ethnicity, exposing disparities in the adaptation capacity of these population groups. Our findings support the need for group-specific interventions and regular monitoring of the health risk to non-optimal temperatures to inform urban public health policies.

Extreme environmental temperatures and motorcycle crashes: a time-series analysis

Extreme temperature could affect traffic crashes by influencing road safety, vehicle performance, and drivers' behavior and abilities. Studies evaluating the impacts of extreme temperatures on the risk of traffic crashes have mainly overlooked the potential role of vehicle air conditioners. The aim of this study, therefore, was to evaluate the effect of exposure to extreme cold and hot temperatures on seeking medical attention due to motorcycle crashes. The study was conducted in Iran by using medical attendance for motorcycle crashes from March 2011 to June 2017. Data on daily minimum, mean and maximum temperature (°C), relative humidity (%), wind velocity (km/h), and precipitation (mm/day) were collected. We developed semi-parametric generalized additive models following a quasi-Poisson distribution with the distributed nonlinear lag model to estimate the immediate and lagged associations (reported as relative risk [RR], and 95% confidence interval [CI]). Between March 2011 and June 2017, 36,079 medical attendances due to motorcycle road traffic crashes were recorded (15.8 ± 5.92 victims per day). In this time period, the recorded temperature ranged from -11.2 to 45.4 °C (average: 25.5 ± 11.0 °C). We found an increased risk of medical attendance for motorcycle crashes (based on maximum daily temperature) at both extremely cold (1st percentile) and hot (99th percentile) temperatures and also hot (75th percentile) temperatures, mainly during lags 0 to 3 days (e.g., RR: 1.12 [95% CI: 1.05: 1.20]; RR: 1.08 [95% CI: 1.01: 1.16]; RR: 1.20 [95% CI: 1.09: 1.32] at lag0 for extremely cold, hot, and extremely hot conditions, respectively). The risk estimates for extremely hot temperatures were larger than hot and extremely cold temperatures. We estimated that 11.01% (95% CI: 7.77:14.06) of the medical attendance for motorcycle crashes is estimated to be attributable to non-optimal temperature (using mean temperature as exposure variable). Our findings have important public health messaging, given the considerable burden associated with road traffic injury, particularly in low- and middle-income countries.

Data supporting the short-term health effects of temperature and air pollution in Valencia, Spain

The data presented in this article is part in essence of a more extensive dataset aimed at evaluating patterns of change in the temperature–mortality relationship on population health in the city of Valencia, Spain on population health in the city of Valencia, Spain. The complete dataset was used in the framework of the European multi-city project PHASE (Public Health Adaptation Strategies to Extreme weather events) [1]. The data includes daily counts of all-cause mortality, excluding external causes and cardiovascular and respiratory diseases. All-cause mortality is also classified by gender and age groups. Besides temperature, we included other meteorological variables and air pollutants from the PHASE dataset, as well as influenza epidemics. The variable Saharan dust events was also added. All these data were collected from public Governmental data repositories accessible under request. The dataset of this article provides a basis for comparison with similar models for time-series regression, allowing researchers to integrate additional model components without duplication of effort.

Association between ambient temperature and cardiovascular disease hospitalisations among farmers in suburban northwest China

Cardiovascular disease (CVD) has become a severe public health and social issue in China. However, in northwest China, evidence on the association between ambient temperature and CVD hospitalisations in suburban farmers is somewhat limited. We collected CVD hospitalisations and meteorological data (2012-2015) in Zhangye suburbs and assessed the temperature-related risk and burden of admission by fitting a distributed lag nonlinear model to probe the relationship between ambient temperature and CVD hospitalisations among farmers in suburban northwest China. The results show that 23,921 cases of CVD admissions were recorded from 2012 to 2015. There was a "U-shaped" association between temperature and hospitalisations. Compared with the minimum admissions temperature (MAT) at 15.3 °C, the cumulative relative risk (RR) over lag 0-21 days was 1.369 (95% CI 0.980-1.911) for extreme cold temperature (1st percentile, -15 °C), 1.353 (95% CI 1.063-1.720) for moderate cold (5th percentile, -11 °C), 1.415 (95% CI 1.117-1.792) for extreme heat (99th percentile, 26 °C), and 1.241 (95% CI 1.053-1.464) for moderate heat (95th percentile, 24 °C). Female farmers were more susceptible to low and high temperatures than male farmers. Farmers aged ≥ 65 years old were more sensitive to low temperatures, while farmers aged < 65 years old were more sensitive to high temperatures. A total of 13.4% (3,208 cases) of the hospitalisation burden for CVD were attributed to temperature exposure, with the moderate range of temperatures accounting for the most significant proportion (12.2%). Ambient temperature, primarily moderate temperatures, might be an essential factor for cardiovascular-related hospitalisations among farmers in suburban northwest China.

Influence of temperature on mortality in the French overseas regions: a pledge for adaptation to heat in tropical marine climates

CONTEXT

Tropical areas and small islands are identified as highly vulnerable to climate change, and already experiencing shifts in their temperature distribution. However, the knowledge on the health impacts of temperatures under tropical marine climate is limited. We explored the influence of temperature on mortality in four French overseas regions located in French Guiana, French West Indies, and in the Indian Ocean, between 2000 and 2015.

METHOD

Distributed lag non-linear generalized models linking temperature and mortality were developed in each area, and relative risks were combined through a meta-analysis. Models were used to estimate the fraction of mortality attributable to non-optimal temperatures. The role of humidity was also investigated.

RESULTS

An increased risk of mortality was observed when the temperature deviated from median. Results were not modified when introducing humidity. Between 2000 and 2015, 979 deaths [confidence interval (CI) 95% 531:1359] were attributable to temperatures higher than the 90th percentile of the temperature distribution, and 442 [CI 95% 178:667] to temperature lower than the 10th percentile.

DISCUSSION

Heat already has a large impact on mortality in the French overseas regions. Results suggest that adaptation to heat is relevant under tropical marine climate.

Assessing seasonality and the role of its potential drivers in environmental epidemiology: a tutorial

Several methods have been used to assess the seasonality of health outcomes in epidemiological studies. However, little information is available on the methods to study the changes in seasonality before and after adjusting for environmental or other known seasonally varying factors. Such investigations will help us understand the role of these factors in seasonal variation in health outcomes and further identify currently unknown or unmeasured risk factors. This tutorial illustrates a statistical procedure for examining the seasonality of health outcomes and their changes, after adjusting for potential environmental drivers by assessing and comparing shape, timings and size. We recommend a three-step procedure, each carried out and compared before and after adjustment: (i) inspecting the fitted seasonal curve to determine the broad shape of seasonality; (ii) identifying the peak and trough of seasonality to determine the timings of seasonality; and (iii) estimating the peak-to-trough ratio and attributable fraction to measure the size of seasonality. Reporting changes in these features on adjusting for potential drivers allows readers to understand their role in seasonality and the nature of any residual seasonal pattern. Furthermore, the proposed approach can be extended to other health outcomes and environmental drivers.

Short-Term Effects of Apparent Temperature on Cause-Specific Mortality in the Urban Area of Thessaloniki, Greece

Although there is a growing interest in the association between ambient temperatures and mortality, little evidence is available for Thessaloniki, the second largest city of Greece. In this study, we present an assessment of the effects of temperature on daily mortality from 2006 to 2016 in the urban area of Thessaloniki, by describing the exposure-lag-response association between temperature and cause-specific mortality with the use of a distributed lag non-linear model (DLNM). A J-shaped relationship was found between temperature and mortality. The highest values of risk were evident for respiratory (RR > 10) and cardiovascular causes (RR > 3), probably due to the fact that health status of individuals with chronic respiratory and cardiovascular diseases rapidly deteriorates during hot periods. Cold effects had longer lags of up to 15 days, whereas heat effects were short-lived, up to 4 days. Percentage change in all- and cause-specific mortality per 1 °C change above and below Minimum Mortality Temperature showed a larger increase for all-cause mortality in heat (1.95%, 95% CI: 1.07–2.84), in contrast to a smaller increase in cold (0.54%, 95% CI: 0, 1.09). Overall, 3.51% of all-cause deaths were attributable to temperature, whereas deaths attributed to heat (2.34%) were more than deaths attributed to cold (1.34%). The findings of this study present important evidence for planning public-health interventions, to reduce the health impact of extreme temperatures.

Mortality Related to Air Temperature in European Cities, Based on Threshold Regression Models

There is a wealth of scientific literature that scrutinizes the relationship between mortality and temperature. The aim of this paper is to identify the nexus between temperature and three different causes of mortality (i.e., cardiological, respiratory, and cardiorespiratory) for three countries (Scotland, Spain, and Greece) and eleven cities (i.e., Glasgow, Edinburgh, Aberdeen, Dundee, Madrid, Barcelona, Valencia, Seville, Zaragoza, Attica, and Thessaloniki), emphasizing the differences among these cities and comparing them to gain a deeper understanding of the relationship. To quantify the association between temperature and mortality, temperature thresholds are defined for each city using a robust statistical analysis, namely threshold regression analysis. In a more detailed perspective, the threshold used is called Minimum Mortality Temperature (MMT), the temperature above or below which mortality is at minimum risk. Afterward, these thresholds are compared based on the geographical coordinates of each city. Our findings show that concerning all-causes of mortality under examination, the cities with higher latitude have lower temperature thresholds compared to the cities with lower latitude. The inclusion of the relationship between mortality and temperature in the array of upcoming climate change implications is critical since future climatic scenarios show an overall increase in the ambient temperature.

Sex differences in temperature-related all-cause mortality in the Netherlands

PURPOSE

Over the last few decades, a global increase in both cold and heat extremes has been observed with significant impacts on human mortality. Although it is well-identified that older individuals (> 65 years) are most prone to temperature-related mortality, there is no consensus on the effect of sex. The current study investigated if sex differences in temperature-related mortality exist in the Netherlands.

METHODS

Twenty-three-year ambient temperature data of the Netherlands were combined with daily mortality data which were subdivided into sex and three age classes (< 65 years, 65-80 years,  ≥ 80 years). Distributed lag non-linear models were used to analyze the effect of ambient temperature on mortality and determine sex differences in mortality attributable to the cold and heat, which is defined as mean daily temperatures below and above the Minimum Mortality Temperature, respectively.

RESULTS

Attributable fractions in the heat were higher in females, especially in the oldest group under extreme heat (≥ 97.5th percentile), whilst no sex differences were found in the cold. Cold- and heat-related mortality was most prominent in the oldest age group (≥ 80 years) and to a smaller extent in the age group between 65-80 years. In the age group < 65 years temperature-related mortality was only significant for males in the heat.

CONCLUSION

Mortality in the Netherlands represents the typical V- or hockey-stick shaped curve with a higher daily mortality in the cold and heat than at milder temperatures in both males and females, especially in the age group ≥ 80 years. Heat-related mortality was higher in females than in males, especially in the oldest age group (≥ 80 years) under extreme heat, whilst in the cold no sex differences were found. The underlying cause may be of physiological or behavioral nature, but more research is necessary.

Effects of ambient temperature on cardiovascular disease: a time-series analysis of 229288 deaths during 2009-2017 in Qingdao, China

The association between ambient temperature and cardiovascular mortality varied by regions, populations, and climates. We estimated the relative risk (RR) of cardiovascular mortality using 229,288 death cases of cardiovascular disease in Qingdao China from 1 January 2009, to 31 December 2017. A distributed lag non-linear model was used. The temperature showed a negative association with the cardiovascular mortality. The RR of cardiovascular death at -4.8 °C was 2.05 (95% CI: 1.55, 2.69). The high temperature had acute and short-term effects with the maximum risk occurring 0 day of exposure. The low temperature had the greatest effect on the 4th lag day. The cold temperature effect was stronger for males than females. The estimates of temperature-related cardiovascular mortality risk were higher in people age ≥75 years. Our study showed that the cold and hot ambient temperature had a relationship with the risk of cardiovascular mortality.

Heat and cold-related morbidity risk in north-east of Iran: a time-stratified case crossover design

This study aimed to estimate morbidity risk/number attributed to air extreme temperatures using time-stratified case crossover study and distributed lag non-linear model in a region of Iran during 2015-2019. A time-stratified case crossover design based on aggregated exposure data was used in this study. In order to have no overlap bias in the estimations, a fixed and disjointed window by using 1-month strata was used in the design. A conditional Poisson regression model allowing for over dispersion (Quasi-Poisson) was applied into Distributed Lag Non-linear Model (DLNM). Different approaches were applied to estimate Optimum Temperature (OT). In the model, the interaction effect between temperature and humidity was assessed to see if the impact of heat or cold on Hospital Admissions (HAs) are different between different levels of humidity. The cumulative effect of heat during 21 days was not significant and it was the cold that had significant cumulative adverse effect on all groups. While the number of HAs attributed to any ranges of heat, including medium, high, extreme, and even all values were negligible, but a large number was attributable to cold values; about 10000 HAs were attributable to all values of cold temperature, of which about 9000 were attributed to medium range and about 1000 and less than 500 were attributed to high and extreme values of cold, respectively. This study highlights the need for interventions in cold seasons by policymakers. The results inform researchers as well as policy makers to address both men and women and elderly when any plan or preventive program is developed in the area under study.

Geographical Variations of the Minimum Mortality Temperature at a Global Scale: A Multicountry Study

Background

Minimum mortality temperature (MMT) is an important indicator to assess the temperature-mortality association, indicating long-term adaptation to local climate. Limited evidence about the geographical variability of the MMT is available at a global scale.

Methods

We collected data from 658 communities in 43 countries under different climates. We estimated temperature-mortality associations to derive the MMT for each community using Poisson regression with distributed lag nonlinear models. We investigated the variation in MMT by climatic zone using a mixed-effects meta-analysis and explored the association with climatic and socioeconomic indicators.

Results

The geographical distribution of MMTs varied considerably by country between 14.2 and 31.1 °C decreasing by latitude. For climatic zones, the MMTs increased from alpine (13.0 °C) to continental (19.3 °C), temperate (21.7 °C), arid (24.5 °C), and tropical (26.5 °C). The MMT percentiles (MMTPs) corresponding to the MMTs decreased from temperate (79.5th) to continental (75.4th), arid (68.0th), tropical (58.5th), and alpine (41.4th). The MMTs indreased by 0.8 °C for a 1 °C rise in a community's annual mean temperature, and by 1 °C for a 1 °C rise in its SD. While the MMTP decreased by 0.3 centile points for a 1 °C rise in a community's annual mean temperature and by 1.3 for a 1 °C rise in its SD.

Conclusions

The geographical distribution of the MMTs and MMTPs is driven mainly by the mean annual temperature, which seems to be a valuable indicator of overall adaptation across populations. Our results suggest that populations have adapted to the average temperature, although there is still more room for adaptation.

Effects of ambient temperature and fall-related injuries in Ma'anshan, Anhui Province, China: a distributed lag nonlinear analysis

Despite the significant economic cost of falls and injuries to individuals and communities, little is known about the impact of meteorological factors on the incidence of fall-related injuries (FRIs). Therefore, a time-series study was conducted to explore the effects of meteorological factors on FRIs in Ma'anshan City, East China. Injury data from 2011 to 2017 were collected from the National Injury Monitoring Station in Ma'anshan City. A distributed lag nonlinear model was used in this study to evaluate the correlation between ambient temperature and fall injuries. The results showed a significant exposure-response relationship between temperature and FRIs in Ma'anshan City. The high temperatures increased the risk of FRIs (RR = 1.110; 95% CI, 1.005-1.225; lag 0). The lag effect appeared at lag 10 (RR = 1.032; 95% CI, 1.003-1.063), and then gradually remained stable after lag 25 (RR = 1.077; 95% CI, 1.045-1.110). The effect of ambient temperature varied with age and gender. The lag effect of high temperature appeared in the male group after lag 15 (RR = 1.042; 95% CI, 1.006-1.079). In contrast, the effect of the female group appeared for the first time at lag 0 (RR = 1.187; 95% CI, 1.042-1.352). And the ≥ 60 years subgroup seemed to be more sensitive in low temperature (RR = 1.017; 95% CI, 1.004-1.031; lag 0; RR = 1.003; 95% CI, 1.000-1.007; lag 25). The cumulative result is similar to the single-day effect. From the results, this study would help the establishment of fall-related injury prediction and provide evidence for the formulation and implementation of preventive strategies and measures in the future.

The association between temperature and cause-specific mortality in the Klang Valley, Malaysia

This study aims to examine the relationship between daily temperature and mortality in the Klang Valley, Malaysia, over the period 2006-2015. A quasi-Poisson generalized linear model combined with a distributed lag non-linear model (DLNM) was used to estimate the association between the mean temperature and mortality categories (natural n=69,542, cardiovascular n= 15,581, and respiratory disease n=10,119). Particulate matter with an aerodynamic diameter below 10 μm (PM₁₀) and surface ozone (O₃) was adjusted as a potential confounding factor. The relative risk (RR) of natural mortality associated with extreme cold temperature (1st percentile of temperature, 25.2 °C) over lags 0-28 days was 1.26 (95% confidence interval (CI): 1.00, 1.60), compared with the minimum mortality temperature (28.2 °C). The relative risk associated with extremely hot temperature (99th percentile of temperature, 30.2 °C) over lags 0-3 days was 1.09 (95% CI: 1.02, 1.17). Heat effects were immediate whereas cold effects were delayed and lasted longer. People with respiratory diseases, the elderly, and women were the most vulnerable groups when it came to the effects of extremely high temperatures. Extreme temperatures did not dramatically change the temperature-mortality risk estimates made before and after adjustments for air pollutant (PM₁₀ and O₃) levels.

Estimation of Heat-Attributable Mortality Using the Cross-Validated Best Temperature Metric in Switzerland and South Korea

This study presents a novel method for estimating the heat-attributable fractions (HAF) based on the cross-validated best temperature metric. We analyzed the association of eight temperature metrics (mean, maximum, minimum temperature, maximum temperature during daytime, minimum temperature during nighttime, and mean, maximum, and minimum apparent temperature) with mortality and performed the cross-validation method to select the best model in selected cities of Switzerland and South Korea from May to September of 1995-2015. It was observed that HAF estimated using different metrics varied by 2.69-4.09% in eight cities of Switzerland and by 0.61-0.90% in six cities of South Korea. Based on the cross-validation method, mean temperature was estimated to be the best metric, and it revealed that the HAF of Switzerland and South Korea were 3.29% and 0.72%, respectively. Furthermore, estimates of HAF were improved by selecting the best city-specific model for each city, that is, 3.34% for Switzerland and 0.78% for South Korea. To the best of our knowledge, this study is the first to observe the uncertainty of HAF estimation originated from the selection of temperature metric and to present the HAF estimation based on the cross-validation method.

Increased susceptibility to temperature variation for non-accidental emergency ambulance dispatches in Shenzhen, China

Most studies focused on the temporal trend of mortality risk associated with temperature exposure. The relative role of heat, cold, and temperature variation (TV) on morbidity and its temporal trends are explored insufficiently. This study aims to investigate the temporal trends of emergency ambulance dispatch (EAD) risk and the attributable burden of heat, cold, and hourly temperature variation (HTV). We collected time-series data of daily EAD and ambient temperature in Shenzhen from 2010 to 2017. HTV was calculated as the standard deviation of the hourly temperatures between 2 consecutive days. Quasi-Poisson generalized additive models (GAM) with a time-varying distributed lag nonlinear model (DLNM) were applied to examine temporal trends of the HTV-, heat-, and cold-EAD association. The temporal variation of the attributable fraction (AF%) and attributable number (AN) for different temperature exposures was also calculated. The largest RR was observed in extreme cold [1.30 (95% CI: 1.18, 1.43)] and moderate cold [1.25 (95% CI: 1.17, 1.34)]. Significant increasing trends in HTV-related effects and burden were observed, especially for the extreme HTV effects (P for interaction < 0.05). Decreasing trends were observed in the heat-related effect and burden, though it showed no significance (P for interaction = 0.46). There was no clear change pattern of cold-related effects and burdens. Overall, the three temperature exposure caused 13.7% of EAD, of which 4.1%, 4.3%, and 5.3% were attributed to HTV, heat, and cold, respectively. All the temperature indexes in this study, especially the cold effect, are responsible for the increased risk of EAD. People have become more susceptible to HTV over the recent decade. However, there is no clear evidence to support the temporal change of the population's susceptibility to heat and cold. Thus, in addition to heat and cold, the emergency ambulance service department should pay more attention to HTV under climate change.

Association between ambient temperature and childhood respiratory hospital visits in Beijing, China: a time-series study (2013-2017)

Little is known on the potential impact of temperature on respiratory morbidity, especially for children whose respiratory system can be more vulnerable to climate changes. In this time-series study, Poisson generalized additive models combined with distributed lag nonlinear models were used to assess the associations between ambient temperature and childhood respiratory morbidity. The impacts of extreme cold and hot temperatures were calculated as cumulative relative risks (cum.RRs) at the 1st and 99th temperature percentiles relative to the minimum morbidity temperature percentile. Attributable fractions of respiratory morbidity due to cold or heat were calculated for temperatures below or above the minimum morbidity temperature. Effect modifications by air pollution, age, and sex were assessed in stratified analyses. A total of 877,793 respiratory hospital visits of children under 14 years old between 2013 and 2017 were collected from Beijing Children's Hospital. Overall, we observed J-shaped associations with greater respiratory morbidity risks for exposure to lower temperatures, and higher fraction of all-cause respiratory hospital visits was caused by cold (33.1%) than by heat (0.9%). Relative to the minimum morbidity temperature (25 °C, except for rhinitis, which is 31 °C), the cum.RRs for extreme cold temperature (-6 °C) were 2.64 (95%CI: 1.51-4.61) for all-cause respiratory hospital visits, 2.73 (95%CI: 1.44-5.18) for upper respiratory infection, 2.76 (95%CI: 1.56-4.89) for bronchitis, 2.12 (95%CI: 1.30-3.47) for pneumonia, 2.06 (95%CI: 1.27-3.34) for rhinitis, and 4.02 (95%CI: 2.14-7.55) for asthma, whereas the associations between extreme hot temperature (29 °C) and respiratory hospital visits were not significant. The impacts of extreme cold temperature on asthma hospital visits were greater at higher levels of ozone (O₃) exposure (> 50th percentile). Our findings suggest significantly increased childhood respiratory morbidity risks at extreme cold temperature, and the impact of extreme cold temperature on asthma hospital visits can be enhanced under higher level exposure to O₃.

Time-series analysis of daily ambient temperature and emergency department visits in five US cities with a comparison of exposure metrics derived from 1-km meteorology products

BACKGROUND

Ambient temperature observations from single monitoring stations (usually located at the major international airport serving a city) are routinely used to estimate heat exposures in epidemiologic studies. This method of exposure assessment does not account for potential spatial variability in ambient temperature. In environmental health research, there is increasing interest in utilizing spatially-resolved exposure estimates to minimize exposure measurement error.

METHODS

We conducted time-series analyses to investigate short-term associations between daily temperature metrics and emergency department (ED) visits for well-established heat-related morbidities in five US cities that represent different climatic regions: Atlanta, Los Angeles, Phoenix, Salt Lake City, and San Francisco. In addition to airport monitoring stations, we derived several exposure estimates for each city using a national meteorology data product (Daymet) available at 1 km spatial resolution.

RESULTS

Across cities, we found positive associations between same-day temperature (maximum or minimum) and ED visits for heat-sensitive outcomes, including acute renal injury and fluid and electrolyte imbalance. We also found that exposure assessment methods accounting for spatial variability in temperature and at-risk population size often resulted in stronger relative risk estimates compared to the use of observations at airports. This pattern was most apparent when examining daily minimum temperature and in cities where the major airport is located further away from the urban center.

CONCLUSION

Epidemiologic studies based on single monitoring stations may underestimate the effect of temperature on morbidity when the station is less representative of the exposure of the at-risk population.

Impact of ambient temperature on cardiovascular disease hospital admissions in farmers in China's Western suburbs

Cardiovascular disease (CVD) has been a major threat to global public health. The association between temperature and CVD has been widely studied and reported in cities in developed countries. However, information from developing countries, especially from suburbs and countryside, is quite limited. In this study, the daily time series data on CVD hospital admissions in farmers in the suburbs of Tianshui, China, and the meteorological data from 2012 to 2015, were collected; besides, a quasi-Poisson regression with a distributed-lag non-linear model (DLNM) was used to explore the impact of local daily mean temperature on CVD hospital admissions in suburban farmers. This study found that, first, from 2011 to 2015, a total of 30,611 person-times of CVD hospital admissions in farmers were recorded; second, there was a "J-shaped" relation between temperature and CVD hospital admissions, and both low and high temperature increased the risk of hospital admission, but the impact of high temperature was greater; third, compared with the minimum hospitalization temperature (MHT) at 0.3 °C, during 0 to 21 lag days, the cumulative relative risk (RR) for extreme cold and heat (1st and 99th percentile of temperature, respectively) was 1.117 (95% CI 0.941-1.325) and 1.740 (95% CI 1.302-2.327), respectively, and that of moderate cold and heat (5st and 95th percentile of temperature, respectively) was 1.029 (95% CI 0.958-1.106) and 1.572 (95% CI 1.210-2.042), respectively; fourth, compared with male and ≥ 65 years groups, the risk for low temperature was greater for female and < 65 years groups, the risk for high temperature was just the opposite; last, about 21.04% of CVD hospital admissions burden were attributed to the ambient temperature, and most of (about 19.26%) were caused by moderate heat. In Tianshui, alongside with extreme temperature, the moderate temperature might be an important risk factor for CVD hospital admissions in suburban farmers.

Contrasting patterns of temperature related mortality and hospitalization by cardiovascular and respiratory diseases in 52 Spanish cities

BACKGROUND

Climate change is a severe public health challenge. Understanding to what extent fatal and non-fatal consequences of specific diseases are associated with temperature may help to improve the effectiveness of preventive public health efforts. This study examines the effects of temperature on deaths and hospital admissions by cardiovascular and respiratory diseases, empathizing the difference between mortality and morbidity.

METHODS

Daily counts for mortality and hospital admissions by cardiovascular and respiratory diseases were collected for the 52 provincial capital cities in Spain, between 1990 and 2014. The association with temperature in each city was investigated by means of distributed lag non-linear models using quasi-Poisson regression. City-specific exposure-response curves were pooled by multivariate random-effects meta-analysis to obtain countrywide risk estimates of mortality and hospitalizations due to heat and cold, and attributable fractions were computed.

RESULTS

Heat and cold exposure were identified to be associated with increased risk of cardiovascular and respiratory mortality. Heat was not found to have an impact on hospital admissions. The estimated fraction of mortality attributable to cold was of greater magnitude in hospitalizations (17.5% for cardiovascular and 12.5% for respiratory diseases) compared to deaths (9% and 2.7%, respectively).

CONCLUSIONS

There were noteworthy differences between temperature-related mortality and hospital admissions regarding cardiovascular and respiratory diseases, hence reinforcing the convenience of cause-specific measures to prevent temperature-related deaths.

Impact of Extreme Temperatures on Ambulance Dispatches Due to Cardiovascular Causes in North-West Spain

Introduction and objectives. The increase in mortality and hospital admissions associated with high and low temperatures is well established. However, less is known about the influence of extreme ambient temperature conditions on cardiovascular ambulance dispatches. This study seeks to evaluate the effects of minimum and maximum daily temperatures on cardiovascular morbidity in the cities of Vigo and A Coruña in North-West Spain, using emergency medical calls during the period 2005–2017. Methods. For the purposes of analysis, we employed a quasi-Poisson time series regression model, within a distributed non-linear lag model by exposure variable and city. The relative risks of cold- and heat-related calls were estimated for each city and temperature model. Results. A total of 70,537 calls were evaluated, most of which were associated with low maximum and minimum temperatures on cold days in both cities. At maximum temperatures, significant cold-related effects were observed at lags of 3–6 days in Vigo and 5–11 days in A Coruña. At minimum temperatures, cold-related effects registered a similar pattern in both cities, with significant relative risks at lags of 4 to 12 days in A Coruña. Heat-related effects did not display a clearly significant pattern. Conclusions. An increase in cardiovascular morbidity is observed with moderately low temperatures without extremes being required to establish an effect. Public health prevention plans and warning systems should consider including moderate temperature range in the prevention of cardiovascular morbidity.

Social inequalities in heat-attributable mortality in the city of Turin, northwest of Italy: a time series analysis from 1982 to 2018

BACKGROUND

Understanding context specific heat-health risks in urban areas is important, especially given anticipated severe increases in summer temperatures due to climate change effects. We investigate social inequalities in the association between daily temperatures and mortality in summer in the city of Turin for the period 1982-2018 among different social and demographic groups such as sex, age, educational level, marital status and household occupants.

METHODS

Mortality data are represented by individual all-cause mortality counts for the summer months between 1982 and 2018. Socioeconomic level and daily mean temperature were assigned to each deceased. A time series Poisson regression with distributed lag non-linear models was fitted to capture the complex nonlinear dependency between daily mortality and temperature in summer. The mortality risk due to heat is represented by the Relative Risk (RR) at the 99th percentile of daily summer temperatures for each population subgroup.

RESULTS

All-cause mortality risk is higher among women (1.88; 95% CI = 1.77, 2.00) and the elderly (2.13; 95% CI = 1.94, 2.33). With regard to education, the highest significant effects for men is observed among higher education levels (1.66; 95% CI = 1.38, 1.99), while risks for women is higher for the lower educational level (1.93; 95% CI = 1.79, 2.08). Results on marital status highlighted a stronger association for widower in men (1.66; 95% CI = 1.38, 2.00) and for separated and divorced in women (2.11; 95% CI = 1.51, 2.94). The risk ratio of household occupants reveals a stronger association for men who lived alone (1.61; 95% CI = 1.39, 1.86), while for women results are almost equivalent between alone and not alone groups.

CONCLUSIONS

The associations between heat and mortality is unequal across different aspects of social vulnerability, and, inter alia, factors influencing the population vulnerability to temperatures can be related to demographic, social, and economic aspects. A number of issues are identified and recommendations for the prioritisation of further research are provided. A better knowledge of these effect modifiers is needed to identify the axes of social inequality across the most vulnerable population sub-groups.

Projection of mortality attributed to heat and cold; the impact of climate change in a dry region of Iran, Kerman

BACKGROUND

Estimating the effects of climate change on human health can help health policy makers plan for the future. In Iran, there are few studies, about investigating the effects of climate change on mortality. This study aimed to project the effect of low (cold) and high (heat) temperature on mortality in a dry region of Iran, Kerman.

METHODS

Mortality attributed to temperature was projected by estimating the temperature-mortality relation for the observed data, projection of future temperatures by the statistical downscaling model (SDSM), and quantifying the attributable fraction by applying the observed temperature-mortality relation on the projected temperature. Climate change projection was done by three climate scenarios base on Representative Concentration Pathways (RCP2.6, RCP4.5 and RCP8.5). Adaptation was considered by using different minimum mortality temperatures (MMT) and risk reduction approaches. The current decade (2010-19) was considered as the reference period.

RESULTS

All three climate change scenarios, showed that the mean of temperature will rise about 1 °C, by 2050 in Kerman. The number of deaths attributed to heat were obviously higher than cold in all periods. Assuming no adaptation, over 3700 deaths attributed to temperature will happen in each decade (2020s, 2030s and 2040s) in the future, in which over 3000 deaths will be due to heat and over 450 due to cold. In the predictions, as Minimum Mortality Temperature (MMT) went up, the contribution of heat to mortality slightly decreased, and cold temperature played a more important role. By considering the risk reduction due to adaptation, the contribution of heat in mortality slightly and insignificantly decreased.

CONCLUSION

The results showed that although low temperatures will contribute to temperature-related mortality in the future, but heat will be a stronger risk factor for mortality, especially if adaptation is low.

Association between moderately cold temperature and mortality in China

Ambient air temperature is a key factor affecting human health. Adverse effects of extreme weather on mortality have been well explored and expounded in numerous epidemiological studies. The relationship between moderate temperature and mortality is, however, underexplored. This study quantitatively investigated the temperature-dependent mortality burden in China. Data on daily average temperature and mortality in 15 Chinese cities during 2010-2016 were collected for this study. The association between temperature and city-specific mortality was investigated with a quasi-Poisson regression combined with a distributed lag nonlinear model across lag 0-21 days. The results were then included in a multivariate meta-analysis to derive the pooled estimates of the effect of temperature on mortality at the multi-city level. Mortality fractions attributable to cold and heat (i.e., at temperatures below and above the minimum mortality temperature (MMT)) were calculated. Additionally, temperature ranges were further divided into 1 °C intervals of ambient temperature, and the attributable fractions were calculated for each range. The MMT varied from the 71th to 93th percentiles of temperature in the 15 Chinese cities, centering at the 78th percentile at the multi-city level. In total, 12.65% of non-accidental mortality was attributable to non-optimum temperature, of which cold and hot temperatures corresponded to attributable fractions of 11.38% and 1.27%, respectively. The results of temperature stratifications suggested that moderately cold temperatures provided the highest contribution to mortality caused by temperature. Specifically, the highest attributable fractions were at 7 °C, 7 °C, 8 °C, 8 °C, 4 °C, 4 °C, 5 °C, 7 °C, 7 °C, 4 °C, 5 °C, 5 °C, 6 °C, 11 °C, and 12 °C, for Harbin, Changchun, Shenyang, Urumqi, Beijing, Tianjin, Shijiazhuang, Xining, Lanzhou, Nanjing, Shanghai, Hefei, Chengdu, Kunming, and Guangzhou, respectively. Cold temperature was responsible for a higher proportion of deaths than heat. Moderate cold temperature contributed to most of the total health burden. Finally, the cumulative total counts of deaths caused by moderate cold were the largest. Although moderate cold conferred a slightly lower relative risk than extreme cold, it was more common than extreme cold. Taken together, our results show that the effects of moderate cold temperature on health should receive more attention. Furthermore, our findings could help improve the prediction of climate change effects on human health and support the development of response strategies for the changing climate.

Comparison of temperature-mortality associations using observed weather station and reanalysis data in 52 Spanish cities

BACKGROUND

Most studies use temperature observation data from weather stations near the analyzed region or city as the reference point for the exposure-response association. Climatic reanalysis data sets have already been used for climate studies, but are not yet used routinely in environmental epidemiology.

METHODS

We compared the mortality-temperature association using weather station temperature and ERA-5 reanalysis data for the 52 provincial capital cities in Spain, using time-series regression with distributed lag non-linear models.

RESULTS

The shape of temperature distribution is very close between the weather station and ERA-5 reanalysis data (correlation from 0.90 to 0.99). The overall cumulative exposure-response curves are very similar in their shape and risks estimates for cold and heat effects, although risk estimates for ERA-5 were slightly lower than for weather station temperature.

CONCLUSIONS

Reanalysis data allow the estimation of the health effects of temperature, even in areas located far from weather stations or without any available.

Long Term Adaptation to Heat Stress: Shifts in the Minimum Mortality Temperature in the Netherlands

It is essentially unknown how humans adapt or will adapt to heat stress caused by climate change over a long-term interval. A possible indicator of adaptation may be the minimum mortality temperature (MMT), which is defined as the mean daily temperature at which the lowest mortality occurs. Another possible indicator may be the heat sensitivity, i.e., the percentage change in mortality per 1°C above the MMT threshold, or heat attributable fraction (AF), i.e., the percentage relative excess mortality above MMT. We estimated MMT and heat sensitivity/AF over a period of 23 years for older adults (≥65 years) in the Netherlands using three commonly used methods. These methods are segmented Poisson regression (SEG), constrained segmented distributed lag models (CSDL), and distributed lag non-linear models (DLNM). The mean ambient temperature increased by 0.03°C/year over the 23 year period. The calculated mean MMT over the 23-year period differed considerably between methods [16.4 ± 1.2°C (SE) (SEG), 18.9 ± 0.5°C (CSDL), and 15.3 ± 0.4°C DLNM]. MMT increased during the observed period according to CSDL (0.11 ± 0.05°C/year) and DLNM (0.15 ± 0.02°C/year), but not with SEG. The heat sensitivity, however, decreased for the latter method (0.06%/°C/year) and did not change for CSDL. Heat AF was calculated for the DLNM method and decreased with 0.07%/year. Based on these results we conclude that the susceptibility of humans to heat decreases over time, regardless which method was used, because human adaptation is shown by either an increase in MMT (CSDL and DLNM) or a decrease in heat sensitivity for unchanged MMT (SEG). Future studies should focus on what factors (e.g., physiological, behavioral, technological, or infrastructural adaptations) influence human adaptation the most, so it can be promoted through adaptation policies. Furthermore, future studies should keep in mind that the employed method influences the calculated MMT, which hampers comparability between studies.

Schumann resonance and cardiovascular hospital admission in the area of Granada, Spain: An event coincidence analysis approach

The study of bio-effects of Schumann resonances is a very complex issue. There is a need to identify mechanisms and pathways that explain how Extremely Low Frequency magnetic fields affect biology or human health. This particular study tries to identify statistical associations between ELF magnetic fields in the province of Granada (Spain) and cardiovascular related hospital admission in the same province for the period April, 1st 2013 to March, 31st 2014. Research is developed under an epidemiological approach based on an Event Coincidence Analysis statistical method. Clustered events, statistically significant (ECA shuffle-surrogate test p = .01 and p < .01), were found for the minimum values of the first and the third Schuman resonances frequency on east-west and north-south directions, and for the amplitude parameter of the second resonance and the total signal energy in the north-south direction. Empirical measurements of SR parameters were recorded at the Sierra Nevada Mountain in Granada province (Spain). Results show a clear coincidence of the events for the minima amplitudes of Shuman resonances and energy in the north-south orientation and the number of the cardiovascular related hospital admissions. Further research is needed with longer temporal series and a new approach based on gender seems to be also interesting for future studies.

Statistical Modelling of Temperature-Attributable Deaths in Portuguese Metropolitan Areas under Climate Change: Who Is at Risk?

Several studies emphasize that temperature-related mortality can be expected to have differential effects on different subpopulations, particularly in the context of climate change. This study aims to evaluate and quantify the future temperature-attributable mortality due to circulatory system diseases by age groups (under 65 and 65+ years), in Lisbon metropolitan area (LMA) and Porto metropolitan area (PMA), over the 2051–2065 and 2085–2099 time horizons, considering the greenhouse gas emissions scenario RCP8.5, in relation to a historical period (1991–2005). We found a decrease in extreme cold-related deaths of 0.55% and 0.45% in LMA, for 2051–2065 and 2085–2099, respectively. In PMA, there was a decrease in cold-related deaths of 0.31% and 0.49% for 2051–2065 and 2085–2099, respectively, compared to 1991–2005. In LMA, the burden of extreme heat-related mortality in age group 65+ years is slightly higher than in age group <65 years, at 2.22% vs. 1.38%, for 2085–2099. In PMA, only people aged 65+ years showed significant temperature-related burden of deaths that can be attributable to hot temperatures. The heat-related excess deaths increased from 0.23% for 2051–2065 to 1.37% for 2085–2099, compared to the historical period.

The Association between Air Temperature and Mortality in Two Brazilian Health Regions

Air temperature, both cold and hot, has impacts on mortality and morbidities, which are exacerbated by poor health service and protection responses, particularly in under-developed countries. This study was designed to analyze the effects of air temperature on the risk of deaths for all and specific causes in two regions of Brazil (Florianopolis and Recife), between 2005 and 2014. The association between temperature and mortality was performed through the fitting of a quasi-Poisson non-linear lag distributed model. The association between air temperature and mortality was identified for both regions. The results showed that temperature exerted influence on both general mortality indicators and specific causes, with hot and cold temperatures bringing different impacts to the studied regions. Cerebrovascular and cardiovascular deaths were more sensitive to cold temperatures for Florianopolis and Recife, respectively. Based on the application of the very-well documented state-of-the-art methodology, it was possible to conclude that there was evidence that extreme air temperature influenced general and specific deaths. These results highlighted the importance of consolidating evidence and research in tropical countries such as Brazil as a way of understanding climate change and its impacts on health indicators.

Global drivers of minimum mortality temperatures in cities

Human mortality shows a pronounced temperature dependence. The minimum mortality temperature (MMT) as a characteristic point of the temperature-mortality relationship is influenced by many factors. As MMT estimates are based on case studies, they are sporadic, limited to data-rich regions, and their drivers have not yet been clearly identified across case studies. This impedes the elaboration of spatially comprehensive impact studies on heat-related mortality and hampers the temporal transfer required to assess climate change impacts. Using 400 MMTs from cities, we systematically establish a generalised model that is able to estimate MMTs (in daily apparent temperature) for cities, based on a set of climatic, topographic and socio-economic drivers. A sigmoid model prevailed against alternative model setups due to having the lowest Akaike Information Criterion (AICc) and the smallest RMSE. We find the long-term climate, the elevation, and the socio-economy to be relevant drivers of our MMT sample within the non-linear parametric regression model. A first model application estimated MMTs for 599 European cities (>100 000 inhabitants) and reveals a pronounced decrease in MMTs (27.8-16 °C) from southern to northern cities. Disruptions of this pattern across regions of similar mean temperatures can be explained by socio-economic standards as noted for central eastern Europe. Our alternative method allows to approximate MMTs independently from the availability of daily mortality records. For the first time, a quantification of climatic and non-climatic MMT drivers has been achieved, which allows to consider changes in socio-economic conditions and climate. This work contributes to the comparability among MMTs beyond location-specific and regional limits and, hence, towards a spatially comprehensive impact assessment for heat-related mortality.

Short-term effects of ambient temperature on non-external and cardiovascular mortality among older adults of metropolitan areas of Mexico

Multi-city studies assessing the association between acute exposure to temperature and mortality in Latin American are limited. To analyze the short-term effect of changes in temperature (increase and decrease) on daily non-external and cardiovascular mortality from 1998 to 2014, in people 65 years old and over living in 10 metropolitan areas of Mexico. Analyses were performed through Poisson regression models with distributed lag non-linear models. Statistical comparison of minimum mortality temperature (MMT) and city-specific cutoffs of 24-h temperature mean values (5th/95th and 1st/99th percentiles) were used to obtain the mortality relative Risk (RR) for cold/hot and extreme cold/extreme hot, respectively, for the same day and lags of 0-3, 0-7, and 0-21 days. A meta-analysis was conducted to synthesize the estimates (RR_pooled). Significant non-linear associations of temperature-mortality relation were found in U or inverted J shape. The best predictors of mortality associations with cold and heat were daily temperatures at lag 0-7 and lag 0-3, respectively. RR_pooled of non-external causes was 6.3% (95%CI 2.7, 10.0) for cold and 10.2% (95%CI 4.4, 16.2) for hot temperatures. The RR_pooled for cardiovascular mortality was 7.1% (95%CI 0.01, 14.7) for cold and 7.1% (95%CI 0.6, 14.0) for hot temperatures. Results suggest that, starting from the MMT, the changes in temperature are associated with an increased risk of non-external and specific causes of mortality in elderly people. Generally, heat effects on non-external and specific causes of mortality occur immediately, while cold effects occur within a few days and last longer.

Heat waves, ambient temperature, and risk of myocardial infarction: an ecological study in the Community of Madrid

INTRODUCTION AND OBJECTIVES

Episodes of extreme heat are associated with increased morbidity and mortality in chronically-ill patients but there is a need to clearly establish the relationship between extreme heat and myocardial infarction. The aim of this study was to analyze the relationship between the incidence of ST-segment elevation myocardial infarction (STEMI) and maximum temperature, in particular during heat wave alert periods (HWAP).

METHODS

The population studied consisted of confirmed STEMI cases registered in the Infarction Code of the Community of Madrid between June 2013 and June 2017. Incidence rate ratios (IRR) adjusted for trend and seasonality and 95%CI were estimated using time series regression models.

RESULTS

A total of 6465 cases of STEMI were included; 212 cases occurred during the 66-day period of HWAP and 1816 cases during the nonalert summer period (IRR, 1.14; 95%CI, 0.96-1.35). The minimum incidence rate was observed at the maximum temperature of 18°C. Warmer temperatures were not associated with a higher incidence (IRR,1.03; 95%CI, 0.76-1.41), whereas colder temperatures were significantly associated with an increased risk (IRR, 1.25; 95%CI, 1.02-1.54). No effect modification was observed by age or sex.

CONCLUSIONS

We did not find an increased risk of STEMI during the 66 days of HWAP in the Community of Madrid between June 2013 and June 2017. However, an increased risk was found during colder temperatures. No extra health resources for STEMI management are required during periods of extreme heat, but should be considered during periods of cold weather.

Predicted temperature-increase-induced global health burden and its regional variability

An increase in the global health burden of temperature was projected for 459 locations in 28 countries worldwide under four representative concentration pathway scenarios until 2099. We determined that the amount of temperature increase for each 100 ppm increase in global CO₂ concentrations is nearly constant, regardless of climate scenarios. The overall average temperature increase during 2010-2099 is largest in Canada (1.16 °C/100 ppm) and Finland (1.14 °C/100 ppm), while it is smallest in Ireland (0.62 °C/100 ppm) and Argentina (0.63 °C/100 ppm). In addition, for each 1 °C temperature increase, the amount of excess mortality is increased largely in tropical countries such as Vietnam (10.34%p/°C) and the Philippines (8.18%p/°C), while it is decreased in Ireland (-0.92%p/°C) and Australia (-0.32%p/°C). To understand the regional variability in temperature increase and mortality, we performed a regression-based modeling. We observed that the projected temperature increase is highly correlated with daily temperature range at the location and vulnerability to temperature increase is affected by health expenditure, and proportions of obese and elderly population.

Hands-on Tutorial on a Modeling Framework for Projections of Climate Change Impacts on Health

Supplemental Digital Content is available in the text.

Reliable estimates of future health impacts due to climate change are needed to inform and contribute to the design of efficient adaptation and mitigation strategies. However, projecting health burdens associated to specific environmental stressors is a challenging task because of the complex risk patterns and inherent uncertainty of future climate scenarios. These assessments involve multidisciplinary knowledge, requiring expertise in epidemiology, statistics, and climate science, among other subjects. Here, we present a methodologic framework to estimate future health impacts under climate change scenarios based on a defined set of assumptions and advanced statistical techniques developed in time-series analysis in environmental epidemiology. The proposed methodology is illustrated through a step-by-step hands-on tutorial structured in well-defined sections that cover the main methodological steps and essential elements. Each section provides a thorough description of each step, along with a discussion on available analytical options and the rationale on the choices made in the proposed framework. The illustration is complemented with a practical example of study using real-world data and a series of R scripts included as Supplementary Digital Content; http://links.lww.com/EDE/B504, which facilitates its replication and extension on other environmental stressors, outcomes, study settings, and projection scenarios. Users should critically assess the potential modeling alternatives and modify the framework and R code to adapt them to their research on health impact projections.