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

Ambient temperature and mortality due to acute myocardial infarction in Brazil: an ecological study of time-series analyses

Ambient temperature may lead to decompensation of cardiovascular diseases and deaths by acute myocardial infarction (AMI). Little is known about this relationship in South American countries located in regions of a hot climate. This study aims to investigate the effects of ambient temperature on mortality due to AMI in six Brazilian micro-regions, which present different climates. We analyzed daily records of deaths by AMI between 1996 and 2013. We estimated the accumulate relative and attributable risks with lags of up to 14 days, using distributed non-linear lag model. Micro-regions that were closest to the equator did not show an association between temperature and mortality. The lowest risk temperatures varied between 22 °C and 28 °C, in the Southern region of Brazil and the Midwest region, respectively. Low temperatures associated with the highest mortality risk were observed in the same areas, varying between 5 °C and 15 °C. The number of deaths attributed to cold temperatures varied from 176/year in Brasilia to 661/year in São Paulo and those deaths attributed to hot temperatures in Rio de Janeiro amounted to 115/year. We showed the relative risk and the attributable risk of warmer and colder days in tropical regions. The estimate of the number of deaths due to climate, varying according to each area, is a way of bringing information to those responsible for health policies based on easily-understood measurements.

Degrees and dollars - Health costs associated with suboptimal ambient temperature exposure

Suboptimal ambient temperature exposure significantly affects public health. Previous studies have primarily focused on risk assessment, with few examining the health outcomes from an economic perspective. To inform environmental health policies, we estimated the economic costs of health outcomes associated with suboptimal temperature in the Minneapolis/St. Paul Twin Cities Metropolitan Area. We used a distributed lag nonlinear model to estimate attributable fractions/cases for mortality, emergency department visits, and emergency hospitalizations at various suboptimal temperature levels. The analyses were stratified by age group (i.e., youth (0-19 years), adult (20-64 years), and senior (65+ years)). We considered both direct medical costs and loss of productivity during economic cost assessment. Results show that youth have a large number of temperature-related emergency department visits, while seniors have large numbers of temperature-related mortality and emergency hospitalizations. Exposures to extremely low and high temperatures lead to $2.70 billion [95% empirical confidence interval (eCI): $1.91 billion, $3.48 billion] (costs are all based on 2016 USD value) economic costs annually. Moderately and extremely low and high temperature leads to $9.40 billion [eCI: $6.05 billion, $12.57 billion] economic costs. The majority of the economic costs are consistently attributed to cold (>75%), rather than heat exposures and to mortality (>95%), rather than morbidity. Our findings support prioritizing temperature-related health interventions designed to minimize the economic costs by targeting seniors and to reduce attributable cases by targeting youth.

Increasing mitigation ambition to meet the Paris Agreement's temperature goal avoids substantial heat-related mortality in U.S. cities

Current greenhouse gas mitigation ambition is consistent with ~3°C global mean warming above preindustrial levels. There is a clear need to strengthen mitigation ambition to stabilize the climate at the Paris Agreement goal of warming of less than 2°C. We specify the differences in city-level heat-related mortality between the 3°C trajectory and warming of 2° and 1.5°C. Focusing on 15 U.S. cities where reliable climate and health data are available, we show that ratcheting up mitigation ambition to achieve the 2°C threshold could avoid between 70 and 1980 annual heat-related deaths per city during extreme events (30-year return period). Achieving the 1.5°C threshold could avoid between 110 and 2720 annual heat-related deaths. Population changes and adaptation investments would alter these numbers. Our results provide compelling evidence for the heat-related health benefits of limiting global warming to 1.5°C in the United States.

A time series analysis of the relationship between apparent temperature, air pollutants and ischemic stroke in Madrid, Spain

The understanding of the role of environment on the pathogenesis of stroke is gaining importance in the context of climate change. This study analyzes the temporal pattern of ischemic stroke (IS) in Madrid, Spain, during a 13-year period (2001-2013), and the relationship between ischemic stroke (admissions and deaths) incidence and environmental factors on a daily scale by using a quasi-Poisson regression model. To assess potential delayed and non-linear effects of air pollutants and Apparent Temperature (AT), a biometeorological index which represents human thermal comfort on IS, a lag non-linear model was fitted in a generalized additive model. The mortality rate followed a downward trend over the studied period, however admission rates progressively increased. Our results show that both increases and decreases in AT had a marked relationship with IS deaths, while hospital admissions were only associated with low AT. When analyzing the cumulative effects (for lag 0-14 days), with an AT of 1.7 °C (percentile 5%) a RR of 1.20 (95% CI, 1.05-1.37) for IS mortality and a RR of 1.09 (95% CI, 0.91-1.29) for morbidity is estimated. Concerning gender differences, men show higher risks of mortality in low temperatures and women in high temperatures. No significant relationship was found between air pollutant concentrations and IS morbi-mortality, but this result must be interpreted with caution, since there are strong spatial fluctuations of the former between nearby geographical areas that make it difficult to perform correlation analyses.

Short-term effects of air pollution and temperature on cattle mortality in the Netherlands

BACKGROUND

Extreme temperatures and air pollution are both associated with increased mortality risk in humans. However, the effects of temperature and air pollution on cattle have not been investigated much before.

OBJECTIVES

Short-term effects of temperature (heat and cold) and air pollution on cattle mortality were investigated and quantified in the Netherlands during 2012-2017.

METHODS

Daily data on cattle mortality, weather conditions and mean levels of particulate matter (PM₁₀), ozone (O₃), ammonia (NH₃) and nitrogen dioxide (NO₂) of the Netherlands during 2012-2017 were collected. Associations were investigated with time-series regression using distributed lag non-linear models including lags of up to 25 days. Effects of temperature were expressed as those associated with extreme and moderate heat or cold, defined as Temperature Humidity Index (THI) values below the 1st and 5th percentile, and above the 95th and 99th percentile of the national THI distribution. Effects of air pollutants were expressed per 10 μg/m³ change in daily mean concentrations.

RESULTS

Both high and low temperatures were associated with increased mortality amongst different age groups. For instance, the newborn calves of at most 14 days showed a cumulative relative risk (RR) of 2.13 (95%CI: 1.99-2.28) for extreme heat and the pre-weaned calves (15-55 days) showed a cumulative RR of 1.50 (95%CI: 1.37-1.64) for extreme cold. Associations of air pollution with mortality were not consistent, except for the effect of ozone of lag 0-7 and lag 0-25. Exposure to O₃ in the newborn calves resulted in a cumulative RR of 1.09 (95%CI: 1.04-1.4) for lag 0-7 and 1.09 (95%CI: 1.03-1.16) for lag 0-25.

CONCLUSIONS

Both high and low temperatures were associated with increased mortality amongst pre-weaned calves of 15-55 days, whereas associations in weaned calves (56 days - 1 year) were only observed for low temperatures and in newborn calves of at most 14 days and lactating cattle >2 years only for high temperatures. Associations of air pollution with mortality in all age groups were not consistent, except for the effect of ozone of lag 0-7 and lag 0-25.

Bootstrap approach to validate the performance of models for predicting mortality risk temperature in Portuguese Metropolitan Areas

BACKGROUND

There has been increasing interest in assessing the impacts of extreme temperatures on mortality due to diseases of the circulatory system. This is further relevant for future climate scenarios where marked changes in climate are expected. This paper presents a solid method do identify the relationship between extreme temperatures and mortality risk by using as predictors simulated temperature data for cold and hot conditions in two urban areas in Portugal.

METHODS

Based on the mortality and meteorological data from Porto Metropolitan Area (PMA) and Lisbon Metropolitan Area (LMA), a distributed lag nonlinear model (DLNM) was implemented to estimate the temperature effects on mortality due to diseases of the circulatory system. The performance of the models was validated via bootstrapping approaching by creating resamples with replacement from the validating data. Bootstrapping was also used to identify the best candidate model and to evaluate the sensitivity of the spline functions to the exposure-lag-response relationship.

RESULTS

It is found that the model is able to reproduce the temperature-related mortality risk for two metropolitan areas. Temperature previously simulated by climate models is useful and even better than observed temperature. Although, the biases in predictions in both metropolitan areas are low, mortality risk predictions in PMA are more accurate than in LMA. Using parametric bootstrapping, we found that the overall cumulative association estimated under different bi-dimensional exposure-lag-response relationship are relatively stable, especially for the model selected by Quasi-Akaike Information Criteria (QAIC). Exposure to summer temperature conditions is best related to mortality risk. The association between winter temperature and mortality risk is somewhat less strong.

CONCLUSIONS

The use of QAIC to choose from several candidate models provides valid predictions and reduced the uncertainty in the estimated relative risk for circulatory disease mortality. Our findings can be applied to better understand the characteristics and facilitate the prevention of circulatory disease mortality in Porto and Lisbon Metropolitan Areas, namely if we consider the actual context of climate change.

Effects of heat on first-ever strokes and the effect modification of atmospheric pressure: A time-series study in Shenzhen, China

BACKGROUND

Stroke is a leading cause of death globally. Extreme temperatures may induce stroke, but evidence on the effects of heat on first-ever strokes is not clear. Low air pressure can lead to depression and an increase in blood pressure, and it may exacerbate the health impact of heat. In this study, we aimed to evaluate the effects of heat on first-ever strokes, the possible sensitive populations, and the effect of modification of atmospheric pressure.

METHODS

We collected data on 142,569 first-ever strokes during 2005-2016 in Shenzhen, a coastal city in southern China, with subtropical oceanic monsoon climate. We fitted a time-series Poisson model in our study, estimating the association between daily mean temperature and first-ever strokes in hot months, with a distributed lag non-linear model with 7 days of lag. We calculated strokes attributable to heat in various gender, age groups, household register types, stroke subtypes, and atmospheric pressure levels.

RESULTS

Heat had a significant cumulative association with first-ever strokes, and the risk of strokes increased with the rise in temperature after it was higher than 30 °C (the 85th percentile). In total, 1.95% (95% empirical CI 0.63-3.20%) of first-ever strokes were attributable to high temperature. The attributable fraction and attributable number of heat were statistically significant in male, female, middle-aged and old patients, immigrant patients, and CBI patients. The fraction attributable to heat was 3.33% in the low atmospheric pressure group, and the number of estimated daily attributable strokes at low atmospheric pressure levels was higher than that of medium and high atmospheric pressure levels (p < 0.01).

CONCLUSIONS

High temperatures in hot months may trigger first-ever strokes, and low atmospheric pressure may exacerbate the effect. We mainly found associations between heat and first-ever strokes for intracerebral hemorrhage, middle-aged and old patients, as well as immigrant patients.

Socio-geographic disparity in cardiorespiratory mortality burden attributable to ambient temperature in the United States

Compared with relative risk, attributable fraction (AF) is more informative when assessing the mortality burden due to some environmental exposures (e.g., ambient temperature). Up to date, however, available AF-based evidence linking temperature with mortality has been very sparse regionally and nationally, even for the leading mortality types such as cardiorespiratory deaths. This study aimed to quantify national and regional burden of cardiorespiratory mortality (CRM) attributable to ambient temperature in the USA, and to explore potential socioeconomic and demographic sources of spatial heterogeneity between communities. Daily CRM and weather data during 1987-2000 for 106 urban communities across the mainland of USA were acquired from the publicly available National Morbidity, Mortality and Air Pollution Study (NMMAPS). We did the data analysis using a three-stage analytic approach. We first applied quasi-Poisson regression incorporated with distributed lag nonlinear model to estimate community-specific temperature-CRM associations, then pooled these associations at the regional and national level through a multivariate meta-analysis, and finally estimated the temperature-AF of CRM and performed subgroup analyses stratified by community-level characteristics. Both low and high temperatures increased short-term CRM risk, while temperature-CRM associations varied by regions. Nationally, the fraction of cardiorespiratory deaths caused by the total non-optimum, low, and high temperatures was 7.58% (95% empirical confidence interval, 6.68-8.31%), 7.15% (6.31-7.85%), and 0.43% (0.37-0.46%), respectively. Greater temperature-AF was identified in two northern regions (i.e., Industrial Midwest and North East) and communities with lower temperature and longitude, higher latitude, and moderate humidity. Additionally, higher vulnerability appeared in locations with higher urbanization level, more aging population, less White race, and lower socioeconomic status. Ambient temperature may be responsible for a large fraction of cardiorespiratory deaths. Also, temperature-AF of CRM varied considerably by geographical and climatological factors, as well as community-level disparity in socioeconomic status.

Threshold Evaluation of Emergency Risk Communication for Health Risks Related to Hazardous Ambient Temperature

Emergency risk communication (ERC) programs that activate when the ambient temperature is expected to cross certain extreme thresholds are widely used to manage relevant public health risks. In practice, however, the effectiveness of these thresholds has rarely been examined. The goal of this study is to test if the activation criteria based on extreme temperature thresholds, both cold and heat, capture elevated health risks for all-cause and cause-specific mortality and morbidity in the Minneapolis-St. Paul Metropolitan Area. A distributed lag nonlinear model (DLNM) combined with a quasi-Poisson generalized linear model is used to derive the exposure-response functions between daily maximum heat index and mortality (1998-2014) and morbidity (emergency department visits; 2007-2014). Specific causes considered include cardiovascular, respiratory, renal diseases, and diabetes. Six extreme temperature thresholds, corresponding to 1st-3rd and 97th-99th percentiles of local exposure history, are examined. All six extreme temperature thresholds capture significantly increased relative risks for all-cause mortality and morbidity. However, the cause-specific analyses reveal heterogeneity. Extreme cold thresholds capture increased mortality and morbidity risks for cardiovascular and respiratory diseases and extreme heat thresholds for renal disease. Percentile-based extreme temperature thresholds are appropriate for initiating ERC targeting the general population. Tailoring ERC by specific causes may protect some but not all individuals with health conditions exacerbated by hazardous ambient temperature exposure.

Heat-related mortality trends under recent climate warming in Spain: A 36-year observational study

BACKGROUND

Anthropogenic greenhouse gas emissions have increased summer temperatures in Spain by nearly one degree Celsius on average between 1980 and 2015. However, little is known about the extent to which the association between heat and human mortality has been modified. We here investigate whether the observed warming has been associated with an upward trend in excess mortality attributable to heat or, on the contrary, a decrease in the vulnerability to heat has contributed to a reduction of the mortality burden.

METHODS AND FINDINGS

We analysed a dataset from 47 major cities in Spain for the summer months between 1980 and 2015, which included daily temperatures and 554,491 deaths from circulatory and respiratory causes, by sex. We applied standard quasi-Poisson regression models, controlling for seasonality and long-term trends, and estimated the temporal variation in heat-related mortality with time-varying distributed lag nonlinear models (DLNMs). Results pointed to a reduction in the relative risks of cause-specific and cause-sex mortality across the whole range of summer temperatures. These reductions in turn explained the observed downward trends in heat-attributable deaths, with the only exceptions of respiratory diseases for women and both sexes together. The heat-attributable deaths were consistently higher in women than in men for both circulatory and respiratory causes. The main limitation of our study is that we were not able to account for air pollution in the models because of data unavailability.

CONCLUSIONS

Despite the summer warming observed in Spain between 1980 and 2015, the decline in the vulnerability of the population has contributed to a general downward trend in overall heat-attributable mortality. This reduction occurred in parallel with a decline in the vulnerability difference between men and women for circulatory and cardiorespiratory mortality. Despite these advances, the risk of death remained high for respiratory diseases, and particularly in women.

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.

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

BACKGROUND

There is an extensive literature describing temperature-mortality associations in developed regions, but research from developing countries, and Africa in particular, is limited.

METHODS

We 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.

RESULTS

We 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.

CONCLUSIONS

An 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.

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

BACKGROUND

Rich 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.

METHODS

Our 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.

RESULTS

The 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.

CONCLUSIONS

The 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.