Temperature and mortality in nine US cities

Integrating Urban Form, Function, and Energy Fluxes in a Heat Exposure Indicator in View of Intra-Urban Heat Island Assessment and Climate Change Adaptation

Cities worldwide are getting warmer due to the combined effects of urban heat and climate change. To this end, local policy makers need to identify the most thermally vulnerable areas within cities. The Local Climate Zone (LCZ) scheme highlights local-scale variations; however, its classes, although highly valuable, are to a certain extent generalized in order to be universally applicable. High spatial resolution indicators have the potential to better reflect city-specific challenges; in this paper, the Urban Heat Exposure (UHeatEx) indicator is developed, integrating the physical processes that drive the urban heat island (UHI). In particular, the urban form is modeled using remote sensing and geographical information system (GIS) techniques, and used to estimate the canyon aspect ratio and the storage heat flux. The Bowen ratio is calculated using the aerodynamic resistance methodology and downscaled remotely sensed surface temperatures. The anthropogenic heat flux is estimated via a synergy of top–down and bottom–up inventory approaches. UHeatEx is applied to the city of Athens, Greece; it is correlated to air temperature measurements and compared to the LCZs classification. The results reveal that UHeatEx has the capacity to better reflect the strong intra-urban variability of the thermal environment in Athens, and thus can be supportive for adaptation responses. High-resolution climate projections from the EURO-CORDEX ensemble for the region show that the adverse effects of the existing thermal inequity are expected to worsen in the coming decades.

The effects of temperature on short-term mortality risk in Kuwait: A time-series analysis

BACKGROUND

In light of climate change, health risks are expected to be exacerbated by extreme temperatures. Many studies showed that high and low ambient temperatures are associated with increased short-term mortality risk, but little is known about these risks in Kuwait and the Gulf Region.

OBJECTIVE

To examine the dose-response relationship between 24-h average ambient temperatures and daily mortality risk in Kuwait.

METHODS

We gathered mortality and meteorological data from 2010 to 2016 in Kuwait. We did a time-series analysis using a negative binomial distribution, and studied the lag effects of temperature with distributed lag non-linear models.

RESULTS

A total of 33,574 all-cause non-accidental deaths were analyzed. The relationship was shown to be non-linear. Overall relative risks of death comparing the 1st percentile (10.9 °C) and the 99th percentile (42.7 °C) to the optimum temperature were 1.67 (1.02-2.73), and 1.65 (1.09-2.48), respectively. Cold effects persisted for 9 days, while the effects of hot temperatures were the highest at lag 0 and only persisted for a week. Adjusting for PM₁₀ and ozone did not change the temperature-mortality estimates.

CONCLUSION

Our findings show evidence that there is a statistically significant positive association between temperature extremes and mortality in Kuwait. The evidence has significant implications in assessing climate vulnerability and provides insight into environmental challenges in an inherently hot and arid region.

Influence of the spatial resolution of the exposure estimate in determining the association between heat waves and adverse health outcomes

BACKGROUND

Area-level estimates of temperature may lead to exposure misclassification in studies examining associations between heat waves and health outcomes. Our study compared the association between heat waves and preterm birth (PTB) or non-accidental death (NAD) using exposure metrics at varying levels of spatial resolution: ZIP codes, 12.5 km, and 1 km.

METHOD

Using geocoded residential addresses on birth (1990-2010) and death (1997-2010) records from Alabama, USA, we implemented a time-stratified case-crossover design to examine the association between heat waves and PTB or NAD. ZIP code- and 12.5 km heat wave indices (HIs) were derived using air temperatures from Phase 2 of the North American Land Data Assimilation System (NLDAS-2). We downscaled NLDAS-2 data, using land surface temperatures (LST) from the Moderate Resolution Imaging Spectroradiometer (MODIS) product, to estimate fine spatial resolution HIs (1 km).

RESULTS

The association between heat waves and PTB or NAD was significant and positive using ZIP code-, 12.5 km, and 1 km exposure metrics. Moreover, results show that these three-exposure metric analyses produced similar effect estimates. Urban heat islands were evident with the 1 km metric. When analyses were stratified by rurality, we found associations in urban areas were more positive than in rural areas.

CONCLUSIONS

Comparing results of models with a varying spatial resolution of the exposure metric allows for examination of potential bias associated with exposure misclassification.

Mortality and morbidity associated with ambient temperatures in Taiwan

BACKGROUND

This study evaluated integrated risks of all-cause mortality, emergency room visits (ERVs), and outpatient visits associated with ambient temperature in all cities and counties of Taiwan. In addition, the modifying effects of socio-economic and environmental factors on temperature-health associations were also evaluated.

METHODS

A distributed lag non-linear model was applied to estimate the cumulative relative risks (RRs) with confidence intervals of all-cause mortality, ERVs, and outpatient visits associated with extreme temperature events. Random-effect meta-analysis was used to estimate the pooled RR of all-cause mortality, ERVs, and outpatient visits influenced by socio-economic and environmental factors.

RESULTS

Temperature-related risks varied with study area and health outcome. Meta-analysis showed greater all-cause mortality risk occurred in low temperatures than in high temperatures. Integrated RR of all-cause mortality was 1.71 (95% confidence interval [CI]:1.43-2.04) in the 5th percentile temperature and 1.10 (95% CI: 1.05-1.15) in the 95th percentile temperature, while the lowest mortality risk was in the 60th percentile temperature (22.2 °C). Risk for ERVs increased when temperature increased (RR was 1.21 [95% CI: 1.17-1.26] in 95th percentile temperature), but risk of outpatient visits increased at low temperatures (RR was 1.06 [95% CI: 1.01-1.12] in the 5th percentile temperature). Certain socio-economic factors significantly modified low-temperature-related mortality risks, including number of employed populations, elders living alone from lower-income families, and public and medical services.

CONCLUSIONS

This study found that mortality and outpatient visits were higher at low temperature, while ERVs risk was higher at high temperature. Future plans for public health and emerging medical services responding to extreme temperatures should consider regional and integrated evaluations of temperature-related health risks and modifying factors.

Effect of Health-Related Uncertainty and Natural Variability on Health Impacts and Cobenefits of Climate Policy

Climate policy can mitigate health risks attributed to intensifying air pollution under climate change. However, few studies quantify risks of illness and death, examine their contribution to climate policy benefits, or assess their robustness in light of natural climate variability. We employ an integrated modeling framework of the economy, climate, air quality, and human health to quantify the effect of natural variability on U.S. air pollution impacts under future climate and two global policies (2 and 2.5 °C stabilization scenarios) using 150 year ensemble simulations for each scenario in 2050 and 2100. Climate change yields annual premature deaths related to fine particulate matter and ozone (95CI: 25 000-120 000), heart attacks (900-9400), and lost work days (3.6M-4.9M) in 2100. It raises air pollution health risks by 20%, while policies avert these outcomes by 40-50% in 2050 and 70-88% in 2100. Natural variability introduces "climate noise", yielding some annual estimates with negative cobenefits, and others that reach 100% of annual policy costs. This "noise" is three times the magnitude of uncertainty (95CI) in health and economic responses in 2050. Averaging five annual simulations reduces this factor to two, which is still substantially larger than health-related uncertainty. This study quantifies the potential for inaccuracy in climate impacts projected using too few annual simulations.

Heat-Related Health Impacts under Scenarios of Climate and Population Change

Recent assessments have found that a warming climate, with associated increases in extreme heat events, could profoundly affect human health. This paper describes a new modeling and analysis framework, built around the Benefits Mapping and Analysis Program-Community Edition (BenMAP), for estimating heat-related mortality as a function of changes in key factors that determine the health impacts of extreme heat. This new framework has the flexibility to integrate these factors within health risk assessments, and to sample across the uncertainties in them, to provide a more comprehensive picture of total health risk from climate-driven increases in extreme heat. We illustrate the framework's potential with an updated set of projected heat-related mortality estimates for the United States. These projections combine downscaled Coupled Modeling Intercomparison Project 5 (CMIP5) climate model simulations for Representative Concentration Pathway (RCP)4.5 and RCP8.5, using the new Locating and Selecting Scenarios Online (LASSO) tool to select the most relevant downscaled climate realizations for the study, with new population projections from EPA's Integrated Climate and Land Use Scenarios (ICLUS) project. Results suggest that future changes in climate could cause approximately from 3000 to more than 16,000 heat-related deaths nationally on an annual basis. This work demonstrates that uncertainties associated with both future population and future climate strongly influence projected heat-related mortality. This framework can be used to systematically evaluate the sensitivity of projected future heat-related mortality to the key driving factors and major sources of methodological uncertainty inherent in such calculations, improving the scientific foundations of risk-based assessments of climate change and human health.

Association between apparent temperature and acute coronary syndrome admission in Rasht, Iran

OBJECTIVE

Our objective was to assess the relations between apparent temperature and incidence of acute coronary syndrome (ACS) in Rasht, Iran.

METHODS

We used a time-series analysis to investigate the relationship between apparent temperature and hospital admission from 2005 to 2014. Distributed lag non-linear models were used to estimate the association between ACS hospitalisation and apparent temperature. To examine the high-temperature effect on ACS hospital admission, the relative risk of ACS hospital admission associated with high temperature, the 99th percentile of temperature (34.7°C) compared with the 75th percentile of temperature (26.9°C), was calculated. To assess the cold effect on ACS hospital admission, the relative risk of ACS hospital admission associated with cold temperature, the first percentile of temperature (-0.2°C) compared with the 25th percentile of temperature (8.2°C), was evaluated.

RESULTS

The cumulative effect of hot exposure on ACS admissions was statistically significant, with a relative risk of 2.04 (95% CI 1.06 to 4.16). The cumulative effect of cold temperature on ACS admissions was found to be non-significant. The highest risk of ACS admission in women was in 38°C (RR, 2.03, 95%  CI 1.04 to 4.18). The effect of hot temperature on ACS admission occurred immediately (lag 0) (RR, 1.09, 95%  CI 1.001 to 1.19).

CONCLUSIONS

The high apparent temperature is correlated with a higher ACS admission especially on the same day. These findings may have implications for developing intervention strategies to reduce and prevent temperature-related morbidity especially in the elderly.

Heat exposure during outdoor activities in the US varies significantly by city, demography, and activity

Environmental heat is a growing public health concern in cities. Urbanization and global climate change threaten to exacerbate heat as an already significant environmental cause of human morbidity and mortality. Despite increasing risk, very little is known regarding determinants of outdoor urban heat exposure. To provide additional evidence for building community and national-scale resilience to extreme heat, we assess how US outdoor urban heat exposure varies by city, demography, and activity. We estimate outdoor urban heat exposure by pairing individual-level data from the American Time Use Survey (2004-2015) with corresponding meteorological data for 50 of the largest metropolitan statistical areas in the US. We also assess the intersection of activity intensity and heat exposure by pairing metabolic intensities with individual-level time-use data. We model an empirical relationship between demographic indicators and daily heat exposure with controls for spatiotemporal factors. We find higher outdoor heat exposure among the elderly and low-income individuals, and lower outdoor heat exposure in females, young adults, and those identifying as Black race. Traveling, lawn and garden care, and recreation are the most common outdoor activities to contribute to heat exposure. We also find individuals in cities with the most extreme temperatures do not necessarily have the highest outdoor heat exposure. The findings reveal large contrasts in outdoor heat exposure between different cities, demographic groups, and activities. Resolving the interplay between exposure, sensitivity, adaptive capacity, and behavior as determinants of heat-health risk will require advances in observational and modeling tools, especially at the individual scale.

Synergistic Effects of Ambient Temperature and Air Pollution on Health in Europe: Results from the PHASE Project

We studied the potential synergy between air pollution and meteorology and their impact on mortality in nine European cities with data from 2004 to 2010. We used daily series of Apparent Temperature (AT), measurements of particulate matter (PM₁₀), ozone (O₃), and nitrogen dioxide (NO₂) and total non-accidental, cardiovascular, and respiratory deaths. We applied Poisson regression for city-specific analysis and random effects meta-analysis to combine city-specific results, separately for the warm and cold seasons. In the warm season, the percentage increase in all deaths from natural causes per °C increase in AT tended to be greater during high ozone days, although this was only significant for all ages when all causes were considered. On low ozone days, the increase in the total daily number of deaths was 1.84% (95% CI 0.87, 2.82), whilst it was 2.20% (95% CI 1.28, 3.13) in the high ozone days per 1 °C increase in AT. Interaction with PM₁₀ was significant for cardiovascular (CVD) causes of death for all ages (2.24% on low PM₁₀ days (95% CI 1.01, 3.47) whilst it is 2.63% (95% CI 1.57, 3.71) on high PM₁₀ days) and for ages 75+. In days with heat waves, no consistent pattern of interaction was observed. For the cold period, no evidence for synergy was found. In conclusion, some evidence of interactive effects between hot temperature and the levels of ozone and PM₁₀ was found, but no consistent synergy could be identified during the cold season.

Short-Term Effects of Heat on Mortality and Effect Modification by Air Pollution in 25 Italian Cities

Evidence on the health effects of extreme temperatures and air pollution is copious. However few studies focused on their interaction. The aim of this study is to evaluate daily PM10 and ozone as potential effect modifiers of the relationship between temperature and natural mortality in 25 Italian cities. Time-series analysis was run for each city. To evaluate interaction, a tensor product between mean air temperature (lag 0⁻3) and either PM10 or ozone (both lag 0⁻5) was defined and temperature estimates were extrapolated at low, medium, and high levels of pollutants. Heat effects were estimated as percent change in mortality for increases in temperature between 75th and 99th percentiles. Results were pooled by geographical area. Differential temperature-mortality risks by air pollutants were found. For PM10, estimates ranged from 3.9% (low PM10) to 14.1% (high PM10) in the North, from 3.6% to 24.4% in the Center, and from 7.5% to 21.6% in the South. Temperature-related mortality was similarly modified by ozone in northern and central Italy, while no effect modification was observed in the South. This study underlines the synergistic effects of heat and air pollution on mortality. Considering the predicted increase in heat waves and stagnation events in the Mediterranean countries such as Italy, it is time to enclose air pollution within public health heat prevention plans.

The relationship between diurnal temperature range and COPD hospital admissions in Changchun, China

Diurnal temperature range (DTR) has been suggested to be an adverse health factor especially related to respiratory and cardiovascular diseases. In the current study, we investigated the association between DTR and chronic obstructive pulmonary disease (COPD) hospital admissions during 2009 to 2012 in northeast city of Changchun, China. Based on generalized additive model (GAM), the effects were expressed as relative risk (RR) values of COPD with 95% confidence intervals (CIs) with each 1 °C increase in DTR. And they were significantly increased with an increment of 1 °C in DTR, modified by season, age, and sex. The elderly were more vulnerable, with relative risk values of 1.048 (1.029, 1.066) in cold season and 1.037 (1.021, 1.053) in warm season. Regarding the gender, the DTR effect on females was greater during cold season and the RR value was 1.051 (1.033, 1.069) on the current day (lag 0). The greater estimates for males appeared at lag 7 days, with RR of 1.019 (0.998, 1.040). A season-specific effect was detected that the relative risk values with per 1 °C increase in DTR were greater in cold season than in warm season. These findings support the hypothesis of significant relationship between DTR and COPD in Changchun, one northeast city of China.

Towards establishing evidence-based guidelines on maximum indoor temperatures during hot weather in temperate continental climates

Rising environmental temperatures represent a major threat to human health. The activation of heat advisories using evidence-based thresholds for high-risk outdoor ambient temperatures have been shown to be an effective strategy to save lives during hot weather. However, although the relationship between weather and human health has been widely defined by outdoor temperature, corresponding increases in indoor temperature during heat events can also be harmful to health especially in vulnerable populations. In this review, we discuss our current understanding of the relationship between outdoor temperature and human health and examine how human health can also be adversely influenced by high indoor temperatures during heat events. Our assessment of the existing literature revealed a high degree of variability in what can be considered an acceptable indoor temperature because there are differences in how different groups of people may respond physiologically and behaviorally to the same living environment. Finally, we demonstrate that both non-physiological (e.g., geographical location, urban density, building design) and physiological (e.g., sex, age, fitness, state of health) factors must be considered when defining an indoor temperature threshold for preserving human health in a warming global climate.

Ambient Temperature and Sudden Infant Death Syndrome in the United States

BACKGROUND

Sudden infant death syndrome (SIDS) is a leading cause of infant mortality in the United States. While thermal stress is implicated in many risk factors for SIDS, the association between ambient temperature and SIDS remains unclear.

METHODS

We obtained daily individual-level infant mortality data and outdoor temperature data from 1972 to 2006 for 210 US cities. We applied a time-stratified case-crossover analysis to determine the effect of ambient temperature on the risk of SIDS by season. We stratified the analysis by race, infant age, and climate.

RESULTS

There were a total of 60,364 SIDS cases during our study period. A 5.6°C (10°F) higher daily temperature on the same day was associated with an increased SIDS risk of 8.6% (95% confidence interval [CI] = 3.6%, 13.8%) in the summer, compared with a 3.1% decrease (95% CI = -5.0%, -1.3%) in the winter. Summer risks were greater among black infants (18.5%; 95% CI = 9.3%, 28.5%) than white infants (3.6%; 95% CI = -2.3%, 9.9%), and among infants 3-11 months old (16.9%; 95% CI = 8.9%, 25.5%) than infants 0-2 months old (2.7%; 95% CI = -3.5%, 9.2%). The temperature-SIDS association was stronger in climate clusters in the Midwest and surrounding northern regions.

CONCLUSIONS

Temperature increases were associated with an elevated risk of SIDS in the summer, particularly among infants who were black, 3 months old and older, and living in the Midwest and surrounding northern regions.

Projecting future climate change impacts on heat-related mortality in large urban areas in China

Global climate change is anticipated to raise overall temperatures and has the potential to increase future mortality attributable to heat. Urban areas are particularly vulnerable to heat because of high concentrations of susceptible people. As the world's largest developing country, China has experienced noticeable changes in climate, partially evidenced by frequent occurrence of extreme heat in urban areas, which could expose millions of residents to summer heat stress that may result in increased health risk, including mortality. While there is a growing literature on future impacts of extreme temperatures on public health, projecting changes in future health outcomes associated with climate warming remains challenging and underexplored, particularly in developing countries. This is an exploratory study aimed at projecting future heat-related mortality risk in major urban areas in China. We focus on the 51 largest Chinese cities that include about one third of the total population in China, and project the potential changes in heat-related mortality based on 19 different global-scale climate models and three Representative Concentration Pathways (RCPs). City-specific risk estimates for high temperature and all-cause mortality were used to estimate annual heat-related mortality over two future twenty-year time periods. We estimated that for the 20-year period in Mid-21st century (2041-2060) relative to 1970-2000, incidence of excess heat-related mortality in the 51 cities to be approximately 37,800 (95% CI: 31,300-43,500), 31,700 (95% CI: 26,200-36,600) and 25,800 (95% CI: 21,300-29,800) deaths per year under RCP8.5, RCP4.5 and RCP2.6, respectively. Slowing climate change through the most stringent emission control scenario RCP2.6, relative to RCP8.5, was estimated to avoid 12,900 (95% CI: 10,800-14,800) deaths per year in the 51 cities in the 2050s, and 35,100 (95% CI: 29,200-40,100) deaths per year in the 2070s. The highest mortality risk is primarily in cities located in the North, East and Central regions of China. Population adaptation to heat is likely to reduce excess heat mortality, but the extent of adaptation is still unclear. Future heat mortality risk attributable to exposure to elevated warm season temperature is likely to be considerable in China's urban centers, with substantial geographic variations. Climate mitigation and heat risk management are needed to reduce such risk and produce substantial public health benefits.

The Effects of Apparent Temperature on Cardiovascular Mortality Using a Distributed Lag Nonlinear Model Analysis: 2005 to 2014

The relationship between apparent temperature and cardiovascular disease (CVD) mortality was studied in Rasht, Iran, from 2005 to 2014. The effects of apparent temperature on CVD mortality were investigated using the distributed lag nonlinear model. Data on all types of cardiovascular mortality cases according to the International Classification of Diseases were collected from the only cardiovascular hospital in Rasht, and the meteorological variables were obtained from Rasht Meteorological Center during the period of study. Our findings showed that low temperatures had significant impacts on CVD mortality, and a reverse J-shaped temperature-mortality relationship was found. Moreover, immediate effects of hot temperatures on CVD mortality with the strongest effects on the same day but delayed effects of cold temperature was observed. This study showed that exposure to both hot and cold apparent temperatures was associated with increased cardiovascular mortality in Rasht.

Respiratory Effects of Indoor Heat and the Interaction with Air Pollution in Chronic Obstructive Pulmonary Disease

RATIONALE

There is limited evidence of the effect of exposure to heat on chronic obstructive pulmonary disease (COPD) morbidity, and the interactive effect between indoor heat and air pollution has not been established.

OBJECTIVES

To determine the effect of indoor and outdoor heat exposure on COPD morbidity and to determine whether air pollution concentrations modify the effect of temperature.

METHODS

Sixty-nine participants with COPD were enrolled in a longitudinal cohort study, and data from the 601 participant days that occurred during the warm weather season were included in the analysis. Participants completed home environmental monitoring with measurement of temperature, relative humidity, and indoor air pollutants and simultaneous daily assessment of respiratory health with questionnaires and portable spirometry.

MEASUREMENTS AND MAIN RESULTS

Participants had moderate to severe COPD and spent the majority of their time indoors. Increases in maximal indoor temperature were associated with worsening of daily Breathlessness, Cough, and Sputum Scale scores and increases in rescue inhaler use. The effect was detected on the same day and lags of 1 and 2 days. The detrimental effect of temperature on these outcomes increased with higher concentrations of indoor fine particulate matter and nitrogen dioxide (P < 0.05 for interaction terms). On days during which participants went outdoors, increases in maximal daily outdoor temperature were associated with increases in Breathlessness, Cough, and Sputum Scale scores after adjusting for outdoor pollution concentrations.

CONCLUSIONS

For patients with COPD who spend the majority of their time indoors, indoor heat exposure during the warmer months represents a modifiable environmental exposure that may contribute to respiratory morbidity. In the context of climate change, adaptive strategies that include optimization of indoor environmental conditions are needed to protect this high-risk group from the adverse health effects of heat.

Estimating daily minimum, maximum, and mean near surface air temperature using hybrid satellite models across Israel

Meteorological stations measure air temperature (Ta) accurately with high temporal resolution, but usually suffer from limited spatial resolution due to their sparse distribution across rural, undeveloped or less populated areas. Remote sensing satellite-based measurements provide daily surface temperature (Ts) data in high spatial and temporal resolution and can improve the estimation of daily Ta. In this study we developed spatiotemporally resolved models which allow us to predict three daily parameters: Ta Max (day time), 24h mean, and Ta Min (night time) on a fine 1km grid across the state of Israel. We used and compared both the Aqua and Terra MODIS satellites. We used linear mixed effect models, IDW (inverse distance weighted) interpolations and thin plate splines (using a smooth nonparametric function of longitude and latitude) to first calibrate between Ts and Ta in those locations where we have available data for both and used that calibration to fill in neighboring cells without surface monitors or missing Ts. Out-of-sample ten-fold cross validation (CV) was used to quantify the accuracy of our predictions. Our model performance was excellent for both days with and without available Ts observations for both Aqua and Terra (CV Aqua R² results for min 0.966, mean 0.986, and max 0.967; CV Terra R² results for min 0.965, mean 0.987, and max 0.968). Our research shows that daily min, mean and max Ta can be reliably predicted using daily MODIS Ts data even across Israel, with high accuracy even for days without Ta or Ts data. These predictions can be used as three separate Ta exposures in epidemiology studies for better diurnal exposure assessment.

Case-crossover analysis of heat-coded deaths and vulnerable subpopulations: Oklahoma, 1990-2011

The extent of the association between temperature and heat-coded deaths, for which heat is the primary cause of death, remains largely unknown. We explored the association between temperature and heat-coded deaths and potential interactions with various demographic and environmental factors. A total of 335 heat-coded deaths that occurred in Oklahoma from 1990 through 2011 were identified using heat-related International Classification of Diseases codes, cause-of-death nomenclature, and narrative descriptions. Conditional logistic regression models examined the association between temperature and heat index on heat-coded deaths. Interaction by demographic factors (age, sex, marital status, living alone, outdoor/heavy labor occupations) and environmental factors (ozone, PM₁₀, PM_2.5) was also explored. Temperatures ≥99 °F (the median value) were associated with approximately five times higher odds of a heat-coded death as compared to temperatures <99 °F (adjusted OR = 4.9, 95% CI 3.3, 7.2). The effect estimates were attenuated when exposure to heat was characterized by heat index. The interaction results suggest that effect of temperature on heat-coded deaths may depend on sex and occupation. For example, the odds of a heat-coded death among outdoor/heavy labor workers exposed to temperatures ≥99 °F was greater than expected based on the sum of the individual effects (observed OR = 14.0, 95% CI 2.7, 72.0; expected OR = 4.1 [2.8 + 2.3-1.0]). Our results highlight the extent of the association between temperature and heat-coded deaths and emphasize the need for a comprehensive, multisource definition of heat-coded deaths. Furthermore, based on the interaction results, we recommend that states implement or expand heat safety programs to protect vulnerable subpopulations, such as outdoor workers.

Climatic conditions and human mortality: spatial and regional variation in the United States

Previous research on climatic conditions and human mortality in the United States has three gaps: largely ignoring social conditions, lack of nationwide focus, and overlooking potential spatial variations. Our goal is to understand whether climatic conditions contribute to mortality after considering social conditions and to investigate whether spatial non-stationarity exists in these factors. Applying geographically weighted regression to a unique nationwide county-level dataset, we found that (1) net of other factors, average July temperatures are positively (detrimentally) associated with mortality while January temperatures mainly have a curvilinear relationship, (2) the mortality-climatic condition associations are spatially non-stationary, (3) the relationships between social conditions (e.g., social capital) and mortality are stable geographically, and (4) without a spatial approach to understanding the environment-mortality relationship, important spatial variations are overlooked. Our findings suggest that a universal approach to coping with the relationships between rapid climate changes and health may not be appropriate and effective.

Spatiotemporal estimation of air temperature patterns at the street level using high resolution satellite imagery

Although meteorological monitoring stations provide accurate measurements of Air Temperature (AT), their spatial coverage within a given region is limited and thus is often insufficient for exposure and epidemiological studies. In many applications, satellite imagery measures energy flux, which is spatially continuous, and calculates Brightness Temperature (BT) that used as an input parameter. Although both quantities (AT-BT) are physically related, the correlation between them is not straightforward, and varies daily due to parameters such as meteorological conditions, surface moisture, land use, satellite-surface geometry and others. In this paper we first investigate the relationship between AT and BT as measured by 39 meteorological stations in Israel during 1984-2015. Thereafter, we apply mixed regression models with daily random slopes to calibrate Landsat BT data with monitored AT measurements for the period 1984-2015. Results show that AT can be predicted with high accuracy by using BT with high spatial resolution. The model shows relatively high accuracy estimation of AT (R²=0.92, RMSE=1.58°C, slope=0.90). Incorporating meteorological parameters into the model generates better accuracy (R²=0.935) than the AT-BT model (R²=0.92). Furthermore, based on the relatively high model accuracy, we investigated the spatial patterns of AT within the study domain. In the latter we focused on July-August, as these two months are characterized by relativity stable synoptic conditions in the study area. In addition, a temporal change in AT during the last 30years was estimated and verified using available meteorological stations and two additional remote sensing platforms. Finally, the impact of different land coverage on AT were estimated, as an example of future application of the presented approach.

Seasonal and temperature modifications of the association between fine particulate air pollution and cardiovascular hospitalization in New York state

It is known that extreme temperature and ambient air pollution are each independently associated with human health outcomes. However, findings from the few studies that have examined modified effects by seasons and the interaction between air pollution and temperature on health endpoints are inconsistent. This study examines the effects of short-term PM_2.5 (particulate matter less than or equal to 2.5μm in aerodynamic diameter) on hospitalization for cardiovascular diseases (CVDs), its modifications by season and temperature, and whether these effects are heterogeneous across different regions in New York State (NYS). We used daily average temperature and PM_2.5 concentrations as exposure indicators and performed a time series analysis with a quasi-Poisson model, controlling for possible confounders, such as time-relevant variables and dew point, for CVDs in NYS, 1991-2006. Stratification parametric models were applied to evaluate the modifying effects by seasons and temperature. Across the whole year, a 10-μg/m³ increment in PM_2.5 concentration accounted for a 1.37% increase in CVDs (95% confidence interval (CI): 0.90%, 1.84%) in New York City, Long Island & Hudson. The PM_2.5 effect was strongest in winter, with an additional 2.06% (95% CI: 1.33%, 2.80%) increase in CVDs observed per 10-μg/m³ increment in PM_2.5. Temperature modified the PM_2.5 effects on CVDs, and these modifications by temperature on PM_2.5 effects on CVDs were found at low temperature days. These associations were heterogeneous across four PM_2.5 concentration regions. PM_2.5 was positively associated with CVD hospitalizations. The short-term PM_2.5 effect varied with season and temperature levels, and stronger effects were observed in winter and at low temperature days.

Out-of-hospital cardiac arrest risk attributable to temperature in Japan

Several studies have estimated the associations between extreme temperatures and mortality and morbidity; however, few have investigated the attributable fraction for a wide range of temperatures on the risk of out-of-hospital cardiac arrest (OHCA). We obtained daily records of OHCA cases in the 47 Japanese prefectures between 2005 and 2014. We examined the relationship between OHCA and temperature for each prefecture using a Poisson regression model combined with a distributed lag non-linear model. The estimated prefecture-specific associations were pooled at the nationwide level using a multivariate random-effect meta-analysis. A total of 659,752 cases of OHCA of presumed-cardiac origin met the inclusion criteria. Overall, 23.93% (95% empirical confidence interval [eCI]: 20.15–26.19) of OHCA was attributable to temperature. The attributable fraction to low temperatures was 23.64% (95% eCI: 19.76–25.87), whereas that of high temperatures was 0.29% (95% eCI: 0.21–0.35). The attributable fraction for OHCA was related to moderate low temperature with an overall estimate of 21.86% (95% eCI: 18.10–24.21). Extreme temperatures were responsible for a small fraction. The majority of temperature-related OHCAs were attributable to lower temperatures. The attributable risk of extremely low and high temperatures was markedly lower than that of moderate temperatures.

The interactive effects between high temperature and air pollution on mortality: A time-series analysis in Hefei, China

Recent evidence suggests that there may be an interaction between air pollution and heat on mortality, which is pertinent in the context of global climate change. We sought to examine this interaction in Hefei, a hot and polluted Chinese city. We conducted time-series analyses using daily mortality, air pollutant concentration (including particulate matter with aerodynamic diameter <10μm (PM₁₀), sulphur dioxide (SO₂) and nitrogen dioxide (NO₂)), and temperature data from 2008 to 2014. We applied quasi-Poisson regression models with natural cubic splines and examined the interactive effects using temperature-stratified models. Subgroup analyses were conducted by age, gender, and educational levels. We observed consistently stronger associations between air pollutants and mortality at high temperatures than at medium temperatures. These differences were statistically significant for the associations between PM₁₀ and non-accidental mortality and between all pollutants studied and respiratory mortality. Mean percentage increases in non-accidental mortality per 10μg/m³ at high temperatures were 2.40% (95% confidence interval: 0.64 to 4.20) for PM₁₀, 7.77% (0.60 to 15.00) for SO₂, and 6.83% (-1.37 to 15.08) for NO₂. The estimates for PM₁₀ were 3.40% (0.96 to 5.90) in females and 4.21% (1.44 to 7.05) in the illiterate, marking them as more vulnerable. No clear trend was identified by age. We observed an interaction between air pollutants and high temperature on mortality in Hefei, which was stronger in females and the illiterate. This may be due to differences in behaviours affecting personal exposure to high temperatures and has potential policy implications.

Acute Effects of Nitrogen Dioxide on Cardiovascular Mortality in Beijing: An Exploration of Spatial Heterogeneity and the District-specific Predictors

The exploration of spatial variation and predictors of the effects of nitrogen dioxide (NO₂) on fatal health outcomes is still sparse. In a multilevel case-crossover study in Beijing, China, we used mixed Cox proportional hazard model to examine the citywide effects and conditional logistic regression to evaluate the district-specific effects of NO₂ on cardiovascular mortality. District-specific predictors that could be related to the spatial pattern of NO₂ effects were examined by robust regression models. We found that a 10 μg/m³ increase in daily mean NO₂ concentration was associated with a 1.89% [95% confidence interval (CI): 1.33–2.45%], 2.07% (95% CI: 1.23–2.91%) and 1.95% (95% CI: 1.16–2.72%) increase in daily total cardiovascular (lag03), cerebrovascular (lag03) and ischemic heart disease (lag02) mortality, respectively. For spatial variation of NO₂ effects across 16 districts, significant effects were only observed in 5, 4 and 2 districts for the above three outcomes, respectively. Generally, NO₂ was likely having greater adverse effects on districts with larger population, higher consumption of coal and more civilian vehicles. Our results suggested independent and spatially varied effects of NO₂ on total and subcategory cardiovascular mortalities. The identification of districts with higher risk can provide important insights for reducing NO₂ related health hazards.

Chronic effects of temperature on mortality in the Southeastern USA using satellite-based exposure metrics

Climate change may affect human health, particularly for elderly individuals who are vulnerable to temperature changes. While many studies have investigated the acute effects of heat, only a few have dealt with the chronic ones. We have examined the effects of seasonal temperatures on survival of the elderly in the Southeastern USA, where a large fraction of subpopulation resides. We found that both seasonal mean temperature and its standard deviation (SD) affected long-term survival among the 13 million Medicare beneficiaries (aged 65+) in this region during 2000–2013. A 1 °C increase in summer mean temperature corresponded to an increase of 2.5% in death rate. Whereas, 1 °C increase in winter mean temperature was associated with a decrease of 1.5%. Increases in seasonal temperature SD also influence mortality. We decomposed seasonal mean temperature and its temperature SD into long-term geographic contrasts between ZIP codes and annual anomalies within ZIP code. Effect modifications by different subgroups were also examined to find out whether certain individuals are more vulnerable. Our findings will be critical to future efforts assessing health risks related to the future climate change.

The burden of stroke mortality attributable to cold and hot ambient temperatures: Epidemiological evidence from China

BACKGROUND

Few data are available on the attributable burden, such as absolute excess or relative excess, of stroke death due to temperature.

METHODS

We collected data on daily temperature and stroke mortality from 16 large Chinese cities during 2007-2013. First, we applied a distributed lag non-linear model to estimate the city-/age-/gender-specific temperature-mortality association over lag 0-14days. Then, pooled estimates were calculated using a multivariate meta-analysis. Attributable deaths were calculated for cold and heat, defined as temperatures below and above the minimum-mortality temperature (MMT). Moderate and extreme temperatures were defined using cut-offs at the 2.5th and 97.5th percentiles of temperature.

RESULTS

The city-specific MMT increased from the north to the south, with a median of 24.9(o)C. Overall, 14.5% (95% empirical confidence interval: 11.5-17.0%) of stroke mortality (114, 662 deaths) was attributed to non-optimum temperatures, with the majority being attributable to cold (13.1%, 9.7-15.7%). The proportion of temperature-related death had a decreasing trend by latitude, ranging from 22.7% in Guangzhou to 6.3% in Shenyang. Moderate temperatures accounted for 12.6% (9.1-15.3%) of stroke mortality, whereas extreme temperatures accounted for only 2.0% (1.6-2.2%) of stroke mortality. Estimates of death burden due to both cold and heat were higher among males and the elderly, compared with females and the youth.

CONCLUSIONS

The burden of temperature-related stroke mortality increased from the north to the south. Most of this burden was caused by cold temperatures. The stroke burden was higher among males and the elderly. This information has important implications for preventing stroke due to adverse temperatures in vulnerable subpopulations in China.

The Effects of Air Pollution and Temperature on COPD

Chronic Obstructive Pulmonary Disease (COPD) affects 12-16 million people in the United States and is the third-leading cause of death. In developed countries, smoking is the greatest risk factor for the development of COPD, but other exposures also contribute to the development and progression of the disease. Several studies suggest, though are not definitive, that outdoor air pollution exposure is linked to the prevalence and incidence of COPD. Among individuals with COPD, outdoor air pollutants are associated with loss of lung function and increased respiratory symptoms. In addition, outdoor air pollutants are also associated with COPD exacerbations and mortality. There is much less evidence for the impact of indoor air on COPD, especially in developed countries in residences without biomass exposure. The limited existing data suggests that indoor particulate matter and nitrogen dioxide concentrations are linked to increased respiratory symptoms among patients with COPD. In addition, with the projected increases in temperature and extreme weather events in the context of climate change there has been increased attention to the effects of heat exposure. Extremes of temperature-both heat and cold-have been associated with increased respiratory morbidity in COPD. Some studies also suggest that temperature may modify the effect of pollution exposure and though results are not conclusive, understanding factors that may modify susceptibility to air pollution in patients with COPD is of utmost importance.

"APEC blue"--The effects and implications of joint pollution prevention and control program

To ensure good air quality in Beijing during Asia-Pacific Economic Cooperation (APEC) China 2014, Beijing and its neighboring five provinces and the associated cities were combined under the Joint Prevention and Control of Atmospheric Pollution (JPCAP) program, which implemented rigorous cooperative emission reduction measures. The program was a unique and large-scale artificial experiment that showed that such measures can achieve excellent results, and it led to the popular "APEC blue" catchphrase (i.e., Beijing's skies became blue as pollution levels decreased). This artificial experiment provided the means to effectively conduct JPCAP strategies in the future. Accordingly, our research focused on the characteristics of the six primary pollutants in Beijing. We found that the JPCAP measures directly reduced concentrations of all pollutants except O3. Through correlation analysis, we found that the band distribution of the cities with strong correlations in PM2.5 and PM10 concentrations was affected by wind conditions. Therefore, JPCAP measures should account for specific seasonal and climatic conditions. Based on cluster analysis using the results from the correlation analysis, we divided 13 cities within a 300-km radius of Beijing into different groups according to the similarity of their PM2.5 and PM10 correlation coefficients. For JPCAP measures relevant to PM2.5 and PM10, we found differences in the degrees of collaboration among cities. Therefore, depending upon the pollutant type, the JPCAP strategy should account for the cities involved, the scope of the core area, and the optimal cities to involve in the collaborative efforts based on cost-effectiveness and collaborative difficulty among the involved cities.

Estimating daily air temperature across the Southeastern United States using high-resolution satellite data: A statistical modeling study

Accurate estimates of spatio-temporal resolved near-surface air temperature (Ta) are crucial for environmental epidemiological studies. However, values of Ta are conventionally obtained from weather stations, which have limited spatial coverage. Satellite surface temperature (Ts) measurements offer the possibility of local exposure estimates across large domains. The Southeastern United States has different climatic conditions, more small water bodies and wetlands, and greater humidity in contrast to other regions, which add to the challenge of modeling air temperature. In this study, we incorporated satellite Ts to estimate high resolution (1km×1km) daily Ta across the southeastern USA for 2000-2014. We calibrated Ts-Ta measurements using mixed linear models, land use, and separate slopes for each day. A high out-of-sample cross-validated R(2) of 0.952 indicated excellent model performance. When satellite Ts were unavailable, linear regression on nearby monitors and spatio-temporal smoothing was used to estimate Ta. The daily Ta estimations were compared to the NASA's Modern-Era Retrospective Analysis for Research and Applications (MERRA) model. A good agreement with an R(2) of 0.969 and a mean squared prediction error (RMSPE) of 1.376°C was achieved. Our results demonstrate that Ta can be reliably predicted using this Ts-based prediction model, even in a large geographical area with topography and weather patterns varying considerably.

The impact of temperature on mortality in a subtropical city: effects of cold, heat, and heat waves in São Paulo, Brazil

Understanding how weather impacts health is critical, especially under a changing climate; however, relatively few studies have investigated subtropical regions. We examined how mortality in São Paulo, Brazil, is affected by cold, heat, and heat waves over 14.5 years (1996-2010). We used over-dispersed generalized linear modeling to estimate heat- and cold-related mortality, and Bayesian hierarchical modeling to estimate overall effects and modification by heat wave characteristics (intensity, duration, and timing in season). Stratified analyses were performed by cause of death and individual characteristics (sex, age, education, marital status, and place of death). Cold effects on mortality appeared higher than heat effects in this subtropical city with moderate climatic conditions. Heat was associated with respiratory mortality and cold with cardiovascular mortality. Risk of total mortality was 6.1% (95% confidence interval 4.7, 7.6%) higher at the 99th percentile of temperature than the 90th percentile (heat effect) and 8.6% (6.2, 11.1%) higher at the 1st compared to the 10th percentile (cold effect). Risks were higher for females and those with no education for heat effect, and males for cold effect. Older persons, widows, and non-hospital deaths had higher mortality risks for heat and cold. Mortality during heat waves was higher than on non-heat wave days for total, cardiovascular, and respiratory mortality. Our findings indicate that mortality in São Paulo is associated with both cold and heat and that some subpopulations are more vulnerable.

Increased mortality associated with extreme-heat exposure in King County, Washington, 1980-2010

Extreme heat has been associated with increased mortality, particularly in temperate climates. Few epidemiologic studies have considered the Pacific Northwest region in their analyses. This study quantified the historical (May to September, 1980-2010) heat-mortality relationship in the most populous Pacific Northwest County, King County, Washington. A relative risk (RR) analysis was used to explore the relationship between heat and all-cause mortality on 99th percentile heat days, while a time series analysis, using a piece-wise linear model fit, was used to estimate the effect of heat intensity on mortality, adjusted for temporal trends. For all ages, all causes, we found a 10% (1.10 (95% confidence interval (CI), 1.06, 1.14)) increase in the risk of death on a heat day versus non-heat day. When considering the intensity effect of heat on all-cause mortality, we found a 1.69% (95% CI, 0.69, 2.70) increase in the risk of death per unit of humidex above 36.0°C. Mortality stratified by cause and age produced statistically significant results using both types of analyses for: all-cause, non-traumatic, circulatory, cardiovascular, cerebrovascular, and diabetes causes of death. All-cause mortality was statistically significantly modified by the type of synoptic weather type. These results demonstrate that heat, expressed as humidex, is associated with increased mortality on heat days, and that risk increases with heat's intensity. While age was the only individual-level characteristic found to modify mortality risks, statistically significant increases in diabetes-related mortality for the 45-64 age group suggests that underlying health status may contribute to these risks.

All-Cause and Cause-Specific Risk of Emergency Transport Attributable to Temperature: A Nationwide Study

Although several studies have estimated the associations between mortality or morbidity and extreme temperatures in terms of relative risk, few studies have investigated the risk of emergency transport attributable to the whole temperature range nationwide.We acquired data on daily emergency ambulance dispatches in all 47 prefectures of Japan from 2007 to 2010. We examined the relationship between emergency transport and temperature for each prefecture using a Poisson regression model in a distributed lag nonlinear model with adjustment for time trends. A random-effect multivariate meta-analysis was then applied to pool the estimates at the national level. Attributable morbidity was calculated for high and low temperatures, which were defined as those above or below the optimum temperature (ie, the minimum morbidity temperature) and for moderate and also extreme temperatures, which were defined using cutoffs at the 2.5th and 97.5th temperature percentiles.A total of 15,868,086 cases of emergency transport met the inclusion criteria. The emergency transport was attributable to nonoptimal temperature. The median minimum morbidity percentile was in the 79th percentile for all causes, the 96th percentile for cardiovascular disease, and the 92th percentile for respiratory disease. The fraction attributable to low temperature was 6.94% (95% eCI: 5.93-7.70) for all causes, 17.93% (95% eCI: 16.10-19.25) for cardiovascular disease, and 12.19% (95% eCI: 9.90-13.66) for respiratory disease, whereas the fraction attributable to high temperature was small (all causes = 1.01%, 95% eCI: 0.90-1.11; cardiovascular disease = 0.10%, 95% eCI: 0.04-0.14; respiratory disease = 0.29%, 95% eCI: 0.07-0.50). The all-cause morbidity risk that was attributable to temperature was related to moderate cold, with an overall estimate of 6.41% (95% eCI: 5.47-7.20). Extreme temperatures were responsible for a small fraction, which corresponded to 0.57% (95% eCI: 0.50-0.62) for extreme low temperature and 0.29% (95% eCI: 0.26-0.32) for extreme high temperature. The same trends were observed for cardiovascular and respiratory diseases.The majority of temperature-related emergency transport burden was attributable to lower temperature. The effect of extremely high or low temperatures was markedly lower than that attributable to moderately nonoptimal temperatures.

Regional Projections of Extreme Apparent Temperature Days in Africa and the Related Potential Risk to Human Health

Regional climate modelling was used to produce high resolution climate projections for Africa, under a “business as usual scenario”, that were translated into potential health impacts utilizing a heat index that relates apparent temperature to health impacts. The continent is projected to see increases in the number of days when health may be adversely affected by increasing maximum apparent temperatures (AT) due to climate change. Additionally, climate projections indicate that the increases in AT results in a moving of days from the less severe to the more severe Symptom Bands. The analysis of the rate of increasing temperatures assisted in identifying areas, such as the East African highlands, where health may be at increasing risk due to both large increases in the absolute number of hot days, and due to the high rate of increase. The projections described here can be used by health stakeholders in Africa to assist in the development of appropriate public health interventions to mitigate the potential health impacts from climate change.

Individual-level and community-level effect modifiers of the temperature-mortality relationship in 66 Chinese communities

OBJECTIVES

To examine the modification of temperature-mortality association by factors at the individual and community levels.

DESIGN AND METHODS

This study investigated this issue using a national database comprising daily data of 66 Chinese communities for 2006-2011. A 'threshold-natural cubic spline' distributed lag non-linear model was utilised to estimate the mortality effects of daily mean temperature, and then examined the modification of the relationship by individual factors (age, sex, education level, place of death and cause of death) using a meta-analysis approach and community-level factors (annual temperature, population density, sex ratio, percentage of older population, health access, household income and latitude) using a meta-regression method.

RESULTS

We found significant effects of high and low temperatures on mortality in China. The pooled excess mortality risk was 1.04% (95% CI 0.90% to 1.18%) for a 1°C temperature decrease below the minimum mortality temperature (MMT), and 3.44% (95% CI 3.00% to 3.88%) for a 1°C temperature increase above MMT. At the individual level, age and place of death were found to be significant modifiers of cold effect, while age, sex, place of death, cause of death and education level were effect modifiers of heat effect. At the community level, communities with lower socioeconomic status and higher annual temperature were generally more vulnerable to the mortality effects of high and low temperatures.

CONCLUSIONS

This study identifies susceptibility based on both individual-level and community-level effect modifiers; more attention should be given to these vulnerable individuals and communities to reduce adverse health effects of extreme temperatures.

Assessment of Short- and Long-Term Mortality Displacement in Heat-Related Deaths in Brisbane, Australia, 1996-2004

BACKGROUND

Mortality displacement (or "harvesting") has been identified as a key issue in the assessment of the temperature-mortality relationship. However, only a few studies have addressed the "harvesting" issue and findings have not been consistent.

OBJECTIVES

We examined the potential impact of both short- and long-term harvesting effects on heat-related deaths in Brisbane, Australia.

METHODS

We collected data on daily counts of deaths (nonaccidental, cardiovascular, and respiratory), weather, and air pollution in Brisbane from 1 January 1996 to 30 November 2004. We estimated heat-related deaths, identified potential short-term mortality displacement, and assessed how and to what extent the impact of summer temperature on mortality was modified by mortality in the previous winter using a Poisson time-series regression combined with distributed lag nonlinear model (DLNM).

RESULTS

There were significant associations between temperature and each mortality outcome in summer. We found evidence of short-term mortality displacement for respiratory mortality, and evidence of longer-term mortality displacement for nonaccidental and cardiovascular mortality when the preceding winter's mortality was low. The estimated heat effect on mortality was generally stronger when the preceding winter mortality level was low. For example, we estimated a 22% increase in nonaccidental mortality (95% CI: 14, 30) with a 1°C increase in mean temperature above a 28°C threshold in summers that followed a winter with low mortality, compared with 12% (95% CI: 7, 17) following a winter with high mortality. The short- and long-term mortality displacement appeared to jointly influence the assessment of heat-related deaths.

CONCLUSIONS

We found evidence of both short- and long-term harvesting effects on heat-related mortality in Brisbane, Australia. Our finding may clarify temperature-related health risks and inform effective public health interventions to manage the health impacts of climate change.

Short-Term Effect of Ambient Temperature and the Risk of Stroke: A Systematic Review and Meta-Analysis

BACKGROUND AND PURPOSE

The relationship between stroke and short-term temperature changes remains controversial. Therefore, we conducted a systematic review and meta-analysis to investigate the association between stroke and both high and low temperatures, and health assessment.

METHODS

We searched PubMed, Embase, Cochrane, China National Knowledge Infrastructure (CNKI) and Wanfang Data up to 14 September 2014. Study selection, quality assessment, and author-contractions were steps before data extraction. We converted all estimates effects into relative risk (RR) per 1 °C increase/decrease in temperature from 75th to 99th or 25th to 1st percentiles, then conducted meta-analyses to combine the ultimate RRs, and assessed health impact among the population.

RESULTS

20 articles were included in the final analysis. The overall analysis showed a positive relationship between 1 °C change and the occurrence of major adverse cerebrovascular events (MACBE), 1.1% (95% confidence intervals (CI), 0.6 to 1.7) and 1.2% (95% CI, 0.8 to 1.6) increase for hot and cold effects separately. The same trends can be found in both effects of mortality and the cold effect for morbidity. Hot temperature acted as a protective factor of hemorrhage stroke (HS), -1.9% (95% CI, -2.8 to -0.9), however, it acted as a risk factor for ischemic stroke (IS), 1.2% (95% CI, 0.7 to 1.8).

CONCLUSION

Short-term changes of both low and high temperature had statistically significant impacts on MACBE.

A Case-Only Study of Vulnerability to Heat Wave-Related Mortality in New York City (2000-2011)

BACKGROUND

As a result of climate change, the frequency of extreme temperature events is expected to increase, and such events are associated with increased morbidity and mortality. Vulnerability patterns, and corresponding adaptation strategies, are most usefully conceptualized at a local level.

METHODS

We used a case-only analysis to examine subject and neighborhood characteristics that modified the association between heat waves and mortality. All deaths of New York City residents from 2000 through 2011 were included in this analysis. Meteorological data were obtained from the National Climatic Data Center. Modifying characteristics were obtained from the death record and geographic data sets.

RESULTS

A total of 234,042 adult deaths occurred during the warm season of our study period. Compared with other warm-season days, deaths during heat waves were more likely to occur in black (non-Hispanic) individuals than other race/ethnicities [odds ratio (OR) = 1.08; 95% CI: 1.03, 1.12], more likely to occur at home than in institutions and hospital settings (OR = 1.11; 95% CI: 1.06, 1.16), and more likely among those living in census tracts that received greater public assistance (OR = 1.05; 95% CI: 1.01, 1.09). Finally, deaths during heat waves were more likely among residents in areas of the city with higher relative daytime summer surface temperature and less likely among residents living in areas with more green space.

CONCLUSION

Mortality during heat waves varies widely within a city. Understanding which individuals and neighborhoods are most vulnerable can help guide local preparedness efforts.

Variation in vulnerability to extreme-temperature-related mortality in Japan: A 40-year time-series analysis

BACKGROUND

Although the impact of extreme heat and cold on mortality has been documented in recent years, few studies have investigated whether variation in susceptibility to extreme temperatures has changed in Japan.

METHODS

We used data on daily total mortality and mean temperatures in Fukuoka, Japan, for 1973-2012. We used time-series analysis to assess the effects of extreme hot and low temperatures on all-cause mortality, stratified by decade, gender, and age, adjusting for time trends. We used a multivariate meta-analysis with a distributed lag non-linear model to estimate pooled non-linear lag-response relationships associated with extreme temperatures on mortality.

RESULTS

The relative risk of mortality increased during heat extremes in all decades, with a declining trend over time. The mortality risk was higher during cold extremes for the entire study period, with a dispersed pattern across decades. Meta-analysis showed that both heat and cold extremes increased the risk of mortality. Cold effects were delayed and lasted for several days, whereas heat effects appeared quickly and did not last long.

CONCLUSIONS

Our study provides quantitative evidence that extreme heat and low temperatures were significantly and non-linearly associated with the increased risk of mortality with substantial variation. Our results suggest that timely preventative measures are important for extreme high temperatures, whereas several days' protection should be provided for extreme low temperatures.

Cardiovascular mortality associated with low and high temperatures: determinants of inter-region vulnerability in China

The objectives of this study were to estimate the effects of temperature on cardiovascular mortality in 26 regions in the south and west of China from 2008 to 2011, and to identify socioeconomic and demographic factors contributing to such inter-region variation in the temperature effect. A separate Poisson generalized additive model (GAM) was fitted to estimate percent changes in cardiovascular mortality at low and high temperatures on a daily basis for each region. The model used the smooth functions to model the nonlinear effects of temperature and humidity and to control for the seasonal factor using the calendar time variable. Given variation in the magnitude of the temperature effect on cardiovascular mortality, we employed a Bayesian network (BN) to identify potential region-specific socioeconomic and demographic factors that may explain the variation. In most regions, an increasing trend in high or low temperature was associated with an increase in cardiovascular mortality, with variation in the magnitude of the temperature effects across regions. Three factors, including per capita years of education (as an indicator of economic status), percentage of the population over 65 years of age and percentage of women had direct impact on cold-related cardiovascular mortality. Number of hospital beds (as an indicator of the availability of medical resources), percentage of population engaged in industrial occupations, and percentage of women showed direct impact on heat-related cardiovascular mortality. Due to the socioeconomic and demographic inequalities between regions, the development of customized prevention and adaptation programs to address the low/high temperatures in vulnerable regions should be prioritized.

Long-range fine particulate matter from the 2002 Quebec forest fires and daily mortality in Greater Boston and New York City

During July 2002, forest fires in Quebec, Canada, blanketed the US East Coast with a plume of wood smoke. This "natural experiment" exposed large populations in northeastern US cities to significantly elevated concentrations of fine particulate matter (PM2.5), providing a unique opportunity to test the association between daily mortality and ambient PM2.5 levels that are uncorrelated with societal activity rhythms. We obtained PM2.5 measurement data and mortality data for a 4-week period in July 2002 for the Greater Boston metropolitan area (which has a population of over 1.7 million people) and New York City (which has a population of over 8 million people). Daily average PM2.5 concentrations were markedly increased for 3 days over this period, reaching as high as 63 μg/m3 for Greater Boston and 86 μg/m3 for New York City from background ambient levels of 4-48 μg/m3 in the non-smoke days. We examined temporal patterns of natural-cause deaths and 24-h ambient PM2.5 concentrations in July 2002 and did not observe any discernible increase in daily mortality subsequent to the dramatic elevation in ambient PM2.5 levels. Comparison to mortality rates over the same time periods in 2001 and 2003 showed no evidence of impact. Results from Poisson regression analyses suggest that 24-h ambient PM2.5 concentrations were not associated with daily mortality. In conclusion, substantial short-term elevation in PM2.5 concentrations from forest fire smoke were not followed by increased daily mortality in Greater Boston or New York City.

Heat-attributable deaths between 1992 and 2009 in Seoul, South Korea

BACKGROUND

Climate change may significantly affect human health. The possible effects of high ambient temperature must be better understood, particularly in terms of certain diseases' sensitivity to heat (as reflected in relative risks [RR]) and the consequent disease burden (number or fraction of cases attributable to high temperatures), in order to manage the threat.

PURPOSE

This study investigated the number of deaths attributable to abnormally high ambient temperatures in Seoul, South Korea, for a wide range of diseases.

METHOD

The relationship between mortality and daily maximum temperature using a generalized linear model was analyzed. The threshold temperature was defined as the 90th percentile of maximum daily temperatures. Deaths were classified according to ICD-10 codes, and for each disease, the RR and attributable fractions were determined. Using these fractions, the total number of deaths attributable to daily maximum temperatures above the threshold value, from 1992 to 2009, was calculated. Data analyses were conducted in 2012-2013.

RESULTS

Heat-attributable deaths accounted for 3,177 of the 271,633 deaths from all causes. Neurological (RR 1.07; 95% CI, 1.04-1.11) and mental and behavioral disorders (RR 1.04; 95% CI, 1.01-1.07) had relatively high increases in the RR of mortality. The most heat-sensitive diseases (those with the highest RRs) were not the diseases that caused the largest number of deaths attributable to high temperatures.

CONCLUSION

This study estimated RRs and deaths attributable to high ambient temperature for a wide variety of diseases. Prevention-related policies must account for both particular vulnerabilities (heat-sensitive diseases with high RRs) and the major causes of the heat mortality burden (common conditions less sensitive to high temperatures).

Temperature, ozone, and mortality in urban and non-urban counties in the northeastern United States

BACKGROUND

Most health effects studies of ozone and temperature have been performed in urban areas, due to the available monitoring data. We used observed and interpolated data to examine temperature, ozone, and mortality in 91 urban and non-urban counties.

METHODS

Ozone measurements were extracted from the Environmental Protection Agency's Air Quality System. Meteorological data were supplied by the National Center for Atmospheric Research. Observed data were spatially interpolated to county centroids. Daily internal-cause mortality counts were obtained from the National Center for Health Statistics (1988-1999). A two-stage Bayesian hierarchical model was used to estimate each county's increase in mortality risk from temperature and ozone. We examined county-level associations according to population density and compared urban (≥1,000 persons/mile(2)) to non-urban (<1,000 persons/mile(2)) counties. Finally, we examined county-level characteristics that could explain variation in associations by county.

RESULTS

A 10 ppb increase in ozone was associated with a 0.45% increase in mortality (95% PI: 0.08, 0.83) in urban counties, while this same increase in ozone was associated with a 0.73% increase (95% PI: 0.19, 1.26) in non-urban counties. An increase in temperature from 70°F to 90°F (21.2°C 32.2°C) was associated with a 8.88% increase in mortality (95% PI: 7.38, 10.41) in urban counties and a 8.08% increase (95% PI: 6.16, 10.05) in non-urban counties. County characteristics, such as population density, percentage of families living in poverty, and percentage of elderly residents, partially explained the variation in county-level associations.

CONCLUSIONS

While most prior studies of ozone and temperature have been performed in urban areas, the impacts in non-urban areas are significant, and, for ozone, potentially greater. The health risks of increasing temperature and air pollution brought on by climate change are not limited to urban areas.

Increased hospital admissions associated with extreme-heat exposure in King County, Washington, 1990-2010

Increased morbidity and mortality have been associated with extreme heat events, particularly in temperate climates. Few epidemiologic studies have considered the impact of extreme heat events on hospitalization rates in the Pacific Northwest region. This study quantifies the historic (May to September 1990-2010) heat-morbidity relationship in the most populous Pacific Northwest County, King County, Washington. A relative risk (RR) analysis was used to explore the association between heat and all non-traumatic hospitalizations on 99th percentile heat days, whereas a time series analysis using a piecewise linear model approximation was used to estimate the effect of heat intensity on hospitalizations, adjusted for temporal trends and day of the week. A non-statistically significant 2% [95% CI: 1.02 (0.98, 1.05)] increase in hospitalization risk, on a heat day vs. a non-heat day, was noted for all-ages and all non-traumatic causes. When considering the effect of heat intensity on admissions, we found a statistically significant 1.59% (95% CI: 0.9%, 2.29%) increase in admissions per degree increase in humidex above 37.4°C. Admissions stratified by cause and age produced statistically significant results with both relative risk and time series analyses for nephritis and nephrotic syndromes, acute renal failure, and natural heat exposure hospitalizations. This study demonstrates that heat, expressed as humidex, is associated with increased hospital admissions. When stratified by age and cause of admission, the non-elderly age groups (<85 years) experience significant risk for nephritis and nephrotic syndromes, acute renal failure, natural heat exposure, chronic obstructive pulmonary disease, and asthma hospitalizations.

Vulnerability to extreme heat by socio-demographic characteristics and area green space among the elderly in Michigan, 1990-2007

OBJECTIVES

We examined how individual and area socio-demographic characteristics independently modified the extreme heat (EH)-mortality association among elderly residents of 8 Michigan cities, May-September, 1990-2007.

METHODS

In a time-stratified case-crossover design, we regressed cause-specific mortality against EH (indicator for 4-day mean, minimum, maximum or apparent temperature above 97th or 99 th percentiles). We examined effect modification with interactions between EH and personal marital status, age, race, sex and education and ZIP-code percent "non-green space" (National Land Cover Dataset), age, race, income, education, living alone, and housing age (U.S. Census).

RESULTS

In models including multiple effect modifiers, the odds of cardiovascular mortality during EH (99 th percentile threshold) vs. non-EH were higher among non-married individuals (1.21, 95% CI=1.14-1.28 vs. 0.98, 95% CI=0.90-1.07 among married individuals) and individuals in ZIP codes with high (91%) non-green space (1.17, 95% CI=1.06-1.29 vs. 0.98, 95% CI=0.89-1.07 among individuals in ZIP codes with low (39%) non-green space). Results suggested that housing age may also be an effect modifier. For the EH-respiratory mortality association, the results were inconsistent between temperature metrics and percentile thresholds of EH but largely insignificant.

CONCLUSIONS

Green space, housing and social isolation may independently enhance elderly peoples' heat-related cardiovascular mortality vulnerability. Local adaptation efforts should target areas and populations at greater risk.

When are we most vulnerable to temperature variations in a day?

Daily temperature measures are commonly used when examining the association between temperature and mortality. In fact, temperature measures are available 24 hours a day and more detailed records may provide a better prediction of mortality compared to daily statistics. In this article, monthly stratified analysis modeling for mortality is conducted for the total population as well as the stratified elderly and younger subgroups. We identified the most significant time during the day that is associated with daily mortality. Surprisingly, the estimates of relative risk and magnitude of associations derived from the hourly temperature measures are similar or even stronger compared to those modeled by the daily statistics. This phenomenon remains true for lagged hourly temperature measures and the changing patterns of associations from January through December are revealed. In summary, people are the most vulnerable to temperature variations in the early morning around 5 am and the night time around 8 pm.