The effect of ambient temperature on diabetes mortality in China: A multi-city time series study

The relationship of short-term exposure to meteorological factors on diabetes mellitus mortality risk in Hefei, China: a time series analysis

OBJECTIVES

The study aims to explore whether short-term exposure to meteorological factors has a potential association with the risk of diabetes mellitus (DM) mortality.

METHODS

During the period 2015-2018, we collected daily data on meteorological factors and deaths of diabetic patients in Hefei. A total of 1101 diabetic deaths were recorded. We used structural equation modeling to initially explore the relationships among air pollutants, meteorological variables, and mortality, and generalized additive modeling (GAM) and distributional lag nonlinear modeling (DLNM) to explore the relationship between meteorological factors and the mortality risk of DM patients. We also stratified by age and gender. The mortality risk in diabetic patients was expressed by relative risks (RR) and 95% confidence intervals (CI) for both single and cumulative days.

RESULTS

Single-day lagged results showed a high relative humidity (RH) (75th percentile, 83.71%), a fairly high average temperature (T mean) (95th percentile, 30.32 °C), and an extremely low diurnal temperature range (DTR) (5th percentile, 3.13 °C) were positively related to the mortality risk of DM. Stratified results showed that high and very high levels of T mean were significantly positively linked to the mortality risk of DM among females and the elderly, while very high levels of DTR were linked to the mortality risk in men and younger populations.

CONCLUSION

In conclusion, this study found that short-duration exposure to quite high T mean, high RH, and very low DTR were significantly positively related to the mortality risk of DM patients. For women and older individuals, exposure to high and very high T mean environments should be minimized. Men and young adults should be aware of daily temperature changes.

Temperature, relative humidity and elderly type 2 diabetes mortality: A spatiotemporal analysis in Shandong, China

BACKGROUND

The mortality of type 2 diabetes mellitus (T2DM) can be affected by environmental factors. However, few studies have explored the effects of environmental factors across diverse regions over time. Given the vulnerability observed in the elderly group in previous research, this research applied Bayesian spatiotemporal models to assess the associations in the elderly group.

METHODS

Data on T2DM death in the elderly group (aged over 60 years old) at the county level were collected from the National Death Surveillance System between 1st January 2013 and 31st December 2019 in Shandong Province, China. A Bayesian spatiotemporal model was employed with the integrated Nested Laplace Approach to explore the associations between socio-environmental factors (i.e., temperatures, relative humidity, the Normalized Difference Vegetation Index (NDVI), particulate matter with a diameter of 2.5 μm or less (PM2.5) and gross domestic product (GDP)) and T2DM mortality.

RESULTS

T2DM mortality in the elderly group was found to be associated with temperature and relative humidity (i.e., temperature: Relative Risk (RR) = 1.41, 95% Credible Interval (CI): 1.27-1.56; relative humidity: RR = 1.05, 95% CI:1.03-1.06), while no significant associations were found with NDVI, PM2.5 and GDP. In winter, significant impacts from temperature (RR = 1.18, 95% CI: 1.06-1.32) and relative humidity (RR = 0.94, 95% CI: 0.89-0.99) were found. Structured and unstructured spatial effects, temporal trends and space-time interactions were considered in the model.

CONCLUSIONS

Higher mean temperatures and relative humidities increased the risk of elderly T2DM mortality in Shandong Province. However, a higher humidity level decreased the T2DM mortality risk in winter in Shandong Province. This research indicated that the spatiotemporal method could be a useful tool to assess the impact of socio-environmental factors on health by combining the spatial and temporal effects.

Associations of short-term ambient temperature exposure with lung function in middle-aged and elderly people: A longitudinal study in China

The short-term associations of ambient temperature exposure with lung function in middle-aged and elderly Chinese remain obscure. The study included 19,128 participants from the Dongfeng-Tongji cohort's first (2013) and second (2018) follow-ups. The lung function for each subject was determined between April and December 2013 and re-assessed in 2018, with three parameters (forced vital capacity [FVC], forced expiratory volume in 1 s [FEV1], and peak expiratory flow [PEF]) selected. The China Meteorological Data Sharing Service Center provided temperature data during the study period. In the two follow-ups, a total of 25,511 records (average age: first, 64.57; second, 65.80) were evaluated, including 10,604 males (41.57%). The inversely J-shaped associations between moving average temperatures (lag01-lag07) and FVC, FEV1, and PEF were observed, and the optimum temperatures at lag04 were 16.5 °C, 18.7 °C, and 16.2 °C, respectively. At lag04, every 1 °C increase in temperature was associated with 14.07 mL, 9.78 mL, and 62.72 mL/s increase in FVC, FEV1, and PEF in the low-temperature zone ( Collapse

Key Words

• Ambient temperature
• Generalized additive mixed model
• Linear mixed-effects model
• Lung function
• Middle-aged and elderly people
• Vulnerable groups

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Affiliation(s)

Weihong Qiu Department of Occupational and Environmental Health, School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan 430030, China Department of Epidemiology and Health Statistics, School of Public Health, Fujian Medical University, Fuzhou 350122, China
Bin Wang Department of Occupational and Environmental Health, School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan 430030, China
Xiaobing Feng Department of Occupational and Environmental Health, School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan 430030, China
Heng He Department of Epidemiology and Health Statistics, School of Public Health, Fujian Medical University, Fuzhou 350122, China
Lieyang Fan Department of Occupational and Environmental Health, School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan 430030, China
Zi Ye Department of Occupational and Environmental Health, School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan 430030, China
Xiuquan Nie Department of Occupational and Environmental Health, School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan 430030, China
Ge Mu Department of Occupational and Environmental Health, School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan 430030, China
Wei Liu Department of Occupational and Environmental Health, School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan 430030, China
Dongming Wang Department of Occupational and Environmental Health, School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan 430030, China
Min Zhou Department of Occupational and Environmental Health, School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan 430030, China
Weihong Chen Department of Occupational and Environmental Health, School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan 430030, China

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Impacts of heatwaves on type 2 diabetes mortality in China: a comparative analysis between coastal and inland cities

The impacts of extreme temperatures on diabetes have been explored in previous studies. However, it is unknown whether the impacts of heatwaves appear variations between inland and coastal regions. This study aims to quantify the associations between heat exposure and type 2 diabetes mellitus (T2DM) deaths in two cities with different climate features in Shandong Province, China. We used a case-crossover design by quasi-Poisson generalized additive regression with a distributed lag model with lag 2 weeks, controlling for relative humidity, the concentration of air pollution particles with a diameter of 2.5 µm or less (PM2.5), and seasonality. The wet- bulb temperature (Tw) was used to measure the heat stress of the heatwaves. A significant association between heatwaves and T2DM deaths was only found in the coastal city (Qingdao) at the lag of 2 weeks at the lowest Tw = 14℃ (relative risk (RR) = 1.49, 95% confidence interval (CI): 1.11-2.02; women: RR = 1.51, 95% CI: 1.02-2.24; elderly: RR = 1.50, 95% CI: 1.08-2.09). The lag-specific effects were significant associated with Tw at lag of 1 week at the lowest Tw = 14℃ (RR = 1.14, 95% CI: 1.03-1.26; women: RR = 1.15, 95% CI: 1.01-1.31; elderly: RR = 1.15, 95% CI: 1.03-1.28). However, no significant association was found in Jian city. The research suggested that Tw was significantly associated with T2DM mortality in the coastal city during heatwaves on T2DM mortality. Future strategies should be implemented with considering socio-environmental contexts in regions.

Hourly Heat Exposure and Acute Ischemic Stroke

Importance

Previous studies have demonstrated the associations of daily high temperature with hospitalizations and mortality from ischemic stroke, but the hourly association of ambient heat and acute ischemic stroke (AIS) onset has been rarely examined.

Objectives

To evaluate the association between hourly high ambient temperature and the onset of AIS.

Design, Setting, and Participants

This time-stratified case-crossover study was conducted using a nationwide registry that collects data from more than 200 stroke centers in China. Participants were adult patients with AIS who were hospitalized in the warm seasons between January 1, 2019, and December 31, 2021.

Exposures

Hourly temperature and single-hour temperature exposure lag up to 24 hours before the AIS onset (lag 0 hours to lag 24 hours).

Main Outcomes and Measures

The main outcome was onset of AIS. Associations between hourly mean temperatures and AIS onset were analyzed using conditional logistic regression integrated with the distributed lag nonlinear model. Stratification analyses were applied to examine potential association modifiers. Several sensitivity analyses were conducted to examine the robustness of the results.

Results

A total of 82 455 patients with AIS (mean [SD] age, 65.8 [11.9] years; 52 267 males [63.4%]) were included in the final analysis. A monotonically increasing risk of AIS onset was associated with higher temperatures. The excess AIS risk occurred immediately at lag 0 hours and persisted for 10 hours. Compared with the reference temperature (12.1 °C), the cumulative odds ratio (OR) over lag 0 to 10 hours of AIS onset associated with extremely high temperature (33.3 °C) was 1.88 (95% CI, 1.65-2.13) nationwide. The exposure-response curve was steeper in the north than in the south (OR, 1.80 [95% CI, 1.53-2.11] vs 1.57 [95% CI, 1.31-1.87]). The ORs were greater for males and patients with a history of dyslipidemia or atrial fibrillation, but the differences were not significant.

Conclusions and Relevance

Results of this study suggest that hourly heat exposure is associated with increased risk of AIS onset. This finding may benefit the formulation of public health strategies to reduce cerebrovascular risk associated with high ambient temperature under global warming.

Effects of apparent temperature on daily outpatient and inpatient visits for cause-specific respiratory diseases in Ganzhou, China: a time series study

BACKGROUND

Non-optimum temperatures are associated with increased risk of respiratory diseases, but the effects of apparent temperature (AT) on respiratory diseases remain to be investigated.

METHODS

Using daily data from 2016 to 2020 in Ganzhou, a large city in southern China, we analyzed the impact of AT on outpatient and inpatient visits for respiratory diseases. We considered total respiratory diseases and five subtypes (influenza and pneumonia, upper respiratory tract infection (URTI), lower respiratory tract infection (LRTI), asthma and chronic obstructive pulmonary disease [COPD]). Our analysis employed a distributed lag nonlinear model (DLNM) combined with a generalized additive model (GAM).

RESULTS

We recorded 94,952 outpatients and 72,410 inpatients for respiratory diseases. We found AT significantly non-linearly associated with daily outpatient and inpatient visits for total respiratory diseases, influenza and pneumonia, and URTI, primarily during comfortable AT levels, while it was exclusively related with daily inpatient visits for LRTI and COPD. Moderate heat (32.1 °C, the 75.0th centile) was observed with a significant effect on both daily outpatient and inpatient visits for total respiratory diseases at a relative risk of 1.561 (1.161, 2.098) and 1.276 (1.027, 1.585), respectively (both P < 0.05), while the results of inpatients became insignificant with the adjustment for CO and O3. The attributable fractions in outpatients and inpatients were as follows: total respiratory diseases (24.43% and 18.69%), influenza and pneumonia (31.54% and 17.33%), URTI (23.03% and 32.91%), LRTI (37.49% and 30.00%), asthma (9.83% and 3.39%), and COPD (30.67% and 10.65%). Stratified analyses showed that children ≤5 years old were more susceptible to moderate heat than older participants.

CONCLUSIONS

In conclusion, our results indicated moderate heat increase the risk of daily outpatient and inpatient visits for respiratory diseases, especially among children under the age of 5.

Impact of environmental factors on diabetes mortality: A comparison between inland and coastal areas

BACKGROUND

Diabetes mortality varies between coastal and inland areas in Shandong Province, China. However, evidence about the reasons for this disparity is limited. We assume that distinct environmental conditions may contribute to the disparities in diabetes mortality patterns between coastal and inland areas.

METHOD

Qingdao and Jinan were selected as typical coastal and inland cities in Shandong Province, respectively, with similar socioeconomic but different environmental characteristics. Data on diabetes deaths and environmental factors (i.e., temperature, relative humidity and air pollution particles with a diameter of 2.5 μm or less (PM2.5)) were collected from 2013 to 2020. Spatial kriging methods were used to estimate the aggregated diabetes mortality at the city level. A distributed lag non-linear model (DLNM) was used to quantify the possible cumulative and non-cumulative associations between environmental factors and diabetes mortality by age, sex and location.

RESULTS

In the coastal city (Qingdao), the maximum cumulative relative risks (RRs) of temperature and PM2.5 associated with diabetes deaths were 2.54 (95 % confidence interval (CI): 1.25-5.15), and 1.17 (95 % CI: 1.01-1.37) respectively, at lag 1 week. In the inland city (Jinan), only temperature exhibited significant cumulative associations with diabetes deaths (RR = 1.54, 95 % CI: 1.07-2.23 at 29 °C). Lower relative humidity (22 %-45 %) had a lag-specific association with diabetes deaths in inland areas at lag 3 weeks (RR = 1.33, 95 % CI: 1.03-1.70 at 22 %).

CONCLUSION

Despite the lower PM2.5 concentrations in the coastal location, diabetes mortality exhibited stronger links to environmental variables in the coastal city than in the inland city. These findings suggest that the control of air pollution could decrease the mortality burden of diabetes, even in the region with relatively good air quality. Additionally, the spatial estimation method is recommended to identify associations between environmental factors and diseases in studies with limited data.

Effects of Short- And Medium-Term Exposures to Lower Air Temperature on 71 Novel Biomarkers of Subclinical Inflammation: Results from the KORA F4 Study

Increasing evidence has revealed that exposure to low temperatures is linked to a higher risk of chronic diseases and death; however, the mechanisms underlying the observed associations are still poorly understood. We performed a cross-sectional analysis with 1115 participants from the population-based KORA F4 study, which was conducted in Augsburg, Germany, from 2006 to 2008. Seventy-one inflammation-related protein biomarkers were analyzed in serum using proximity extension assay technology. We employed generalized additive models to explore short- and medium-term effects of air temperature on biomarkers of subclinical inflammation at cumulative lags of 0-1 days, 2-6 days, 0-13 days, 0-27 days, and 0-55 days. We found that short- and medium-term exposures to lower air temperature were associated with higher levels in 64 biomarkers of subclinical inflammation, such as Protein S100-A12 (EN-RAGE), Interleukin-6 (IL-6), Interleukin-10 (IL-10), C-C motif chemokine 28 (CCL28), and Neurotrophin-3 (NT-3). More pronounced associations between lower air temperature and higher biomarker of subclinical inflammation were observed among older participants, people with cardiovascular disease or prediabetes/diabetes, and people exposed to higher levels of air pollution (PM2.5, NO2, and O3). Our findings provide intriguing insight into how low air temperature may cause adverse health effects by activating inflammatory pathways.

Temporal trend and global burden of type 2 diabetes attributable to non-optimal temperature, 1990-2019: an analysis for the Global Burden of Disease Study 2019

Exposure to hot or cold temperatures was reported to be associated with increased mortality and morbidity of type 2 diabetes, but few studies have estimated the temporal trend and global burden of type 2 diabetes attributable to non-optimal temperature. Based on the Global Burden of Disease Study 2019, we collected data on the numbers and rates of deaths and disability-adjusted life years (DALYs) of type 2 diabetes attributed to non-optimal temperature. The joinpoint regression analysis was used to estimate the temporal trends of the age-standardized rate of mortality and DALYs from 1990 to 2019 by average annual percentage change (AAPC). From 1990 to 2019, globally, the numbers of deaths and DALYs of type 2 diabetes attributable to non-optimal temperature increased by 136.13% (95% (uncertainty interval) UI: 87.04% to 277.76%) and 122.26% (95% UI: 68.77% to 275.59%), with the number from 0.05 (95% UI: 0.02 to 0.07) million and 0.96 (95% UI: 0.37 to 1.51) million in 1990 to 0. 11 (95% UI: 0.07 to 0.15) million and 2.14 (95% UI: 1.35 to 3.13) million in 2019. The age-standardized mortality rate (ASMR) and DALYs rate (ASDR) of type 2 diabetes attributable to non-optimal temperature showed an increasing trend in the high temperature effect and lower (low, low-middle and middle) socio-demographic index (SDI) region, with AAPCs of 3.17%, 1.24%, 1.61%, and 0.79% (all P < 0.05), respectively. The greatest increased ASMR and ASDR were observed in Central Asia, followed by Western Sub-Saharan Africa and South Asia. Meanwhile, the contribution of type 2 diabetes burden attributable to high temperature gradually increased globally and in five SDI regions. In addition, the global age-specific rate of mortality and DALYs of type 2 diabetes attributable to non-optimal temperature for both men and women almost increased with age in 2019. The global burden of type 2 diabetes attributable to non-optimal temperature increased from 1990 to 2019, particularly in high temperature, regions with lower SDI, and the older population. Appropriate temperature interventions are necessary to curb climate change and increasing diabetes.

A distributed lag non-linear time-series study of ambient temperature and healthcare-associated infections in Hefei, China

Little is known about the effects of temperature on healthcare-associated infections (HAIs). A distributed lag non-linear model was used to estimate the association between ambient temperature and HAIs in Hefei, China. In total, 9,592 HAIs were included. The effect of low temperature (-0.1°C, 2.5th percentile) was significant on the current day (RR = 1.108, 95%CI:1.003-1.222), and then appeared on the 4th day (RR = 1.045, 95%CI:1.007-1.084) and the 5th day (RR = 1.033, 95%CI:1.006-1.061). The cumulative lag effects of low temperature lasted from the 5th to 10th days (RR = 1.123-1.143), and a long-term cumulative lag effect was observed on the 14th day (RR = 1.157, 95%CI:1.001-1.338). The lag effect of high temperature (31.0°C, 97.5th percentile) was not statistically significant. However, the effects of temperatures on HAIs were not significant among gender or age subgroups. This study suggests that the low temperatures have acute and lag effects on HAIs in Hefei, China.

Urban-rural disparity in heatwave effects on diabetes mortality in eastern China: A case-crossover analysis in 2016-2019

Diabetics are sensitive to high ambient temperature due to impaired thermoregulation. However, available evidence on the impact of prolonged high temperature (i.e., heatwave) on diabetes deaths is limited and whether urban and rural areas differ in heatwave vulnerability remains unknown so far. A time-stratified case-crossover analysis was employed to estimate the association between heatwaves and diabetes deaths in 1486 districts (509 urban and 977 rural areas) of eastern China (Jiangsu Province), 2016-2019. For each decedent, residential heatwave exposure was measured by matching daily mean temperatures to the geocoded residential address. We adopted nine-tiered heatwave definitions incorporating intensity and duration. Stratified analyses by decedents' characteristics (gender, age, and education) were also conducted. During the study period, there were 18,685 deaths from diabetes (urban proportion: 36.95 %, p-value for urban-rural difference < 0.05). Heatwaves were associated with an increased risk of diabetes deaths, with greater and longer-lasting effects in rural areas than urban areas [e.g., rural odds ratio (OR): 1.19 (95 % confidence interval (CI): 1.14, 1.25) vs. urban OR: 1.09 (95 % CI: 1.05, 1.12)]. Risk of diabetes deaths increased with the intensity of heatwaves in rural areas (p-value for trend <0.01), but not in urban areas. Stratified analyses in rural areas suggested that females and less-educated people were more vulnerable to heatwave-related diabetes deaths. Our findings revealed the urban-rural disparity in the risk of diabetes deaths associated with heatwaves. Rural diabetics should be made aware of the increased death risk posed by heatwaves in the context of warming climate.

Age- and Gender-Specific Differences in the Seasonal Distribution of Diabetes Mortality in Shandong, China: A Spatial Analysis

Diabetes mortality in Shandong is higher than the national average in China. This study first explored diabetes mortality variation spatially at the county/district level among adults aged over 30 years in terms of age and gender, specifically by season. Daily diabetes mortality data were collected from 31 mortality surveillance points across Shandong Province in 2014. A geographic information system, spatial kriging interpolation and a spatial clustering method were used to examine the spatial patterns of diabetes mortality at the county/district level by season. Sensitivity analysis was conducted using diabetes mortality data from 10 mortality surveillance points from 2011 to 2020. As a result, the total diabetes mortality in eastern counties/districts was the highest (relative risk (RR) of cluster: 1.58, p = 0.00) across the whole province. For subgroups, women had higher mortality (16.84/100,000) than men (12.15/100,000), people aged over 75 years were the most vulnerable (93.91/100,000) and the highest-risk season was winter. However, the mortality differences between winter and summer were smaller in eastern and coastal regions than in other regions for all gender- and age-specific groups. The findings provide further evidence for early warning and precision preventative strategies for diabetes mortality in different regions of Shandong Province. Future research is required to identify the risk factors for diabetes and understand the differences in the social and environmental contexts.

Associations between cold spells and hospital admission and mortality due to diabetes: A nationwide multi-region time-series study in Korea

BACKGROUND

Climate change is predicted to increase the frequency, intensity, and duration of extreme cold events in the mid-latitudes. However, although diabetes is one of the most critical metabolic diseases due to its high and increasing prevalence worldwide, few studies have investigated the short-term association between cold exposure and diabetes-related outcomes.

OBJECTIVE

The aim of this study was to investigate the associations between cold spells and their characteristics (intensity, duration, and seasonal timing) and hospital admission and mortality due to diabetes.

METHODS

This study used claims data from the National Health Insurance Service and cause-specific mortality data from Statistics Korea (2010-2019). Cold spells were defined as ≥2 consecutive days with a daily mean temperature lower than the region-specific 5th percentile during the cold season (November-March). Quasi-Poisson regressions combined with distributed lag models were used to assess the associations between exposures and outcomes in 16 regions across the Republic of Korea. Meta-analyses were conducted to pool the region-specific estimates.

RESULTS

Exposure to cold spells was associated with an increased risk of hospital admission [relative risk (RR) = 1.45, 95% confidence interval (CI): 1.26, 1.66] and mortality (RR = 2.02, 95% CI: 1.37, 2.99) due to diabetes. The association between cold spells and hospital admission due to diabetes was stronger for cold spells that were more intense, longer, and occurred later during the cold season. The association between cold spells and diabetes-related mortality was stronger for more intense and longer cold spells.

CONCLUSION

This study emphasizes the importance of developing effective interventions against cold spells, including education on the dangers of cold spells and early alarm systems. Further studies are needed to create real-world interventions and evaluate their effectiveness in improving diabetes-related outcomes.

Impact of high, low, and non-optimum temperatures on chronic kidney disease in a changing climate, 1990-2019: A global analysis

BACKGROUND

Although a few studies have reported the relationship between high and low temperatures and chronic kidney disease (CKD), the global burden of CKD attributable to extreme heat and cold in recent decades remains unknown.

METHODS

Based on the Global Burden of Disease Study (GBD) 2019, we obtained data on age-standardized mortality rates (ASMR) and age-standardized rates of disability-adjusted life years (ASDR) per 100 000 population of the CKD attributable to non-optimum temperatures from 1990 to 2019. The annual mean temperature of each country was used to divide each country into five climate zones (tropical, subtropical, warm-temperate, cool-temperate, and boreal). The locally weighted regression model was used to estimate the burden for different climate zones and Socio-demographic index (SDI) regions.

RESULTS

In 1990, the ASMR and ASDR due to high temperature estimated -0.01 (95% UI, -0.74 to 0.44) and -0.32 (-21.66 to 12.66) per 100 000 population, respectively. In 2019, the ASMR and ASDR reached 0.10 (-0.28 to 0.38) and 2.71 (-8.07 to 10.46), respectively. The high-temperature burden increased most rapidly in tropical and low SDI regions. There were 0.99 (0.59 to 1.39) ASMR attributable to low-temperature in 1990, which increased to 1.05 (0.61-1.49) in 2019. While the ASDR due to low temperature declined from 22.03 (12.66 to 30.64) in 1990 to 20.43 (11.30 to 29.26) in 2019. Overall, the burden of CKD attributable to non-optimal temperatures has increased from 1990 to 2019. CKD due to hypertension and diabetes mellitus were the primary causes of CKD death attributable to non-optimum temperatures in 2019 with males and older adults being more susceptible to these temperatures.

CONCLUSIONS

The CKD burden due to high, low, and non-optimum temperatures varies considerably by regions and countries. The burden of CKD attributable to high temperature has been increasing since 1990.

Excess out-of-hospital cardiac arrests due to ambient temperatures in South Korea from 2008 to 2018

Out-of-hospital cardiac arrest (OHCA) is a notable public health issue with negative outcomes, such as high mortality and aftereffects. Additionally, the adverse effects of extreme temperatures on health have become more important under climate change; however, few studies have investigated the relationship between temperature and OHCA. In this study, we examined the association between temperature and OHCA and its underlying risk factors. We conducted a two-stage time-series analysis using a Poisson regression model with a distributed lag non-linear model (DLNM) and meta-analysis, based on a nationwide dataset from South Korea (2008-2018). We found that 17.4% of excess OHCA was attributed to cold, while 0.9% was attributed to heat. Based on central estimates, excess OHCA attributed to cold were more prominent in the population with hypertension comorbidity (31.0%) than the populations with diabetes (24.3%) and heart disease (17.4%). Excess OHCA attributed to heat were larger in the populations with diabetes (2.7%) and heart disease comorbidity (2.7%) than the population with hypertension (1.2%) based on central estimates. Furthermore, the time-varying excess OHCA attributed to cold have decreased over time, and although those of heat did not show a certain pattern during the study period, there was a weak increasing tendency since 2011. In conclusion, we found that OHCAs were associated with temperature, and cold temperatures showed a greater impact than that of hot temperatures. The effects of cold and hot temperatures on OHCA were more evident in the populations with hypertension, diabetes, and heart diseases, compared to the general population. In addition, the impacts of heat on OHCA increased in recent years, while those of cold temperatures decreased. Our results provide scientific evidence for policymakers to mitigate the OHCA burden attributed to temperature.

Association between heat exposure and hospitalization for diabetic ketoacidosis, hyperosmolar hyperglycemic state, and hypoglycemia in Japan

BACKGROUND

An increase in extreme heat events has been reported along with global warming. Heat exposure in ambient temperature is associated with all-cause diabetes mortality and all-cause hospitalization in diabetic patients. However, the association between heat exposure and hospitalization for hyperglycemic emergencies, such as diabetic ketoacidosis (DKA), hyperosmolar hyperglycemic state (HHS), and hypoglycemia is unclear. The objective of our study is to clarify the impact of heat exposure on the hospitalization for DKA, HHS, and hypoglycemia.

METHODS

Data of daily hospitalizations for hyperglycemic emergencies (i.e., DKA or HHS) and hypoglycemia was extracted from a nationwide administrative database in Japan and linked with temperature in each prefecture in Japan during 2012-2019. We applied distributed lag non-linear model to evaluate the non-linear and lagged effects of heat exposure on hospitalization for hyperglycemic emergencies.

RESULTS

The pooled relative risk for hyperglycemic emergencies of heat effect (the 90th percentile of temperature with reference to the 75th percentile of temperature) and extreme heat effect (the 99th percentile of temperature with reference to the 75th percentile of temperature) over 0-3 lag days was 1.27 (95 %CI: 1.16-1.39) and 1.64 (95 %CI: 1.38-1.93), respectively. The pooled relative risk for heat effect on hospitalization for hypoglycemia and extreme heat effect over 0-3 lag days was 1.33 (95 %CI: 1.17-1.52) and 1.65 (95 %CI: 1.29-2.10), respectively. These associations were consistent by type of hyperglycemic emergencies and type of diabetes and were generally consistent by regions.

DISCUSSION

Heat exposure was associated with hospitalizations for DKA, HHS and hypoglycemia. These results may be useful to guide preventive actions for the risk of fatal hyperglycemic emergencies and hypoglycemia.

Spatiotemporal relationship between temperature and non-accidental mortality: Assessing effect modification by socioeconomic status

BACKGROUND

Most published studies have assessed the overall health impact of temperature by using one-station or multiple-station averaged meteorological and air quality data. Concern has arisen about whether the temperature health impact is homogeneous across the whole territory geographically, since green space and socioeconomic factors may modify the impact.

OBJECTIVE

This study aims at investigating how small-area mortality is modified by local temperature and other meteorological, air quality, green space, and socioeconomic factors of small geographic units in a subtropical urban setting.

METHODS

Data on meteorological, air pollutants, and non-accidental mortality count in Hong Kong during 2006-2016 were obtained. Combined with green space and socioeconomic data, spatiotemporal analysis using Generalized Additive Mixed Models was conducted to examine the temperature-mortality relationship, adjusted for seasonality, long-term trend, other meteorological factors, pollutants, socioeconomic characteristics and green space.

RESULTS

Socioeconomic status was found to modify the temporal temperature-mortality relationship. A J-shape association was identified for most areas in Hong Kong, where a sharp increase of mortality was observed when daily minimum temperature dropped lower than the turning point. However, for people living in the most affluent areas, after the initial increase there was a decrease of mortality for colder days. Besides, when comparing the two spatiotemporal models (i.e. using nearby or central temperature monitoring station), while leaving the other predictors unchanged, this study showed that there was little difference in the overall model performances.

CONCLUSION

This study indicated that the daily fluctuation of mortality was associated with daily temperature, while the spatial variation of mortality within this city could be explained by the geographical distribution of green space and socioeconomic factors. Since people living in affluent areas were found to be more tolerant of cold temperatures, it would be more efficient to tailor cold temperature health education and warning information for socioeconomically deprived communities.

The Association between Weather and Emergency Department Visitation for Diabetes in Roanoke, Virginia

Diabetes mellitus imposes a significant and increasing health burden on the US population. Our objective is to determine if weather is related to daily variations in emergency department (ED) visits for diabetes mellitus in Roanoke, Virginia. A time series of daily ED visits for diabetes mellitus at the Carilion Clinic in southwestern Virginia is associated with daily minimum temperature from 2010-2017. Associations between ED visits (through a 14-day lag period) and temperature are examined using generalized additive models and distributed lag nonlinear models. Heat and cold waves are identified at low and high thresholds, and ED visitation during these events is compared to prior control periods using a time-stratified case crossover approach. ED visits for diabetes exhibit a U-shaped relationship with temperature, with a higher relative risk (RR) during cold events (RR = 1.05) vs. warm events (RR = 1.02). When minimum temperatures are below freezing, ED visitation peaks starting 2 days afterward, with RRs approaching 1.04. The RR on warm days (minimum temperature > 10 °C) approaches 1.02 but peaks on the day of or the day following the elevated temperatures. Cold waves increase the odds of ED visits by up to 11% (p = 0.01), whereas heat waves exhibit no significant effect (p = 0.07). The increasing health burden linked to diabetes requires new research on environmental factors that might exacerbate related illness. When examined in the context of climate change impacts on local weather variations, these kinds of linkages between environment and disease can aid in facility staffing and public health messaging during extreme weather events.

A Novel Machine Learning Approach for Severity Classification of Diabetic Foot Complications Using Thermogram Images

Diabetes mellitus (DM) is one of the most prevalent diseases in the world, and is correlated to a high index of mortality. One of its major complications is diabetic foot, leading to plantar ulcers, amputation, and death. Several studies report that a thermogram helps to detect changes in the plantar temperature of the foot, which may lead to a higher risk of ulceration. However, in diabetic patients, the distribution of plantar temperature does not follow a standard pattern, thereby making it difficult to quantify the changes. The abnormal temperature distribution in infrared (IR) foot thermogram images can be used for the early detection of diabetic foot before ulceration to avoid complications. There is no machine learning-based technique reported in the literature to classify these thermograms based on the severity of diabetic foot complications. This paper uses an available labeled diabetic thermogram dataset and uses the k-mean clustering technique to cluster the severity risk of diabetic foot ulcers using an unsupervised approach. Using the plantar foot temperature, the new clustered dataset is verified by expert medical doctors in terms of risk for the development of foot ulcers. The newly labeled dataset is then investigated in terms of robustness to be classified by any machine learning network. Classical machine learning algorithms with feature engineering and a convolutional neural network (CNN) with image-enhancement techniques are investigated to provide the best-performing network in classifying thermograms based on severity. It is found that the popular VGG 19 CNN model shows an accuracy, precision, sensitivity, F1-score, and specificity of 95.08%, 95.08%, 95.09%, 95.08%, and 97.2%, respectively, in the stratification of severity. A stacking classifier is proposed using extracted features of the thermogram, which is created using the trained gradient boost classifier, XGBoost classifier, and random forest classifier. This provides a comparable performance of 94.47%, 94.45%, 94.47%, 94.43%, and 93.25% for accuracy, precision, sensitivity, F1-score, and specificity, respectively.

Impact of low-intensity heat events on mortality and morbidity in regions with hot, humid summers: a scoping literature review

The objective of this study is to determine the impacts of low-intensity heat on human health in regions with hot, humid summers. Current literature has highlighted an increase in mortality and morbidity rates during significant heat events. While the impacts on high-intensity events are established, the impacts on low-intensity events, particularly in regions with hot, humid summers, are less clear. A scoping review was conducted searching three databases (PubMed, EMBASE, Web of Science) using key terms based on the inclusion criteria. We included papers that investigated the direct human health impacts of low-intensity heat events (single day or heatwaves) in regions with hot, humid summers in middle- and high-income countries. We excluded papers written in languages other than English. Of the 600 publications identified, 33 met the inclusion criteria. Findings suggest that low-intensity heatwaves can increase all-cause non-accidental, cardiovascular-, respiratory- and diabetes-related mortality, in regions experiencing hot, humid summers. Impacts of low-intensity heatwaves on morbidity are less clear, with research predominantly focusing on hospitalisation rates with a range of outcomes. Few studies investigating the impact of low-intensity heat events on emergency department presentations and ambulance dispatches were found. However, the data from a limited number of studies suggest that both of these outcome measures increase during low-intensity heat events. Low-intensity heat events may increase mortality. There is insufficient evidence of a causal effect of low-intensity heat events on increasing morbidity for a firm conclusion. Further research on the impact of low-intensity heat on morbidity and mortality using consistent parameters is warranted.

Estimation of Relative Risk of Mortality and Economic Burden Attributable to High Temperature in Wuhan, China

In the context of climate change, most of the global regions are facing the threat of high temperature. Influenced by tropical cyclones in the western North Pacific Ocean, high temperatures are more likely to occur in central China, and the economic losses caused by heat are in urgent need of quantification to form the basis for health decisions. In order to study the economic burden of high temperature on the health of Wuhan residents between 2013 and 2019, we employed meta-analysis and the value of statistical life (VSL) approach to calculate the relative risk of high temperature health endpoints, the number of premature deaths, and the corresponding economic losses in Wuhan City, China. The results suggested that the pooled estimates of relative risk of death from high temperature health endpoints was 1.26 [95% confidence interval (CI): 1.15, 1.39]. The average number of premature deaths caused by high temperature was estimated to be 77,369 (95% CI: 48,906–105,198) during 2013–2019, and the induced economic losses were 156.1 billion RMB (95% CI: 92.28–211.40 billion RMB), accounting for 1.81% (95% CI: 1.14–2.45%) of Wuhan's annual GDP in the seven-year period. It can be seen that high temperature drives an increase in the premature deaths, and the influence of high temperature on human health results in an economic burden on the health system and population in Wuhan City. It is necessary for the decision-makers to take measures to reduce the risk of premature death and the proportion of economic loss of residents under the impacts of climate change.

Impact of short-term exposure to extreme temperatures on diabetes mellitus morbidity and mortality? A systematic review and meta-analysis

The relationship between diabetes mellitus and short-term exposure to extreme temperatures remains controversial. A systematic review and meta-analysis were performed to assess the association between extreme temperatures and diabetes mellitus morbidity and mortality. PubMed, Embase, the Cochrane Library, Web of Science, and the Cumulative Index to Nursing and Allied Health Literature (CINAHL) were searched since inception to January 1, 2019, and updated on November 17, 2020. The results were combined using random effects model and reported as relative risk (RR) with 95% confidence interval (CI). In total, 32 studies met the inclusion criteria. (1) Both heat and cold exposures have impact on diabetes. (2) For heat exposure, the subgroup analysis revealed that the effect on diabetes mortality (RR=1.139, 95% CI: 1.089-1.192) was higher than morbidity (RR=1.012, 95% CI: 1.004-1.019). (3) With the increase of definition threshold, the impact of heat exposure on diabetes rose. (4) A stronger association between heat exposure and diabetes was observed in the elderly (≥ 60 years old) (RR=1.040, 95% CI: 1.017-1.064). In conclusion, short-term exposure to both heat and cold temperatures has impact on diabetes. The elderly is the vulnerable population of diabetes exposure to heat temperature. Developing definitions of heatwaves at the regional level are suggested.

Exploring the Relationship between Mumps and Meteorological Factors in Shandong Province, China Based on a Two-Stage Model

Background: Small-scale studies have identified temperature and other meteorological factors as risk factors for human health. However, only a few have quantified the specific impact of meteorological factors on mumps. A quantitative examination of the exposure–response relationship between meteorological factors and mumps is needed to provide new insights for multi-city analysis. Methods: The daily recorded number of mumps cases and meteorological data in 17 cities of Shandong Province from 2009 to 2017 were collected. A two-stage model was built to explore the relationship between meteorological factors and mumps. Results: A total of 104,685 cases of mumps were recorded from 2009 to 2017. After controlling for seasonality and long-term trends, the effect of low temperature on mumps was significant at the provincial level, with a cumulative RR of 1.035 (95%CI: 1.002–1.069) with a 1-day lagged effect. The proportion of primary and middle school students was determined as an effect modifier, which had a significant impact on mumps (Stat = 8.374, p = 0.039). There was heterogeneity in the combined effect of temperature on mumps (Q = 95.447, p = 0.000), and its size was I² = 49.7%. Conclusions: We have identified a non-linear relationship between mumps and temperature in Shandong Province. In particular, low temperatures could bring more cases of mumps, with certain lagged effects. More public health measures should be taken to reduce the risks when temperatures are low, especially for cities with a high proportion of primary and secondary school students.

The effect of the heatwave on the morbidity and mortality of diabetes patients; a meta-analysis for the era of the climate crisis

INTRODUCTION

From the perspective of public health, the climate crisis is also causing many health problems worldwide. In contrast with the cardiovascular, respiratory, and urinary system, the adverse effects of heatwaves on the endocrine system, particularly in people with diabetes mellitus (DM), are not well established to date. In this study, the author investigated the morbidity and mortality changes of DM patients during heatwave periods, using the meta-analysis method.

METHODS

The author searched MEDLINE, EMBASE, and the Cochrane Library until March 12, 2020. The quality of each included study was assessed using the National Institutes of Health (NIH) Quality Assessment tools. The meta-analysis was conducted using the studies with a relative risk (RR) estimate and odds ratio (OR) estimate. The subgroup analysis and the meta-ANOVA analysis were conducted using various covariates, including lag days considered.

RESULTS

Only 36 articles were included in the meta-analysis. The pooled RR of mortality and of morbidity for diabetics under the heatwave were 1.18 (95% CI 1.13-1.25) and 1.10 (95% CI 1.06-1.14). For mortality studies, whether or not the lag days considered were 10 days or more was only a significant covariate for the meta-ANOVA analysis (Q = 3.17, p = 0.075). For morbidity studies, the definition of the heatwave (Q = 65.94, p < 0.0001), whether or not the maximum temperature was 40 °C or more (Q = 4.78, p = 0.0288), and the type of morbidity (Q = 60.23, p < 0.0001) were significant covariates for the analysis.

DISCUSSION

The mortality and morbidity risks of diabetes patients under the heatwave were mildly increased by about 18 percent for mortality and 10 percent for overall morbidity. The mortality risk of diabetics can increase more when lag days of 10 days or more are considered than when lag days of less than 10 days are considered. These valuable findings can be used in developing public health strategies to cope with heatwaves in the current era of aggravating global warming and climate crisis.

Environmental Risk Factors and Health: An Umbrella Review of Meta-Analyses

Background: Environmental health is a growing area of knowledge, continually increasing and updating the body of evidence linking the environment to human health. Aim: This study summarizes the epidemiological evidence on environmental risk factors from meta-analyses through an umbrella review. Methods: An umbrella review was conducted on meta-analyses of cohort, case-control, case-crossover, and time-series studies that evaluated the associations between environmental risk factors and health outcomes defined as incidence, prevalence, and mortality. The specific search strategy was designed in PubMed using free text and Medical Subject Headings (MeSH) terms related to risk factors, environment, health outcomes, observational studies, and meta-analysis. The search was limited to English, Spanish, and French published articles and studies on humans. The search was conducted on September 20, 2020. Risk factors were defined as any attribute, characteristic, or exposure of an individual that increases the likelihood of developing a disease or death. The environment was defined as the external elements and conditions that surround, influence, and affect a human organism or population’s life and development. The environment definition included the physical environment such as nature, built environment, or pollution, but not the social environment. We excluded occupational exposures, microorganisms, water, sanitation and hygiene (WASH), behavioral risk factors, and no-natural disasters. Results: This umbrella review found 197 associations among 69 environmental exposures and 83 diseases and death causes reported in 103 publications. The environmental factors found in this review were air pollution, environmental tobacco smoke, heavy metals, chemicals, ambient temperature, noise, radiation, and urban residential surroundings. Among these, we identified 65 environmental exposures defined as risk factors and 4 environmental protective factors. In terms of study design, 57 included cohort and/or case-control studies, and 46 included time-series and/or case-crossover studies. In terms of the study population, 21 included children, and the rest included adult population and both sexes. In this review, the largest body of evidence was found in air pollution (91 associations among 14 air pollution definitions and 34 diseases and mortality diagnoses), followed by environmental tobacco smoke with 24 associations. Chemicals (including pesticides) were the third larger group of environmental exposures found among the meta-analyses included, with 19 associations. Conclusion: Environmental exposures are an important health determinant. This review provides an overview of an evolving research area and should be used as a complementary tool to understand the connections between the environment and human health. The evidence presented by this review should help to design public health interventions and the implementation of health in all policies approach aiming to improve populational health.

Interactive effect between temperature and fine particulate matter on chronic disease hospital admissions in the urban area of Tianjin, China

This study focuses on effects of fine particulate matter (PM_2.5) on chronic disease under different levels of temperature. We obtained type 2 diabetes, cerebral stroke and coronary heart disease hospital admissions (HAs) from five hospitals in urban Tianjin as well as the concentrations of PM_2.5, nitrogen dioxide (NO₂) and sulphur dioxide (SO₂). We used distributed lag nonlinear models to explore nonlinear and lag effects of PM_2.5. In single-pollutant models, PM_2.5 was positively associated with type 2 diabetes, cerebral stroke and coronary heart disease HAs, with strongest effects at lag1, lag0 and lag06, respectively. The corresponding relative risk rates (RR%) were 1.836%, 2.083% and 6.428%. In co-pollutant models, the correlation between PM_2.5 and HAs on high-temperature days was generally stronger than that on low-temperature days. This study indicated that PM_2.5 can increase HA rates for these chronic diseases, and effects of PM_2.5 on high-temperature days were stronger than that on low-temperature days.

Burden of cause-specific mortality attributable to heat and cold: A multicity time-series study in Jiangsu Province, China

Previous epidemiological studies primarily examined the temperature-related mortality burden of all-cause or cardiovascular diseases (CVD) and respiratory diseases. However, evidence on the heat- and cold-attributable mortality burden from other specific causes is limited. This paper aimed to systematically examine the association of heat and cold with a comprehensive spectrum of plausible temperature-related diseases, and to estimate the mortality burdens attributable to heat and cold. In the time-series study of 11 cities in Jiangsu, China, distributed lag non-linear models were applied to estimate city-specific temperature-mortality associations, and then meta-analysis was conducted to pool the estimates. A total of 1,368,648 cases of death were included in this study. Both extreme heat and cold were associated with increased mortality risks from all-cause, CVD, respiratory diseases, nervous diseases, and external causes. Short-term exposures to heat and cold were associated with excess burden of mortality for several specific diseases, accounting for 16.38% (95% eCI, 7.27-22.31%) for myocardial infarction (MI), 12.41% (95% eCI, 8.81-15.07%) for stroke, 27.97% (95% eCI, 18.42-33.35%) for hypertensive heart disease, 25.18% (95% eCI, 18.42-29.63%) for chronic obstructive pulmonary disease, and 28.46% (95% eCI: 4.93-33.57%) for Alzheimer's and dementia. Diabetes was only associated with extreme heat, with 4.61% (95% eCI, 0.13-7.13%) of diabetes mortality attributable to heat. In total, 11.98% (95% eCI, 10.46-13.08%) of mortality was attributable to heat and cold, with 3.49% (95% eCI, 2.87-4.00%) attributable to heat and 8.48% (95% eCI, 7.31-9.49%) attributable to cold, and about 64% of this overall temperature-related mortality burden was found in 6 aforementioned specific causes and about 10% of mortality burden in external causes. Extreme heat and/or cold are associated with increased risks of mortality from a wide range of causes, including previously identified causes in cardiorespiratory diseases and under-studied causes such as diabetes and Alzheimer's and dementia. Future research is needed to confirm the substantial mortality burden of heat and cold.

The Mortality Risk and Socioeconomic Vulnerability Associated with High and Low Temperature in Hong Kong

(1) Background: The adverse health effect associated with extreme temperature has been extensively reported in the current literature. Some also found that temperature effect may vary among the population with different socioeconomic status (SES), but found inconsistent results. Previous studies on the socioeconomic vulnerability of temperature effect were mainly achieved by multi-city or country analysis, but the large heterogeneity between cities may introduce additional bias to the estimation. The linkage between death registry and census in Hong Kong allows us to perform a city-wide analysis in which the study population shares virtually the same cultural, lifestyle and policy environment. This study aims to examine and compare the high and low temperature on morality in Hong Kong, a city with a subtropical climate and address a key research question of whether the extreme high and low temperature disproportionally affects population with lower SES. (2) Methods: Poisson-generalized additive models and distributed-lagged nonlinear models were used to examine the association between daily mortality and daily mean temperature between 2007–2015 with other meteorological and confounding factors controlled. Death registry was linked with small area census and area-level median household income was used as the proxy for socioeconomic status. (3) Results: 362,957 deaths during the study period were included in the analysis. The minimum mortality temperature was found to be 28.9 °C (82nd percentile). With a subtropical climate, the low temperature has a stronger effect than the high temperature on non-accidental, cardiovascular, respiratory and cancer deaths in Hong Kong. The hot effect was more pronounced in the first few days, while cold effect tended to last up to three weeks. Significant heat effect was only observed in the lower SES groups, whilst the extreme low temperature was associated with significantly higher mortality risk across all SES groups. The older population were susceptible to extreme temperature, especially for cold. (4) Conclusions: This study raised the concern of cold-related health impact in the subtropical region. Compared with high temperature, low temperature may be considered a universal hazard to the entire population in Hong Kong rather than only disproportionally affecting people with lower SES. Future public health policy should reconsider the strategy at both individual and community levels to reduce temperature-related mortality.

Projections of temperature-related cause-specific mortality under climate change scenarios in a coastal city of China

BACKGROUND

Numerous studies have been conducted to project temperature-related mortality under climate change scenarios. However, most of the previous evidence has been limited to the total or non-accidental mortality, resulting in insufficient knowledge on the influence of climate change on different types of disease.

OBJECTIVES

We aimed to project future temperature impact on mortality from 16 causes under multiple climate change models in a coastal city of China.

METHODS

We first estimated the baseline exposure-response relationships between daily average temperature and cause-specific mortality during 2009-2018. Then, we acquired downscaled future temperature projections from 28 general circulation models (GCMs) under two Representative Concentration Pathway (RCP4.5 and RCP8.5). Finally, we combined these exposure-response associations with projected temperature to estimate the change in the temperature-related death burden in different future decades in comparison to the 2010 s, assuming no demographic changes and population acclimatization.

RESULTS

We found a consistently decreasing trend in cold-related mortality but a steep rise in heat-related mortality among 16 causes under climate change scenarios. Compared with the 2010 s, the net change in the fraction of total mortality attributable to temperature are projected to -0.54% (95% eCI: -1.69% to 0.71%) and -0.38% (95% eCI: -2.73% to 2.12%) at the end of the 21st century under RCP4.5 and RCP8.5, respectively. However, the magnitude of future cold and heat effects varied by different causes of death. A net reduction of future temperature-related death burden was observed among 10 out of 15 causes, with estimates ranging from -5.02% (95% eCI: -17.42% to 2.50%) in mental disorders to -1.01% (95% eCI: -5.56% to 3.28%) in chronic lower respiratory disease. Conversely, the rest diseases are projected to experience a potential net increase of temperature-related death burden, with estimates ranging from 0.44% (95% eCI: -4.40% to 6.02%) in ischemic heart disease and 4.80% (95% eCI: -0.04% to 9.84%) in external causes.

CONCLUSIONS

Our study indicates that the mortality burden of climate change varied greatly by the mortality categories. Further investigations are warranted to comprehensively understand the impacts of climate change on different types of disease across various regions.

Heat-related mortality at the beginning of the twenty-first century in Rio de Janeiro, Brazil

Temperature record-breaking events, such as the observed more intense, longer-lasting, and more frequent heat waves, pose a new global challenge to health sectors worldwide. These threats are of particular interest in low-income regions with limited investments in public health and a growing urban population, such as Brazil. Here, we apply a comprehensive interdisciplinary climate-health approach, including meteorological data and a daily mortality record from the Brazilian Health System from 2000 to 2015, covering 21 cities over the Metropolitan Region of Rio de Janeiro. The percentage of absolute mortality increase due to summer extreme temperatures is estimated using a negative binomial regression modeling approach and maximum/minimum temperature-derived indexes as covariates. Moreover, this study assesses the vulnerability to thermal stress for different age groups and both genders and thoroughly analyzes four extremely intense heat waves during 2010 and 2012 regarding their impacts on the population. Results showed that the highest absolute mortality values during heat-related events were linked to circulatory illnesses. However, the highest excess of mortality was related to diabetes, particularly for women within the elderly age groups. Moreover, results indicate that accumulated heat stress conditions during consecutive days preferentially preceded by persistent periods of moderate-temperature, lead to higher excess mortality rather than sporadic single hot days. This work may provide directions in human health policies related to extreme climate events in large tropical metropolitan areas from developing countries, contributing to altering the historically based purely reactive response.

Controlling and preventing climate-sensitive noncommunicable diseases in urban sub-Saharan Africa

Research continues to highlight the link between climate change and health outcomes. There is, however, limited evidence in research, policies and in the Sustainable Development Goals (SDGs) about the impact of environmental factors on noncommunicable diseases (NCDs) for people living in urban areas of sub-Saharan Africa (SSA). Important is that 80% of NCDs are taking place in low- and middle-income countries (LMICs) and linked to a third of the deaths in SSA. The question is, what would these statistics look like if environmental risk factors (e.g., pollution, chemicals) for NCDs, linked to climate change, were prevented and controlled. This article presents a framework for understanding climatic pathways' impacts on climate-sensitive NCDs and achieving the SDGs. It further explains how current global mitigation interventions in high income urban settings, with implied health co-benefits for NCD reduction (i.e., promoting use of less polluting vehicles, bicycles, walking, public transport, green spaces), experience major implementation challenges in SSA cities (i.e., too costly, lack of availability, poor road conditions, gender and cultural norms, security problems). Recommendations are made for applying this framework to control climate change impacts on NCDs and achieving the SDGs in SSA cities. These include, support for more research on the climate - NCD nexus, ensuring health professional training includes sustainable health education, and including a focus on climate change and health in primary and secondary school curricula. Further recommendations for addressing climate-sensitive NCDs and urban environmental health towards achieving and sustaining the SDGs, are linked to promoting climate-sensitive and health policies and governance, as well as controlling the influence of advertising. Lastly, improving communication of research findings for policy makers and the public in a manner for informed policy making, and how to comprehend this information to promote the reduction and prevention of NCDs in urban SSA, is key.

Diabetes mortality burden attributable to short-term effect of PM10 in China

Ambient air pollution may be associated with diabetes mellitus. However, evidence from developing countries is limited although the concentrations of air pollution are disproportionably higher in these countries. We collected daily data on diabetes mortality, air pollution, and weather conditions from 16 Chinese provincial cities during 2007-2013. A quasi-Poisson regression combined with a distributed lag model was used to quantify the city-specific mortality risk of PM₁₀ (particulate matter with aerodynamic diameter < 10 μm). Then, a random-effect meta-analysis was conducted to pool effect estimates from 16 cities. We also calculated the attributable fraction and attributable number of diabetes mortality due to PM₁₀. Effects of PM₁₀ were found to be acute and limited to 3 days. Harvesting effect of PM₁₀ was found during lag 4-10 days on diabetes mortality. An increase of 0.17% (95%CI: 0.01-0.34), 0.48% (95%CI: 0.22-0.73), and 0.53% (95%CI: 0.27-0.80) in diabetes mortality was associated with per 10 μg/m³ increase in PM₁₀ at lag 0, 0-4 and 0-10 days, respectively. Totally, 5.76% (95%CI: 2.59-8.00%) and 5878 (95%CI: 2639-8163) deaths due to diabetes could be attributable to PM₁₀. If the concentration of PM₁₀ attained the Chinese government and WHO targets, the reduction in number of PM_2.5-attributed diabetes deaths was 2016 and 5528, respectively. Higher effect estimates of PM₁₀ were observed among females and those aged 0-64 years old at lag 0 day, while greater cumulative effects of PM₁₀ were among males, the elderly aged 75 or over, and the illiterate at lag 0-10 days. However, the between-group differences were not statistically significant. It is one of the few studies on examining the attributable burden of diabetes mortality caused by particulate matter. Our findings indicated that effective efforts on controlling air pollution could reduce a prominent number of air pollution-related diabetes deaths.

Geographical disparities in the impacts of heat on diabetes mortality and the protective role of greenness in Thailand: A nationwide case-crossover analysis

Diabetes is a major public health problem globally, and heat exposure may be a potential risk factor for death among diabetes. This study examines the association between heat and diabetes mortality in different regions of Thailand and investigates whether heat effects are modified by regional greenness. Daily temperature and daily diabetes deaths data were obtained for 60 provinces of Thailand during 2000-2008. A case-crossover analysis was conducted to quantify the odds of heat-related death among diabetes. Meta-regression was then used to examine potential modification effects of regional greenness (as represented by the Normalized Difference Vegetation Index) on heat-related mortality. A strong association between heat and diabetes mortality was found in Thailand, with important regional variations. Nationally, the pooled odds ratio of diabetes mortality was 1.10 (95% confidence interval (CI): 1.06-1.14) for heat (90th percentile of temperature) and 1.20 (95% CI: 1.10-1.30) for extreme heat (99th percentile of temperature) compared with the minimum mortality temperature, across lag 0-1 days. Central and northeast Thailand were the most vulnerable regions. Regional greenness modified the effects of heat, with lower mortality impacts in areas of higher levels of greenness. In conclusion, heat exposure increases mortality risk in diabetes, with large geographical variations in risk suggesting the need for region-specific public health strategies. Increasing greenness levels may help to reduce the burden of heat on diabetes in Thailand against the backdrop of a warming climate.

Effects of Ambient Temperature on Acute Exacerbations of Chronic Obstructive Pulmonary Disease: Results from a Time-Series Analysis of 143318 Hospitalizations

Purpose

To evaluate the associations between acute exacerbations of chronic obstructive pulmonary disease (AECOPD) hospitalizations and daily mean temperature (Tmean) as well as daily apparent temperature (AT), and to explore the practical values of these two indices in policymaking and patient education.

Methods

Daily AECOPD hospitalizations and Meteorological data in Beijing were obtained between 2013 and 2016. Distributed lag non-linear model was adopted to investigate the association between daily ambient temperature and AECOPD hospitalizations. The cumulative effects of cold/hot temperature were abstracted. For the extreme and moderate low-temperature effect estimates, we, respectively, computed the RR of AECOPD hospitalizations at the 1st and 10th percentiles of temperature in comparison with that at the 25th percentile of temperature. For the extreme and moderate high temperature effect estimates, we, respectively, computed the RR of AECOPD hospitalizations at the 99th and 90th percentiles of temperature in comparison with that at the 75th percentile of temperature.

Results

During the study period, 143, 318 AECOPD hospitalizations were collected. A reverse J-shape relationship was found between temperature and AECOPD hospitalizations. When comparing the effect of Tmean, higher RRs were associated with increases in AT on AECOPD hospitalizations but a lower value of Akaike’s Information Criterion for quasi-Poisson (Q-AIC). The RR of extremely low temperature of Tmean and AT were 1.55 (95% CI: 1.21,2.00) and 2.08 (95% CI: 1.44,3.01), respectively. Moderate low temperature also had an adverse impact on AECOPD hospitalizations. No associations were found between high temperature and AECOPD risk. We found the females and those aged <65 years to be more susceptible to temperature change.

Conclusion

Lower temperature is associated with a higher risk for AECOPD hospitalizations. Ambient temperature is probably a better predictor in terms of quantifying risk than mean temperature when studying temperature impact on health.

Daily ambient temperature is associated with biomarkers of kidney injury in older Americans

BACKGROUND

Increases in ambient temperature have recently been associated with increased emergency department visits and hospital admissions for acute renal failure. However, potential biological mechanisms through which short-term ambient temperature affects kidney function are not known.

METHODS

We used multiple regression models to evaluate the association between 1- and 3-day average, ambient temperature levels and two biomarkers of kidney injury (neutrophil gelatinase-associated lipocalin (NGAL) and adiponectin), among 3377 individuals over 57 years of age enrolled in the National Social Life, Health, and Aging Project. Ambient temperature was estimated on a 6-km grid covering the conterminous United States using ambient temperature measurements obtained from the National Climatic Data Center (NCDC). NGAL and adiponectin levels were measured from whole blood collected for each participant. All health effect models were adjusted for a number of demographics, socioeconomic, health behavior, medical history variables, with non-linear exposure-response relationships examined using natural cubic splines.

RESULTS

The relationship between 1- and 3-day average temperature and both NGAL and adiponectin levels was significant and non-linear, with largely null associations below 10 °C, and positive association for temperatures >10 °C. In fully adjusted, linear multiple regression models restricted to >10 °C, NGAL and adiponectin levels increased by 1.89% (95% CI: 0.77, 3.91) and 2.51% (95% CI: 1.34, 3.69), respectively, for a 1 °C increase in daily average temperature. Additionally, every 1 °C increase in temperature over 10 °C was associated with a 1.83% increased odds of having plasma NGAL levels consistent with acute kidney injury (>150 μg/L).

CONCLUSIONS

In a cohort of older men and women in the United States, our study is the first to observe that short-term ambient temperature exposures were significantly associated with biomarkers of kidney injury. These associations suggest that ambient temperature exposures could be an important risk factor for renal pathology.

Association between Heat Exposure and Hospitalization for Diabetes in Brazil during 2000-2015: A Nationwide Case-Crossover Study

BACKGROUND

Exposure to excessive heat, which will continue to increase with climate change, is associated with increased morbidity due to a range of noncommunicable diseases (NCDs). Whether this is true for diabetes is unknown.

OBJECTIVES

We aimed to quantify the relationship between heat exposure and risk of hospitalization due to diabetes in Brazil.

METHODS

Data on hospitalizations and weather conditions were collected from 1,814 cities during the hot seasons from 2000 to 2015. A time-stratified case-crossover design was used to quantify the association between hospitalization for diabetes and heat exposure. Region-specific odds ratios (ORs) were used to calculate the attributable fractions (AFs).

RESULTS

A total of 553,351 hospitalizations associated with diabetes were recorded during 2000-2015. Every 5°C increase in daily mean temperature was associated with 6% [OR=1.06; 95% confidence interval (CI): 1.04, 1.07] increase in hospitalization due to diabetes with lag 0-3 d. The association was greatest (OR=1.18; 95% CI: 1.13, 1.23) in those ≥80y of age, but did not vary by sex, and was generally consistent by region and type of diabetes. Assuming a causal association, we estimated that 7.3% (95% CI: 3.5, 10.9) of all hospitalizations due to diabetes in the hot season could be attributed to heat exposure during the study period.

DISCUSSION

Short-term heat exposure may increase the burden of diabetes-related hospitalization, especially among the very elderly. As global temperatures continue to rise, this burden is likely to increase. https://doi.org/10.1289/EHP5688.

Acute Myocardial Infarction Hospitalizations between Cold and Hot Seasons in an Island across Tropical and Subtropical Climate Zones-A Population-Based Study

We investigated the effects of cold and hot seasons on hospital admissions for acute myocardial infarction (AMI) at the junction of tropical and subtropical climate zones. The hospitalization data of 6897 AMI patients from January 1997 to December 2011 were obtained from the database of the National Health Insurance, including date of admission, gender, age, and comorbidities of hypertension, diabetes mellitus (DM), and dyslipidemia. A comparison of AMI prevalence between seasons and the association of season-related AMI occurrences with individual variables were assessed. AMI hospitalizations in the cold season (cold-season-AMIs) were significantly greater than those in the hot season (OR 1.15; 95% CI 1.10–1.21). In the subtropical region, cold-season-AMIs were strongly and significantly associated with the ≥65 years group (OR1.28; 95% CI 1.11 to 1.48). In the tropical region, cold-season-AMIs, in association with dyslipidemia relative to non-dyslipidemia, were significantly strong in the non-DM group (OR 1.45; 95% CI 1.01 to 2.09) but weak in the DM group (OR 0.74; 95% CI 0.55 to 0.99). The cold season shows increased risks for AMI, markedly among the ≥65 years cohort in the subtropical region, and among the patients diagnosed with either DM or dyslipidemia but not both in the tropical region. Age and comorbidity of metabolic dysfunction influence the season-related incidences of AMI in different climatic regions.

Cold spell and mortality in 31 Chinese capital cities: Definitions, vulnerability and implications

BACKGROUND

In the context of global warming, most researches have been conducted on health influences of heat waves, with limited understanding of health impacts of cold spells, especially for developing countries.

METHODS

We collected daily mortality and meteorological data for 31 capital cities across China during the maximum period of 2007-2013. A quasi-Poisson regression model combined with a distributed lag non-linear model was used to estimate the short-term effects of cold spells on mortality in cold seasons (November to March). 19 definitions of cold spell were clearly compared, including three definitions from the China Meteorological Administration (CMA) and 16 definitions by combining two temperature indicators (daily minimum and mean temperature), two temperature thresholds (3rd and 5th percentile) and four durations of at least 2-5 days. Then, a random effect meta-analysis was applied to pool the effect estimates at national level. Furthermore, a stratified analysis was constructed to identify the vulnerable subpopulations to cold spells.

RESULTS

The definition, in which daily mean temperature falls below 5th percentile for at least two consecutive days, produced the optimum model fit performance. Generally, the mortality risk increased to the maximum after 3-6 days' exposure to cold spell and then leveled off in the next 3 weeks. The pooled relative risks (RR) of non-accidental mortality for cold spells were 1.03 (95% CI: 1.01-1.05), 1.27 (1.19-1.35) and 1.55 (1.40-1.70) at lag 0, lag 0-14 and lag 0-27 days, respectively. The greatest effect estimates of cold spells were found among total respiratory diseases and COPD, with RR of 1.88 (1.65-2.11) and 1.88 (1.58-2.19), respectively. The elderly, less-educated individuals and residents in southern China were more vulnerable to cold spells.

CONCLUSION

There are remarkable mortality effects of cold spells, with effect estimates varying with the definition of cold spell and subpopulations. Using the official definition of cold spells may fail to capture the mortality risk associated with cold spells. These findings may facilitate the development of cold alert warning system and preventive actions to the vulnerable populations.

Health impact of climate change in cities of middle-income countries: the case of China

BACKGROUND

This review examines the human health impact of climate change in China. Through reviewing available research findings under four major climate change phenomena, namely extreme temperature, altered rainfall pattern, rise of sea level and extreme weather events, relevant implications for other middle-income population with similar contexts will be synthesized.

SOURCES OF DATA

Sources of data included bilingual peer-reviewed articles published between 2000 and 2018 in PubMed, Google Scholar and China Academic Journals Full-text Database.

AREAS OF AGREEMENT

The impact of temperature on mortality outcomes was the most extensively studied, with the strongest cause-specific mortality risks between temperature and cardiovascular and respiratory mortality. The geographical focuses of the studies indicated variations in health risks and impacts of different climate change phenomena across the country.

AREAS OF CONTROVERSY

While rainfall-related studies predominantly focus on its impact on infectious and vector-borne diseases, consistent associations were not often found.

GROWING POINTS

Mental health outcomes of climate change had been gaining increasing attention, particularly in the context of extreme weather events. The number of projection studies on the long-term impact had been growing.

AREAS TIMELY FOR DEVELOPING RESEARCH

The lack of studies on the health implications of rising sea levels and on comorbidity and injury outcomes warrants immediate attention. Evidence is needed to understand health impacts on vulnerable populations living in growing urbanized cities and urban enclaves, in particular migrant workers. Location-specific climate-health outcome thresholds (such as temperature-mortality threshold) will be needed to support evidence-based clinical management plans and health impact mitigation strategies to protect vulnerable communities.

Impact of heat on mortality and morbidity in low and middle income countries: A review of the epidemiological evidence and considerations for future research

Heat waves and high air temperature are associated with increased morbidity and mortality. However, the majority of research conducted on this topic is focused on high income areas of the world. Although heat waves have the most severe impacts on vulnerable populations, relatively few studies have studied their impacts in low and middle income countries (LMICs). The aim of this paper is to review the existing evidence in the literature on the impact of heat on human health in LMICs. We identified peer-reviewed epidemiologic studies published in English between January 1980 and August 2018 investigating potential associations between high ambient temperature or heat waves and mortality or morbidity. We selected studies according to the following criteria: quantitative studies that used primary and/or secondary data and report effect estimates where ambient temperature or heat waves are the main exposure of interest in relation to human morbidity or mortality within LMICs. Of the total 146 studies selected, eighty-two were conducted in China, nine in other countries of East Asia and the Pacific, twelve in South Asia, ten in Sub-Saharan Africa, eight in the Middle East and North Africa, and seven in each of Latin America and Europe. The majority of studies (92.9%) found positive associations between heat and human morbidity/mortality. Additionally, while outcome variables and study design differed greatly, most utilized a time-series study design and examined overall heath related morbidity/mortality impacts in an entire population, although it is notable that the selected studies generally found that the elderly, women, and individuals within the low socioeconomic brackets were the most vulnerable to the effects of high temperature. By highlighting the existing evidence on the impact of extreme heat on health in LMICs, we hope to determine data needs and help direct future studies in addressing this knowledge gap. The focus on LMICs is justified by the lack of studies and data studying the health burden of higher temperatures in these regions even though LMICs have a lower capacity to adapt to high temperatures and thus an increased risk.

Heatwaves and diabetes in Brisbane, Australia: a population-based retrospective cohort study

Background

Available data on the effects of heatwaves on hospitalizations for diabetes and the post-discharge status of diabetics are scarce. This study aimed to assess the effects of heatwaves on hospitalizations and post-discharge deaths for diabetes, and to identify the individual- and community-level characteristics [i.e. age, gender, Socio-economic Indexes for Areas (SEIFA), and normalized difference vegetation index (NDVI)] that modified heatwave effects.

Methods

Health data were extracted from a cohort study which included patients in Brisbane, Australia, who were hospitalized due to diabetes from 1st January 2005 to 31st December 2013, and died within 2 months after they were discharged. Data on community-level modifiers, including SEIFA and NDVI (i.e. urban vegetation), were obtained from Australian Bureau of Statistics and Australian Bureau of Meteorology, respectively. Case-crossover design was used to quantify the effects of heatwaves on hospitalizations and post-discharge deaths due to diabetes. Four heatwave definitions incorporating both intensity (i.e. 90th, 95th, 97th and 99th percentiles of mean temperature distribution) and duration (2 days), as well as excess heat factor (EHF), were used. A case-only design was adopted to identify the modifiers of heatwave effects.

Results

There were 10 542 hospitalizations for diabetes, and 513 patients died due to diabetes within 2 months after discharge. During low-intensity heatwave days (i.e. 90th percentile & 2 days), we did not observe a significant increase in hospitalizations for diabetes [9% at lag 0; 95% confidence interval (CI): –3%, 23%; P = 0.146], but we observed a significant increase in post-discharge deaths (46% at lag 2; 95% CI: 3%, 107%; P = 0.036). During middle-intensity heatwave days (i.e. 95th percentile & 2 days), hospitalizations for diabetes increased by 19% at lag 0 (95% CI: 2%, 39%; P = 0.026), and post-discharge deaths increased by 64% at lag 0 (95% CI: 6%, 154%; P = 0.027). During high-intensity heatwave days (i.e. 97th percentile & 2 days), hospitalizations for diabetes increased by 37% at lag 1 (95% CI: 11%, 69%; P = 0.004) and post-discharge deaths increased by 137% at lag 1 (95% CI: 39%, 303%; P = 0.002). When heatwave intensity increased to 99th percentile, we did not observe a significant increase in hospitalizations (–1% at lag 0; 95% CI: –38%, 59%; P = 0.870) or post-discharge deaths (79% at lag 0; 95% CI: –39%, 431%; P = 0.301). When we used EHF to define heatwaves, we observed significant increases of hospitalizations (7%; 95% CI: 1%, 15%; P = 0.039) and post-discharge deaths (68%, 95% CI: 10%, 158%; P = 0.017) during heatwave days, compared with non-heatwave days. Children and male diabetics were particularly vulnerable to heatwave effects, but we did not find any significant modification effect of SEIFA or NDVI on the associations of heatwaves with hospitalizations and post-discharge deaths due to diabetes.

Conclusion

Heatwaves may lead to hospitalizations of diabetics and their premature deaths. Heat-related diabetes burden in children may increase as climate warms and with increasing obesity rates in adolescents.

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.

The effect of ambient temperature on the activity of influenza and influenza like illness in Jiangsu Province, China

OBJECTIVE

We aimed to evaluate and quantify the association between ambient temperature and activity of influenza like illness (ILI) and influenza in Jiangsu Province, China.

METHOD

Daily data of meteorology, influenza-like illness and detected influenza virus from 1 April 2013 to 27 March 2016 were collected. Distributed lag non-linear model (DLNM) was used to quantify the exposure-lag-response of ILI and influenza activity to daily average temperature.

RESULT

Influenza A virus (Flu-A) circulated throughout the year with two peaks at -4 °C and 28 °C respectively, while influenza B (Flu-B) viruses were usually tested positive in winter or early spring and peaked at 5 °C. The lag-response curves revealed that the RR of ILI increased with time and peaked 1 day later at low temperature (3 °C), however, the maximum RR of ILI caused by high temperature (26 °C) appeared immediately on day 0, the similar phenomena of immediate effect to ILI at high temperature were also observed in the lag-response curve for Flu-A or Flu-B.

CONCLUSION

ILI and Flu-A experienced two peaks of circulates at both low and high temperature in Jiangsu. The influenza viruses activity did drive up the rising of ILI%, particularly the activity of Flu-A which circulated throughout the year played a crucial role. Regional homogeneity was the relatively mainstream in aspects of cumulative association between influenza activity and temperature in Jiangsu Province.

Vulnerability to the impact of temperature variability on mortality in 31 major Chinese cities

Few studies have analyzed the health effects of temperature variability (TV) accounting for both interday and intraday variations in ambient temperature. In this study, TV was defined as the standard deviations of the daily minimum and maximum temperature during different exposure days. Distributed lag non-linear Poisson regression model was used to examine the city-specific effect of TV on mortality in 31 Chinese municipalities and provincial capital cities. The national estimate was pooled through a meta-analysis based on the restricted maximum likelihood estimation. To assess effect modification on TV-mortality association by individual characteristics, stratified analyses were further fitted. Potential effect modification by city characteristics was performed through a meta-regression analysis. In total, 259 million permanent residents and 4,481,090 non-accidental deaths were covered in this study. The effect estimates of TV on mortality were generally increased by longer exposure days. A 1 °C increase in TV at 0-7 days' exposure was associated with a 0.60% (95% CI: 0.25-0.94%), 0.65% (0.24-1.05%), 0.82% (0.29-1.36%), 0.86% (0.42-1.31%), 0.98% (0.57-1.39%) and 0.54% (-0.11-1.20%) increase in non-accidental, cardiovascular, IHD, stroke, respiratory and COPD mortalities, respectively. Those with lower levels of educational attainment were significantly susceptible to TV. Cities with dense population, higher mean temperatures, and relative humidity and lower diurnal temperature ranges also had higher mortality risks caused by TV. This study demonstrated that TV had considerable health effects. An early warning system to alert residents about large temperature variations is recommended, which may have a significant impact on the community awareness and public health.

Short-term association between ambient temperature and acute myocardial infarction hospitalizations for diabetes mellitus patients: A time series study

BACKGROUND

Acute myocardial infarction (AMI) is the leading cause of death among people with diabetes mellitus (DM) and has been found to occur more frequently with extreme temperatures. With the increasing prevalence of DM and the rising global mean temperature, the number of heat-related AMI cases among DM patients may increase. This study compares excess risk of AMI during periods of extreme temperatures between patients with DM and without DM.

METHODS

Distributed lag nonlinear models (DLNMs) were used to estimate the short-term association between daily mean temperature and AMI admissions (International Classification of Diseases 9th revision [ICD-9] code: 410.00-410.99), stratified by DM status (ICD-9: 250.00-250.99), to all public hospitals in Hong Kong from 2002 to 2011, adjusting for other meteorological variables and air pollutants. Analyses were also stratified by season, age group, gender, and admission type (first admissions and readmissions). The admissions data and meteorological data were obtained from the Hong Kong Hospital Authority (HA) and the Hong Kong Observatory (HKO).

FINDINGS

A total of 53,769 AMI admissions were included in the study. AMI admissions among DM patients were linearly and negatively associated with temperature in the cold season (cumulative relative risk [cumRR] [95% confidence interval] in lag 0-22 days (12 °C versus 24 °C) = 2.10 [1.62-2.72]), while those among patients without DM only started increasing when temperatures dropped below 22 °C with a weaker association (cumRR = 1.43 [1.21-1.69]). In the hot season, AMI hospitalizations among DM patients started increasing when the temperature dropped below or rose above 28.8 °C (cumRR in lag 0-4 days [30.4 versus 28.8 °C] = 1.14 [1.00-1.31]), while those among patients without DM showed no association with temperature. The differences in sensitivity to temperature between patients with DM and without DM were most apparent in the group <75 years old and among first-admission cases in the cold season. The main limitation of this study was the unavailability of data on individual exposure to ambient temperature.

CONCLUSIONS

DM patients had a higher increased risk of AMI admissions than non-DM patients during extreme temperatures. AMI admissions risks among DM patients rise sharply in both high and low temperatures, with a stronger effect in low temperatures, while AMI risk among non-DM patients only increased mildly in low temperatures. Targeted health protection guidelines should be provided to warn DM patients and physicians about the dangers of extreme temperatures. Further studies to project the impacts of AMI risks on DM patients by climate change are warranted.

Diurnal temperature range in relation to death from stroke in China

BACKGROUND

Stroke is the second leading cause of death in the world. It has multiple risk factors of which some, such as ambient temperature, are less well documented.

OBJECTIVE

We aimed to examine the association between diurnal temperature range (DTR) and stroke mortality, and to test the possible effect modification of this association according to gender, age and educational level.

METHODS

Daily data on weather and stroke mortality from 16 provincial capital cities in China for the years 2007-2013 were obtained, with a total of 788,783 deaths from stroke. A quasi-Poisson generalized linear regression combined with a distributed lag non-linear model was used to examine the city-specific DTR effect on stroke mortality. The pooled effects of DTR on stroke mortality were then obtained using a meta-analysis, which was based on restricted maximum likelihood estimation.

RESULTS

The DTR impacts were generally limited to a period of eight days, while significant effects during lag 0-8 days were only found in the cities of Beijing, Zhengzhou, Nanjing, Hefei, Chongqing and Changsha. The DTR effects were significantly and negatively associated with latitudes at lag 0-10 days (r_s = - 0.640, P = 0.008). An increase of 1 °C in DTR was associated with pooled estimate of 0.66% (95%CI: 0.28-1.05%), 0.12% (- 0.26% to 0.51%) and 0.67% (0.26-1.07%) increases in stroke mortality at lag 0-10 days during the total, hot and cold days, respectively. The impact of DTR was much higher in southern China than in northern China [1.02% (0.62% to 1.43%) versus 0.10% (-0.27% to 0.47%) ]. For the individual characteristics, only females, the elderly aged ≥ 65 years, and those with lower educational attainment were vulnerable to DTR.

CONCLUSIONS

DTR has considerable effects on risk of mortality from stroke in various cities in China, especially among the elderly, females, those with low educational level, and people living in southern China. The results can inform decisions on developing programs to protect vulnerable subpopulations from adverse impacts of DTR.