Associations Between Extreme Temperatures and Cardiovascular Cause-Specific Mortality: Results From 27 Countries.

BACKGROUND: Cardiovascular disease is the leading cause of death worldwide. Existing studies on the association between temperatures and cardiovascular deaths have been limited in geographic zones and have generally considered associations with total cardiovascular deaths rather than cause-specific cardiovascular deaths. METHODS: We used unified data collection protocols within the Multi-Country Multi-City Collaborative Network to assemble a database of daily counts of specific cardiovascular causes of death from 567 cities in 27 countries across 5 continents in overlapping periods ranging from 1979 to 2019. City-specific daily ambient temperatures were obtained from weather stations and climate reanalysis models. To investigate cardiovascular mortality associations with extreme hot and cold temperatures, we fit case-crossover models in each city and then used a mixed-effects meta-analytic framework to pool individual city estimates. Extreme temperature percentiles were compared with the minimum mortality temperature in each location. Excess deaths were calculated for a range of extreme temperature days. RESULTS: The analyses included deaths from any cardiovascular cause (32 154 935), ischemic heart disease (11 745 880), stroke (9 351 312), heart failure (3 673 723), and arrhythmia (670 859). At extreme temperature percentiles, heat (99th percentile) and cold (1st percentile) were associated with higher risk of dying from any cardiovascular cause, ischemic heart disease, stroke, and heart failure as compared to the minimum mortality temperature, which is the temperature associated with least mortality. Across a range of extreme temperatures, hot days (above 97.5th percentile) and cold days (below 2.5th percentile) accounted for 2.2 (95% empirical CI [eCI], 2.1-2.3) and 9.1 (95% eCI, 8.9-9.2) excess deaths for every 1000 cardiovascular deaths, respectively. Heart failure was associated with the highest excess deaths proportion from extreme hot and cold days with 2.6 (95% eCI, 2.4-2.8) and 12.8 (95% eCI, 12.2-13.1) for every 1000 heart failure deaths, respectively. CONCLUSIONS: Across a large, multinational sample, exposure to extreme hot and cold temperatures was associated with a greater risk of mortality from multiple common cardiovascular conditions. The intersections between extreme temperatures and cardiovascular health need to be thoroughly characterized in the present day-and especially under a changing climate.

Effects of Coexposure to Air Pollution from Vegetation Fires and Extreme Heat on Mortality in Upper Northern Thailand.

Background: understanding the effects of coexposure to compound extreme events, such as air pollution and extreme heat, is important for reducing current and future health burdens. This study investigated the independent and synergistic effects of exposure to air pollution from vegetation fires and extreme heat on all-cause mortality in Upper Northern Thailand. Methods: we used a time-stratified case-crossover study design with a conditional quasi-Poisson model to examine the association between mortality and coexposure to air pollution due to vegetation fire events (fire-PM2.5) and extreme heat. Extreme heat days were defined using the 90th and 99th percentile thresholds for daily maximum temperature. Results: we observed a significant positive excess risk of mortality due to independent exposure to fire-PM2.5 and extreme heat, but not an interactive effect. All-cause mortality risk increased by 0.9% (95% confidence interval (CI): 0.1, 1.8) for each 10 µg/m3 increase in fire-PM2.5 on the same day and by 12.8% (95% CI: 10.5, 15.1) on extreme heat days (90th percentile) relative to nonextreme heat days. Conclusion: this study showed that exposure to PM2.5 from vegetation fires and extreme heat independently increased all-cause mortality risk in UNT. However, there was no evidence of a synergistic effect of these events.

Interplay of Climate Change and Air Pollution- Projection of the under-5 mortality attributable to ambient particulate matter (PM2.5) in South Asia.

Ambient fine particulate matter (PM2.5) pollution is a leading health risk factor for children under- 5 years, especially in developing countries. South Asia is a PM2.5 hotspot, where climate change, a potential factor affecting PM2.5 pollution, adds a major challenge. However, limited evidence is available on under-5 mortality attributable to PM2.5 under different climate change scenarios. This study aimed to project under-5 mortality attributable to long-term exposure to ambient PM2.5 under seven air pollution and climate change mitigation scenarios in South Asia. We used a concentration-risk function obtained from a previous review to project under-5 mortality attributable to ambient PM2.5. With a theoretical minimum risk exposure level of 2.4 µg/m3, this risk function was linked to gridded annual PM2.5 concentrations from atmospheric modeling to project under-5 mortality from 2010 to 2049 under different climate change mitigation scenarios. The scenarios were developed from the Aim/Endues global model based on end-of-pipe (removing the emission of air pollutants at the source, EoP) and 2 °C target measures. Our results showed that, in 2010-2014, about 306.8 thousand under-5 deaths attributable to PM2.5 occurred in South Asia under the Reference (business as usual) scenario. The number of deaths was projected to increase in 2045-2049 by 36.6% under the same scenario and 7.7% under the scenario where EoP measures would be partially implemented by developing countries (EoPmid), and was projected to decrease under other scenarios, with the most significant decrease (81.2%) under the scenario where EoP measures would be fully enhanced by all countries along with the measures to achieve 2 °C target (EoPmaxCCSBLD) across South Asia. Country-specific projections of under-5 mortality varied by country. The current emission control strategy would not be sufficient to reduce the number of deaths in South Asia. Robust climate change mitigation and air pollution control policy implementation is required.

The effect modification of PM2.5 and ozone on the short-term associations between temperature and mortality across the urban areas of Japan.

BACKGROUND: The acute effects of temperature and air pollution on mortality are well-known environmental factors that have been receiving more recognition lately. However, the health effects resulting from the interaction of air pollution and temperature remain uncertain, particularly in cities with low levels of pollution. This study aims to examine the modification effects of particulate matter with a diameter of 2.5 µm or less (PM2.5) and ozone (O3) on the association between temperature and mortality. METHODS: We collected the daily number of all-cause, cardiovascular, and respiratory mortality from 20 major cities in Japan from 2012-2018. We obtained meteorological data from the Japan Meteorological Agency and air pollution data from the National Institute for Environmental Studies. We conducted analyses using a quasi-Poisson regression model with a distributed lag non-linear model for temperature in each city and subsequently performed a random-effects meta-analysis to derive average estimates. RESULTS: We found that high levels of O3 might positively modify the mortality risk of heat exposure, especially for cardiovascular diseases. Subgroups such as the elderly and females were susceptible. We did not observe consistent evidence of effect modification by PM2.5, including effect modification on cold by both pollutants. CONCLUSION: PM2.5 and O3 may positively modify the short-term association between heat and mortality in the urban areas of Japan. These results highlight the need for public health policies and interventions to address the collective impacts of both temperature and air pollution.

Association between greenness and cardiovascular risk factors: Results from a large cohort study in Thailand.

BACKGROUND: The risk of cardiovascular diseases may be reduced by residing in green environments. However, there are relatively few longitudinal cohort studies, especially in Southeast Asia, that focused on the health benefits of long-term greenness exposure in young adults. The present study examined the association between long-term exposure to residential greenness and self-reported morbidities in participants of the Thai Cohort Study (TCS) in Thailand from 2005 to 2013. METHODS: The self-reported outcomes, including high blood pressure, high blood cholesterol, and diabetes, were reported in 2005, 2009, and 2013, where the study participants provided the exact year of disease occurrence. Greenness was assessed by the satellite-based Normalized Difference Vegetation Index (NDVI) and Enhanced Vegetation Index (EVI), with a spatial resolution of 250 m. Long-term exposure to NDVI and EVI of each participant's sub-district was averaged over the period of person-time. We used Cox proportional hazards models to examine the association between greenness and health outcomes. Associations with self-reported morbidity were measured using hazard ratios (HRs) per interquartile range (IQR) increase in NDVI and EVI. RESULTS: After adjusting for potential confounders, we observed that an IQR increase in NDVI was associated with lower incidence of high blood pressure (HR = 0.92, 95% CI: 0.89, 0.97) and high blood cholesterol (HR = 0.89, 95%CI: 0.87, 0.92), but not significantly associated with diabetes (HR = 0.93, 95%CI: 0.85, 1.01). EVI was also inversely associated with self-reported high blood pressure (HR = 0.92, 95%CI: 0.88, 0.96), high blood cholesterol (HR = 0.89, 95%CI: 0.87, 0.91), and diabetes (HR = 0.92, 95%CI: 0.85, 0.99). CONCLUSIONS: Long-term exposure to residential greenness was inversely associated with self-reported high blood pressure, high blood cholesterol, and diabetes in participants of TCS. Our study provides evidence that greenness exposure may reduce cardiovascular disease risk factors in adult population.

Daily temperature effects on under-five mortality in a tropical climate country and the role of local characteristics.

BACKGROUND: Climate change and its subsequent effects on temperature have raised global public health concerns. Although numerous epidemiological studies have shown the adverse health effects of temperature, the association remains unclear for children aged below five years old and those in tropical climate regions. METHODS: We conducted a two-stage time-stratified case-crossover study to examine the association between temperature and under-five mortality, spanning the period from 2014 to 2018 across all six regions in Malaysia. In the first stage, we estimated region-specific temperature-mortality associations using a conditional Poisson regression and distributed lag nonlinear models. We used a multivariate meta-regression model to pool the region-specific estimates and examine the potential role of local characteristics in the association, which includes geographical information, demographics, socioeconomic status, long-term temperature metrics, and healthcare access by region. RESULTS: Temperature in Malaysia ranged from 22 °C to 31 °C, with a mean of 27.6 °C. No clear seasonality was observed in under-five mortality. We found no strong evidence of the association between temperature and under-five mortality, with an "M-" shaped exposure-response curve. The minimum mortality temperature (MMT) was identified at 27.1 °C. Among several local characteristics, only education level and hospital bed rates reduced the residual heterogeneity in the association. However, effect modification by these variables were not significant. CONCLUSION: This study suggests a null association between temperature and under-five mortality in Malaysia, which has a tropical climate. The "M-" shaped pattern suggests that under-fives may be vulnerable to temperature changes, even with a small temperature change in reference to the MMT. However, the weak risks with a large uncertainty at extreme temperatures remained inconclusive. Potential roles of education level and hospital bed rate were statistically inconclusive.

Long-term trends in mortality risk associated with short-term exposure to air pollution in 10 Japanese cities between 1977 and 2015.

BACKGROUND AND AIM: Short-term associations between air pollution and mortality have been well reported in Japan, but the historical changes in mortality risk remain unknown. We examined temporal changes in the mortality risks associated with short-term exposure to four criteria air pollutants in selected Japanese cities. METHODS: We collected daily mortality data for non-accidental causes (n = 5,748,206), cardiovascular (n = 1,938,743) and respiratory diseases (n = 777,266), and air pollutants (sulfur dioxide [SO2], nitrogen dioxide [NO2], suspended particulate matter [SPM], and oxidants [Ox]) in 10 cities from 1977 to 2015. We performed two-stage analysis with 5-year stratification to estimate the relative risk (RR) of mortality per 10-unit increase in the 2-day moving average of air pollutant concentrations. In the first stage, city-specific associations were assessed using a quasi-Poisson generalized linear regression model. In the second stage, city-specific estimates were pooled using a random-effects meta-analysis. Linear trend and ratio of relative risks (RRR) were computed to examine temporal changes. RESULTS: When stratifying the analysis by every 5 years, average concentrations in each sub-period decreased for SO2, NO2, and SPM (14.2-2.3 ppb, 29.4-17.5 ppb, 52.1-20.6 µg/m3, respectively) but increased for Ox (29.1-39.1 ppb) over the study period. We found evidence of a negative linear trend in the risk of cardiovascular mortality associated with SPM across sub-periods. However, the risks of non-accidental and respiratory mortality per 10-unit increase in SPM concentration were significantly higher in the most recent period than in the earliest period. Other gaseous pollutants did not show such temporal risk change. The risks posed by these pollutants were slightly to moderately heterogeneous in the different cities. CONCLUSIONS: The mortality risks associated with short-term exposure to SPM changed, with different trends by cause of death, in 10 cities over 39 years whereas the risks for other gaseous pollutants were relatively stable.

Associations between residential greenness and air pollution and the incident metabolic syndrome in a Thai worker cohort.

Increasing air pollution and decreasing exposure to greenness may contribute to the metabolic syndrome (MetS). We examined associations between long-term exposure to residential greenness and air pollution and MetS incidence in the Bangkok Metropolitan Region, Thailand. Data from 1369 employees (aged 52-71 years) from the Electricity Generating Authority of Thailand cohort from 2002 to 2017 were analyzed. The greenness level within 500 m of each participant's residence was measured using the satellite-derived Normalized Difference Vegetation Index (NDVI) and Enhanced Vegetation Index (EVI). The kriging approach was used to generate the average concentration of each air pollutant (PM10, CO, SO2, NO2, and O3) at the sub-district level. The average long-term exposure to air pollution and greenness for each participant was calculated over the same period of person-time. Cox proportional hazards models were used to analyze the greenness-air pollution-MetS associations. The adjusted hazard ratio of MetS was 1.42 (95% confidence interval (CI): 1.32, 1.53), 1.22 (95% CI: 1.15, 1.30), and 2.0 (95% CI: 1.82, 2.20), per interquartile range increase in PM10 (9.5 µg/m3), SO2 (0.9 ppb), and CO (0.3 ppm), respectively. We found no clear association between NDVI or EVI and the incidence of MetS. On the contrary, the incident MetS was positively associated with NDVI and EVI for participants exposed to PM10 at concentrations more than 50 µg/m3. In summary, the incidence of MetS was positively associated with long-term exposure to air pollution. In areas with high levels of air pollution, green spaces may not benefit health outcomes.

Long-term air pollution exposure and self-reported morbidity: A longitudinal analysis from the Thai cohort study (TCS).

BACKGROUND: Several studies have shown the health effects of air pollutants, especially in China, North American and Western European countries. But longitudinal cohort studies focused on health effects of long-term air pollution exposure are still limited in Southeast Asian countries where sources of air pollution, weather conditions, and demographic characteristics are different. The present study examined the association between long-term exposure to air pollution and self-reported morbidities in participants of the Thai cohort study (TCS) in Bangkok metropolitan region (BMR), Thailand. METHODS: This longitudinal cohort study was conducted for 9 years from 2005 to 2013. Self-reported morbidities in this study included high blood pressure, high blood cholesterol, and diabetes. Air pollution data were obtained from the Thai government Pollution Control Department (PCD). Particles with diameters ≤10 µm (PM10), sulfur dioxide (SO2), nitrogen dioxide (NO2), ozone (O3), and carbon monoxide (CO) exposures were estimated with ordinary kriging method using 22 background and 7 traffic monitoring stations in BMR during 2005-2013. Long-term exposure periods to air pollution for each subject was averaged as the same period of person-time. Cox proportional hazards models were used to examine the association between long-term air pollution exposure with self-reported high blood pressure, high blood cholesterol, diabetes. Results of self-reported morbidity were presented as hazard ratios (HRs) per interquartile range (IQR) increase in PM10, O3, NO2, SO2, and CO. RESULTS: After controlling for potential confounders, we found that an IQR increase in PM10 was significantly associated with self-reported high blood pressure (HR = 1.13, 95% CI: 1.04, 1.23) and high blood cholesterol (HR = 1.07, 95%CI: 1.02, 1.12), but not with diabetes (HR = 1.05, 95%CI: 0.91, 1.21). SO2 was also positively associated with self-reported high blood pressure (HR = 1.22, 95%CI: 1.08, 1.38), high blood cholesterol (HR = 1.20, 95%CI: 1.11, 1.30), and diabetes (HR = 1.21, 95%CI: 0.92, 1.60). Moreover, we observed a positive association between CO and self-reported high blood pressure (HR = 1.07, 95%CI: 1.00, 1.15), but not for other diseases. However, self-reported morbidities were not associated with O3 and NO2. CONCLUSIONS: Long-term exposure to air pollution, especially for PM10 and SO2 was associated with self-reported high blood pressure, high blood cholesterol, and diabetes in subjects of TCS. Our study supports that exposure to air pollution increases cardiovascular disease risk factors for younger population.

COVID-19 pandemic modifies temperature and heat-related illness ambulance transport association in Japan: a nationwide observational study.

BACKGROUND: During the COVID-19 pandemic, several illnesses were reduced. In Japan, heat-related illnesses were reduced by 22% compared to pre-pandemic period. However, it is uncertain as to what has led to this reduction. Here, we model the association of maximum temperature and heat-related illnesses in the 47 Japanese prefectures. We specifically examined how the exposure and lag associations varied before and during the pandemic. METHODS: We obtained the summer-specific, daily heat-related illness ambulance transport (HIAT), exposure variable (maximum temperature) and covariate data from relevant data sources. We utilized a stratified (pre-pandemic and pandemic), two-stage approach. In each stratified group, we estimated the 1) prefecture-level association using a quasi-Poisson regression coupled with a distributed lag non-linear model, which was 2) pooled using a random-effects meta-analysis. The difference between pooled pre-pandemic and pandemic associations was examined across the exposure and the lag dimensions. RESULTS: A total of 321,655 HIAT cases was recorded in Japan from 2016 to 2020. We found an overall reduction of heat-related risks for HIAT during the pandemic, with a wide range of reduction (10.85 to 57.47%) in the HIAT risk, across exposure levels ranging from 21.69 °C to 36.31 °C. On the contrary, we found an increment in the delayed heat-related risks during the pandemic at Lag 2 (16.33%; 95% CI: 1.00, 33.98%). CONCLUSION: This study provides evidence of the impact of COVID-19, particularly on the possible roles of physical interventions and behavioral changes, in modifying the temperature-health association. These findings would have implications on subsequent policies or heat-related warning strategies in light of ongoing or future pandemics.

Regulatory Role of Sugars on the Settlement Inducing Activity of a Conspecific Cue in Pacific Oyster Crassostrea gigas.

This study evaluated the larval settlement inducing effect of sugars and a conspecific cue from adult shell extract of Crassostrea gigas. To understand how the presence of different chemical cues regulate settlement behavior, oyster larvae were exposed to 12 types of sugars, shell extract-coated and non-coated surfaces, and under varied sugar exposure times. Lectin-glycan interaction effects on settlement and its localization on oyster larval tissues were investigated. The results showed that the conspecific cue elicited a positive concentration dependent settlement inducing trend. Sugars in the absence of a conspecific cue, C. gigas adult shell extract, did not promote settlement. Whereas, in the presence of the cue, showed varied effects, most of which were found inhibitory at different concentrations. Sugar treated larvae exposed for 2 h showed significant settlement inhibition in the presence of a conspecific cue. Neu5Ac, as well as GlcNAc sugars, showed a similar interaction trend with wheat germ agglutinin (WGA) lectin. WGA-FITC conjugate showed positive binding on the foot, velum, and mantle when exposed to GlcNAc sugars. This study suggests that a WGA lectin-like receptor and its endogenous ligand are both found in the larval chemoreceptors and the shell Ethylenediaminetetraacetic acid (EDTA) extract that may complementarily work together to allow the oyster larva greater selectivity during site selection.

Seasonality of mortality under a changing climate: a time-series analysis of mortality in Japan between 1972 and 2015.

BACKGROUND: Ambient temperature may contribute to seasonality of mortality; in particular, a warming climate is likely to influence the seasonality of mortality. However, few studies have investigated seasonality of mortality under a warming climate. METHODS: Daily mean temperature, daily counts for all-cause, circulatory, and respiratory mortality, and annual data on prefecture-specific characteristics were collected for 47 prefectures in Japan between 1972 and 2015. A quasi-Poisson regression model was used to assess the seasonal variation of mortality with a focus on its amplitude, which was quantified as the ratio of mortality estimates between the peak and trough days (peak-to-trough ratio (PTR)). We quantified the contribution of temperature to seasonality by comparing PTR before and after temperature adjustment. Associations between annual mean temperature and annual estimates of the temperature-unadjusted PTR were examined using multilevel multivariate meta-regression models controlling for prefecture-specific characteristics. RESULTS: The temperature-unadjusted PTRs for all-cause, circulatory, and respiratory mortality were 1.28 (95% confidence interval (CI): 1.27-1.30), 1.53 (95% CI: 1.50-1.55), and 1.46 (95% CI: 1.44-1.48), respectively; adjusting for temperature reduced these PTRs to 1.08 (95% CI: 1.08-1.10), 1.10 (95% CI: 1.08-1.11), and 1.35 (95% CI: 1.32-1.39), respectively. During the period of rising temperature (1.3 °C on average), decreases in the temperature-unadjusted PTRs were observed for all mortality causes except circulatory mortality. For each 1 °C increase in annual mean temperature, the temperature-unadjusted PTR for all-cause, circulatory, and respiratory mortality decreased by 0.98% (95% CI: 0.54-1.42), 1.39% (95% CI: 0.82-1.97), and 0.13% (95% CI: - 1.24 to 1.48), respectively. CONCLUSION: Seasonality of mortality is driven partly by temperature, and its amplitude may be decreasing under a warming climate.

Hourly association between ambient PM2.5 and emergency ambulance dispatches in 11 cities in Japan.

Numerous epidemiological studies have demonstrated that short-term exposure to ambient PM2.5 increases mortality and morbidity. Investigating the association using hourly ambient PM2.5 exposure may provide important insights, as current evidence is limited mostly to daily lag term. This study aimed to investigate the hourly association between ambient PM2.5 concentrations and all-cause emergency ambulance dispatches (EAD) in 11 cities in Japan. We used a time-stratified case-crossover design and examined the hourly lags of ambient PM2.5 up to 24 h (unconditional distributed lags and moving average lags) using a conditional Poisson regression model. A significant increase in all-cause EAD was observed at lag 0 h [relative risk (RR): 1.0037 (95% CI: 1.0000, 1.0074)] and all moving average lags. The highest RR was observed within the first 6 h (at lag 0-5 h) [RR: 1.0091 (95% CI: 1.0068, 1.0114)], with a slight ascending pattern. This was followed by a descending pattern at lags 0-11, 0-17, and 0-23 h, but significant positive RR was observed even at lag 0-23 h, when the lowest RR was observed [RR: 1.0072 (95% CI: 1.0044, 1.0100)]. Though similar pattern was observed among the elderly, a different pattern was observed among the children (gradually ascending pattern). We conclude that all-cause EAD could be triggered by ambient PM2.5 exposure with very short lags.

Assessing frontline HIV service provider efficiency using data envelopment analysis: a case study of Philippine social hygiene clinics (SHCs).

BACKGROUND: Globally, local and frontline HIV service delivery units have been deployed to halt the HIV epidemic. However, with the limited resources, there is a need to understand how these units can deliver their optimum outputs/outcomes efficiently given the inputs. This study aims to determine the efficiency of the social hygiene clinics (SHC) in the Philippines as well as to determine the association of the meta-predictor to the efficiencies. METHODS: In determining efficiency, we used the variables from two data sources namely the 2012 Philippine HIV Costing study and 2011 Integrated HIV Behavioral and Serologic Surveillance, as inputs and outputs, respectively. Various data management protocols and initial assumptions in data matching, imputation and variable selection, were used to create the final dataset with 9 SHCs. We used data envelopment analysis (DEA) to analyse the efficiency, while variations in efficiencies were analysed using Tobit regression with area-specific meta-predictors. RESULTS: There were potentially inefficient use of limited resources among sampled SHC in both aggregate and key populations. Tobit regression results indicated that income was positively associated with efficiency, while HIV prevalence was negatively associated with the efficiency variations among the SHCs. CONCLUSIONS: We were able to determine the inefficiently performing SHCs in the Philippines. Though currently inefficient, these SHCs may adjust their inputs and outputs to become efficient in the future. While there were indications of income and HIV prevalence to be associated with the efficiency variations, the results of this case study may only be limited in generalisability, thus further studies are warranted.

Quantifying excess deaths related to heatwaves under climate change scenarios: A multicountry time series modelling study.

BACKGROUND: Heatwaves are a critical public health problem. There will be an increase in the frequency and severity of heatwaves under changing climate. However, evidence about the impacts of climate change on heatwave-related mortality at a global scale is limited. METHODS AND FINDINGS: We collected historical daily time series of mean temperature and mortality for all causes or nonexternal causes, in periods ranging from January 1, 1984, to December 31, 2015, in 412 communities within 20 countries/regions. We estimated heatwave-mortality associations through a two-stage time series design. Current and future daily mean temperature series were projected under four scenarios of greenhouse gas emissions from 1971-2099, with five general circulation models. We projected excess mortality in relation to heatwaves in the future under each scenario of greenhouse gas emissions, with two assumptions for adaptation (no adaptation and hypothetical adaptation) and three scenarios of population change (high variant, median variant, and low variant). Results show that, if there is no adaptation, heatwave-related excess mortality is expected to increase the most in tropical and subtropical countries/regions (close to the equator), while European countries and the United States will have smaller percent increases in heatwave-related excess mortality. The higher the population variant and the greenhouse gas emissions, the higher the increase of heatwave-related excess mortality in the future. The changes in 2031-2080 compared with 1971-2020 range from approximately 2,000% in Colombia to 150% in Moldova under the highest emission scenario and high-variant population scenario, without any adaptation. If we considered hypothetical adaptation to future climate, under high-variant population scenario and all scenarios of greenhouse gas emissions, the heatwave-related excess mortality is expected to still increase across all the countries/regions except Moldova and Japan. However, the increase would be much smaller than the no adaptation scenario. The simple assumptions with respect to adaptation as follows: no adaptation and hypothetical adaptation results in some uncertainties of projections. CONCLUSIONS: This study provides a comprehensive characterisation of future heatwave-related excess mortality across various regions and under alternative scenarios of greenhouse gas emissions, different assumptions of adaptation, and different scenarios of population change. The projections can help decision makers in planning adaptation and mitigation strategies for climate change.

Green Space and Deaths Attributable to the Urban Heat Island Effect in Ho Chi Minh City.

OBJECTIVES: To quantify heat-related deaths in Ho Chi Minh City, Vietnam, caused by the urban heat island (UHI) and explore factors that may alleviate the impact of UHIs. METHODS: We estimated district-specific meteorological conditions from 2010 to 2013 using the dynamic downscaling model and calculated the attributable fraction and number of mortalities resulting from the total, extreme, and mild heat in each district. The difference in attributable fraction of total heat between the central and outer districts was classified as the attributable fraction resulting from the UHI. The association among attributable fraction, attributable number with a green space, population density, and budget revenue of each district was then explored. RESULTS: The temperature-mortality relationship between the central and outer areas was almost identical. The attributable fraction resulting from the UHI was 0.42%, which was contributed by the difference in temperature distribution between the 2 areas. Every 1-square-kilometer increase in green space per 1000 people can prevent 7.4 deaths caused by heat. CONCLUSIONS: Green space can alleviate the impacts of UHIs, although future studies conducting a heath economic evaluation of tree planting are warranted.

Meteorological factors affecting dengue incidence in Davao, Philippines.

BACKGROUND: Dengue fever is a major public health concern in the Philippines, and has been a significant cause of hospitalizations and deaths among young children. Previous literature links climate change to dengue, and with increasingly unpredictable changing climate patterns, there is a need to understand how these meteorological variables affect dengue incidence in a highly endemic area. METHODS: Weekly dengue incidences (2011-2015) in Davao Region, Philippines were obtained from the Department of Health. Same period of weekly local meteorological variables were obtained from the National Climatic Data Center (NCDC) and the National Oceanic and Atmospheric Administration (NOAA). Wavelet coherence analysis was used to determine the presence of non-stationary relationships, while a quasi-Poisson regression combined with distributed lag nonlinear model (DLNM) was used to analyze the association between meteorological variables and dengue incidences. RESULTS: Significant periodicity was detected in the 7 to 14-week band between the year 2011-2012 and a 26-week periodicity from the year 2013-2014. Overall cumulative risks were particularly high for rainfall at 32 mm (RR: 1.67, 95% CI: 1.07-2.62), while risks were observed to increase with increasing dew point. On the other hand, lower average temperature of 26 °C has resulted to an increased RR of dengue (RR: 1.96, 95% CI: 0.47-8.15) while higher temperature from 27 °C to 31 °C has lower RR. CONCLUSIONS: The observed possible threshold levels of these meteorological variables can be integrated into an early warning system to enhance dengue prediction for better vector control and management in the future.

Incidence and seasonality of Kawasaki disease in children in the Philippines, and its association with ambient air temperature.

Background: Despite an unknown cause, Kawasaki disease (KD) is currently the primary leading cause of acquired heart disease in developed countries in children and has been increasing in recent years. Research efforts have explored environmental factors related to KD, but they are still unclear especially in the tropics. We aimed to describe the incidence of KD in children, assess its seasonality, and determine its association with ambient air temperature in the National Capital Region (NCR), Philippines from January 2009 to December 2019. Methods: Monthly number of KD cases from the Philippine Pediatric Society (PPS) disease registry was collected to determine the incidence of KD. A generalized linear model (GLM) with quasi-Poisson regression was utilized to assess the seasonality of KD and determine its association with ambient air temperature after adjusting for the relevant confounders. Results: The majority of KD cases (68.52%) occurred in children less than five years old, with incidence rates ranging from 14.98 to 23.20 cases per 100,000 population, and a male-to-female ratio of 1.43:1. Seasonal variation followed a unimodal shape with a rate ratio of 1.13 from the average, peaking in March and reaching the lowest in September. After adjusting for seasonality and long-term trend, every one-degree Celsius increase in the monthly mean temperature significantly increased the risk of developing KD by 8.28% (95% CI: 2.12%, 14.80%). Season-specific analysis revealed a positive association during the dry season (RR: 1.06, 95% CI: 1.01, 1.11), whereas no evidence of association was found during the wet season (RR: 1.10, 95% CI: 0.95, 1.27). Conclusion: We have presented the incidence of KD in the Philippines which is relatively varied from its neighboring countries. The unimodal seasonality of KD and its linear association with temperature, independent of season and secular trend, especially during dry season, may provide insights into its etiology and may support enhanced KD detection efforts in the country.

Short-term associations of diarrhoeal diseases in children with temperature and precipitation in seven low- and middle-income countries from Sub-Saharan Africa and South Asia in the Global Enteric Multicenter Study.

BACKGROUND: Diarrhoeal diseases cause a heavy burden in developing countries. Although studies have described the seasonality of diarrhoeal diseases, the association of weather variables with diarrhoeal diseases has not been well characterized in resource-limited settings where the burden remains high. We examined short-term associations between ambient temperature, precipitation and hospital visits due to diarrhoea among children in seven low- and middle-income countries. METHODOLOGY: Hospital visits due to diarrhoeal diseases under 5 years old were collected from seven sites in The Gambia, Mali, Mozambique, Kenya, India, Bangladesh, and Pakistan via the Global Enteric Multicenter Study from December 2007 to March 2011. Daily weather data during the same period were downloaded from the ERA5-Land. We fitted time-series regression models to examine the relationships of daily diarrhoea cases with daily ambient temperature and precipitation. Then, we used meta-analytic tools to examine the heterogeneity between the site-specific estimates. PRINCIPAL FINDINGS: The cumulative relative risk (RR) of diarrhoea for temperature exposure (95th percentile vs. 1st percentile) ranged from 0.24 to 8.07, with Mozambique and Bangladesh showing positive associations, while Mali and Pakistan showed negative associations. The RR for precipitation (95th percentile vs. 1st percentile) ranged from 0.77 to 1.55, with Mali and India showing positive associations, while the only negative association was observed in Pakistan. Meta-analysis showed substantial heterogeneity in the association between temperature-diarrhoea and precipitation-diarrhoea across sites, with I2 of 84.2% and 67.5%, respectively. CONCLUSIONS: Child diarrhoea and weather factors have diverse and complex associations across South Asia and Sub-Saharan Africa. Diarrhoeal surveillance system settings should be conceptualized based on the observed pattern of climate change in these locations.

Short-term associations of PM10 attributed to biomass burning with respiratory and cardiovascular hospital admissions in Peninsular Malaysia.

BACKGROUND: Biomass burning (BB) is a major source of air pollution and particulate matter (PM) in Southeast Asia. However, the health effects of PM smaller than 10 µm (PM10) originating from BB may differ from those of other sources. This study aimed to estimate the short-term association of PM10 from BB with respiratory and cardiovascular hospital admissions in Peninsular Malaysia, a region often exposed to BB events. METHODS: We obtained and analyzed daily data on hospital admissions, PM10 levels and BB days from five districts from 2005 to 2015. We identified BB days by evaluating the BB hotspots and backward wind trajectories. We estimated PM10 attributable to BB from the excess of the moving average of PM10 during days without BB hotspots. We fitted time-series quasi-Poisson regression models for each district and pooled them using meta-analyses. We adjusted for potential confounders and examined the lagged effects up to 3 days, and potential effect modification by age and sex. RESULTS: We analyzed 210 960 respiratory and 178 952 cardiovascular admissions. Almost 50% of days were identified as BB days, with a mean PM10 level of 53.1 µg/m3 during BB days and 40.1 µg/m3 during normal days. A 10 µg/m3 increment in PM10 from BB was associated with a 0.44% (95% CI: 0.06, 0.82%) increase in respiratory admissions at lag 0-1, with a stronger association in adults aged 15-64 years and females. We did not see any significant associations for cardiovascular admissions. CONCLUSIONS: Our findings suggest that short-term exposure to PM10 from BB increased the risk of respiratory hospitalizations in Peninsular Malaysia.