The effect of heat waves on mortality and effect modifiers in four communities of Guangdong Province, China

Exposure to Concurrent Heatwaves and Ozone Pollution and Associations with Mortality Risk: A Nationwide Study in China

BACKGROUND

Concurrent extreme events are projected to occur more frequently under a changing climate. Understanding the mortality risk and burden of the concurrent heatwaves and ozone (O 3 ) pollution may support the formulation of adaptation strategies and early warning systems for concurrent events in the context of climate change.

OBJECTIVES

We aimed to estimate the mortality risk and excess deaths of concurrent heatwaves and O 3 pollution across 250 counties in China.

METHODS

We collected daily mortality, meteorological, and air pollution data for the summer (1 June to 30 September) during 2013-2018. We defined heatwaves and high O 3 pollution days, then we divided the identified days into three categories: a) days with only heatwaves (heatwave-only event), b) days with only high O 3 pollution (high O 3 pollution-only event), and c) days with concurrent heatwaves and high O 3 pollution (concurrent event). A generalized linear model with a quasi-Poisson regression was used to estimate the risk of mortality associated with extreme events for each county. Then we conducted a random-effects meta-analysis to pool the county-specific estimates to derive the overall effect estimates. We used mixed-effects meta-regression to identify the drivers of the heterogeneity. Finally, we estimated the excess death attributable to extreme events (heatwave-only, high O 3 pollution-only, and concurrent events) from 2013 to 2020.

RESULTS

A higher all-cause mortality risk was associated with exposure to the concurrent heatwaves and high O 3 pollution than exposure to a heatwave-only or a high O 3 pollution-only event. The effects of a concurrent event on circulatory and respiratory mortality were higher than all-cause and nonaccidental mortality. Sex and age significantly impacted the association of concurrent events and heatwave-only events with all-cause mortality. We estimated that annual average excess deaths attributed to the concurrent events were 6,249 in China from 2017 to 2020, 5.7 times higher than the annual average excess deaths attributed to the concurrent events from 2013 to 2016. The annual average proportion of excess deaths attributed to the concurrent events in the total excess deaths caused by three types of events (heatwave-only events, high O 3 pollution-only events, and concurrent events) increased significantly in 2017-2020 (31.50%; 95% CI: 26.73%, 35.53%) compared with 2013-2016 (9.65%; 95% CI: 5.67%, 10.81%). Relative excess risk due to interaction revealed positive additive interaction considering the concurrent effect of heatwaves and high O 3 pollution.

DISCUSSION

Our findings may provide scientific basis for establishing a concurrent event early warning system to reduce the adverse health impact of the concurrent heatwaves and high O 3 pollution. https://doi.org/10.1289/EHP13790.

Health risks from extreme heat in China: Evidence from health insurance

Global warming has accentuated the effects of extreme heat on health. Health insurance, functioning as a risk management tool, has the potential to alleviate these impacts. Consequently, this paper investigates the correlation between extreme heat events and the demand for health insurance in China. Using data from the China Health and Nutrition Survey, we have observed a substantial increase in the likelihood of residents purchasing health insurance during extreme heat events. To be specific, for every extra day of extreme heat events annually, there is a 0.3% increase in the probability of purchasing health insurance. This effect is not uniform across different demographic groups. It is particularly pronounced among middle-aged and elderly individuals, rural residents, those with lower educational levels, higher income brackets, and individuals residing in underprivileged areas with limited access to green spaces and healthcare facilities. Furthermore, our study indicates that the increased frequency of extreme heat events not only impacts individuals' physical health but also triggers negative emotions, which in turn drive risk-averse behavior related to health insurance purchases. These findings carry substantial policy implications for mitigating the economic consequences of climate change.

The association of heatwave with drowning mortality in five provinces of China

Drowning is a serious public health problem in the world. Several studies have found that ambient temperature is associated with drowning, but few have investigated the effect of heatwave on drowning. This study aimed to explore the associations between heatwave and drowning mortality, and further estimate the mortality burden of drowning attributed to heatwave in China. Drowning mortality data were collected in 71 prefectures in China during 2013-2018 from provincial vital register system. Meteorological data at the same period were collected from European Centre for Medium-Range Weather Forecasts (ECMWF). A distributed lag non-linear model (DLNM) was first to explore the association between heatwave and drowning mortality in each prefecture. Secondly, the prefecture-specific associations were pooled using meta-analysis. Finally, attributable fractions (AFs) of drowning deaths caused by heatwave were estimated. Compared to normal day, the mortality risk of drowning significantly increased during heatwave (RR = 1.20, 95%CI: 1.18-1.23). Higher risks were observed in males (RR = 1.23, 95%CI: 1.20-1.27) than females (RR = 1.18, 95%CI: 1.13-1.23), in children aged 5-14 years old (RR = 1.24, 95%CI: 1.15-1.33) than other age groups, in urban city (RR = 1.32, 95%CI: 1.28-1.36) than rural area (RR = 1.09, 95%CI: 1.07-1.12) and in Jilin province (RR = 2.85, 95%CI: 1.61-5.06) than other provinces. The AF of drowning deaths due to heatwave was 11.4 % (95%CI: 10.0 %-12.9 %) during heatwave and 1.0 % (95%CI: 0.9 %-1.1 %) during study period, respectively. Moreover, the AFs during study period were higher for male (1.2 %, 95%CI: 1.0 %-1.3 %), children 5-14 years (1.1 %, 95%CI: 0.7 %-1.6 %), urban city (1.6 %, 95%CI: 1.4 %-1.8 %) than their correspondents. These differences were also observed in AFs during heatwave. We found that heatwave may significantly increase the mortality risk of drowning mortality, and its mortality burden attributable to heatwave was noteworthy. Targeted intervention should be carried out to decrease drowning mortality during heatwave.

Mapping social vulnerability indicators to understand the health impacts of climate change: a scoping review

The need to assess and measure how social vulnerability influences the health impacts of climate change has resulted in a rapidly growing body of research literature. To date, there has been no overarching, systematic examination of where this evidence is concentrated and what inferences can be made. This scoping review provides an overview of studies published between 2012 and 2022 on social vulnerability to the negative health effects of climate change. Of the 2115 studies identified from four bibliographic databases (Scopus, Web of Science, PubMed, and CAB Direct), 230 that considered indicators of social vulnerability to climate change impacts on health outcomes were selected for review. Frequency and thematic analyses were conducted to establish the scope of the social vulnerability indicators, climate change impacts, and health conditions studied, and the substantive themes and findings of this research. 113 indicators of social vulnerability covering 15 themes were identified, with a small set of indicators receiving most of the research attention, including age, sex, ethnicity, education, income, poverty, unemployment, access to green and blue spaces, access to health services, social isolation, and population density. The results reveal an undertheorisation and few indicators that conceptualise and operationalise social vulnerability beyond individual sociodemographic characteristics by identifying structural and institutional dimensions of vulnerability, and a preponderance of social vulnerability research in high-income countries. This Review highlights the need for future research, data infrastructure, and policy attention to address structural, institutional, and sociopolitical conditions, which will better support climate resilience and adaptation planning.

Temporal and spatial characteristics of high temperatures, heat waves, and population distribution risk in China from 1951 to 2019

Understanding the relationships between high temperatures (HT) and heat waves (HW) is vital for enhancing human health, especially in areas with dense population. This paper analyzes the temporal and spatial characteristics of different HT and HW intensities, their spatial influence, and the population distribution risk at different HW intensities for 844 meteorological stations between 1951 and 2019. The results indicate that (1) HT and extreme temperature (ET) days are symmetrically distributed along the Huhuanyong Line, from southeast to northwest China. The times, days, and accumulated temperatures of HW, the times, days, and accumulated temperature of strong heat waves (SHW), and the times, days, and accumulated temperature of extreme heat waves (EHW) were distributed similarly; (2) with the increase in high temperatures or heat waves from HT to ET or from HW to SHW, the proportion of stations with an upward trend was always greater in China, while stations with a downward trend were mainly located in the North China Plain and Huai River Basin. For HW, SHW, and EHW, the increasing range of times and days were less than the accumulated temperatures; (3) between 1990 and 2019, there was an expansion of the HW and SHW distribution area with an annual average of more than 10 days, and the EHW distribution area with an annual average of more than 3 days. Moreover, the number of people exposed to HW, SHW, and EHW also increased during this period; and (4) considering the population distribution characteristics and the regional HT and HW characteristics, society needs to form regional adaptation actions for different HT and HW intensities.

Projecting the excess mortality due to heatwave and its characteristics under climate change, population and adaptation scenarios

BACKGROUND

Heatwaves have significant adverse effects on human health. The frequency, duration, and intensity of heatwaves are projected to increase dramatically, in the context of global warming. However, there are few comprehensive assessments of the health impact of heatwaves considering different definitions, and their characteristics under climate change scenarios.

OBJECTIVE

We aimed to compare future excess mortality related to heatwaves among different definitions under climate change, population, and adaptation scenarios in China and further explore the mortality burden associated with heatwave characteristics.

METHODS

Daily data during 2010-2019 were collected in Guangzhou, China. We adopted nine common heatwave definitions and applied quasi-Poisson models to estimate the effects of heatwaves and their characteristics' impact on mortality. We then projected the excess mortality associated with heatwaves and their characteristics concerning climate change, population, and adaptation scenarios.

RESULTS

The relative risks of the nine common heatwave definitions ranged from 1.05 (95% CI: 1.01, 1.10) to 1.24 (95% CI: 1.13, 1.35). Heatwave-related excess mortality will consistently increase in the future decades considering multiple heatwave definitions, with more rapidly increasing rates under the Shared Socioeconomic Path5-8.5 and non-adaptability scenarios. Regarding heatwave characteristics, the intensity is the main factor involved in the threat of heatwaves. The increasing trend of characteristic-related mortality burden is similar to that of heatwaves, and the mortality burden caused by the duration of the heatwaves was the largest among all characteristics.

CONCLUSIONS

This study provides a comprehensive picture of the impact of heatwaves and their characteristics on public health under various climate change scenarios, population changes, and adaptive assumptions. The results may provide important public health implications for policymakers in planning climate change adaptation and mitigation policies, and implementing specific plans.

Heatwave and mental health

Physical health has been associated with ambient temperature and heatwave. With the frequent occurrence of heatwave, the adaptive effects and mechanisms on mental health remain uncertain. On the basis of the China Health and Nutrition Survey, we estimated the relationship between heatwaves and self-assessed mental health scores in the Chinese population aged 50 and above. This study has identified that with each additional heatwave event, mental health scores decreased by an average of 0.027 points, which is equivalent to 0.3% of the average level. Heat is more likely to affect groups with low education, no medical insurance, and living in rural areas. In mechanistic exploration, we found that stress emotion is a fully mediating effect. Heat led to reduced health activities and more frequent drinking, which may lead to lower psychological well-being. Moreover, good dietary preference is a regulator that can help mitigate the adverse effects of heat on mental health. This study corroborates the impact of heat on spiritual welfare, and demonstrates the mechanisms and channels of impact, which can help reduce global economic losses due to mental health problems.

Determining the Impact of Heatwaves on Emergency Ambulance Calls in Queensland: A Retrospective Population-Based Study

Heatwaves are a significant and growing threat to the health and well-being of the residents of Queensland, Australia. This threat is increasing due to climate change. Excess heat increases the demand for health services, including ambulance calls, and the purpose of this study was to explore this impact across Queensland. A state-wide retrospective analysis of heatwaves and emergency 'Triple Zero' (000) calls to Queensland Ambulance (QAS) from 2010-2019 was undertaken. Call data from the QAS and heatwave data from the Bureau of Meteorology were analysed using a case-crossover approach at the postcode level. Ambulance calls increased by 12.68% during heatwaves. The effect was greatest during low-severity heatwaves (22.16%), followed by severe (14.32%) and extreme heatwaves (1.16%). The impact varied by rurality, with those living in very remote areas and major cities most impacted, along with those of low and middle socioeconomic status during low and severe intensity heat events. Lag effects post-heatwave continued for at least 10 days. Heatwaves significantly increase ambulance call centre workload, so ambulance services must actively prepare resources and personnel to address increases in heatwave frequency, duration, and severity. Communities must be informed of the risks of heatwaves at all severities, particularly low severity, and the sustained risks in the days following a heat event.

Mortality Risk Related to Heatwaves in Dezful City, Southwest of Iran

BACKGROUND

We aimed to evaluate the impact of heatwaves on daily deaths due to non-accidental, cardiovascular and respiratory causes in the city of Dezful in Iran from 2013 to 2019.

METHOD

We collected daily ambient temperature and mortality and defined 2 types of heatwaves by combining daily temperature ⩾90th in each month of the study period or since 30 years with duration ⩾2 and 3 days. We used a distributed lag non-linear model to study the association between each type of heatwave definition, and deaths due to non-accidental, cardiovascular and respiratory causes with lags up to 13 days.

RESULTS

There was no discernible correlation in this area, despite the fact that heatwaves raised the risk of death from cardiovascular causes and lowered the risk from respiratory causes. On the other hand, the risk of total non-accidental mortality on days with the heatwaves is significantly higher than normal days. In main effects, the heatwaves have a significant relationship with the risk of total non-accidental mortality (in the first heatwave definition, Cumulative Excess Risk (CER) in lag_0-2 was 10.4 and in second heatwave definition, CER values in lag_{0, 0-2, and 0-6} were 12.4, 29.2, and 38.8 respectively). Also, in added effects, heatwaves have a significant relationship with the risk of total non-accidental mortality (in the first heatwave definition, CER in lag_{0 and 0-2} were 1.79 and 4.11 and in the second heatwave definition, CER values in lag_{0, 0-2, and 0-6} were 7.76, 18.35 and 24.87 respectively). In addition, heatwaves appeared to contribute to a cumulative excess risk of non-accidental death among the male group as well as the older adults.

CONCLUSION

However, the results showed that heatwaves could have detrimental effects on health, even in populations accustomed to the extreme heat. Therefore, early warning systems which monitor heatwaves should provide the necessary warnings to the population, especially the most vulnerable groups.

Systematic identification of heat events associated with emergency admissions to enhance the heat-health action plan in a subtropical city: a data-driven approach

According to the United Nations Office for Disaster Risk Reduction (UNDRR), a heat-health action plan should address various impacts of hazards at different levels, including an early warning system to monitor risks and behaviour enhancement to increase disaster preparedness. It is necessary to comply with guidelines regarding heat duration/intensity. In this study, we developed a data-driven approach to rapidly and systematically estimate the impacts of various heat events on emergency admissions among the adult population (n = 7,086,966) in Hong Kong in order to enhance the heat-health action plan. Immediate, short-term, and long-term impacts determined by 1-day, 4-day, and 8-day windows were estimated to identify specific heat events suitable for early warnings. In addition, underestimated risk, determined by a continuous increase in heat risk after days without significant emergency admissions, was estimated to evaluate potential maladaptive behaviours among a specific subpopulation. Based on age- and gender-specific analyses, 1D, 1D1N, and 2D2N were observed to have a stronger immediate impact on emergency admissions. 1D1N and 2D2N also showed notable short-term and long-term impacts. Based on heat vulnerability factors (age and gender), 2D2N was a higher-priority extreme heat event for early warning measures than 1D1N. Furthermore, men aged 19 to 64 had the highest underestimated risk. Specifically, they had IRR values of 1.113 [1.087, 1.140], 1.061 [1.035, 1.087], and 1.069 [1.043, 1.095] during lag days 3-5 of 3D2N, respectively, possibly due to a lack of adaptive behaviour. By adopting our approach, the duration of heat events with significant health impacts can be identified in order to further enhance relevant heat stress information. This framework can be applied to other cities with a similar background for rapid assessment.

Impact of Heavy PM2.5 Pollution Events on Mortality in 250 Chinese Counties

We explored the impact of heavy PM_2.5 pollution events on the health of residents in 250 counties in China. A time-series approach involving a two-stage analysis was applied to estimate the association between heavy PM_2.5 pollution events and mortality from 2013 to 2018. The associations between heavy (PM_2.5 ≥75 μg/m³ and <150 μg/m³) and extremely heavy (PM_2.5 ≥150 μg/m³) PM_2.5 pollution days with mortality were explored. The added effects of the heavy PM_2.5 pollution events were evaluated by controlling PM_2.5 concentration in the model. From 2013 to 2018, there were 57,279 county days of heavy PM_2.5 pollution and 21,248 county days of extremely heavy PM_2.5 pollution. The risks of mortality during this period of heavy PM_2.5 pollution events increased by 1.22% (95% CI: 0.82-1.63%), 1.14% (95% CI: 0.74-1.53%), 1.09% (95% CI: 0.58-1.60%), and 1.30% (95% CI: 0.40-2.20%), for all-cause, nonaccidental, circulatory, and respiratory mortality, respectively. We also observed that heavy PM_2.5 pollution events had an added effect on mortality risk associated with all-cause, nonaccidental, circulatory, and respiratory mortality, evident from an observed increase by 0.77% (95% CI: 0.29-1.24%), 0.73% (95% CI: 0.27-1.19%), 0.96% (95% CI: 0.37-1.55%), and 0.55% (95% CI: -0.52-1.63%), respectively. Heavy PM_2.5 pollution events increased mortality risks and caused an independent added effect. The findings serve as a foundation for policymakers in developing early warning systems and policy interventions.

Exploring the Climate Temperature Effects on Settlement Intentions of Older Migrants: Evidence from China

Permanent migration across provinces in China has become an important strategy for Chinese older people to respond to a temperature-unfriendly place of residence in late life. However, the relation between temperature effects and permanent settlements of older migrants remains unclear. Based on the data obtained from China Migrants Dynamic Survey, this paper examined how four temperature effects (i.e., cold effect, heat effect, temperature gap effect, and temperature zone effect) play a role in shaping older migrants’ intentions to settle permanently in a destination place by conducting logistic regression analysis. Our findings show that: (1) extreme cold (rather than extreme heat or mild temperature) was found to have significant effects on settlement intentions of older people; (2) relative winter temperature between origin and destination places rather than absolute winter temperature in the destination place has a significant positive effect on the settlement intentions; (3) spatially, older migrants tend to migrate to geographically adjacent temperature zones. Our findings will inform a more effective planning and allocation of services for supporting older people by better understanding trends and intentions of older migrants.

Sensors for Context-Aware Smart Healthcare: A Security Perspective

The advances in the miniaturisation of electronic devices and the deployment of cheaper and faster data networks have propelled environments augmented with contextual and real-time information, such as smart homes and smart cities. These context-aware environments have opened the door to numerous opportunities for providing added-value, accurate and personalised services to citizens. In particular, smart healthcare, regarded as the natural evolution of electronic health and mobile health, contributes to enhance medical services and people's welfare, while shortening waiting times and decreasing healthcare expenditure. However, the large number, variety and complexity of devices and systems involved in smart health systems involve a number of challenging considerations to be considered, particularly from security and privacy perspectives. To this aim, this article provides a thorough technical review on the deployment of secure smart health services, ranging from the very collection of sensors data (either related to the medical conditions of individuals or to their immediate context), the transmission of these data through wireless communication networks, to the final storage and analysis of such information in the appropriate health information systems. As a result, we provide practitioners with a comprehensive overview of the existing vulnerabilities and solutions in the technical side of smart healthcare.

Using machine learning to examine street green space types at a high spatial resolution: Application in Los Angeles County on socioeconomic disparities in exposure

BACKGROUND

Compared to commonly-used green space indicators from downward-facing satellite imagery, street view-based green space may capture different types of green space and represent how environments are perceived and experienced by people on the ground, which is important to elucidate the underlying mechanisms linking green space and health.

OBJECTIVES

This study aimed to evaluate machine learning models that can classify the type of vegetation (i.e., tree, low-lying vegetation, grass) from street view images; and to investigate the associations between street green space and socioeconomic (SES) factors, in Los Angeles County, California.

METHODS

SES variables were obtained from the CalEnviroScreen3.0 dataset. Microsoft Bing Maps images in conjunction with deep learning were used to measure total and types of street view green space, which were compared to normalized difference vegetation index (NDVI) as commonly-used satellite-based green space measure. Generalized linear mixed model was used to examine associations between green space and census tract SES, adjusting for population density and rural/urban status.

RESULTS

The accuracy of the deep learning model was high with 92.5% mean intersection over union. NDVI were moderately correlated with total street view-based green space and tree, and weakly correlated with low-lying vegetation and grass. Total and three types of green space showed significant negative associations with neighborhood SES. The percentage of total green space decreased by 2.62 [95% confidence interval (CI): -3.02, -2.21, p < 0.001] with each interquartile range increase in CalEnviroScreen3.0 score. Disadvantaged communities contained approximately 5% less average street green space than other communities.

CONCLUSION

Street view imagery coupled with deep learning approach can accurately and efficiently measure eye-level street green space and distinguish vegetation types. In Los Angeles County, disadvantaged communities had substantively less street green space. Governments and urban planners need to consider the type and visibility of street green space from pedestrian's perspective.

Effects of extreme temperature on respiratory diseases in Lanzhou, a temperate climate city of China

Under the global climate warming, extreme weather events occur more and more frequently. Epidemiological studies have proved that extreme temperature is strongly correlated with respiratory diseases. We evaluated extreme-temperature effect on respiratory emergency room (ER) visits for 5 years in Lanzhou, a northwest temperate climate city of China from January 1st, 2013, to August 31st, 2017. We built a distributed lag non-linear model (DLNM) to evaluate the lag effect up to 30 days. Results showed the relative risk (RR) of respiratory disease always reached the maximum at lag 0 day and decreased to 1.0 at lag 5 days. Extremely low temperature showed the lag effect of 22 days and the maximum RR was 1.415 (95% CI 1.295-1.546) at lag 0 day. Extremely high temperature showed the lag effect of 7 days and the maximum RR was 1.091 (95% CI 1.069-1.114) at lag 0 day. The elders (age > 65 years) were at the greatest risk to extreme temperatures and the response were very acute. Children (age ≤ 15 years) were at the lowest risk but the lag effect lasted the longest lag days than other subgroups. Males showed longer-term lag effect and higher RR than females. Our study indicated that the extremely low temperature has a significantly greater effect on respiratory diseases than extremely high temperature.

Effects of urbanization on vulnerability to heat-related mortality in urban and rural areas in South Korea: a nationwide district-level time-series study

BACKGROUND

Although urbanization is often an important topic in climate change studies, the complex effect of urbanization on heat vulnerability in urban and rural areas has rarely been studied. We investigated the disparate effects of urbanization on heat vulnerability in urban and rural areas, using nationwide data.

METHODS

We collected daily weather data for all 229 administrative districts in South Korea (2011-17). Population density was applied as an urbanization indicator. We calculated the heat-mortality risk using a distributed lag nonlinear model and analysed the relationship with population density. We also examined district characteristics that can be related to the spatial heterogeneity in heat-mortality risk.

RESULTS

We found a U-shaped association between population density and heat-mortality risk, with the highest risk for rural populations; in urban areas, risk increases with increasing population density. Higher heat-mortality risk was associated with a lower number of hospital beds per person and higher percentage of people requiring recuperation. The association between hospital beds and heat-mortality risk was prominent in high-density urban areas, whereas the association between the percentage of people requiring recuperation and heat-mortality risk was pronounced in rural areas.

CONCLUSIONS

Our findings indicate that the association between population density and heat-mortality risk is different in urban and rural areas, and that district characteristics related to heat-mortality risk also differ by urbanicity. These results can contribute to understanding the complex role of urbanization on heat vulnerability and can provide evidence to policy makers for prioritizing resources.

The association of compound hot extreme with mortality risk and vulnerability assessment at fine-spatial scale

The frequency and intensity of compound hot extremes will be likely to increase in the context of global warming. Epidemiological studies have demonstrated the adverse effect of simple hot extreme events on mortality, but little is known about the effects of compound hot extremes on mortality. Daily meteorological, demographic, and mortality data during 2011-2017 were collected from 160 streets in Guangzhou City, China. We used distributed lag non-linear model (DLNM) to analyze the associations of different hot extremes with mortality risk in each street. Street-specific associations were then combined using a meta-analysis approach. To assess the spatial distribution of vulnerability to compound hot extremes, vulnerable characteristics at street level were selected using random forest model, and then we calculated and mapped spatial vulnerability index (SVI) at each street in Guangzhou. At street level, compared with normal day, compound hot extreme significantly increased mortality risk (relative risk(RR)=1.43, 95%CI:1.28-1.59) with higher risk for female (RR=1.54 [1.35-1.76]) and the elderly(RR for aged 65-74=1.41 [1.14-1.74]; RR for ≥75years=1.63 [1.45-1.84]) than male (RR=1.32 [1.15-1.52]) and population <65 years (RR=1.01 [0.83-1.22]). Areas with high vulnerability were in the urban center and the edge of suburban. High proportion of population over 64 years old in urban center, and high proportions of outdoor workers and population with illiteracy in suburban areas were the determinants of spatial vulnerability. We found that compound hot extreme significantly increased mortality risk at street level, which is modified by socio-economic and demographic factors. Our findings help allocate resources targeting vulnerable areas at fine-spatial scale.°.

Extreme weather events and dengue outbreaks in Guangzhou, China: a time-series quasi-binomial distributed lag non-linear model

Dengue transmission is climate-sensitive and permissive conditions regularly cause large outbreaks in Asia-Pacific area. As climate change progresses, extreme weather events such as heatwaves and unusually high rainfall are predicted more intense and frequent, but their impacts on dengue outbreaks remain unclear so far. This paper aimed to investigate the relationship between extreme weather events (i.e., heatwaves, extremely high rainfall and extremely high humidity) and dengue outbreaks in China. We obtained daily number of locally acquired dengue cases and weather factors for Guangzhou, China, for the period 2006-2015. The definition of dengue outbreaks was based on daily number of locally acquired cases above the threshold (i.e., mean + 2SD of daily distribution of dengue cases during peaking period). Heatwave was defined as ≥2 days with temperature ≥ 95th percentile, and extreme rainfall and humidity defined as daily values ≥95th percentile during 2006-2015. A generalized additive model was used to examine the associations between extreme weather events and dengue outbreaks. Results showed that all three extreme weather events were associated with increased risk of dengue outbreaks, with a risk increase of 115-251% around 6 weeks after heatwaves, 173-258% around 6-13 weeks after extremely high rainfall, and 572-587% around 6-13 weeks after extremely high humidity. Each extreme weather event also had good capacity in predicting dengue outbreaks, with the model's sensitivity, specificity, accuracy, and area under the receiver operating characteristics curve all exceeding 86%. This study found that heatwaves, extremely high rainfall, and extremely high humidity could act as potential drivers of dengue outbreaks.

Heat wave characteristics, mortality and effect modification by temperature zones: a time-series study in 130 counties of China

BACKGROUND

The substantial disease burden attributed to heat waves, and their increasing frequency and intensity due to climate change, highlight the importance of understanding the health consequences of heat waves. We explore the mortality risk due to heat wave characteristics, including the timing in the seasons, the day of the heat wave, the intensity and the duration, and the modifying effect of temperature zones.

METHODS

Heat waves were defined as ≥ 2 days with a temperature ≥99th percentile for the county from 1 May through 30 September. Heat waves were characterized by their intensity, duration, timing in the season, and day of the heat wave. Within each county, we estimated the total non-accidental death and cardiovascular disease mortality during each heat wave compared with non-heat wave days by controlling for potential confounders in summer. We combined individual heat wave effect estimates using a random-effects model to calculate overall effects at the temperature zone and national levels.

RESULTS

The average daily total number of non-accidental deaths was nine in the warm season (across all the counties). Approximately half of the daily total number of non-accidental deaths were cardiovascular-related deaths (approximately four persons per day). The average and maximum temperatures across the study area were 23.1 °C (range: -1.2-35.9 °C) and 28.3 °C (range: 5.4-42.8 °C), respectively. The average relative humidity during the study was 68.9% (range: 8.0-100.0%). Heat waves increase the risk of total non-accidental death by 15.7% [95% confidence interval (CI): 12.5, 18.9] compared with non-heat wave periods, and the risk of cardiovascular-related death increases by 22.0% (95% CI: 16.9, 27.4). The risk of non-accidental death during the first heat wave of the season increases by 16.3% (95% CI: 12.6, 20.2), the risk during the second heat wave increases by 6.3% (95% CI: 2.8, 9.9) and during subsequent heat waves increases by -2.1% (95% CI: -4.6, 0.4). The first day and the second to third days of heat waves increase the risk of total non-accidental death by 11.7% (95% CI: 7.6, 15.9) and 17.0% (95% CI: 13.1, 21.0), respectively. Effects of heat waves on mortality lasted more than 4 days (6.3%, 95% CI: 2.4, 10.5) and are non-significantly different from the first day of heat waves. We found non-significant differences of the heat wave-associated mortality risks across mid-, warm and subtropical temperature zones.

CONCLUSIONS

In China, the effect of heat waves on mortality is acute, and varies by certain characteristics of heat waves. Given these results, national heat wave early warning systems should be developed, as well as precautions and protection warranted according to characteristics of heat waves.

Impact of different heat wave definitions on daily mortality in Bandafassi, Senegal

Objective

The aim of this study is to find the most suitable heat wave definition among 15 different ones and to evaluate its impact on total, age-, and gender-specific mortality for Bandafassi, Senegal.

Methods

Daily weather station data were obtained from Kedougou situated at 17 km from Bandafassi from 1973 to 2012. Poisson generalized additive model (GAM) and distributed lag non-linear model (DLNM) are used to investigate the effect of heat wave on mortality and to evaluate the nonlinear association of heat wave definitions at different lag days, respectively.

Results

Heat wave definitions, based on three or more consecutive days with both daily minimum and maximum temperatures greater than the 90^th percentile, provided the best model fit. A statistically significant increase in the relative risk (RRs 1.4 (95% Confidence Interval (CI): 1.2–1.6), 1.7 (95% CI: 1.5–1.9), 1.21 (95% CI: 1.08–1.3), 1.2 (95% CI: 1.04–1.5), 1.5 (95% CI: 1.3–1.8), 1.4 (95% CI: 1.2–1.5), 1.5 (95% CI: 1.07–1.6), and 1.5 (95% CI: 1.3–1.8)) of total mortality was observed for eight definitions. By using the definition based on the 90^th percentile of minimum and maximum temperature with a 3-day duration, we also found that females and people aged ≥ 55 years old were at higher risks than males and other different age groups to heat wave related mortality.

Conclusion

The impact of heat waves was associated with total-, age-, gender-mortality. These results are expected to be useful for decision makers who conceive of public health policies in Senegal and elsewhere. Climate parameters, including temperatures and humidity, could be used to forecast heat wave risks as an early warning system in the area where we conduct this research. More broadly, our findings should be highly beneficial to climate services, researchers, clinicians, end-users and decision-makers.

Ambient temperatures, heatwaves and out-of-hospital cardiac arrest in Brisbane, Australia

BACKGROUND

The health impacts of temperatures are gaining attention in Australia and worldwide. While a number of studies have investigated the association of temperatures with the risk of cardiovascular diseases, few examined out-of-hospital cardiac arrest (OHCA) and none have done so in Australia. This study examined the exposure-response relationship between temperatures, including heatwaves and OHCA in Brisbane, Australia.

METHODS

A quasi-Poisson regression model coupled with a distributed lag non-linear model was employed, using OHCA and meteorological data between 1 January 2007 and 31 December 2019. Reference temperature was chosen to be the temperature of minimum risk (21.4°C). Heatwaves were defined as daily average temperatures at or above a heat threshold (90th, 95th, 98th, 99th percentile of the yearly temperature distribution) for at least two consecutive days.

RESULTS

The effect of any temperature above the reference temperature was not statistically significant; whereas low temperatures (below reference temperature) increased OHCA risk. The effect of low temperatures was delayed for 1 day, sustained up to 3 days, peaking at 2 days following exposures. Heatwaves significantly increased OHCA risk across the operational definitions. When a threshold of 95th percentile of yearly temperature distribution was used to define heatwaves, OHCA risk increased 1.25 (95% CI 1.04 to 1.50) times. When the heat threshold for defining heatwaves increased to 99th percentile, the relative risk increased to 1.48 (1.11 to 1.96).

CONCLUSIONS

Low temperatures and defined heatwaves increase OHCA risk. The findings of this study have important public health implications for mitigating strategies aimed at minimising temperature-related OHCA.

The effect of cold and heat waves on mortality in Urmia a cold region in the North West of Iran

Few studies have investigated the different extreme temperature effects (heat-cold) of one geographical location at the same time in Iran. This study was conducted to assess the impact of heat and cold waves on mortality in Urmia city, which has a cold and mountainous climate. Distributed Lag Non-linear Models combined with a quasi-Poisson regression were used to assess the impact of heat (HW) and cold waves (CW) on mortality in subgroups, controlled for potential confounders such as long-term trend of daily mortality, day of week effect, holidays, mean temperature, humidity, wind speed and air pollutants. The heat/cold effect was divided into two general categories A-main effect (the effect caused by temperature), B-added effect (the effect caused by persistence of extreme temperature). Results show that there was no relation between HW and respiratory and cardiovascular death, but in main effects, HW_(H1) significantly increased, the risk of Non-Accidental Death (NAD) in lag 0 (Cumulative Excess Risk (CER) _NAD = 31(CI; 4-65)). Also in added effects, HW had a significant effect on NAD (CER _{H1; NAD; lag;0-2} = 31(CI; 5, 51), CER _{H2; NAD; lag;0-2} = 26(CI; 6, 48)). There was no relation between CW and respiratory death and cardiovascular death, but in added effects, CW_(C1) significantly decreased, the risk of non-accidental death in initial lags (CER _{C1; NAD; lag;0-2} = -19 (CI; -35, -2)). It seems that high temperatures and heat waves increase the risk of non-accidental mortality in northwest of Iran.

Impacts of urbanization on the temperature-cardiovascular mortality relationship in Beijing, China

The effect of temperature on cardiovascular disease (CVD) mortality has been extensively studied. However, it remains largely unknown over whether there is any difference between urban and suburban areas within the same city and how urbanization modifies the relationship between temperature and CVD mortality. In order to examine whether the association between temperature and CVD mortality existed difference in urban and suburban areas, and how urbanization modified this association, we used a distributed lag nonlinear model and a generalized additive model to investigate temperature-related CVD mortality in urban and suburban areas in Beijing, China, from 2006 to 2011. The age, gender, and educational attainment of the population were stratified to explore the modifying effect. We observed that the impacts of heat and cold temperature on CVD mortality were higher in suburban areas than in urban areas. In addition, the elderly and illiterate subjects in suburban areas were more vulnerable to both heat and cold than their counterparts in urban areas. Moreover, higher urbanization levels were significantly associated with districts having lower the excess risks for temperature- CVD mortality. Our findings provide evidence that populations in suburban Beijing have higher risk of temperature-related CVD mortality than those in urban areas. Therefore, greater attention should be paid to vulnerable groups in suburban areas to reduce temperature-related health burden.

Effects of the 2018 heat wave on health in the elderly: implications for adaptation strategies to climate change

There has been growing concern over the effects of heat waves on health. However, the effects of heat waves on the health of individuals in vulnerable groups have rarely been examined. We aimed to investigate the acute health effects of heat waves in elderly individuals living in rural areas and to survey their adaptation capacity. Repeated measurements of body temperature (BT), blood pressure, sleep disturbance, and indoor temperature were conducted up to six times for each of 104 elderly individuals living in rural areas of South Korea during the 2018 heat wave. Changes in BT, systolic blood pressure (SBP), and diastolic blood pressure (DBP) according to variations in indoor and outdoor temperature were analyzed using linear mixed effect models controlling for age, sex, smoking, and drug use. We also surveyed heat wave adaptation capacity, heat wave shelters, and self-reported health problems. The average indoor temperature measured during the study period was 30.5°C (range: 22.9-38.3°C) and that of ambient temperature was 30.6°C (range: 24.6-36.3°C). BT significantly increased with indoor and outdoor temperatures. The effect on BT was greater in elderly women and the elderly with hypertension. DBP generally decreased with increasing indoor temperature, though the correlation was only statistically significant among the elderly with hypertension. Only 22 (21.2%) individuals used air conditioners during the heat wave. Most did not use an air conditioner mainly to avoid high electricity costs. Of the participants, 58.7% reported experiencing sleep disturbance, which was the most frequent self-reported health problem. Elderly individuals living in rural areas are directly exposed to high temperatures during heat waves, and their vital signs are sensitive to increases in indoor temperature due to poor adaptation capacity. Well-designed strategies for alleviating health-related stress during heat waves are necessary.

Mitigating heat-related mortality risk in Shanghai, China: system dynamics modeling simulations

Numerous studies in epidemiology, meteorology, and climate change research have demonstrated a significant association between abnormal ambient temperature and mortality. However, there is a shortage of research attention to a systematic assessment of potential mitigation measures which could effectively reduce the heat-related morbidity and mortality risks. This study first illustrates a conceptualization of a systems analysis version of urban framework for climate service (UFCS). It then constructs a system dynamics (SD) model for the UFCS and employs this model to quantify the impacts of heat waves on public health system in Shanghai and to evaluate the performances of two mitigation measures in the context of a real heat wave event in July 2013 in the city. Simulation results show that in comparison with the baseline without mitigation measures, if the hospital system could prepare 20% of beds available for emergency response to heat waves once receiving the warning in advance, the number of daily deaths could be reduced by 40-60 (15.8-19.5%) on the 2 days of day 7 and day 8; if increasing the minimum living allowance of 790 RMB/month in 2013 by 20%, the number of daily deaths could be reduced by 50-70 (17.7-21.9%) on the 2 days of day 8 and day 12. This tool can help policy makers systematically evaluate adaptation and mitigation options based on performance assessment, thus strengthening urban resilience to changing climate.

Heatwave-Related Mortality Risk and the Risk-Based Definition of Heat Wave in South Korea: A Nationwide Time-Series Study for 2011-2017

Studies on the pattern of heatwave mortality using nationwide data that include rural areas are limited. This study aimed to assess the risk of heatwave-related mortality and evaluate the health risk-based definition of heatwave. We collected data on daily temperature and mortality from 229 districts in South Korea in 2011–2017. District-specific heatwave-related mortality risks were calculated using a distributed lag model. The estimates were pooled in the total areas and for each urban and rural area using meta-regression. In the total areas, the threshold point of heatwave mortality risk was estimated at the 93rd percentile of temperature, and it was lower in urban areas than in rural areas (92nd percentile vs. 95th percentile). The maximum risk of heatwave-related mortality in the total area was 1.11 (95% CI: 1.01–1.22), and it was slightly greater in rural areas than in the urban areas (RR: 1.23, 95% CI: 0.99–1.53 vs. RR: 1.10, 95% CI: 1.01–1.20). The results differ by age- and cause-specific deaths. In conclusion, the patterns of heatwave-related mortality risk vary by area and sub-population in Korea. Thus, more target-specific heatwave definitions and action plans should be established according to different areas and populations.

Local actions to health risks of heatwaves and dengue fever under climate change: Strategies and barriers among primary healthcare professionals in southern China

BACKGROUND

Climate change and extreme weather poses significant threats to community health, which need to be addressed by local health workforce. This study investigated the perceptions of primary healthcare professionals in Southern China on individual and institutional strategies for actions on health impacts of climate change and the related barriers.

METHODS

A mixed methodological approach was adopted, involving a cross-sectional questionnaire survey of 733 primary healthcare professionals (including medical doctors, nurses, public health practitioners, allied health workers and managers) selected through a multistage cluster randomized sampling strategy, and in-depth interviews of 25 key informants in Guangdong Province, China. The questionnaire survey investigated the perceptions of respondents on the health impacts of climate change and the individual and institutional actions that need to be taken in response to climate change. Multivariate logistic regression models were established to determine sociodemographic factors associated with the perceptions. The interviews tapped into coping strategies and perceived barriers in primary health care to adapt to tackle challenges of climate change. Contents analyses were performed to extract important themes.

RESULTS AND CONCLUSION

The majority (64%) of respondents agreed that climate change is happening, but only 53.6% believed in its human causes. Heat waves and infectious diseases were highly recognized as health problems associated with climate change. There was a strong consensus on the need to strengthen individual and institutional capacities in response to health impacts of climate change. The respondents believed that it is important to educate the public, take active efforts to control infectious vectors, and pay increased attention to the health care of vulnerable populations. The lack of funding and limited local workforce capacity is a major barrier for taking actions. Climate change should be integrated into primary health care development through sustainable governmental funding and resource support.

Cardiorespiratory effects of heatwaves: A systematic review and meta-analysis of global epidemiological evidence

BACKGROUND

Heatwaves affect human health and global heatwave-related disease burden will continue to rise as climate change proceeds, but the effects of heatwaves on cardiovascular and respiratory diseases have not yet been investigated globally and nationally.

OBJECTIVES

This systematic review and meta-analysis aim to quantify heatwave effects on four major health outcomes: cardiovascular and respiratory morbidity and mortality.

METHODS

We searched PubMed, Scopus, Embase, and Web of Science for relevant studies from database inception to November 2018. Categories of morbidity included hospital admissions, emergency department visits, and ambulance attendances/call-outs. A random-effects meta-analysis model was used to pool previous estimates of heatwave effects on mortality and morbidity due to cardiovascular and respiratory diseases. Subgroup analyses by gender, age, and disease cause were conducted. Sensitivity analyses were performed by the categories of morbidity, heatwave definitions, study design, and using a leave-one-out cross validation approach. This study is registered with PROSPERO (number: CRD42018101964).

RESULTS

We identified 54 studies conducted in 20 countries. In total, there were significant associations between heatwaves and cardiovascular mortality (risk estimates (RE): 1.149, 95% confidence interval (CI): 1.090, 1.210) and respiratory mortality (RE: 1.183, 95%CI: 1.092, 1.282), but the magnitude of these associations varied across countries and studies. Heatwaves appeared to be marginally associated with cardiovascular and respiratory morbidities (RE: 0.999, 95%CI: 0.996, 1.002, p-value = 0.61 for cardiovascular morbidity; RE: 1.043, 95%CI: 0.995, 1.093; p-value = 0.08 for respiratory morbidity). For mortality, significant associations were observed for the elderly, ischemic heart disease, stroke, heart failure, and chronic obstructive pulmonary disease. Sensitivity analyses suggested that these findings were robust.

CONCLUSION

Mortality of cardiovascular and respiratory diseases appeared to be more vulnerable to heatwaves in comparison to morbidity. Considering high heterogeneity detected between studies and limited investigations into subpopulations, more research are required to provide a clearer picture of how heatwaves affect cardiovascular and respiratory diseases in different settings.

The effects of excess degree-hours on mortality in Guangzhou, China

BACKGROUND

Prior studies that examined the association between temperature and mortality relied on mean temperature, maximum temperature, minimum temperature, humidex, and daily temperature variability, not accounting for variations in hourly temperature throughout the day. We proposed an indicator, excess degree-hours, to examine the association between temperature and mortality.

METHODS

A distributed lag non-linear model (DLNM) was used to determine the hot (27.8 °C) and cold (24.3 °C) threshold. Hourly temperature in Guangzhou, China were summarized with extreme heat expressed as sum of degree-hours >27.8 °C and extreme cold as sum of degree-hours <24.3 °C within one day from January 1, 2012 to December 31, 2015. We then estimated the associations of daily mortality with hot and cold degree-hours in both hot and cold season. We also calculated the mortality burden of excess degree-hours.

RESULTS

An interquartile range (IQR) increase of hot degree-hours was associated with 2.11% (95% confidence interval [95% CI]: 1.25%, 2.98%), 3.74% (95% CI: 0.71%, 6.86%), and 2.63% (95% CI: 0.70%, 4.59%) increments in non-injury related death, respiratory mortality, and cardiovascular mortality, respectively. While the corresponding excess risk for an IQR increase of cold degree-hours was 2.42% (95% CI: 1.97%, 2.88%), 3.16% (95% CI: 2.57%, 3.76%), and 2.93% (95% CI: 1.98%, 3.88%). The estimated mortality burdens for hot and cold degree-hours were 1366,2465, respectively.

CONCLUSION

The excess degree-hours reduced to a single indication in duration and intensity is an approach and shows a different perspective and significant extreme weather effects on human health.

Potential effects of heat waves on the population dynamics of the dengue mosquito Aedes albopictus

Extreme weather events affect the development and survival of disease pathogens and vectors. Our aim was to investigate the potential effects of heat waves on the population dynamics of Asian tiger mosquito (Aedes albopictus), which is a major vector of dengue and Zika viruses. We modeled the population abundance of blood-fed mosquito adults based on a mechanistic population model of Ae. albopictus with the consideration of diapause. Using simulated heat wave events derived from a 35-year historical dataset, we assessed how the mosquito population responded to different heat wave characteristics, including the onset day, duration, and the average temperature. Two important observations are made: (1) a heat wave event facilitates the population growth in the early development phase but tends to have an overall inhibitive effect; and (2) two primary factors affecting the development are the unusual onset time of a heat wave and a relatively high temperature over an extended period. We also performed a sensitivity analysis using different heat wave definitions, justifying the robustness of the findings. The study suggests that particular attention should be paid to future heat wave events with an abnormal onset time or a lasting high temperature in order to develop effective strategies to prevent and control Ae. albopictus-borne diseases.

Understanding the population dynamics of Asian Tiger mosquito (Ae. albopictus)–the most prevalent vector of global epidemics including West Nile virus, dengue fever, Zika–could shed lights on improving the understanding of vector transmission as well as developing effective disease control strategies. It is widely acknowledged that the life cycle of Ae. albopictus is firmly regulated by meteorological factors in a non-linear way and is sensitive to climate change. Our study extends the understanding about how extreme heat events manipulate the mosquito population abundance. We adopted an existing mechanistic population model of Ae. albopictus, combined with a rich set of simulated heat wave events derived from a 35-year historical dataset, to quantify the mosquito’s responses to different heat wave characteristics. We found that an abnormal onset time and a lasting high temperature play the most important role in affecting the mosquito population dynamics. We also performed a sensitive analysis by changing the definition of the heat wave, justifying the rigor of the conclusion. This research provides implications for developing public health intervention strategies: to control dengue fever, Zika, as well as other far-reaching mosquito-borne epidemics, priority should be given to heat wave events with an abnormal onset time or a lasting high temperature.

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.

Spatial Assessment of Urban Climate Change Vulnerability during Different Urbanization Phases

In urban areas, concentrated populations and societal changes intensify the influence of climate change. However, few studies have focused on vulnerability to climate-related risks on the scale of a single urban area. Against this backdrop, we reconstructed a spatial vulnerability framework based on the drivers-pressures-state-impact-response (DPSIR) model to reflect the complex interactions between urbanization and climate change and to integrate the natural and socio-economic factors of urban areas into this framework. Furthermore, to explore the relationship between rapid urbanization and climate change, we studied data from two years that represented different stages of urbanization. The results showed that the index framework was able to reconcile these two concepts to reflect the complex interactions between urbanization and climate change. The assessment results indicate that the overall degree of climate change vulnerability exhibits a generally increasing and dispersing trend after rapid urbanization. The increasing trend is influenced by an increase in low-vulnerability areas, and the dispersing trend is influenced by anthropogenic activities caused by rapid urbanization. The changes are reflected in the following observations: 1. The suburbs are affected by their own natural environmental characteristics and rapid urbanization; the vulnerability level has risen in most areas but has declined in certain inland areas. 2. High-vulnerability regions show minor changes during this stage due to the lasting impact of climate change. Finally, the main environmental problems faced by high-vulnerability areas are discussed based on existing research.

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.

Mining Social Media to Identify Heat Waves

Heat waves are one of the deadliest of natural hazards and their frequency and intensity will likely increase as the climate continues to warm. A challenge in studying these phenomena is the lack of a universally accepted quantitative definition that captures both temperature anomalies and associated mortality. We test the hypothesis that social media mining can be used to identify heat wave mortality. Applying the approach to India, we find that the number of heat-related tweets correlates with heat-related mortality much better than traditional climate-based indicators, especially at larger scales, which identify many heat wave days that do not lead to excess mortality. We conclude that social media based heat wave identification can complement climatic data and can be used to: (1) study heat wave impacts at large scales or in developing countries, where mortality data are difficult to obtain and uncertain, and (2) to track dangerous heat wave events in real time.

A new method to estimate the temperature-CVD mortality relationship

Few detailed, individual-focused studies have researched the added effect of temperature on cardiovascular disease (CVD), particularly in China. Moreover, no prior studies have explored the exposure-response relationship among all populations and different sub-sociodemographic groups. A distributed lag nonlinear model (DLNM) was applied to evaluate the adverse health effects of temperature on CVD mortality for all populations and different sub-sociodemographic groups (by age, sex, educational level, living arrangement, and occupation) in Beijing. Based on the exposure-response relationships, firstly, we proposed a new model (COCKTAIL, Code Of Climate Key To An Ill) for revealing the split-and-merge relationships of the temperature-CVD mortality curve. This method could be used to apply the CVD deaths in a studied area to forecast the exposure-response relationships in the same area in the future. Secondly, this is the most detailed study to analyze the relationship between temperature and CVD mortality for different subgroups among the existing researches for developed and developing countries. We found that the cold temperature (at - 14 °C) was the risk factor for people with low socioeconomic status, especially for single people (including unmarried, divorced, and widowed), for indoor workers, and for people with low education, compared with the minimum mortality temperature, with a cumulative increase of 3.9 (80%CI, 2.9-5.4), 3.8 (80%CI, 2.8-5.1), and 4.5 (80%CI, 3.1-6.3) times respectively. Meanwhile, the hot temperature (at 35 °C) was the risk factor for CVD death, with a cumulative increase of 2.6 (80%CI, 2.0-3.4) for females, and 3.1 (80%CI, 2.4-4.2) for single people. The varying CVD vulnerability in terms of CVD mortality among various groups may assist governments in preparing health resources and taking measures to prevent or reduce temperature-related deaths.

Effects of Extreme Temperatures on Mortality and Hospitalization in Ho Chi Minh City, Vietnam

There is a lack of research focusing on the association of temperature with mortality and hospitalization in developing countries with tropical climates and a low capacity to cope with the influences of extreme weather events. This study aimed to examine and compare the effect of temperature, including heat waves, on mortality and hospitalization in the most populous city of Vietnam. We used quasi-Poisson time series regression coupled with the distributed lag non-linear model (DLNM) to examine the overall pattern and compare the temperature-health outcome relationship. The main and added effects of heat waves were evaluated. The main effect of heat waves significantly increased the risk of all cause-specific mortality. Significant main effects of heat waves on hospitalization were observed only for elderly people and people with respiratory diseases (elderly, relative risk (RR) = 1.28, 95% confidence interval (CI) = 1.14–3.45; respiratory diseases, RR = 1.3, 95% CI = 1.19–1.42). The RRs of the main effect were substantially higher than those of the added effect in mortality; the same was applicable for hospitalizations of people with respiratory diseases and elderly people. The findings of this study have important implications for public health adaptation and prevention program implementation in the protection of residents from the adverse health effects of temperature.

Modification Effects of Population Expansion, Ageing, and Adaptation on Heat-Related Mortality Risks Under Different Climate Change Scenarios in Guangzhou, China

(1) Background: Although the health effects of future climate change have been examined in previous studies, few have considered additive impacts of population expansion, ageing, and adaptation. We aimed to quantify the future heat-related years of life lost (YLLs) under different Representative Concentration Pathways (RCP) scenarios and global-scale General Circulation Models (GCMs), and further to examine relative contributions of population expansion, ageing, and adaptation on these projections. (2) Methods: We used downscaled and bias-corrected projections of daily temperature from 27 GCMs under RCP2.6, 4.5, and 8.5 scenarios to quantify the potential annual heat-related YLLs in Guangzhou, China in the 2030s, 2060s, and 2090s, compared to those in the 1980s as a baseline. We also explored the modification effects of a range of population expansion, ageing, and adaptation scenarios on the heat-related YLLs. (3) Results: Global warming, particularly under the RCP8.5 scenario, would lead to a substantial increase in the heat-related YLLs in the 2030s, 2060s, and 2090s for the majority of the GCMs. For the total population, the annual heat-related YLLs under the RCP8.5 in the 2030s, 2060s, and 2090s were 2.2, 7.0, and 11.4 thousand, respectively. The heat effects would be significantly exacerbated by rapid population expansion and ageing. However, substantial heat-related YLLs could be counteracted by the increased adaptation (75% for the total population and 20% for the elderly). (4) Conclusions: The rapid population expansion and ageing coinciding with climate change may present an important health challenge in China, which, however, could be partially counteracted by the increased adaptation of individuals.

Effects of extreme temperatures on hospital emergency room visits for respiratory diseases in Beijing, China

Extreme temperature is closely associated with human health, but limited evidence is available for the effects of extreme temperatures on respiratory diseases in China. The goal of this study is to evaluate the effects of extreme temperatures on hospital emergency room (ER) visits for respiratory diseases in Beijing, China. We used a distributed lag non-linear model (DLNM) coupled with a generalized additive model (GAM) to estimate the association between extreme temperatures and hospital ER visits for different age and gender subgroups in Beijing from 2009 to 2012. The results showed that the exposure-response curve between temperature and hospital ER visits was almost W-shaped, with increasing relative risks (RRs) at extremely low temperature. In the whole year period, strong acute hot effects were observed, especially for the elders (age > 65 years). The highest RR associated with the extremely high temperature was 1.36 (95% CI, 0.96-1.92) at lag 0-27. The longer-lasting cold effects were found the strongest at lag 0-27 for children (age ≤ 15 years) and the relative risk was 1.96 (95% CI, 1.70-2.26). We also found that females were more susceptible to extreme temperatures than males.

The relationship between extreme temperature and emergency incidences: a time series analysis in Shenzhen, China

Extreme temperature has been reported to be associated with an increase in acute disease incidence in several cities. However, few similar studies were carried out in Shenzhen, which is a subtropical city located in the southern China. This study explored the relationship between the emergency incidences and extreme temperatures, and investigated the role of air pollutants played in the temperature-related effects on human health in Shenzhen. We conducted a distributed lag nonlinear model study on the effect of extreme temperatures on emergency incidences in Shenzhen city during 2013-2017. Here, only the total emergency incidences, emergency incidences for respiratory diseases, and cardiovascular diseases were taken into consideration. Air pollution, subgroups, and seasons were adjusted to investigate the impacts of extreme temperatures on emergency incidences. Relative risk (RR) and 95% confidence intervals were calculated with the R software. From lag 0 to 21 days, the RR of temperature-total emergency department visits, temperature-cardiovascular, and temperature-respiratory diseases was 1.09 (95% CI: 0.98-1.20), 1.22 (95% CI: 0.96-1.56), and 1.06 (95% CI: 0.70-1.60) at extremely low temperature (first percent of temperature, 10 °C), respectively. During the same lag days, the RR was 1.02 (95 % CI: 0.92-1.14), 0.64 (95% CI: 0.49-0.86), and 0.92 (95% CI: 0.56-1.53) between extremely high temperature and total emergency department visits, cardiovascular, and respiratory diseases, respectively. The cumulative effects gradually went up with time for all types of emergency incidences in warm seasons (5 days moving average of temperature < 22 °C). However, the cumulative effects of total emergency incidences and Cvd emergency incidences were increased within the first lag 5 days, and then decreased until lag 21 in hot seasons (5 days moving average of temperature ≥ 22 °C). The cumulative effects of Res emergency incidences showed a declined trend from lag 0 to lag 21. The elderly (≥ 65, P1: RR = 1.49, 95% CI (1.30, 1.71); P99: RR = 0.86, 95% CI (0.71, 1.04)) and men (P1: RR = 1.27, 95% CI (1.14, 1.42)) seemed to be more vulnerable to extreme temperature than the younger (≤ 64, P1: RR = 1.19, 95% CI (1.08, 1.32); P99: RR = 1.00, 95% CI (0.89, 1.12)) and women (P1: RR = 1.17, 95%CI (1.06, 1.30)). The effects of extremely low temperature on all types of emergency incidences were stronger than those of extremely high temperature in the whole year. In addition, impacts of cold weather lasted about several days while those of hot weather were acute and rapid. An increased frequency of emergency incidences is predicted by rising temperatures variations. These results have clinical and public health implications for the management of emergency incidences.

Exploring the effects of high temperature on mortality in four cities in the Philippines using various heat wave definitions in different mortality subgroups

Background: Sustained high temperatures, specifically heat waves (HW), increase the risk of dying, especially among risk populations, which are highly vulnerable to its additional effect. In developing countries, there are only a few studies which focused on the magnitude of the risks attributed to HWs.

Objectives: This study explored the HW effects using 15 HW definitions through the combination of duration (> 2, > 4, and > 7 consecutive days) and intensity (at the ≥ 90th, ≥ 95th, ≥ 97th, ≥ 98th, and ≥ 99th temperature percentiles).

Methods: Daily mortality count data from 2006–2010 were obtained from the four tropical cities of the Philippines, and were further stratified by mortality sub-groups, such as cause of death, sex, and age. The same period of daily maximum temperature and relative humidity were also collected. We used a distributed lag non-linear model to determine the risks associated with the main temperature effects, as well as the added HW effects.

Results: It has been observed that the main temperature effects comprise a substantial portion of the risks compared to the HW effects, even across the mortality sub-groups. Further stratification by the sub-groups showed significant HW effects among the young and male populations.

Conclusions: Results of this study can be of use to improve (1) candidate HW definition identification/selection, and (2) risk population-specific strategies, taking into consideration the risk attributions.

A better indicator to measure the effects of meteorological factors on cardiovascular mortality: heat index

Although many studies have examined the correlation between temperature and mortality from cardiovascular diseases (CVD), other meteorological factors, such as relative humidity, may modify the relationship. Yet the studies on this aspect are relatively few. We chose a heat index (HI, which is an index that combines air temperature and relative humidity) as an alternative indicator of temperature, and used a distributed lag nonlinear model (DLNM) to analyze the combined effects of temperature and relative humidity on CVD mortality among all of the Beijing residents and subsociodemographic groups by age, sex, and occupation. The heat index can better reflect the human-perceived temperature when relative humidity is combined with air temperature. The results show that females, elderly people, and outdoor workers have higher vulnerability levels in regard to a high heat index. The strongest effect of heat index was found among females, for which the highest mortality risk was about 2.4 (95% CI 1.8-3) times greater than the lowest mortality risk. In addition, we found that there is a significant interaction effect of temperature and relative humidity on CVD mortality. The impact of extreme high temperature may be exacerbated by increases in humidity. Based on these results, we draw the risk level map of CVD death under different temperatures and grades of relative humidity. These findings may aid governments in the development of more accurate heat alerts and the provision of measures to prevent or reduce temperature-related deaths.

Heatwave and health events: A systematic evaluation of different temperature indicators, heatwave intensities and durations

OBJECTIVES

Temperature observation time and type influenced the assessment of heat impact on mortality, and different health events may have different temperature thresholds beyond which these health events increase substantially. This study aimed to investigate whether temperature observation time and type influenced the assessment of heatwave impact on morbidity, to assess how heatwave duration modified heatwave impact on morbidity, and to examine whether there was a consistent temperature threshold beyond which five different types of health events increased sharply.

METHODS

Minutely air temperature data in Brisbane, Australia, were collected and converted into five daily temperature indicators observed at different time points or calculated using different approaches. Twenty-nine heatwave definitions for each temperature indicator were used to examine the effects of heatwaves on five health events (i.e., ambulance service uses, emergency department attendances (EDAs), hospitalizations, possible EDAs of heat and/or dehydration, and possible hospitalizations of heat and/or dehydration) by quasi-Poisson models.

RESULTS

Mean temperature was slightly better than maximum temperature in predicting heatwave impact on morbidity (P<0.05), and no appreciable difference in model performance was observed amongst different mean temperature indicators. Two-day-duration heatwaves were more detrimental than longer-lasting heatwaves when heatwave intensity was not high, and 97th percentile appeared to be a consistent temperature threshold for most heatwave-related health events (P<0.05).

CONCLUSIONS

It seems desirable in the development of heatwave definition and early warning systems to use mean temperature as an exposure indicator, and to adopt the 97th percentile of temperature as the trigger in Brisbane. Health sectors need to better prepare for short-lasting heatwaves.

Influences of socioeconomic vulnerability and intra-urban air pollution exposure on short-term mortality during extreme dust events

Air pollution has been shown to be significantly associated with morbidity and mortality in urban areas, but there is lack of studies focused on extreme pollution events such as extreme dust episodes in high-density Asian cities. However, such cities have had extreme climate episodes that could have adverse health implications for downwind areas. More importantly, few studies have comprehensively investigated the mortality risks of extreme dust events for socioeconomically vulnerable populations. This paper examined the association between air pollutants and mortality risk in Hong Kong from 2006 to 2010, with a case-crossover analysis, to determine the elevated risk after an extreme dust event in a high-density city. The results indicate that PM_10-2.5 dominated the all-cause mortality effect at the lag 0 day (OR: 1.074 [1.051, 1.098]). This study also found that people who were aged ≥ 65, economically inactive, or non-married had higher risks of all-cause mortality and cardiorespiratory mortality during days with extreme dust events. In addition, people who were in areas with higher air pollution had significantly higher risks of all-cause mortality and cardiorespiratory mortality. In conclusion, the results of this study can be used to target the vulnerable among a population or an area and the day(s) at risk to assist in health protocol development and emergency planning, as well as to develop early warnings for the general public in order to mitigate potential mortality risk for vulnerable population groups caused by extreme dust events.

Temporal changes in morality attributed to heat extremes for 57 cities in Northeast Asia

Recent studies have reported that heat-related mortality decreased by adaptation during decades. However, since the frequency of extreme heat events is increasing, it is difficult to conclude with certainty that the heat mortality burden is decreasing. To examine temporal changes in mortality attributed to heat extremes in Northeast Asia, we collected temperature and mortality data covering the years 1972-2012 from 57 cities of 3 countries (Taiwan, Korea, and Japan) in Northeast Asia. Poisson regression curves were fitted to the data from each city. The temporal changes in heat-mortality association were estimated with a time-varying distributed lag non-linear model. Heat extremes were defined as temperatures greater than the 97.5th percentiles of city-specific average temperatures. Attributable deaths were calculated considering temporal variations in exposure and relative risk. The estimates were then pooled through meta-analysis. The results show that the mortality risk on extreme heat days declined during the study period in all countries. However, as summer temperatures in Japan have shown more heat extremes over time, the mortality risk attributed to heat increased during 2003-2012 (0.32%) compared with 1972-1981 (0.19%). Thus, to assess the total health burden due to heat extremes related to climate change, public health strategies should focus on the temporal variation in heat-mortality association as well as changes in the distribution of heat extremes overtime.

Different response of human mortality to extreme temperatures (MoET) between rural and urban areas: A multi-scale study across China

BACKGROUND

The environmental variation in mortality due to extreme temperatures has been well-documented by many studies. Mortality to extreme temperatures (MoET) was recognized to vary geographically, either by countries within a region or by areas within a country. However, so far, little attention has been paid to rural residents, with even lesser attention on the potential rural-urban differences. The aim of our study was to offer a quite comprehensive analysis on the differences in temperature-mortality relationship between rural and urban areas across China.

METHOD

A distributed lag nonlinear model was built to describe the temperature-mortality relationship, based on the mortality data and meteorological variable of 75 communities in China from 2007 to 2012. Subsequently, a meta-analysis was applied to compare the differences in the temperature-mortality relationship between rural and urban areas at various levels.

RESULTS

Distinct responses regarding MoET between rural and urban areas were observed at different spatial scales. At regional level, more U-shaped curves were observed for temperature-mortality relationships in urban areas, while more J-shaped curves were observed in rural areas. At national scale, we found that the cold effect was stronger in rural areas (RR: rural 1.69 vs. urban 1.51), while heat effect was stronger in urban areas (RR: rural 1.01 vs. urban 1.12). Moreover, the modifying influence of air pollution on temperature-mortality relationship was found to be very limited.

CONCLUSION

The difference in response of MoET between rural and urban areas was noticeable, cold effect is more significant in China both in rural and urban areas. Additionally, urban areas in southern China and rural areas in northern China suffered more from extreme temperature events. Our findings suggest that differences in rural-urban responses to MoET should be taken seriously when intervention measures for reducing the risks to residents' health were adopted.

Ambient temperature and added heat wave effects on hospitalizations in California from 1999 to 2009

Investigators have examined how heat waves or incremental changes in temperature affect health outcomes, but few have examined both simultaneously. We utilized distributed lag nonlinear models (DLNM) to explore temperature associations and evaluate possible added heat wave effects on hospitalizations in 16 climate zones throughout California from May through October 1999-2009. We define heat waves as a period when daily mean temperatures were above the zone- and month-specific 95th percentile for at least two consecutive days. DLNMs were used to estimate climate zone-specific non-linear temperature and heat wave effects, which were then combined using random effects meta-analysis to produce an overall estimate for each. With higher temperatures, admissions for acute renal failure, appendicitis, dehydration, ischemic stroke, mental health, non-infectious enteritis, and primary diabetes were significantly increased, with added effects from heat waves observed for acute renal failure and dehydration. Higher temperatures also predicted statistically significant decreases in hypertension admissions, respiratory admissions, and respiratory diseases with secondary diagnoses of diabetes, though heat waves independently predicted an added increase in risk for both respiratory types. Our findings provide evidence that both heat wave and temperature exposures can exert effects independently.

Characterizing prolonged heat effects on mortality in a sub-tropical high-density city, Hong Kong

Extreme hot weather events are likely to increase under future climate change, and it is exacerbated in urban areas due to the complex urban settings. It causes excess mortality due to prolonged exposure to such extreme heat. However, there is lack of universal definition of prolonged heat or heat wave, which leads to inadequacies of associated risk preparedness. Previous studies focused on estimating temperature-mortality relationship based on temperature thresholds for assessing heat-related health risks but only several studies investigated the association between types of prolonged heat and excess mortality. However, most studies focused on one or a few isolated heat waves, which cannot demonstrate typical scenarios that population has experienced. In addition, there are limited studies on the difference between daytime and nighttime temperature, resulting in insufficiency to conclude the effect of prolonged heat. In sub-tropical high-density cities where prolonged heat is common in summer, it is important to obtain a comprehensive understanding of prolonged heat for a complete assessment of heat-related health risks. In this study, six types of prolonged heat were examined by using a time-stratified analysis. We found that more consecutive hot nights contribute to higher mortality risk while the number of consecutive hot days does not have significant association with excess mortality. For a day after five consecutive hot nights, there were 7.99% [7.64%, 8.35%], 7.74% [6.93%, 8.55%], and 8.14% [7.38%, 8.88%] increases in all-cause, cardiovascular, and respiratory mortality, respectively. Non-consecutive hot days or nights are also found to contribute to short-term mortality risk. For a 7-day-period with at least five non-consecutive hot days and nights, there was 15.61% [14.52%, 16.70%] increase in all-cause mortality at lag 0-1, but only -2.00% [-2.83%, -1.17%] at lag 2-3. Differences in the temperature-mortality relationship caused by hot days and hot nights imply the need to categorize prolonged heat for public health surveillance. Findings also contribute to potential improvement to existing heat-health warning system.

Ambient temperature and cardiovascular mortality: a systematic review and meta-analysis

INTRODUCTION

Our study aims at identifying and quantifying the relationship between the cold and heat exposure and the risk of cardiovascular mortality through a systematic review and meta-analysis.

MATERIAL AND METHODS

A systematic review and meta-analysis were conducted based on the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guideline. Peer-reviewed studies about the temperature and cardiovascular mortality were retrieved in the MEDLINE, Web of Science, and Scopus databases from January 2000 up to the end of 2015. The pooled effect sizes of short-term effect were calculated for the heat exposure and cold exposure separately. Also, we assessed the dose-response relationship of temperature-cardiovascular mortality by a change in units of latitudes, longitude, lag days and annual mean temperature by meta-regression.

RESULT

After screening the titles, abstracts and full texts, a total of 26 articles were included in the meta-analysis. The risk of cardiovascular mortality increased by 5% (RR, 1.055; 95% CI [1.050-1.060]) for the cold exposure and 1.3% (RR, 1.013; 95% CI [1.011-1.015]) for the heat exposure. The short-term effects of cold and heat exposure on the risk of cardiovascular mortality in males were 3.8% (RR, 1.038; 95% CI [1.034-1.043]) and 1.1%( RR, 1.011; 95% CI [1.009-1.013]) respectively. Moreover, the effects of cold and heat exposure on risk of cardiovascular mortality in females were 4.1% (RR, 1.041; 95% CI [1.037-1.045]) and 1.4% (RR, 1.014; 95% CI [1.011-1.017]) respectively. In the elderly, it was at an 8.1% increase and a 6% increase in the heat and cold exposure, respectively. The greatest risk of cardiovascular mortality in cold temperature was in the 14 lag days (RR, 1.09; 95% CI [1.07-1.010]) and in hot temperatures in the seven lag days (RR, 1.14; 95% CI [1.09-1.17]). The significant dose-response relationship of latitude and longitude in cold exposure with cardiovascular mortality was found. The results showed that the risk of cardiovascular mortality increased with each degree increased significantly in latitude and longitude in cold exposure (0.2%, 95% CI [0.006-0.035]) and (0.07%, 95% CI [0.0003-0.014]) respectively. The risk of cardiovascular mortality increased with each degree increase in latitude in heat exposure (0.07%, 95% CI [0.0008-0.124]).

CONCLUSION

Our findings indicate that the increase and decrease in ambient temperature had a relationship with the cardiovascular mortality. To prevent the temperature- related mortality, persons with cardiovascular disease and the elderly should be targeted. The review has been registered with PROSPERO (registration number CRD42016037673).

Seasonal association between ambient ozone and mortality in Zhengzhou, China

Different seasonal health effects of ambient ozone (O₃) have been reported in previous studies. This might be due to inappropriate adjustment of temperature in different seasons. We used daily data on non-accidental mortality and ambient air pollution in Zhengzhou from January 19, 2013 to June 30, 2015. Season-stratified analyses using generalized additive models were conducted to evaluate the seasonal associations with adjustment of temperature with different lagged days (lag0-1 for warm season, lag0-14 for cold season). We recorded a total of 70,443 non-accidental deaths in Zhengzhou during the study period. Significant associations were observed between ambient O₃ and mortality in cold season. Every 10-μg/m³ increment of 24-h O₃ of 1-day lagged time was associated with a 1.38% (95% CI 0.60, 2.16%) increase in all cause mortality, 1.35% (95% CI 0.41, 2.30%) increase in cardiovascular mortality, and 1.78% (95% CI 0.43, 3.14%) increase in respiratory mortality. Similar associations were observed when using daily 1- and 8-h maximum concentrations of O₃. No significant association was found during warm season. This study suggests a more pronounced ozone-mortality association in cold season in Zhengzhou, and we suggest that different lagged temperatures should be considered when examining the seasonal health effects of ambient ozone.