Is the association between temperature and mortality modified by age, gender and socio-economic status?

Yu, Weiwei; Vaneckova, Pavla; Mengersen, Kerrie; Pan, Xiaochuan; Tong, Shilu

doi:10.1016/j.scitotenv.2010.04.058

Cited by 159 publications

(103 citation statements)

References 43 publications

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“…16,17,21,26,35,[38][39][40] Additionally, climate change is likely to exacerbate the risk of heatwaves given the predicted increase in average temperatures in SEQ. 7,11,35 Hence, heatwave management certainly comprises an important task for stakeholders in SEQ to minimize potential heatwave impacts upon its population.…”

Section: Resultsmentioning

confidence: 99%

“…15 Such vulnerable groups include the elderly (particularly women), persons with chronic conditions and/or disabilities, persons in heat-exposed living conditions, the socially isolated, people living in culturally and linguistically diverse communities, and people engaged in strenuous physical activity outdoors. [16][17][18][19] Risk factors may also include housing characteristics, socioeconomic conditions or environmental impacts such as UHIEs. 18,20 To address increased risk of heatwave events, a number of cities globally have developed heatwave management plans and other adaptation measures to reduce associated health risks.…”

Section: Heatwave Managementmentioning

confidence: 99%

“…16,26,36,39 In the absence of adaptation measures, predicted population growth, temperature increases and an aging population could increase heat-related deaths in Brisbane from the current estimated 134 per year to over 1,000 deaths per year by 2050. www.landesbioscience.comData relating to relationships between ambient high temperatures, mortality and socio-demographic factors is relatively scarce for subtropical regions such as SEQ, and scholars have called for better identification of the region's most vulnerable groups during heatwave events. 17 Anecdotal evidence of previous heatwaves in SEQ indicates that many elderly people as well as other vulnerable groups were largely ignorant of the risks posed by heatwaves or of measures they could take to reduce risks, and that social isolation exacerbated vulnerabilities of many individuals. 41 A study by Loughnan et al found a significant correlation between adverse health impacts of heat in SEQ and the following: age (particularly for people aged over 65 years), need for assistance, accessibility to emergency services, urban design, aged care facilities, single-person households, population density, UHIE during night-time, and land cover.…”

Section: 29mentioning

confidence: 99%

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Managing health impacts of heat in South East Queensland, Australia

2014

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Heatwaves kill more people than any other natural hazard in Australia. Current literature on managing health risks of heatwaves highlights the importance of implementing urban planning measures, and engaging with vulnerable groups on a local level to better understand perceptions of risk and tailor health protection measures. This paper reviews arrangements to reduce heatwave health risks in South East Queensland in response to these themes. A literature search and document analysis, stakeholder interviews, and multi-stakeholder cross-sectoral workshops revealed that although heatwave management is not always considered by local government and disaster management stakeholders, many urban planning measures to minimize urban heat have been pursued. However, greater information from vulnerable groups is still needed to better inform heatwave management measures. IntroductionHeatwaves have been associated with increased morbidity, mortality and hospital admissions in many metropolitan regions globally, including the South East Queensland region (SEQ) in Australia.1-5 Climate change is projected to increase the frequency and severity of heatwave events in SEQ, along with an increase in mean and maximum temperatures. 6,7 This could have critical implications for human settlements in the region as urban areas are especially sensitive to heatwave events because of the urban heat island effect (UHIE), 8,a thereby exacerbating heat exposure for urban residents. This paper contributes to inform multi-scale heatwave management efforts by focusing on the example of SEQ. It draws on the findings of the Human Settlements component of the South East Queensland Climate Adaptation Research Initiative (SEQ-CARI), a 3-year integrated multi-sectoral study of climate change adaptation options for human settlements in SEQ, including urban planning and management, coastal management, physical infrastructure, emergency management and human health. To this end, the paper is structured in 3 parts. The first part presents the SEQCARI research approach followed by a literature review on heatwave management broadly. The second part presents background information on SEQ and investigates cross-sectoral ambivalences to heatwave management and risks based on document analysis, literature review and empirical data derived from stakeholder workshops and interviews. The paper concludes by providing insights that can inform the development of heat management measures under a changing climate. Research ApproachThe Human Settlements component of SEQCARI aimed to explore and develop a range of appropriate adaptation strategies, policies and practices in each sector and across sectors, for better governance and management in response to the impacts of climate change. The research project was specifically directed to the SEQ region due to the earlier recognition of this region as one of 6 climate change 'vulnerability hotspots' in Australia. 10 The region is particularly vulnerable because of its coastal location and the distribution and location of its...

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Section: Resultsmentioning

confidence: 99%

Section: Heatwave Managementmentioning

confidence: 99%

Section: 29mentioning

confidence: 99%

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Managing health impacts of heat in South East Queensland, Australia

2014

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“…The detailed GAM was as follows [35]: where Y t represents the number of daily CVD deaths on day t; T t denotes the daily mean temperature; τ H and τ C are the heat and cold temperature thresholds, respectively; s(.) denotes the smoothing splines function; x it denotes API and meteorological factors; time t refers to calendar time; z j represents DOW and public holidays; α is the intercept term; β C , β H , and δ j are coefficients; and ε t is the residual [39].…”

Section: Discussionmentioning

confidence: 99%

Temperature and Cardiovascular Mortality Associations in Four Southern Chinese Cities: A Time-Series Study Using a Distributed Lag Non-Linear Model

Huang

Tan²,

2017

Sustainability

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Abstract:Few studies on population-specific health effects of extreme temperature on cardiovascular diseases (CVDs) deaths have been conducted in the subtropical and tropical climates of China. We examined the association between extreme temperature and CVD across four cities in China. We performed a two-stage analysis; we generated city-specific estimates using a distributed lag non-linear model (DLNM) and estimated the overall effects by conducting a meta-analysis. Heat thresholds of 29 • C, 29 • C, 29 • C, and 30 • C and cold thresholds of 6 • C, 10 • C, 14 • C, and 15 • C were observed in Hefei, Changsha, Nanning, and Haikou, respectively. The lag periods for heat-related CVD mortality were observed only for 0-2 days, while those of cold-related CVD mortality were observed for 10-15 days. The meta-analysis showed that a 1 • C increase above the city-specific heat threshold was associated with average overall CVD mortality increases of 4.6% (3.0%-6.2%), 6.4% (3.4%-9.4%), and 0.2% (−4.8%-5.2%) for all ages, ≥65 years, and <65 years over a lag period of 0-2 days, respectively. Similarly, a 1 • C decrease below the city-specific cold threshold was associated with average overall CVD mortality increases of 4.2% (3.0%-5.4%), 4.9% (3.5%-6.3%), and 3.1% (1.7%-4.5%), for all ages, ≥65 years, and <65 years over a lag period of 0-15 days, respectively. This work will help to take appropriate measures to reduce temperature-mortality risk in different populations in the subtropical and tropical climates of China.

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“…The apparent temperature range was selected based on visual inspection of the plots (20)(21)(22) . The temperature corresponding to the model with the lowest AIC value was chosen as the threshold temperature.…”

Section: Modelmentioning

confidence: 99%

Time Course of Apparent Temperature Effects on Cardiovascular Mortality: A Comparative Study of Beijing, China and Brisbane, Australia

Sun¹,

Li²,

Jayasinghe³

et al. 2012

PHR

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This comparative study aimed to clarify the different characteristics of time course of apparent temperature and their effect on cardiovascular mortality in Beijing, China, and Brisbane, Australia. The present study used polynomial distributed lag models to explore the lagged effects of apparent temperature on daily cardiovascular mortality up to 27 days in Beijing, China (2005-2009), and Brisbane, Australia (2004. The results show a longer lagged effect on cold days and a shorter lagged effect on hot days. The cut-off points in Beijing and Brisbane were 22℃ and 27℃, respectively. In Beijing, a statistically significant association was observed for lags of 0-3 days and lags of 3-18 days on hot and cold days, respectively. In Brisbane, a significant association was found for lags of 3-4 days and lags of 10-21 days on hot and cold days, respectively. The lagged effects extended longer for cold apparent temperature but were immediate for hot apparent temperature. Though the cut-off point in Brisbane was higher than in Beijing, the population in Beijing was more resistant to high temperature above the cut-off point than the population in Brisbane.

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Is the association between temperature and mortality modified by age, gender and socio-economic status?

Cited by 159 publications

References 43 publications

Managing health impacts of heat in South East Queensland, Australia

Managing health impacts of heat in South East Queensland, Australia

Temperature and Cardiovascular Mortality Associations in Four Southern Chinese Cities: A Time-Series Study Using a Distributed Lag Non-Linear Model

Time Course of Apparent Temperature Effects on Cardiovascular Mortality: A Comparative Study of Beijing, China and Brisbane, Australia

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