Daily temperature and mortality: a study of distributed lag non-linear effect and effect modification in Guangzhou

Yang, Jun; Chen, Ou; Ding, Yan; Zhou, Ying-Xue; Chen, Pingyan

doi:10.1186/1476-069x-11-63

Cited by 205 publications

(150 citation statements)

References 37 publications

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“…We found that the temperature-mortality relationships were non-linear for four types of mortality. Consistent with previous studies on temperature-mortality (Lin et al 2011;Yang et al 2012;Wu et al 2013), we also found that high and low temperature were associated with increased mortality in subtropical areas of China. Significant associations between cold temperatures and mortality appeared after 3 days and lasted longer than the associations between high temperatures and mortality, which were acute and of short duration.…”

Section: Discussionsupporting

confidence: 92%

Effects of temperature on mortality in Hong Kong: a time series analysis

Chan

2014

Int J Biometeorol

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Although interest in assessing the impacts of hot temperature and mortality in Hong Kong has increased, less evidence on the effect of cold temperature on mortality is available. We examined both the effects of heat and cold temperatures on daily mortality in Hong Kong for the last decade (2002)(2003)(2004)(2005)(2006)(2007)(2008)(2009)(2010)(2011). A quasi-Poisson model combined with a distributed lag non-linear model was used to assess the non-linear and delayed effects of temperatures on cause-specific and age-specific mortality.Non-linear effects of temperature on mortality were identified. The relative risk of non-accidental mortality associated with cold temperature (11.1°C, 1 st percentile of temperature) relative to 19.4°C(25 th percentile of temperature) was 1.17 (95% confidence interval (CI): 1.04, 1.29) for lags 0-13. The relative risk of non-accidental mortality associated with high temperature (31.5°C, 99 th percentile of temperature) relative to 27.8°C (75 th percentile of temperature) was 1.09 (95% CI: 1.03, 1.17) for lags 0-3. In Hong Kong, extreme cold and hot temperatures increased the risk of mortality. The effect of cold lasted longer and greater than that of heat. People older than 75 years were the most vulnerable group to cold temperature, while people aged 65-74 were the most vulnerable group to hot temperature.Our findings may have implications for developing intervention strategies for extreme cold and hot temperatures.

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Section: Discussionsupporting

confidence: 92%

Effects of temperature on mortality in Hong Kong: a time series analysis

Chan

2014

Int J Biometeorol

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“…Some previous studies have suggested that temperature effects on health outcomes are generally robust or even independent of air pollution (Anderson and Bell 2009;Yang et al 2012), but others have found interactive or synergistic effects between temperature and air pollution leading to some sort of hyper-additive mortality effect in Europe (Keatinge et al 2000;Burkart et al 2013) and the United States (Ren et al 2008). Table 4 displays the comparison of extreme temperature effects with and without pollutions in our study, indicating that air pollution could aggravate the extreme cold-related CVD mortality risk (increased from 2.20 to 2.35 when considering the impact of air pollution) but does not have significant Mortality risk at the 99th percentile of temperature relative to that at the MMT, with the 0-3 days' lag impact on the extreme heat-related mortality risk (1.45 vs. 1.46 for relative mortality risk without and with consideration of air pollution).…”

Section: Limitations and Implicationsmentioning

confidence: 99%

“…This document identifies and characterizes related risks in urban areas, particularly public health risks; the health risks from extreme temperature events are considered an especially important task for climate action planning (NDRC 2016). Existing studies have examined temperature-mortality relationships according to different study objectives; some have focused on a single city (Guo et al 2011;Yang et al 2012;Chen et al 2015), and others have concentrated on special climatic or geographic zones (Curriero et al 2002;Li et al 2014;Gao et al 2015;. But few studies have examined the issue in city clusters.…”

Section: Introductionmentioning

confidence: 99%

“…As the world is increasingly urbanized, the twentyfirst century agenda would have to focus on greatly reducing vulnerabilities of people and infrastructure in urban areas to the impacts of a changing climate (IPCC 2014). Due to their dense population and significant economic status, cities have become hot spots of health risk caused by extreme temperature events (Yang et al 2012;Chen et al 2015).…”

Section: Introductionmentioning

confidence: 99%

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Different Mortality Effects of Extreme Temperature Stress in Three Large City Clusters of Northern and Southern China

Zhang

Wang

et al. 2017

Int J Disaster Risk Sci

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Extreme temperature events have affected Chinese city residents more frequently and intensively since the early 2000s, but few studies have identified the impacts of extreme temperature on mortality in different city clusters of China. This study first used a distributed lag, nonlinear model to estimate the county/district-specific effects of extreme temperature on nonaccidental and cardiovascular mortality. The authors then applied a multivariate meta-analysis to pool the estimated effects in order to derive regional temperature-mortality relationship in three large city clusters-the Beijing-Tianjin-Hebei (BTH) region, the Yangtze River Delta (YRD), and the Pearl River Delta (PRD), which represent northern and southern regions. With 0-3 days' lag, the strongest heat-related mortality effect was observed in the BTH region (with relative risk (RR) of 1.29; 95% confidence interval (CI): 1.13-1.47), followed by the YRD (RR = 1.25; 95% CI: 1.13-1.35) and the PRD (RR = 1.14; 95% CI: 1.01-1.28) areas. With 0-21 days' lag, the cold effect was pronounced in all city clusters, with the highest extreme cold-related mortality risk found in the PRD area (RR = 2.27; 95% CI: 1.63-3.16), followed by the YRD area (RR = 1.85; 95% CI: 1.56-2.20) and BTH region (RR = 1.33; 95% CI: 0.96-1.83). People in the southern regions tended to be more vulnerable to cold stress, but the northern population was more sensitive to heat stress. By examining the effects of extreme temperature in city clusters of different regions, our findings underline the role of adaptation towards heat and cold, which has important implications for public health policy making and practice.

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“…In contrast, studies of temperature-related CVD mortality in China are lacking and typically focus on northern China [17,18]. For southern China, only some large cities have been studied, such as Changsha, Kunming, Guangzhou, and Zhuhai [19][20][21][22][23]. Furthermore, these studies mainly focused on the impact of temperature on total mortality not the CVD mortality.…”

Section: Introductionmentioning

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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Daily temperature and mortality: a study of distributed lag non-linear effect and effect modification in Guangzhou

Cited by 205 publications

References 37 publications

Effects of temperature on mortality in Hong Kong: a time series analysis

Effects of temperature on mortality in Hong Kong: a time series analysis

Different Mortality Effects of Extreme Temperature Stress in Three Large City Clusters of Northern and Southern China

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

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