Characterizing the relationship between temperature and mortality in tropical and subtropical cities: a distributed lag non-linear model analysis in Hue, Viet Nam, 2009-2013

被引:41
作者
Dang, Tran Ngoc [1 ,2 ]
Seposo, Xerxes T. [1 ]
Nguyen Huu Chau Duc [3 ,4 ]
Thang, Tran Binh [5 ]
An, Do Dang [6 ]
Hang, Lai Thi Minh [7 ]
Long, Tran Thanh [7 ]
Loan, Bui Thi Hong [8 ]
Honda, Yasushi [9 ]
机构
[1] Univ Tsukuba, Dept Hlth Care Policy & Management, Grad Sch Comprehens Human Sci, Tsukuba, Ibaraki 3058577, Japan
[2] Univ Med & Pharm, Fac Publ Hlth, Dept Environm Hlth, Ho Chi Minh City, Vietnam
[3] Tokyo Med & Dent Univ, Grad Sch Med & Dent Sci, Dept Global Hlth Promot, Tokyo, Japan
[4] Hue Univ Med & Pharm, Dept Pediat, Hue City, Vietnam
[5] Hue Univ Med & Pharm, Inst Community Heath Res, Hue City, Vietnam
[6] Minist Hlth, Int Cooperat Dept, Hanoi, Vietnam
[7] Kagoshima Univ, Grad Sch Med & Dent Sci, Dept Epidemiol & Prevent Med, Kagoshima 890, Japan
[8] Univ Tsukuba, Dept Global Publ Hlth, Grad Sch Comprehens Human Sci, Tsukuba, Ibaraki 3058577, Japan
[9] Univ Tsukuba, Fac Hlth & Sport Sci, Tsukuba, Ibaraki 3058577, Japan
基金
新加坡国家研究基金会;
关键词
high temperature effects; low temperature effects; hot effects; cold effects; time-series regression; HIGH AMBIENT-TEMPERATURE; HEAT-RELATED MORTALITY; TIME-SERIES; AIR-POLLUTION; COLD; POPULATION; WEATHER; ENGLAND; DEATHS; STRESS;
D O I
10.3402/gha.v9.28738
中图分类号
R1 [预防医学、卫生学];
学科分类号
1004 ; 120402 ;
摘要
Background: The relationship between temperature and mortality has been found to be U-, V-, or J-shaped in developed temperate countries; however, in developing tropical/subtropical cities, it remains unclear. Objectives: Our goal was to investigate the relationship between temperature and mortality in Hue, a subtropical city in Viet Nam. Design: We collected daily mortality data from the Vietnamese A6 mortality reporting system for 6,214 deceased persons between 2009 and 2013. A distributed lag non-linear model was used to examine the temperature effects on all-cause and cause-specific mortality by assuming negative binomial distribution for count data. We developed an objective-oriented model selection with four steps following the Akaike information criterion (AIC) rule (i. e. a smaller AIC value indicates a better model). Results: High temperature-related mortality was more strongly associated with short lags, whereas low temperature-related mortality was more strongly associated with long lags. The low temperatures increased risk in all-category mortality compared to high temperatures. We observed elevated temperature-mortality risk in vulnerable groups: elderly people (high temperature effect, relative risk [RR] = 1.42, 95% confidence interval [CI] = 1.11-1.83; low temperature effect, RR = 2.0, 95% CI = 1.13-3.52), females (low temperature effect, RR = 2.19, 95% CI = 1.14-4.21), people with respiratory disease (high temperature effect, RR = 2.45, 95% CI = 0.91-6.63), and those with cardiovascular disease (high temperature effect, RR = 1.6, 95% CI = 1.15-2.22; low temperature effect, RR = 1.99, 95% CI = 0.92-4.28). Conclusions: In Hue, the temperature significantly increased the risk of mortality, especially in vulnerable groups (i. e. elderly, female, people with respiratory and cardiovascular diseases). These findings may provide a foundation for developing adequate policies to address the effects of temperature on health in Hue City.
引用
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页数:11
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