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

• Main Authors: Tran Ngoc Dang (Author), Xerxes T. Seposo (Author), Nguyen Huu Chau Duc (Author), Tran Binh Thang (Author), Do Dang An (Author), Lai Thi Minh Hang (Author), Tran Thanh Long (Author), Bui Thi Hong Loan (Author), Yasushi Honda (Author)
• Format: Book
• Published: Taylor & Francis Group, 2016-01-01T00:00:00Z.
• Subjects: article
• Online Access: Connect to this object online.
• Notes: 1654-9880; 10.3402/gha.v9.28738
• Keywords: high temperature effects; low temperature effects; hot effects; cold effects; time-series regression; Public aspects of medicine; RA1-1270
• Source: Global Health Action, Vol 9, Iss 0, Pp 1-11 (2016)

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.