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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

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      BackgroundThe 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.ObjectivesOur goal was to investigate the relationship between temperature and mortality in Hue, a subtropical city in Viet Nam.DesignWe 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).ResultsHigh 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).ConclusionsIn 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.

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      Most cited references 43

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      Weather-related mortality: how heat, cold, and heat waves affect mortality in the United States.

      Many studies have linked weather to mortality; however, role of such critical factors as regional variation, susceptible populations, and acclimatization remain unresolved. We applied time-series models to 107 US communities allowing a nonlinear relationship between temperature and mortality by using a 14-year dataset. Second-stage analysis was used to relate cold, heat, and heat wave effect estimates to community-specific variables. We considered exposure timeframe, susceptibility, age, cause of death, and confounding from pollutants. Heat waves were modeled with varying intensity and duration. Heat-related mortality was most associated with a shorter lag (average of same day and previous day), with an overall increase of 3.0% (95% posterior interval: 2.4%-3.6%) in mortality risk comparing the 99th and 90th percentile temperatures for the community. Cold-related mortality was most associated with a longer lag (average of current day up to 25 days previous), with a 4.2% (3.2%-5.3%) increase in risk comparing the first and 10th percentile temperatures for the community. Mortality risk increased with the intensity or duration of heat waves. Spatial heterogeneity in effects indicates that weather-mortality relationships from 1 community may not be applicable in another. Larger spatial heterogeneity for absolute temperature estimates (comparing risk at specific temperatures) than for relative temperature estimates (comparing risk at community-specific temperature percentiles) provides evidence for acclimatization. We identified susceptibility based on age, socioeconomic conditions, urbanicity, and central air conditioning. Acclimatization, individual susceptibility, and community characteristics all affect heat-related effects on mortality.
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        Distributed lag non-linear models

        Environmental stressors often show effects that are delayed in time, requiring the use of statistical models that are flexible enough to describe the additional time dimension of the exposure–response relationship. Here we develop the family of distributed lag non-linear models (DLNM), a modelling framework that can simultaneously represent non-linear exposure–response dependencies and delayed effects. This methodology is based on the definition of a ‘cross-basis’, a bi-dimensional space of functions that describes simultaneously the shape of the relationship along both the space of the predictor and the lag dimension of its occurrence. In this way the approach provides a unified framework for a range of models that have previously been used in this setting, and new more flexible variants. This family of models is implemented in the package dlnm within the statistical environment R. To illustrate the methodology we use examples of DLNMs to represent the relationship between temperature and mortality, using data from the National Morbidity, Mortality, and Air Pollution Study (NMMAPS) for New York during the period 1987–2000. Copyright © 2010 John Wiley & Sons, Ltd.
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          High ambient temperature and mortality: a review of epidemiologic studies from 2001 to 2008

           Rupa Basu (2009)
          Background This review examines recent evidence on mortality from elevated ambient temperature for studies published from January 2001 to December 2008. Methods PubMed was used to search for the following keywords: temperature, apparent temperature, heat, heat index, and mortality. The search was limited to the English language and epidemiologic studies. Studies that reported mortality counts or excess deaths following heat waves were excluded so that the focus remained on general ambient temperature and mortality in a variety of locations. Studies focusing on cold temperature effects were also excluded. Results Thirty-six total studies were presented in three tables: 1) elevated ambient temperature and mortality; 2) air pollutants as confounders and/or effect modifiers of the elevated ambient temperature and mortality association; and 3) vulnerable subgroups of the elevated ambient temperature-mortality association. The evidence suggests that particulate matter with less than 10 um in aerodynamic diameter and ozone may confound the association, while ozone was an effect modifier in the warmer months in some locations. Nonetheless, the independent effect of temperature and mortality was withheld. Elevated temperature was associated with increased risk for those dying from cardiovascular, respiratory, cerebrovascular, and some specific cardiovascular diseases, such as ischemic heart disease, congestive heart failure, and myocardial infarction. Vulnerable subgroups also included: Black racial/ethnic group, women, those with lower socioeconomic status, and several age groups, particularly the elderly over 65 years of age as well as infants and young children. Conclusion Many of these outcomes and vulnerable subgroups have only been identified in recent studies and varied by location and study population. Thus, region-specific policies, especially in urban areas, are vital to the mitigation of heat-related deaths.

            Author and article information

            [1 ]Department of Health Care Policy and Management, Graduate School of Comprehensive Human Sciences, University of Tsukuba, Tsukuba, Japan
            [2 ]Department of Environmental Health, Faculty of Public Health, University of Medicine and Pharmacy, Ho Chi Minh City, Viet Nam
            [3 ]Department of Global Health Promotion, Graduate School of Medical and Dental Sciences, Tokyo Medical and Dental University, Tokyo, Japan
            [4 ]Department of Pediatrics, Hue University of Medicine and Pharmacy, Hue City, Viet Nam
            [5 ]Institute for Community Heath Research, Hue University of Medicine and Pharmacy, Hue City, Viet Nam
            [6 ]Department of International Cooperation, Ministry of Health, Hanoi, Viet Nam
            [7 ]Department of Epidemiology and Preventive Medicine, Graduate School of Medical and Dental Sciences, University of Kagoshima, Kagoshima, Japan
            [8 ]Department of Global Public Health, Graduate School of Comprehensive Human Sciences, University of Tsukuba, Tsukuba, Japan
            [9 ]Faculty of Health and Sport Sciences, University of Tsukuba, Tsukuba, Japan
            Author notes
            [* ]Correspondence to: Tran Ngoc Dang, Health Care Policy and Management Laboratory, University of Tsukuba, Building D, Room 742,1-1-1 Tennoudai, Tsukuba, Ibaraki, 305-8577, Japan, Email: ngocdangytcc@

            Responsible Editor: Heiko Becher, University Medical Center Hamburg-Eppendorf, Germany.

            Glob Health Action
            Glob Health Action
            Global Health Action
            Co-Action Publishing
            13 January 2016
            : 9
            © 2016 Tran Ngoc Dang et al.

            This is an Open Access article distributed under the terms of the Creative Commons Attribution 4.0 International License, allowing third parties to copy and redistribute the material in any medium or format and to remix, transform, and build upon the material for any purpose, even commercially, provided the original work is properly cited and states its license.

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