Exploring the effects of high temperature on mortality in four cities in the Philippines using various heat wave definitions in different mortality subgroups

• Main Authors: Xerxes T. Seposo (Author), Tran Ngoc Dang (Author), Yasushi Honda (Author)
• Format: Book
• Published: Taylor & Francis Group, 2017-01-01T00:00:00Z.
• Subjects: article
• Online Access: Connect to this object online.
• Notes: 1654-9880; 10.1080/16549716.2017.1368969
• Keywords: heat wave; philippines; dlnm; mortality sub-groups; tropical; Public aspects of medicine; RA1-1270
• Source: Global Health Action, Vol 10, Iss 1 (2017)

Background: Sustained high temperatures, specifically heat waves (HW), increase the risk of dying, especially among risk populations, which are highly vulnerable to its additional effect. In developing countries, there are only a few studies which focused on the magnitude of the risks attributed to HWs. Objectives: This study explored the HW effects using 15 HW definitions through the combination of duration (> 2, > 4, and > 7 consecutive days) and intensity (at the ≥ 90th, ≥ 95th, ≥ 97th, ≥ 98th, and ≥ 99th temperature percentiles). Methods: Daily mortality count data from 2006-2010 were obtained from the four tropical cities of the Philippines, and were further stratified by mortality sub-groups, such as cause of death, sex, and age. The same period of daily maximum temperature and relative humidity were also collected. We used a distributed lag non-linear model to determine the risks associated with the main temperature effects, as well as the added HW effects. Results: It has been observed that the main temperature effects comprise a substantial portion of the risks compared to the HW effects, even across the mortality sub-groups. Further stratification by the sub-groups showed significant HW effects among the young and male populations. Conclusions: Results of this study can be of use to improve (1) candidate HW definition identification/selection, and (2) risk population-specific strategies, taking into consideration the risk attributions.