Based on Death Information and Using DLNM to Develop a Meteorological Health Index

Objectives  Exploring and establishing a meteorological health index to warn the risk of temperature on human health.

Methods  Using a Distributed Lag Non-linear Model (DLNM) to estimate the effect of temperature on non-accidental mortality in Guangzhou during 2011-2015. Classifying human health risks caused by temperature and estimating the risk level correspond to different temperature ranges.

Results  During the period of study (1 January 2011-31 December 2015), the mean temperature was 21.7℃, relative humidity was 78.6%, and the average number of daily non-accidental death was 132 cases. There was a U-shaped relationship between temperature and mortality in Guangzhou. Both low and high temperatures could cause an increase of death number, the influence of hot temperature was acute while the influence of cold was delayed by 3 days and persisted for longer days. The range of comfortable temperature was 19.4℃~25.4℃, its corresponding RR was 1.02~1.03. The relative risk (RR) of cold effect could be divided into three grades, 1.03~1.17, 1.17~1.31, and 1.32~1.46, and their corresponding temperature ranges were 12.9℃~19.3℃, 8.5℃~12.8℃ and 4.8℃~8.4℃, respectively. The relative risk (RR) of hot effect could be divided into three grades, 1.02~1.08, 1.08~1.13 and 1.13~1.19, and their corresponding temperature ranges were 25.5℃~27.8℃, 27.9℃~29.5℃ and 29.6℃~31.1℃, respectively.

Conclusions  The association between meteorological condition and daily mortality assessed by DLNM could reflect the health risk caused by temperature. It is reasonable to classify the health risk at equal intervals for early warning, which could provide a theoretical support for developing a meteorological health index forecasting service.