OBJECTIVETo explore the impact of the socio-economic factors on the temperature-mortality association in different cities in southern China.

METHODSDaily mortality registration data, meteorological data and air pollution data of the cities as Changsha and Kunming during 2006-2009, and cities as Guangzhou and Zhuhai during 2006-2010, were collected to explore modifying effects, stratified by age, gender, education and place of death, of socio-economic factors on the association between temperature and mortality, by distributed lag non-linear model. The accumulative effect of temperature-mortality were separately analyzed in each city, under the high temperature (0-3 days) and low temperature (0-20 days) situation. The association between temperature and mortality was evaluated by general linear threshold model. The above process was firstly adopted to analyze the impact in single city and then Meta analysis was applied to analyze the impact in several cities by effect-combine.

RESULTSThe relationship between temperature and mortality in the four cities showed nonlinearity. The minimum mortality risk was separately 23.5 °C, 20.5 °C, 25.0 °C and 26.0 °C in Changsha, Kunming, Guangzhou and Zhuhai. The results of effect-combine showed that low-temperature (RR = 1.67, 95%CI:1.54-1.80) has a higher gross effect than high-temperature (RR = 1.11, 95%CI:1.01-1.18) on population. With the age increasing, risk of death increased both under high and low temperature situation, and the effect of low temperature was greater (RR = 1.83, 95%CI:1.65-2.04) for the elderly than it of high temperature (RR = 1.17, 95%CI:1.03-1.33). The mortality risk among females (cold and hot effects(95%CI) were 1.75(1.57-1.97) and 1.11(0.99-1.25), respectively)was higher than it among males (cold and hot effects(95%CI) were 1.59(1.45-1.77) and 1.11(1.03-1.19), respectively). Whereas the mortality risk on higher education population was significantly higher (cold and hot effects (95%CI) were 1.89(1.48-2.45)and 1.34(1.19-1.48), respectively) than it on other educated people.

CONCLUSIONAge, gender, educational level and place of death showed modifying effects on the association between temperature and mortality. The elderly, women and highly educated people were vulnerable to the temperature influence on mortality.

Aged ; Air Pollution ; China ; Cold Temperature ; adverse effects ; Female ; Hot Temperature ; adverse effects ; Humans ; Male ; Mortality ; Nonlinear Dynamics ; Risk ; Socioeconomic Factors

OBJECTIVETo evaluate the impacts of air temperature on years of life lost (YLL) among the residents in Guangzhou and Zhuhai, Guangdong province.

METHODSDaily mortality and meteorology data in Guangzhou and Zhuhai were collected, and distributed lag non-linear model (DLNM) was used to evaluate the cumulative and delayed effects of daily air temperature on YLL of total non-accident mortality. The accumulative effect of air temperature on mortality under the extreme high temperature (0-1 days) and extreme low temperature (0-13 days) situation in Guangzhou and Zhuhai were analyzed respectively.

RESULTSThe average YLL was 1 928.0 in Guangzhou and 202.5 in Zhuhai. The exposure-response functions seemed to be non-linear. The hot effect seemed to be acute and reached the peak at the same day, while the cold effect reached the peak at 5(th) days and lasted for about two weeks. Low temperature had stronger gross effect than high temperature had. The cold effect among males was greater than that among females in Guangzhou. The hot/cold effect on YLL was greater in people aged ≥ 65 years than in people aged < 65 years and in people suffering from respiratory disease than in people suffering from cardiovascular disease in both Guangzhou and Zhuhai.

CONCLUSIONThe effects of high and low temperatures on YLL were obvious, and the impact of low temperature was greater. The elderly and people suffering from respiratory disease or cardiovascular disease are the vulnerable populations.

Aged ; Air ; Cardiovascular Diseases ; epidemiology ; China ; epidemiology ; Extreme Cold ; adverse effects ; Extreme Heat ; adverse effects ; Female ; Humans ; Male ; Middle Aged ; Mortality, Premature ; Nonlinear Dynamics ; Respiratory Tract Diseases ; epidemiology ; Time Factors