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Abstract Background Global climate change is one of the most serious environmental issues faced by humanity, and the resultant change in frequency and intensity of heat waves and cold spells could increase mortality. The influence of temperature on human health could be immediate or delayed. Latitude, relative humidity, and air pollution may influence the temperature–mortality relationship. We studied the influence of temperature on mortality and its lag effect in four Chinese cities with a range of latitudes over 2008–2011, adjusting for relative humidity and air pollution. Methods We recorded the city-specific distributions of temperature and mortality by month and adopted a Poisson regression model combined with a distributed lag nonlinear model to investigate the lag effect of temperature on mortality. Results We found that the coldest months in the study area are December through March and the hottest months are June through September. The ratios of deaths during cold months to hot months were 1.43, 1.54, 1.37 and 1.12 for the cities of Wuhan, Changsha, Guilin and Haikou, respectively. The effects of extremely high temperatures generally persisted for 3 days, whereas the risk of extremely low temperatures could persist for 21 days. Compared with the optimum temperature of each city, at a lag of 21 days, the relative risks (95 % confidence interval) of extreme cold temperatures were 4.78 (3.63, 6.29), 2.38 (1.35, 4.19), 2.62 (1.15, 5.95) and 2.62 (1.44, 4.79) for Wuhan, Changsha, Guilin and Haikou, respectively. The respective risks were 1.35 (1.18, 1.55), 1.19 (0.96, 1.48), 1.22 (0.82, 1.82) and 2.47 (1.61, 3.78) for extreme hot temperatures, at a lag of 3 days. Conclusions Temperature–mortality relationships vary among cities at different latitudes. Local governments should establish regional prevention and protection measures to more effectively confront and adapt to local climate change. The effects of hot temperatures predominantly occur over the short term, whereas those of cold temperatures can persist for an extended number of days.

Background: Esophageal cancer is one of the most common cancers in rural China. The aim of this study was to describe the time trends of esophageal cancer mortality in rural China and to better elucidate the causes of these trends. Methods: The mortality data were obtained from the World Health Organization Mortality Database and the China Health Statistical Yearbook Database. The mortality data were analyzed with age-period-cohort (APC) analysis. Results: Our study indicates that the Age-Standardized Mortality Rates (ASMRs) in rural China generally decreased from 1989 to 2003, and thereafter increased until the year 2008 in both sexes. After 2008, the ASMRs decreased again. The results of APC analysis suggest that the general decrease in esophageal cancer mortality in rural China from 1989 to 2003 might be caused by the downtrend of the cohort effects and period effects, while the general increase in mortality from 2004 to 2008 might be caused by the uptrend of the period effects. The decrease in mortality after 2008 may be relevant to the Four Trillion RMB Investment Plan launched by the Chinese Government. Conclusions: The declining cohort effects were probably related to the improvement of socioeconomic status in childhood and the decreasing consumptions of alcohol drinking and smoking, while the trends of the period effects were relevant to the changes in the dietary pattern. Our findings may help predict future changes in esophageal cancer mortality.

To provide some useful information about the control of air pollution in China, we studied the spatial-temporal characteristics of air pollution in China from 2001–2014. First, we drew several line charts and histograms of the Air Pollution Index (API) and Air Quality Index (AQI) of 31 capital cities and municipalities to research the distribution across different times and cities; then, we researched the spatial clustering of API and AQI; finally, we examined the shift of the gravity center of API and AQI in different years and months. The API values had a decreasing trend: the high values had a clustering trend in some northern cities, and the low values had a clustering trend in some southern cities. The AQI values were relatively low, from 15:00–17:00 during the day. The gravity center of API had a trend of moving south from 2001–2003, then fluctuated in an unordered pattern and moved north in the winter. The AQI gravity center did not have a regular shift during different months. In conclusion, the government should take action to mitigate air pollution in some typical cities, as well as air pollution during the winter.