Objective To investigate the prevalence and relative factors of cognitive disfunction among the community- dwelling old adults. Methods 766 participants over 60 years old dwelling in Luzhou, Sichuan, China were enrolled with Multi-stage stratified sampling. Information about sociodemographic characteristics, lifestyle, health condition, nutrition were interviewed, and their cognitive function was evaluated with Mini-Mental State Examination (MMSE). Results The prevalence of cognitive disfunction was 19.7% among them. Gender (male vs. female, OR=0.577), age (over 90 years vs. 60- 64 years, OR=29.857), administrator (administrator vs. not administrator, OR= 0.360), farmer (farmer vs. not farmer, OR=2.121), nutrition (malnutrition vs. eutrophia, OR=2.460), body weight (underweight vs. normal weight, OR=3.222), living status (UN-Habitat vs. living alone, OR=0.658), marital status (widowed vs. not widowed, OR=2.208), education attainment (junior college vs. illiteracy, OR=0.328), income (over 1000 yuan vs. no income, OR=0.596) significantly related with cognitive disfunction (P<0.05). Multiple Logistic regression analysis showed that old age, occupation (farmer) and malnutrition were independent risk factors for cognitive disfunction. Conclusion The cognitive disfunction related with multi-factors, and need more effective and available intervention in the old adults.

BACKGROUND: There are few multi-city studies on the association between temperature and mortality in basin climates. This study was based on the Sichuan Basin in southwest China to assess the association of basin temperature with non-accidental mortality in the population and with the temperature-related mortality burden. METHODS: Daily mortality data, meteorological and air pollution data were collected for four cities in the Sichuan Basin of southwest China. We used a two-stage time-series analysis to quantify the association between temperature and non-accidental mortality in each city, and a multivariate meta-analysis was performed to obtain the overall cumulative risk. The attributable fractions (AFs) were calculated to access the mortality burden attributable to non-optimal temperature. Additionally, we performed a stratified analyses by gender, age group, education level, and marital status. RESULTS: A total of 751,930 non-accidental deaths were collected in our study. Overall, 10.16% of non-accidental deaths could be attributed to non-optimal temperatures. A majority of temperature-related non-accidental deaths were caused by low temperature, accounting for 9.10% (95% eCI: 5.50%, 12.19%), and heat effects accounted for only 1.06% (95% eCI: 0.76%, 1.33%). The mortality burden attributable to non-optimal temperatures was higher among those under 65 years old, females, those with a low education level, and those with an alternative marriage status. CONCLUSIONS Our study suggested that a significant association between non-optimal temperature and non-accidental mortality. Those under 65 years old, females, and those with a low educational level or alternative marriage status had the highest attributable burden.
Female ; Humans ; China/epidemiology* ; Cities ; Cold Temperature ; Hot Temperature ; Mortality ; Temperature ; Time Factors ; Middle Aged ; Male