BackgroundPM2.5 has become a major component of air pollution in China and has led to a series of health problems. The mortality rate caused by lung cancer has reached the point where it cannot be ignored in China. Air pollution is becoming more and more serious in China, which is increasingly affecting people’s lives and health.MethodsConsidering the variations in the geographical environment in China, this paper studied the relationship between PM2.5 concentration and lung cancer mortality based on the geographical weighted regression model in 31 provinces in 2004 and 2008, autonomous regions and municipalities of China.ResultsThe results indicated there was a significant positive correlation between PM2.5 concentration and lung cancer mortality (r = 0.0052, P = 0.036). Additionally, the longer the time of exposure to PM2.5 is, the higher morbidity is.ConclusionIt is suggested that the Chinese government should launch some environmental policy, especially in those areas with severe PM2.5 pollutions, and keep the citizens away from exposure to PM2.5 pollution in the long term.
By retrieving literature published from 2005 to 2015 from Chinese National Knowledge Infrastructure, Wanfang, Vip, PubMed, and Web of Science, we filtered out studies using the Children's Depression Inventory only and compared left-behind children and non-left-behind children. The methodological quality of the papers was evaluated using the Newcastle-Ottawa Scale. Finally, we included six studies to carry out a meta-analysis. The results showed that the Children's Depression Inventory scores of left-behind children are significantly higher than those of non-left-behind children (standardized mean difference: -0.233, 95% confidence interval: -0.036 to -0.430, p < 0.05).
BackgroundWhether smoking accelerates memory recession has been a topic of significant research. However, randomised controlled trials are not easy to carry out, and does not comply with the ethics of research. And observation method which based on the most readily observed data is easy to draw the wrong conclusions without adjustment. The memory difference between smokers and non-smokers may not really represent the real differences between their memories.MethodsIn response to these limitations, we adopt propensity score method to match the samples and solve the estimated selection bias and confounding bias on elderlies aged 60 years and over based on Chinese Longitudinal Healthy Longevity Survey (2011) data. The respondents are divided into non-smokers, people who used to smoke but not now, and people who used to smoke and still now. To balance the similarity between different groups on their propensity score weighted distributions of pretreatment covariates, we use generalized boosted models to estimate the multiply treatment propensity scores.ResultsThe results show that compared with non-smokers, people who used to smoke and still now respectively have a decrease 0.0283, 0.0735, 0.0091 on self-evaluation memory, daily living activities, and cognitive function. People who used to smoke but not now have a decrease 0.0224 on daily living activities, while have an increase 0.0054 and 0.0104 on self-evaluation memory, and cognitive function.ConclusionThe PSM has considerable utility to control pre-treatment imbalances on observed covariates in non-randomised or observational data.
We used the Geriatric Depression Scale to investigate the depression status of empty nesters living in eastern rural China (N = 967). The results showed that more than half of the participants suffered relatively severe depression and that their mental health was not favorable. Gender, age, level of education, and marital status had a significant influence on depression status. The degree of depression of men was lower than that of women. As participants’ age increased, the degree of depression first rose until the age of 84 and then fell thereafter. The depression of unmarried empty nesters was relatively severe compared to that of married ones. Finally, a higher level of education corresponded with a lower degree of depression. There are varied factors affecting the psychological status of empty nesters in China. To improve their mental state, the government, society, and family need to collaborate and take comprehensive measures.
We analyzed depression in Chinese civil servants, using the Hamilton Depression Rating Scale (HAMD) and a survey completed by people employed by the Civil Service in 6 cities in eastern China. The results showed that the HAMD is a valid and effective measure for assessing depression in Chinese civil servants. As we had assumed, Chinese civil servants manifested a strong sense of despair, which was consistent between the genders. In general, however, depression had a greater impact on female than on male civil servants. In the linear regression model with demographic variables as independent variables, we found that gender, education level, and marital status were significant predictive factors of depression, but income and age were not. We suggest that although civil servants may enjoy a more lucrative job and a better material lifestyle compared to other people in China, the issue of their mental health merits attention.
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