Background: Tumor necrosis factor alpha (TNF-α) plays a key role in the containment of tuberculosis. The relationship between the TNF -238G/A polymorphism and tuberculosis susceptibility remains inconclusive. A comprehensive meta-analysis was made to provide a more precise estimate of the relationship between them. Methods: Multiple search strategies were used. A fixed effect model was takentook to estimate pooled OR with 95% confidence interval (CI) for the association between the TNF -238G/A polymorphism and tuberculosis susceptibility. The Chi-squared-based Q-test and I-squaredI ² statistic were calculated to examine heterogeneity. Begg’s funnel plot and Egger’s test were used to assess publication bias. Results: 9 case-control studies were included in this meta-analysis. No significant heterogeneity was demonstrated, and no obvious publication bias was detected among the included studies. The meta-analysis indicated that there was no significant association between the TNF -238G/A polymorphism and tuberculosis susceptibility (GA+AA versus GG model: OR=1.005, 95% CI: 0.765-1.319; A versus G model: OR=1.000, 95% CI: 0.769-1.300). In the subgroup analyses by ethnicity, types of TB and human immunodeficiency virus (HIV) status, no significant association were identified. Conclusions: The meta-analysis involving 2723 subjects did not detect any association between the TNF -238G/A polymorphism and tuberculosis susceptibility.

In many countries the frequency of eating out has steadily increased over the last few decades, and this behavioris often associated with unhealthy dietary patterns. This study aimed to describe the levels of knowledge, attitude, and behaviors (KAB) related to eating out among university students. A cross-sectional study was conducted in the college town in Chongqing, China with a total of 1634 participants. The mean eating out related KAB scores were: knowledge 11.5 ± 2.9, attitude 17.0 ± 2.8, and behaviors 24.2 ± 4.8 (possible total scores: 20, 24, 40 respectively). As the level of knowledge increased, the percentage of highly satisfactory attitude and behaviors increased. Only 10% of the participants did not eat out for lunch and dinner during weekends in the last month. Gender, ethnicity, mother’s education, monthly boarding expenses, living place during the study, and the frequency of eating out for breakfast were statistically associated with the scores of KAB. In conclusion, Chinese junior students had poor knowledge of and behaviors towards eating out and ate out frequently. Educational interventionsto improve knowledge related eating out are needed in order to promote healthy eating out behaviors among Chinese university students.

Background: The volume of alcohol intake and type of alcohol affect Chinese men’s health. This study investigated changes of alcohol type between 2004 and 2011, explored the trend of change in alcohol type with age and determined the social demographic factors influencing the alcohol intake of Chinese men. Methods: Research data originated from the public database, China Health and Nutrition Survey (CHNS). Three chi-square tests were used to determine the prevalence of different alcohol types (beer, wine and liqueur) and the trend with age among male drinkers from 2004 to 2011. An ordered logistic regression model was established with alcohol intake as the dependent variable and social demography as the independent variable to analyze the influence of these factors on male alcohol intake. Results: This study confirmed that from 2004 to 2011, 70.1% of Chinese men consumed alcohol less than 168 g/w. The popularity of beer was on the rise, while the liqueur alcohol consumption decreased from 2004 to 2011 and the consumption of wine began to rise rapidly after 2006 (p < 0.05 for all). The prevalence of liqueur drinking increased with age and the prevalence of beer drinking decreased with age among Chinese male drinkers (p < 0.05 for all). From 2004 to 2011, a positive correlation appeared between age and male alcohol intake (p < 0.05 for all). In 2004 (OR = 1.22, 95% CI: 1.03–1.44), 2006 (OR = 1.21, 95% CI: 1.02–1.42) and 2011 (OR = 1.51, 95% CI: 1.31–1.75), Chinese men living in rural areas had a high volume of alcohol intake. From 2004 to 2011, the participants had married consumed more alcohol (p < 0.05 for all). In 2004 (OR = 0.61, 95% CI: 0.43–0.88) and 2011 (OR = 0.80, 95% CI: 0.68–0.94), higher education levels were negatively correlated with male alcohol intake. In 2006 (OR = 1.29, 95% CI: 1.07–1.56), 2009 (OR = 1.76, 95% CI: 1.45–2.14) and 2011 (OR = 1.35, 95% CI: 1.13–1.61), male drinkers who were working consumed more alcohol. From 2004 to 2011, a significant positive correlation appeared between tobacco consumption and alcohol intake (p < 0.05 for all). Conclusion: Consumption of three types of alcohol (beer, wine and liqueur) varies with the year. Beer consumption decreases with age, whereas liqueur consumption increases with age. Social demographic factors, such as residence, age, highest education level, working status and tobacco consumption, are related to alcohol intake. Our study affirms the effect of age on the choice of different types of alcohol.

Finding ways to reduce tobacco and alcohol consumption among adolescents has been a major public health challenge in China. In relation to this issue, the current study evaluated the changes in the sociodemographic factors of tobacco and alcohol consumption among Chinese adolescents who are 12–18 years old. Trends in sociodemographic factors associated with tobacco and alcohol consumption were investigated based on the 2004–2011 China Health and Nutrition Survey data. Questionnaires that extracted data on tobacco and alcohol consumption (i.e., prior experience of smoking cigarettes and drinking alcoholic beverages) were distributed. Additional variables (e.g., age, residence, gender, etc.) were used in the analyses. Firth penalized logistic regression was conducted with drinking and smoking status variables as the dependent variables. Male adolescents were more inclined to smoke in 2004, 2006, 2009, and 2011 (p < 0.05 for all). Adolescents aged 15–16 years were more inclined to smoke compared with those aged 12–14 years in 2004, 2006, and 2011 (p < 0.05 for all). Among adolescents aged 15–18 years, older ones were more inclined to not smoke in 2004 (odds ratio (OR) = 0.531, 95% confidence interval (CI) 0.343–0.821). Adolescents who did not attend school were more inclined to smoke in 2004, 2006, 2009, and 2011 (p < 0.05 for all). Adolescents who were drinkers were more inclined to smoke in 2004, 2006, 2009, and 2011 (p < 0.05 for all). Male adolescents were more likely to drink in 2004, 2006, and 2009 (p < 0.05 for all). In 2006 and 2009, adolescents aged 15–16 years were more inclined to drink compared with those aged 12–14 years (p < 0.05 for all). Among adolescents aged 15–18 years, older ones were less inclined to drink in 2004 (OR = 0.719, 95% CI 0.527–0.980) and 2006 (OR = 0.716, 95% CI 0.527–0.972). Adolescents who smoked were more likely to drink in 2004, 2006, 2009, and 2011 (p < 0.05 for all). The prevalence of tobacco and alcohol consumption among adolescents has not changed significantly. The current study identified adolescent high-risk groups for tobacco and alcohol consumption.

Objectives: This study aimed to assess the prevalence of prolonged television, computer, and mobile phone viewing times and examined related sociodemographic factors among Chinese pregnant women. Methods: In this study, a cross-sectional survey was implemented among 2400 Chinese pregnant women in 16 hospitals of 5 provinces from June to August in 2015, and the response rate of 97.76%. We excluded women with serious complications and cognitive disorders. The women were asked about their television, computer, and mobile phone viewing during pregnancy. Prolonged television watching or computer viewing was defined as spending more than two hours on television or computer viewing per day. Prolonged mobile phone viewing was watching more than one hour on mobile phone per day. Results: Among 2345 pregnant women, about 25.1% reported prolonged television viewing, 20.6% reported prolonged computer viewing, and 62.6% reported prolonged mobile phone viewing. Pregnant women with long mobile phone viewing times were likely have long TV (Estimate = 0.080, Standard Error (SE) = 0.016, p < 0.001) and computer viewing times (Estimate = 0.053, SE = 0.022, p = 0.015). Pregnant women with long TV (Estimate = 0.134, SE = 0.027, p < 0.001) and long computer viewing times (Estimate = 0.049, SE = 0.020, p = 0.015) were likely have long mobile phone viewing times. Pregnant women with long TV viewing times were less likely to have long computer viewing times (Estimate = −0.032, SE = 0.015, p = 0.035), and pregnant women with long computer viewing times were less likely have long TV viewing times (Estimate = −0.059, SE = 0.028, p = 0.035). Pregnant women in their second pregnancy had lower prolonged computer viewing times than those in their first pregnancy (Odds Ratio (OR) 0.56, 95% Confidence Interval (CI) 0.42–0.74). Pregnant women in their second pregnancy were more likely have longer prolonged mobile phone viewing times than those in their first pregnancy (OR 1.25, 95% CI 1.01–1.55). Conclusions: The high prevalence rate of prolonged TV, computer, and mobile phone viewing times was common for pregnant women in their first and second pregnancy. This study preliminarily explored the relationship between sociodemographic factors and prolonged screen time to provide some indication for future interventions related to decreasing screen-viewing times during pregnancy in China.