In this study, we estimated the short-term effects of ambient air pollution on respiratory disease hospitalization in Taiyuan, China. Daily data of respiratory disease hospitalization, daily concentration of ambient air pollutants and meteorological factors from 1 October 2014 to 30 September 2017 in Taiyuan were included in our study. We conducted a time-series study design and applied a generalized additive model to evaluate the association between every 10-μg/m³ increment of air pollutants and percent increase of respiratory disease hospitalization. A total of 127,565 respiratory disease hospitalization cases were included in this study during the present period. In single-pollutant models, the effect values in multi-day lags were greater than those in single-day lags. PM_2.5 at lag02 days, SO₂ at lag03 days, PM₁₀ and NO₂ at lag05 days were observed to be strongly and significantly associated with respiratory disease hospitalization. No significant association was found between O₃ and respiratory disease hospitalization. SO₂ and NO₂ were still significantly associated with hospitalization after adjusting for PM_2.5 or PM₁₀ into two-pollutant models. Females and younger population for respiratory disease were more vulnerable to air pollution than males and older groups. Therefore, some effective measures should be taken to strengthen the management of the ambient air pollutants, especially SO₂ and NO₂, and to enhance the protection of the high-risk population from air pollutants, thereby reducing the burden of respiratory disease caused by ambient air pollution.

This study draws on Bourdieu’s theory of capitals to analyze the relative importance of economic, cultural, and social capital on health behaviors in Chinese middle-aged and older adults. Based on data from the China Family Panel Studies of 2016 (N = 15,147), we first harnessed a binary logistic regression model to discuss the associations between the three capitals and four types of health behaviors (i.e., physical exercise, smoking, binge drinking and stay-up). Using the sheaf coefficients technique, we then compared the relative effects of three of the capitals on health behaviors. The results suggest that cultural capital is the most influential one, which would significantly increase physical exercise and stay-up behaviors, and reduce smoking and binge drinking behaviors. Economic capital is also an important predictor, that may reduce smoking behavior but increase binge drinking and stay-up behaviors. Social capital has shown the least importance, although it would still be saliently associated with physical exercise, smoking and stay-up behaviors. In addition, some significant group disparities are also identified. This article is one of the first to explain health behavior inequalities through a Bourdieusian capital-based approach in Chinese contexts.

Background: The novel coronavirus disease (COVID-19) was first reported in Wuhan, China. The mass population mobility in China during the Spring Festival has been considered a driver to the transmission of COVID-19, but it still needs more empirical discussion. Methods: Based on the panel data from Hubei, China between January 6th and February 6th, 2020, a random effects model was used to estimate the impact of population mobility on the transmission of COVID-19. Stata version 12.0 was used, and p < 0.05 was considered statistically significant. Results: The COVID-19 was more likely to be confirmed within 11–12 days after people moved from Wuhan to 16 other prefecture-level cities in Hubei Province, which suggests a period of 11–12 days from contact to being confirmed. The daily confirmed cases and daily increment in incidence in 16 prefecture-level cities show obvious declines 9–12 days post adaptation of city lockdown at the local level. Conclusion: Population mobility is found to be a driver to the rapid transmission of COVID-19, and the lockdown intervention in local prefecture-level cities of Hubei Province has been an effective strategy to block the COVID-19 epidemic.