Background: As lung cancer has shown a continuously increasing trend in many countries, it is essential to stay abreast of lung cancer mortality information and take informed actions with a theoretical basis derived from appropriate and practical statistical methods. Methods: Age-specific rates were collected by gender and region (urban/rural) and analysed with descriptive methods and age-period-cohort models to estimate the trends in lung cancer mortality in China from 1988 to 2013. Results: Descriptive analysis revealed that the age-specific mortality rates of lung cancer in rural residents increased markedly over the last three decades, and there was no obvious increase in urban residents. APC analysis showed that the lung cancer mortality rates significantly increased with age (20–84), rose slightly with the time period, and decreased with the cohort, except for the rural cohorts born during the early years (1909–1928). The trends in the patterns of the period and cohort effects showed marked disparities between the urban and rural residents. Conclusions: Lung cancer mortality remains serious and is likely to continue to rise in China. Some known measures are suggested to be decisive factors in mitigating lung cancer, such as environmental conservation, medical security, and tobacco control, which should be implemented more vigorously over the long term in China, especially in rural areas.

Background: The prevalence of diabetes mellitus is rapidly increasing in China, but the secular trends in incidence and mortality remain unknown. This study aims to examine time trends from 1990 to 2017 and the net age, period, and cohort effects on diabetes incidence and mortality. Methods: Incidence and mortality rates of diabetes (1990–2017) were collected for each 5-year age group (from 5–9 to 80–84 age group) stratified by gender from the Global Burden of Disease 2017 Study. The average annual percentage changes in incidence and mortality were analyzed by joinpoint regression analysis; the net age, period, and cohort effects on the incidence and mortality were estimated by age-period-cohort analysis. Results: The joinpoint regression analysis showed that age-standardized incidence significantly rose by 0.92% (95% CI: 0.6%, 1.3%) in men and 0.69% in women (95% CI: 0.3%, 1.0%) from 1990 to 2017; age-standardized mortality rates rose by 0.78% (95% CI: 0.6%, 1.0%) in men and decreased by 0.12% (95% CI: −0.4%, 0.1%) in women. For age-specific rates, incidence increased in most age groups, with exception of 30–34, 60–64, 65–69 and 70–74 age groups in men and 25–29, 30–34, 35–39 and 70–74 age groups in women; mortality in men decreased in the younger age groups (from 20–24 to 45–49 age group) while increased in the older age groups (from 50–54 to 80–84 age group), and mortality in women decreased for all age groups with exception of the age group 75–79 and 80–84. The age effect on incidence showed no obvious changes with advancing age while mortality significantly increased with advancing age; period effect showed that both incidence and mortality increased with advancing time period while the period trend on incidence began to decrease since 2007; cohort effect on incidence and mortality decreased from earlier birth cohorts to more recent birth cohorts while incidence showed no material changes from 1982–1986 to 2012–2016 birth cohort. Conclusions: Mortality decreased in younger age groups but increased in older age groups. Incidence increased in most age groups. The net age or period effect showed an unfavorable trend while the net cohort effect presented a favorable trend. Aging likely drives a continued increase in the mortality of diabetes. Timely population-level interventions aiming for obesity prevention, healthy diet and regular physical activity should be conducted, especially for men and earlier birth cohorts at high risk of diabetes.

Background: Environmental tax has been implemented by the government in response to the demands of the residents to control environmental pollution. However, a tax has a wide effect on many interacting aspects of the society. It remains unknown whether enacting an environmental tax for the government can improve the residents’ happiness. This study aimed to examine the impact of air and water pollution on residents’ happiness and evaluate whether an environmental tax can alleviate the impact of air and water pollution on residents’ happiness. Methods: Based on the 2015 Chinese General Social Survey Data, 28 provinces in China were divided into two categories according to their environmental tax rates: baseline-tax areas (n = 13) and high-tax areas (n = 15). The ordered probit model was used to analyze the impact of air and water pollution on the residents’ happiness in baseline-tax areas and high-tax areas, respectively. The Chow Test was used to test whether the impact of environmental pollution on happiness was different between baseline-tax areas and high-tax areas. Results: The impact of air pollution on residents’ happiness was statistically significant in the baseline-tax areas (coefficient −0.162, 95% confidence interval (CI) −0.239, −0.086, p < 0.001), but the significance was weakened in the high-tax areas (coefficient −0.030, 95% CI −0.060, 0.000, p = 0.051). The Chow Test showed that the absolute value of the regression coefficient in the baseline-tax areas was significantly higher than the value in the high-tax areas (F = 12.712, p < 0.001). Similarly, the impact of water pollution on residents’ happiness was statistically significant (coefficient −0.264, 95% CI −0.353, −0.174, p < 0.001) in the baseline-tax areas and in the high-tax areas (coefficient −0.063, 95% CI −0.091, −0.035, p < 0.001), but the Chow Test showed that the absolute value of the regression coefficient in the baseline-tax areas was significantly higher than the value in the high-tax areas (F = 13.758, p < 0.001). Conclusions: Both air and water pollution impair residents’ happiness. The present study shows for the first time that enacting an environmental tax significantly alleviates the negative effect of air and water pollution on residents’ happiness. The findings of the present study provide empirical evidence for the government to levy environmental tax.

Background: The impact of air pollution on residents’ happiness remains unclear and the underlying mechanism remains unknown. We aimed to examine the direct effect of air pollution on residents’ happiness and indirect effect through mediating their health. Methods: Based on the 2017 China Comprehensive Social Survey Data (CGSS), data on happiness were retrieved from 11,997 residents in 28 provinces in China. An ordered-probit model was used to examine the effect of air pollution on residents’ happiness and health, respectively. A stepwise regression was used to derive the direct effect of air pollution on residents’ happiness and indirect effect from health impairment attributable to air pollution. Results: Air pollution was associated with lower levels of health (coef. −0.190, 95% CI −0.212, −0.167, p < 0.001), while health was positively associated with happiness (coef. 0.215, 95% CI 0.196, 0.234, p < 0.001). Mediation analysis methods showed that air pollution impacted residents’ happiness directly and indirectly: the percent of total effect that was mediated through health was 36.97%, and the ratio of indirect to direct effect was 0.5864. Conclusions: Health plays a major mediating role in the relation between air pollution and residents’ happiness. In order to alleviate the impact of air pollution on residents’ happiness, future strategies should focus on health promotion besides reducing air pollutant emission.

Air pollution is an important factor affecting human health and daily life. The Chinese government is making vigorous efforts to control air pollution. The upgrading of the industrial structure is a problem-solving tool in the environment and economic growth cases. This paper aims to explore the relationships among environmental regulation, the upgrading of the industrial structure and air pollution. The PVAR (Panel Vector Auto Regression) model and moderating effect model are used to conduct empirical analysis based on panel data of 30 provinces in China from 2004 to 2020. The analysis of the results provides the following findings. Firstly, environmental regulations can significantly reduce emissions, but the deterioration of air quality does not have a significant impact on the improvement of environmental regulations. Secondly, industrial structure upgrading can reduce air pollution, but the worsening of the air quality will hinder the upgrading of industrial structures. Thirdly, environmental regulation can promote industrial structure upgrading. Lastly, industrial structure upgrading is a moderating variable and can positively moderate the impact of environmental regulations on air pollution.