Background: Previous studies have suggested that exposure to air pollution may increase stroke risk, but the results remain inconsistent. Evidence of more recent studies is highly warranted, especially gas air pollutants. Methods: We searched PubMed, Embase, and Web of Science to identify studies till February 2020 and conducted a meta-analysis on the association between air pollution (PM_2.5, particulate matter with aerodynamic diameter less than 2.5 μm; PM₁₀, particulate matter with aerodynamic diameter less than 10 μm; NO₂, nitrogen dioxide; SO₂, sulfur dioxide; CO, carbon monoxide; O₃, ozone) and stroke (hospital admission, incidence, and mortality). Fixed- or random-effects model was used to calculate pooled odds ratios (OR)/hazard ratio (HR) and their 95% confidence intervals (CI) for a 10 μg/m³ increase in air pollutant concentration. Results: A total of 68 studies conducted from more than 23 million participants were included in our meta-analysis. Meta-analyses showed significant associations of all six air pollutants and stroke hospital admission (e.g., PM_2.5: OR = 1.008 (95% CI 1.005, 1.011); NO₂: OR = 1.023 (95% CI 1.015, 1.030), per 10 μg/m³ increases in air pollutant concentration). Exposure to PM_2.5, SO₂, and NO₂ was associated with increased risks of stroke incidence (PM_2.5: HR = 1.048 (95% CI 1.020, 1.076); SO₂: HR = 1.002 (95% CI 1.000, 1.003); NO₂: HR = 1.002 (95% CI 1.000, 1.003), respectively). However, no significant differences were found in associations of PM₁₀, CO, O₃, and stroke incidence. Except for CO and O₃, we found that higher level of air pollution (PM_2.5, PM₁₀, SO₂, and NO₂) exposure was associated with higher stroke mortality (e.g., PM₁₀: OR = 1.006 (95% CI 1.003, 1.010), SO₂: OR = 1.006 (95% CI 1.005, 1.008). Conclusions: Exposure to air pollution was positively associated with an increased risk of stroke hospital admission (PM_2.5, PM₁₀, SO₂, NO₂, CO, and O₃), incidence (PM_2.5, SO₂, and NO₂), and mortality (PM_2.5, PM₁₀, SO₂, and NO₂). Our study would provide a more comprehensive evidence of air pollution and stroke, especially SO₂ and NO₂.

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.

China has the largest population of older adults, most of whom suffer from one or more noncommunicable diseases (NCDs). The harm of the number of NCDs on the health-related quality of life (HRQOL) of older adults should be taken seriously. A sample of 5166 adults, aged 60 years and older, was included in this study. The Chinese version of the World Health Organization Quality of Life-Old (WHOQOL-OLD) instrument was used to assess the HRQOL. Multiple linear regression models were established to determine the relationship between the number of NCDs and the total score and scores of each dimension of the WHOQOL-OLD scale. After adjusting for confounding factors, suffering from one NCD (B = −0.87, 95% CI = −1.67 to −0.08, p < 0.05), two NCDs (B = −2.89, 95% CI = −3.87 to −1.90, p < 0.001), and three or more NCDs (B = −4.20, 95% CI = −5.36 to −3.05, p < 0.001), all had negative impacts on the HRQOL of older adults. NCDs had significant negative impacts on the HRQOL of older adults, and as the number of NCDs increased, the HRQOL of older adults deteriorated. Therefore, we should pay attention to the prevention and management of NCDs of older adults to prevent the occurrence of multiple NCDs.

This study examined the cross-sectional association among a number of daily health-related behavioral risk factors and sleep among Chinese elderly. A sample of 4993 adults, aged 60 years and older, from the China’s Health-Related Quality of Life Survey for Older Adults 2018 was included in this study. Five daily health-related behaviors, which included smoking, drinking, unhealthy eating habits, insufficient leisure activities, and physical inactivity were measured. Sleep disturbances and sleep quality were used to represent the respondents’ sleep status. Multiple logistic regression models and multiple linear regression models were established. The odds ratios (ORs) of sleep disturbances for those with one to five health-related risk behaviors were 1.41 (95% CI = 1.11 to 1.78), 2.09 (95% CI = 1.66 to 2.63), 2.54 (95% CI = 1.99 to 3.25), 2.12 (95% CI = 1.60 to 2.80), and 2.49 (95% CI = 1.70 to 3.65), respectively. Individuals with one health-related risk behavior (B = 0.14, 95% CI = −0.23 to −0.06), two health-related risk behaviors (B = 0.21, 95% CI = −0.30 to −0.13), three health-related risk behaviors (B = 0.46, 95% CI = −0.55 to −0.37), four health-related risk behaviors (B = 0.50, 95% CI = −0.62 to −0.39), and five health-related risk behaviors (B = 0.83, 95% CI = −1.00 to −0.66) showed lower scores of self-perceived sleep quality. Having multiple health-risk behaviors was positively correlated with a higher risk of sleep disturbances among Chinese elderly. Moreover, elderly individuals with multiple health-related risk behaviors were significantly associated with poorer sleep quality.

Partial or total non-adherence has been recognized as major issues in the long-term management of hypertension. This study aims to investigate the prevalence and associated factors of compliance behaviors among Chinese middle-aged and older hypertensive patients. A sample of 6308 hypertensive patients aged ≥45 years was obtained from the 2015 China Health and Retirement Longitudinal Study (CHARLS) data. Two compliance behaviors were involved including medication and blood pressure monitoring. Stratified binary logistic regression analysis was employed to examine the associated factors. 77.2% of the participants reported medication compliance, and 40.7% complied with blood pressure monitoring. Better medication compliance associated with older age, overweight or obesity, one or ≥3 complications, no drinking, living in urban areas, and health education. Better blood pressure monitoring compliance associated with older age, overweight or obesity, ≥3 complications, normal activities of daily living (ADL), no smoking, sleep duration of 6–8 h, better cognitive function, living in urban areas, education level of middle school or above, and health education. Chinese middle-aged and older hypertensive patients experienced unoptimistic compliance behaviors, especially for blood pressure monitoring. Special attention and targeted interventions are urgent for the high-risk population of poor compliance behaviors, such as rural individuals, low educational population, and younger hypertensive patients.

The phenomenon of growth in drug consumption within the framework of national volume-based procurement (VBP) policy raises speculations about demand release and policy inducing. This study aims to explore the reasons and mechanisms of drug consumption increases following VBP policy from two perspectives. We collected data from the China Drug Supply Information Platform, National Bureau of Statistics and the Joint Procurement Office. Twenty cardiovascular international non-proprietary names (INNs) in the first three VBP batches and 28 observation regions were included, constructing 418 valid INN-region combinations as the unit for analysis. The average monthly consumption volume of VBP cardiovascular drug was assigned as the explained variable. The generalized difference-in-difference method was conducted using the price reduction level and the size of policy assessment task as the policy intensity indicator. Moderating effect model was employed to examine the role of resident’s income level. Increased cardiovascular drug consumption was observed in 285 (68.18%) INN-region combinations after policy implementation. Under VBP policy, the price reduction level was significantly correlated with drug consumption in total (β = 0.144, p < 0.001), as well as in tertiary hospitals, secondary hospitals and primary healthcare centers (PHCs) (all p-values < 0.05). Resident’s income level negatively moderated the impact of price reduction level on drug consumption in total (β = −0.089, p < 0.001) and in secondary hospitals (β = 0.154, p < 0.001) and PHCs (β = −0.2.9, p < 0.001), rather than in tertiary hospitals (β = −0.079, p > 0.05). The size of policy assessment task was positively associated with drug consumption in total (β = 0.052, p < 0.001), as well as in tertiary hospitals, secondary hospitals and PHCs (all p-values < 0.05). Two mechanisms codrive drug consumption increases under VBP policy: first is the improvement of cardiovascular medication access and consumption toward lower-income groups following price reduction, pointing to the fulfillment of unmet needs, and second is policy pressure from supporting assessment measures on hospital drug use, indicating potential overprescribing.