China has experienced a rapid increase in hypertension over the past decade, especially in rural. Therefore, the aim of this research is to examine the dynamic trends in urban-rural disparities in hypertension prevalence, detection, and medication use among Chinese adults from 1993 to 2011. Data were extracted from the seven latest waves of the China Health and Nutrition Survey (CHNS). We used the hukou system to distinguish between urban and rural residents. Chi-square tests were performed to examine urban-rural gaps in hypertension prevalence, detection and medication use. Multiple logistic regressions were used to confirm these disparities and to explore whether the urban-rural gaps have narrowed or widened from 1993 to 2011, after controlling for health-related behaviors, BMI, demographic variables and socioeconomic characteristics. Blinder-Oaxaca decomposition technique was also used to calculate the extent to which urban-rural disparities reflect an endowments effect or a coefficients effect. Hypertension prevalence, detection, and medication use among rural adults were significantly lower than urban adults, with the significant level at p < 0.001. The urban-rural gaps in hypertension prevalence and medication use gradually narrowed during the period 1993–2011, whereas the gaps in hypertension detection grew wider. After controlling for confounding variables, urban adults were about 24.5, 49.4, and 89.5% more likely to be hypertensive, detected, and medicated than their rural counterparts (p < 0.01), respectively. The Blinder-Oaxaca decomposition suggested that approximately 22 and 26% of the urban-rural gap in hypertension detection and medication use could be attributed to coefficient difference, respectively. Although hypertension prevalence among rural adults was comparable to that of urban adults, hypertension detection and medication use of rural adults were still suboptimal. Unusually large urban-rural gaps and an expanding trend in hypertension detection deserve the attention of health policymakers and researchers.

Very few studies have examined the association between light cigarette smoking (i.e., ≤5 cigarettes per day) and mortality. The aim of this study was to examine the association of light cigarette smoking with all-cause and cause-specific mortality among adults in the United States. Data were from 13 waves of the National Health Interview Survey (1997 to 2009) that were linked to the National Death Index records through December 31, 2011. A total of 329,035 participants aged ≥18 years in the United States were included. Deaths were from all cause, cancer, cardiovascular disease (CVD) and respiratory disease and were confirmed by death certification. During a median follow-up of 8.2 years, 34,862 participants died, of which 8415 were from cancer, 9031 from CVD, and 2040 from respiratory disease. Compared with never-smokers, participants who smoked 1–2 (hazard ratios (HR) = 1.94, 95%CI = 1.73–2.16) and 3–5 cigarettes (HR = 1.99, 1.83–2.17) per day were at higher risk of all-cause mortality after adjustment for demographic variables, lifestyle factors and physician-diagnosis of chronic disease. The associations were stronger for respiratory disease-specific mortality, followed by cancer-specific mortality and CVD-specific mortality. For example, the HRs (95% CIs) of smoking 1–2 cigarettes per day were 9.75 (6.15–15.46), 2.28 (1.84–2.84) and 1.93 (1.58–2.36), respectively, for these three cause-specific mortalities. This study indicates that light cigarette smoking increases risk of all-cause and cause-specific mortality in US adults.

Few studies have focused on the sleep quality among migrant elderly following children (MEFC). This study aimed to investigate the effects of chronic disease and mental health on the sleep quality of MEFC in Weifang, China. A cross-sectional study was conducted by multi-stage cluster random sampling, and in total 613 participants were enrolled. Sleep quality and mental health were assessed by the Pittsburgh Sleep Quality Index (PSQI) and the Depression, Anxiety, and Stress Scale (DASS-21), respectively. Chronic disease was assessed by the question “how many chronic diseases do you have?” A descriptive analysis and chi-square test were used to describe participants’ sociodemographic variables, chronic disease, mental health, and sleep quality. The relationship between chronic disease, mental health, and sleep quality was explored by establishing binary logistic regression models. The results showed that 18.3% of MEFC’s sleep quality was poor. MEFCs who were male were more likely to report good sleep quality. MEFCs who have similar monthly family income compared with others around, with multimorbidity, depression, and anxiety were more likely to report poor sleep quality. Nearly 1/5 of MEFCs were having poor sleep quality in this study. Results indicated that chronic diseases, depression, and anxiety were risk factors for the sleep quality of MEFC. Implications for the government, communities, and families of MEFC were given for improving their sleep quality.

In 2009, China unveiled an ambitious national health care reform program, with the goal of providing equitable and affordable basic health care for everyone. This study was intended to partially fill the knowledge gap in understanding of the demand-side impact on health care utilization and affordability among older people in Zhejiang and Gansu provinces of China. We used two waves of data from the pilot survey of CHARLS implemented in 2008 and 2012. Chi-square tests and t tests were performed to examine whether out-of-pocket (OOP) and pharmaceutical spending (PS), as a share of total health expenditures (THEs), have significantly changed following the health reform. Two-part model was employed to confirm these changes after controlling for confounding variables. All analyses were weighted and clustered the standard errors. After controlling for confounding variables, older people in 2012 were 2.1 and 6.8% more likely to use outpatient and inpatient care than they did in 2008, respectively. Among those who have at least one outpatient visit, declines of OOP-to- THEs and PS-to-THEs percentage significantly reduced 0.998 (p < 0.1) and 2.324 (p < 0.01) from 2008 to 2012, respectively. However, conditional on having at least one inpatient stay, no significant reduction in terms of the OOP-to-THEs and even increase in terms of the PS-to-THEs percentage observed between 2008 and 2012. Compared to elderly people in Gansu, Zhejiang aged people had obviously better utilization, lighter inpatient OOP burden and lower inpatient PS proportion, but higher outpatient OOP burden and PS proportion. Although the OOP burden and PS portion had been reduced following the health reform, these impacts were still limited. Better results can be observed in outpatient care than in inpatient care, which provide a strong foundation for the next stage of reform.

Background: Risky health behaviors in childhood, including smoking, alcohol consumption, and having a poor diet, are the major sources of non-communicable diseases in adulthood. This study aimed to examine how parents affect children's risky health behaviors and whether intergenerational transmission differs based on socioeconomic status (SES).Methods: Data were extracted from the 1991–2015 China Health and Nutrition Survey (CHNS). Smoking (n = 5,946), alcohol consumption (n = 7,821), and sugar-sweetened beverages (SSBs) consumption (n = 3,537) were used as proxies for risky health behaviors in children. A binary choice model for panel data with a random-effect specification was employed to examine whether risky health behaviors can be transmitted from parents to their children. Subsequently, we conducted a seemingly unrelated estimation test (SUEST) to explore the differences in parental transmission between the different SES groups.Results: We found strong intergenerational persistence of smoking, alcohol drinking, and SSBs drinking behaviors, except for the mothers' smoking behavior. Mothers had a greater influence on children's alcohol drinking and SSBs drinking behaviors than fathers both in urban and rural areas and in different SES groups. The intergenerational transmission of SSBs drinking behavior exhibited a decreasing trend with increasing SES for both urban and rural families. In urban areas, mothers' alcohol drinking behavior has a decreasing trend with increasing education level, occupation, and income; however, in rural areas, the influence of mothers' alcohol drinking behavior occurred in the same direction with increasing education level and occupation type. In rural areas, the influence of fathers' drinking and smoking behaviors on children appears to mostly increase with increasing SES. Meanwhile, the influence of such behaviors among urban fathers would decrease with increasing SES.Conclusion: Parents' behaviors and SES can influence the initiation of risky health behaviors in their offspring. Thus, to promote healthy behaviors, policymakers can introduce health education programs for parents, particularly for those living in rural areas and with a low SES.

The authors wish to correct the following erratum in this paper