Physical Activity, Obesity, and Hypertension among Adults in a Rapidly Urbanised City.

BACKGROUND: Few studies have explored the relationship between the level of physical activity and the occurrence or prevalence of obesity and hypertension among people residing in urbanised areas. METHOD: A cross-sectional study involving a sample of 1,001 adults was conducted. Descriptive statistics were used to describe sociodemographic variables, physical activity levels, body mass index (BMI), and prevalence of hypertension. Logistic regression models were adopted to investigate the relationship between these factors. RESULTS: A total of 939 respondents who provided valid responses were included. Among them, 56.5% of the participants reported engaging in high levels of physical activity. However, 40.4% of the respondents were classified as overweight or obese, and 31.9% had diagnosed hypertension. After adjusting for sociodemographic factors, logistic regression analysis revealed that physical activity levels were negatively correlated with the prevalence of BMI (OR = 0.564, 95% CI: 0.352-0.905; OR = 0.583, 95% CI: 0.375-0.907) and hypertension (OR = 0.556, 95% CI: 0.348-0.888). CONCLUSIONS: Our study confirms recent evidence regarding the amount of physical activity that is associated with lower prevalence of obesity and hypertension in Pingshan District. Furthermore, different physical activities of various intensity levels had different effects on hypertension. Residents should be encouraged to engage in physical activities and maintain a healthy weight to improve their quality of life.

Built environment, physical activity, and obesity of adults in Pingshan District, Shenzhen City in Southern China.

BACKGROUND: The relation between neighbourhood built environment and obesity has been described as both nuanced and complex. AIM: The objective of this study was to examine the relationship between the built environment, physical activity, and obesity in a rapidly urbanised area of China. SUBJECTS AND METHODS: This is a cross-sectional study. Descriptive statistics were used to describe the socio-demographic variables, physical activity levels and BMI status. Multivariable logistic regression models were used to examine the association between neighbourhood environment, the likelihood of engaging in different types of physical activity, and BMI. RESULTS: A total of 842 respondents completed the questionnaires and were included (84.1% response rate). Among them, 56.4% reported meeting high physical activity levels, while 40.7% were overweight or obese. Multivariable regression analysis showed that better road conditions (ß = 0.122, t = 2.999, p = 0.003) and access to physical activity facilities (ß = 0.121, t = 3.193, p = 0.001) were significantly associated with higher levels of physical activity. Physical activity levels were inversely associated with the likelihood of being overweight (OR = 0.565, 95%CI: 0.3 4 9-0.917) or obese (OR = 0.614, 95%CI: 0.3 9 0-0.966). CONCLUSION: The built environment has an important impact on physical activity. However, the direct impact of leisure physical activity on BMI is not significant. This research provides a summary of recent evidence in Pingshan District on built environments that are most favourable for physical activity and obesity.

Neighbourhood built environment and leisure-time physical activity: A cross-sectional study in southern China.

This study conducted scientific evidence linking neighbourhood built environment to adults' leisure-time physical activity (LTPA) among adults in China. Data were obtained from a questionnaire survey conducted from April to July 2017 among 1002 adults aged 18-69 years old in Pingshan District, Shenzhen, China. Chinese Walkable Environment Scale for urban community residents and International Physical Activity Questionnaire were used to measure participants' neighbourhood built environment and leisure-time physical activity, which was categorised into leisure-time walking (LTW) and leisure-time moderate-to-vigorous physical activity (LTMVPA). A total of 986 participants (mean age = 40.7 years, 53.3% females) were included in this research. Descriptive statistics were used to describe the socio-demographic variables, LTW and LTMVPA by sex. Multivariable logistic regression models were used to examine the association between neighbourhood environment characteristics and the likelihood of engaging in active LTW and LTMVPA. Only 20.7% of participants engaged in active LTW and 17.8% active LTMVPA. Better road condition was associated with higher likelihood of active (at least 150 min/week) LTW and LTMVPA. High perceived esthetic was positively associated with LTW and LTMVPA. Active LTW was related to better perception of traffic condition as well. The improvement of the neighbourhood environment characteristics can promote active LTPA among adults living in Shenzhen, China. Our findings support the importance of considering population health effects in urban planning and development.