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There are many studies on the impact of physical activity on health but few studies on the relationship between physical activity and medical expenditure among the elderly. Based on the China Health and Retirement Longitudinal Survey (CHARLS) database and selected 4456 valid samples, this paper used a two-part model to analyze the effects of high, moderate, and low physical activity intensity on medical expenditure. It is found that the intensity of physical activity was negatively correlated with medical expenditure, and the medical expenditure of the high physical activity intensity group was significantly lower than that of the low physical activity intensity group. For example, compared to people with no physical activity, the total medical expenditure decreased by 22.4%, 40.4%, and 62.5% per week in those with low, moderate, and high physical activity intensity. Thus, the government should provide more places for the elderly to exercise, planning special exercise areas for the elderly in community playgrounds, such as a dancing square, which will also help the elderly to increase their amount of exercise per week and develop a daily exercise habit. [ABSTRACT FROM AUTHOR]

Objective: This study aimed to examine the levels of physical activity (PA), sleep, and mental health (MH), specifically depression, anxiety, and stress, among Chinese university students. It also aimed to analyze the influencing factors of MH, providing a theoretical foundation for developing intervention programs to improve college students' mental health., Methods: A stratified, clustered, and phased sampling method was employed. In September 2022, a survey was conducted among 36,756 university students from 104 higher education institutions across 31 provinces, autonomous regions, and municipalities in China. The participants' PA behaviors, sleep patterns, depressive symptoms (use the CES-D), anxiety symptoms (use the GAD-7), smoking and drinking behaviors, and demographic information were assessed through an online questionnaire using Questionnaire Star software., Results: A total of 30,475 valid questionnaires were completed. The proportion of university students engaging in light-intensity PA was 77.6%. The prevalence of insufficient sleep was 39.5%, whereas the prevalence of poor sleep quality was 16.7%. The prevalence of depressive symptoms was 10%, and the prevalence of anxiety symptoms was 23.3%. Binary logistic regression analysis revealed that engaging in moderate to high-intensity PA and having sufficient and high-quality sleep were associated with a lower likelihood of depressive symptoms (OR = 0.207-0.800, P < 0.01), whereas appropriate sleep duration and higher sleep quality were associated with a lower likelihood of anxiety symptoms (OR = 0.134-0.827, P < 0.001)., Conclusion: The intensity of PA among university students is predominantly light, and the reported rate of insufficient sleep is relatively high. Moderate to high-intensity PA and sufficient high-quality sleep may alleviate MH issues among college students, with an interaction effect observed among PA, sleep, and depression symptoms. Future studies should further explore targeted interventions combining PA and sleep behaviors to enhance the MH of university students., Competing Interests: Declarations. Ethics approval and consent to participate: This study was conducted according to the guidelines of the Declaration of Helsinki, and approved by the Ethics Committee of Nantong University (No 70/2022). Informed consent was obtained from all participants involved in this study. Consent for publication: No applicable. Competing interests: The authors declare no competing interests., (© 2024. The Author(s).)

The novel COVID-19 pandemic spread quickly and continuously influenced global societies. As a vulnerable population that accounted for the highest percentage of deaths from the pandemic, older adults have experienced huge life-altering challenges and increased risks of mental problems during the pandemic. Empirical evidence is needed to develop effective strategies to promote preventive measures and mitigate the adverse psychological impacts of the COVID-19 pandemic. This study aimed to investigate the behavioral responses (i.e., preventive behaviors, physical activity, fruit and vegetable consumption) and mental responses (i.e., depression and loneliness) towards the COVID-19 pandemic among Chinese older adults. A further aim was to identify the associations among demographics, behavioral responses, and mental responses. Using a convenience sampling approach, 516 older adults were randomly recruited from five cities of Hubei province in China. Results of the cross-sectional survey showed that 11.7% of participants did not adhere to the WHO recommended preventive measures, while 37.6% and 8.3% of participants decreased physical activity and fruit–vegetable consumption respectively. For mental responses, 30.8% and 69.2% of participants indicated significantly depressive symptoms and severe loneliness, respectively. Participants' behavioral and mental responses differed significantly in several demographics, such as age group, living situation, marital status, education levels, household income, medical conditions, and perceived health status. Demographic correlates and behavioral responses could significantly predicate the mental response with small-to-moderate effect sizes. This is the first study to investigate the characteristics of behavioral and mental responses of Chinese older adults during the COVID-19 pandemic. Research findings may give new insights into future developments of effective interventions and policies to promote health among older adults in the fight against the pandemic. [ABSTRACT FROM AUTHOR]

Context: Persuasive evidence has shown the inverse associations between physical activity (PA) and the risk of stroke. However, few studies have investigated the associations between different dimensions (intensity, frequency, duration, volume) of PA and the risk of stroke., Objective: To investigate the associations between different dimensions of PA and the risk of stroke in total participants and subgroups., Method: This study included 6250 individuals aged 45 years old and above from the China Health and Retirement Longitudinal Study (CHARLS). PA was divided into vigorous PA (VPA), moderate PA (MPA), and light PA (LPA), and described in different dimensions (intensity, frequency, duration, volume). Stroke was defined on the basis of self-reported diagnosis and related treatments. Binary logistic regression models were established to assess the associations between different dimensions of PA and the risk of stroke in total participants and subgroups stratified by sex., Results: Individuals taking VPA with a frequency of 3-5 d/w, duration of ≥240 min/d, volume of ≥300 min/w had lower risks of strokes in total participants (Odds ratio (OR) = 0.32, 95% confidence interval (CI): 0.13, 0.75; OR = 0.60, 95% CI: 0.38, 0.94; OR = 0.68, 95% CI: 0.46, 0.99, respectively). However, significant associations of VPA with the risk of stroke in men were only observed in the duration of ≥240 min/d and volume of ≥300 min/w (OR = 0.53, 95% CI: 0.30, 0.93; OR = 0.61, 95% CI: 0.38, 0.99, respectively) whereas no significance in women. Compared with individuals taking no MPA, inverse significant associations between the risk of stroke and any level of frequency, duration and volume in MPA were observed in total sample (OR ranging from 0.16-0.40, all p < 0.05), whereas significant associations between the risk of stroke and MPA were found in men except the duration of 10-29 min/d and volume of 150-299 min/w (OR ranging from 0.26-0.35, all p < 0.05), and in women except the frequency of 1-2 d/w and duration of ≥240 min/d (OR ranging from 0.14-0.49, all p < 0.05). No significant associations could be observed in total participants and subgroups between LPA and the risk of stroke., Conclusion: This study revealed some significant associations between different dimensions of PA, especially MPA, and the risk of stroke. Furthermore, the difference of association was observed in the groups with different sex. Further prospective study is needed to determine deeper associations between PA and the risk of stroke.

Background: Neighbourhood environment characteristics have been found to be associated with residents' willingness to conduct physical activity (PA). Traditional methods to assess perceived neighbourhood environment characteristics are often subjective, costly, and time-consuming, and can be applied only on a small scale. Recent developments in deep learning algorithms and the recent availability of street view images enable researchers to assess multiple aspects of neighbourhood environment perceptions more efficiently on a large scale. This study aims to examine the relationship between each of six neighbourhood environment perceptual indicators—namely, wealthy, safe, lively, depressing, boring and beautiful—and residents' time spent on PA in Guangzhou, China. Methods: A human–machine adversarial scoring system was developed to predict perceptions of neighbourhood environments based on Tencent Street View imagery and deep learning techniques. Image segmentation was conducted using a fully convolutional neural network (FCN-8s) and annotated ADE20k data. A human–machine adversarial scoring system was constructed based on a random forest model and image ratings by 30 volunteers. Multilevel linear regressions were used to examine the association between each of the six indicators and time spent on PA among 808 residents living in 35 neighbourhoods. Results: Total PA time was positively associated with the scores for "safe" [Coef. = 1.495, SE = 0.558], "lively" [1.635, 0.789] and "beautiful" [1.009, 0.404]. It was negatively associated with the scores for "depressing" [− 1.232, 0.588] and "boring" [− 1.227, 0.603]. No significant linkage was found between total PA time and the "wealthy" score. PA was further categorised into three intensity levels. More neighbourhood perceptual indicators were associated with higher intensity PA. The scores for "safe" and "depressing" were significantly related to all three intensity levels of PA. Conclusions: People living in perceived safe, lively and beautiful neighbourhoods were more likely to engage in PA, and people living in perceived boring and depressing neighbourhoods were less likely to engage in PA. Additionally, the relationship between neighbourhood perception and PA varies across different PA intensity levels. A combination of Tencent Street View imagery and deep learning techniques provides an accurate tool to automatically assess neighbourhood environment exposure for Chinese large cities. [ABSTRACT FROM AUTHOR]