Prevalence and Associated Lifestyle Factors of Suboptimal Health Status among Chinese Children Using a Multi-Level Model

The mediating effect of lifestyle behaviors on the relationship between self-perceived work stress and suboptimal health status: a cross-sectional study involving Chinese urban workers

STUDY DESIGN

Cross-sectional study.

OBJECTIVES

Suboptimal health status (SHS) is a third state between health and disease. Long-term being SHS will be detrimental to one's ability development. Previous studies have demonstrated the associations of lifestyle behaviors or work stress with SHS, but few studies have comprehensively analyzed the underlying factors and mechanisms between the three. This study aimed to investigate whether lifestyle behaviors mediated the relationship between self-perceived work stress and SHS.

METHODS

A total of 4238 urban workers, who participated in a cross-sectional survey conducted from December 2018 to October 2019, were included. A general linear model was used to explore the associations between lifestyle behaviors and self-perceived work stress with SHS after adjusting for demographic variables. Structural equation modeling was performed to examine the mediation by lifestyle behaviors.

RESULTS

The mean transformed scores of physical, mental, and social SHS were 70.98, 67.17, and 61.72, respectively. Unhealthy lifestyle behaviors and high self-perceived work stress positively affected SHS (P < 0.001). Self-perceived work stress imposed negative effects on physical SHS (β = -0.228, P < 0.001), mental SHS (β = -0.237, P < 0.001), and social SHS (β = -0.092, P < 0.001). The indirect effects of self-perceived work stress on physical SHS (β = -0.139, 95% CI: -0.178 to -0.106), mental SHS (β = -0.106, 95% CI: -0.134 to -0.082), and social SHS (β = -0.121, 95% CI: -0.154 to -0.092) were statistically significant.

CONCLUSIONS

Lifestyle behaviors and self-perceived work stress were significantly associated with SHS among Chinese urban workers. The mediating effects of unhealthy lifestyle behaviors were found in the relationship between high self-perceived work stress and SHS. Future longitudinal research may verify these associations and elucidate the underlying mechanisms.

A Study on Influencing Factors of Physicians' Suboptimal Health Status in Primary Healthcare Institutions

Purpose

This study aims to investigate the current health status of Chinese physicians in primary healthcare institutions (PHI) and the effects of personal characteristics, lifestyle, work-related environment and life-related environment on the subhealth status (SHS) of them.

Methods

A conceptual framework of various influencing factors was constructed with reference to the concept of health-related quality of life before the convenience sampling. Self-administered questionnaires are distributed to acquire the cross-sectional information of nationwide PHI physicians. A logit regression model was constructed to investigate the influence of various factors on the SHS of PHI physicians.

Results

Among 682 valid cases included in the logit regression, 457 physicians were in SHS, with an SHS rate of 67%. The regression results (R2=0.3934, chi-square=337.07, p<0.0001) showed that long working hours (p<0.05), personal income (p<0.05) and life stress (p<0.05) were protective factors for subhealth. The frequency of alcohol consumption (p<0.01), smoking (p<0.05), fear of making mistakes at work (p< 0.001), tension with colleagues (p < 0.0001), and job satisfaction (p < 0.05) were all risk factors. Other factors such as education (p < 0.1) also had an effect on the SHS of primary care physicians.

Conclusion

A large proportion of PHI physicians in China are in SHS and many of them are not aware that they are in a poor health state. The logit regression model showed that factors including worries about the occurrence of accidents, strained relationships with colleagues, job satisfaction, and frequency of smoking and drinking negatively influence the SHS of PHI physicians, which should be paid more attention. Meanwhile, annual personal income, long working hours and life stress are protective factors, which means that these factors need to be encouraged.

Sleep health and its related influencing factors in primary and middle school students in Fuzhou: A large multi-center cross-sectional study

Background

This current study set out to investigate the status of sleep health in 7–20-year-old students in Fuzhou and explore the related influencing factors of sleep health.

Methods

A total of 38,467 children and adolescents in Fuzhou were included in the study through a random stratified cluster sampling. Data were collected from May to June 2019, in 18 primary schools and 18 middle schools from nine districts, Fuzhou. Children's parents and adolescents of sampled classes were invited to fill out a series of questionnaires about the performance of the last 6 months (sociodemographic characteristics, sleep-related lifestyle behaviors, and electronic-products usage). Multiple linear regression was carried out to analyze data.

Results

Of the total 40,888 questionnaires we released, 38,467 were valid and effective with the response rate was 94.08%. The age of the surveyed participants was 11.85 ± 3.1, including 20,013 boys and 18,454 girls. The multiple linear regression analysis identified factors associated with sleep health (p < 0.05): Boy (coef = 0.073, 95% CI: 0.030–0.115), age (coef = 1.797, 95% CI: 0.224–0.243), key school (coef = 2.069, 95% CI: 0.105–0.193), urban (coef = 0.096, 95% CI: 0.054–0.139), excessive daytime sleepiness (coef = 0.535, 95% CI: 0.432–0.639), unhealthy sleep habits (coef = 0.363, 95% CI: 0.307–0.419), eating before sleep (coef = 0.578, 95% CI: 0.527–0.630), using electronic products in bedroom (coef = 0.074, 95% CI: 0.028–0.121), screen time per day during school (coef = 0.260, 95% CI: 0.235–0.284), frequency of using electronics 30 min before bedtime (coef = 0.150, 95% CI: 0.134–0.166), strained relationship with parents (coef = 0.361, 95% CI: 0.270–0.452), strained relationship with peers (coef = 0.267, 95% CI: 0.171–0.363), excessive homework or learning (coef = 0.189, 95% CI: 0.141–0.237), time for doing homework (coef = 0.266, 95% CI: 0.245–0.287), and mood swings frequently (coef = 1.174, 95% CI: 1.127–1.221) negatively impact sleep health. Sleep alone (coef = −0.204, 95% CI: −0.262–0.147) were the risk factors for sleep health. Furthermore, frequent mood swings was considered the most influential factor on overall variables.

Conclusions

Sleep health is associated with factors covered sociodemographic characteristics, family sleep habits, and routine activities before bedtime. Multiple measures should be taken to improve sleep quality in a targeted manner.

Association between Kihon check list score and geriatric depression among older adults from ORANGE registry

OBJECTIVE

Older adults in Japan are tackling health-related challenges brought by comprehensive geriatric symptoms, such as physical and cognitive problems and social-psychological issues. In this nationwide study, we mainly focused on the Kihon checklist (KCL) as certificated necessity of long-term care for Japanese older adults and investigated whether the KCL score was associated with geriatric depression. In addition, we aimed to identify critical factors that influence the relationship between the KCL score and geriatric depression.

METHODS

This survey was a cross-sectional observational study design, performed from 2013 to 2019. A total of 8,760 participants aged 65 years and over were recruited from five cohorts in Japan, consisting of 6,755 persons in Chubu, 1,328 in Kanto, 481 in Kyushu, 49 in Shikoku and 147 in Tohoku. After obtaining informed consent from each participant, assessments were conducted, and outcomes were evaluated according to the ORANGE protocol. We collected data on demographics, KCL, physical, cognitive and mental evaluations. To clarify the relationship between the KCL and geriatric depression or critical factors, a random intercept model of multi-level models was estimated using individual and provincial variables depending on five cohorts.

RESULTS

The KCL score was correlated with depression status. Moreover, the results of a random intercept model showed that the KCL score and geriatric depression were associated, and its association was affected by provincial factors of slow walking speed, polypharmacy and sex difference.

CONCLUSIONS

These results suggest that provincial factors of low walking performance, polypharmacy and sex difference (female) might be clinically targeted to improve the KCL score in older adults.

Associated Factors of Suboptimal Health Status Among Adolescents in China: A Cross-Sectional Study

PURPOSE

Suboptimal health status (SHS) is a state between health and disease, has several adverse effects, although, its main underlying mechanism is still unclear. This study aimed to investigate SHS and its associated factors of adolescents.

METHODS

A community-based cross-sectional study was conducted in the three different geographic locations of China (Shanxi, Guangzhou, and Tibet). A multidimensional sub-health questionnaire of adolescent (MSQA) is used to evaluate SHS. Independent two-sample K-S test was performed for the quantitative data as the non-parametric test, whereas Chi-square test method was applied to explore the difference of discrete variables data between groups. Then finally, multiple logistic regression analysis was applied to analyze the influential factors of SHS.

RESULTS

Among 1461 respondents (between 15 and 18 years old), females proportion (56.47%) was higher than males (43.53%) where SHS was higher in Shanxi followed by Tibet and then Guangdong. The rural area, grade, lack of sleep time, home visit in a week, lack of exercise, a heavy burden of study, smoking, drinking, and fewer friends were the risk factors of SHS, while families living status, seeking help and extroversion were the protective factors.

CONCLUSION

SHS is significantly associated with behavior and lifestyle-related factors. For comprehensively prevention and control of the SHS, it is urgently needed to reduce the risk factors and enhance the protective factors among adolescents.