The Relationship between the Number of Daily Health-Related Behavioral Risk Factors and Sleep Health of the Elderly in China

Liu, Xiaojun; Chen, Jingshu; Zhou, Jiayi; Liu, Jianjian; Lertpitakpong, Chanida; Tan, Anran; Wu, Shaotang; Mao, Zongfu

doi:10.3390/ijerph16244905

Cited by 15 publications

(15 citation statements)

References 35 publications

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“…Our study found that HLS was negatively associated with the risk of OSA and three stratified analyses and five sensitivity analyses yielded similar consistent results, indicating that our results were robust and stable. Our findings on OSA were consistent with those reports on other sleep-related problems such as sleep disturbances [ 41 ] and sleep disruption [ 42 ], though the lifestyle components and overall effect indexes were different across these studies. Liu and colleagues defined five health-risk behaviors including current smoking, current drinking, unhealthy eating habits, insufficient leisure activities, and physical inactivity among the Chinese elderly, and found that the risk of sleep disturbances was positively correlated with the number of multiple health-risk behaviors [ 41 ].…”

Section: Discussionsupporting

confidence: 91%

“…Our findings on OSA were consistent with those reports on other sleep-related problems such as sleep disturbances [ 41 ] and sleep disruption [ 42 ], though the lifestyle components and overall effect indexes were different across these studies. Liu and colleagues defined five health-risk behaviors including current smoking, current drinking, unhealthy eating habits, insufficient leisure activities, and physical inactivity among the Chinese elderly, and found that the risk of sleep disturbances was positively correlated with the number of multiple health-risk behaviors [ 41 ]. A cross-sectional study among postmenopausal Iranian women found that the total score of ten lifestyle factors, including physical health, physical activity, weight control and nutrition, psychological health, spiritual health, social health, medications, and narcotics avoidance, illness prevention, accident prevention, and environmental health, was inversely related to sleep disruption [ 42 ].…”

Section: Discussionsupporting

confidence: 91%

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Association of healthy lifestyle with risk of obstructive sleep apnea: a cross-sectional study

et al. 2022

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Background No studies investigated the whole effect of modifiable lifestyle factors on OSA risk. This study aimed to examine the individual and combined effects of lifestyle factors on OSA risk among Chinese adults. Methods This cross-sectional study included 9733 participants aged 35 to 74 years from the baseline survey of Guangzhou Heart Study. OSA was evaluated by Berlin Questionnaire. The healthy lifestyle score (HLS), representing the overall effect of lifestyles, was derived from seven lifestyle factors: active smoking, passive smoking, alcohol, diet, waist-hip ratio, leisure-time physical activity, and mental status. Odds ratio (OR) with 95% confidence interval (CI) was calculated using the multivariate logistic regression model. Results 8107 participants were divided into the non-OSA group and 1626 participants into the OSA group. No passive smoking (OR 0.83, 95% CI 0.74–0.94), healthy waist-hip ratio (OR 0.67, 95% CI 0.58–0.77) and healthy mental status (OR 0.45, 95% CI 0. 29–0.73) were associated with a reduced risk of OSA after adjusting for confounders, while others not. Participants with higher HLS were negatively associated with OSA risk (P-trend < 0.001). In comparison to the participants with 0–3 HLS, the OR for participants with 4, 5, 6, and 7 HLS was 0.68 (95% CI 0.56–0.84), 0.71 (95% CI 0.59–0.86), 0.62 (95% CI 0.51–0.76) and 0.49 (95% CI 0.37–0.65) after adjusting for confounders. Every 1-score increment of HLS was associated with a 13% lower risk of OSA. Conclusions The results suggest that HLS reflecting the combined effect of multiple-dimensional lifestyle factors was inversely associated with OSA risk. Preventive strategies integrating multiple lifestyle factors may provide a more feasible approach for OSA prevention.

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Section: Discussionsupporting

confidence: 91%

Section: Discussionsupporting

confidence: 91%

Association of healthy lifestyle with risk of obstructive sleep apnea: a cross-sectional study

et al. 2022

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“…The data of this study were derived from China's Health-Related Quality of Life Survey for Older Adults 2018 (CHRQLS-OA 2018) [37]. The CHRQLS-OA 2018 was a cross-sectional survey conducted during the Chinese New Year in 2018, aiming to understand the status of health-related quality of life among Chinese older people aged 60 years old and over.…”

Section: Research Design and Participantsmentioning

confidence: 99%

Association between Personal Social Capital and Loneliness among Widowed Older People

Jiang

Hou

Hao

et al. 2020

IJERPH

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To explore the association between the personal social capital and loneliness among the widowed older adults in China. Data from 1497 widowed older adults were extracted from China’s Health-Related Quality of Life Survey for Older Adults 2018. The Chinese version of the Personal Social Capital Scale (PSCS-16) was used to evaluate the participants’ status of bonding and bridging social capital (BOC and BRC). Loneliness was assessed by the short-form UCLA Loneliness Scale (ULS-8). Multiple linear regression models were established to examine the relationship between social capital and loneliness. The BOC and BRC of rural widowed older people were significantly lower than those of widowed older people in urban areas, while loneliness of rural widowed older people was higher than that of widowed older people in urban areas. The result of the final model showed that loneliness of rural participants was significantly associated with both BOC (B = 0.141, p = 0.001) and BRC (B = −0.116, p = 0.003). The loneliness of the urban widowed sample had no association with both BOC and BRC (p > 0.05). These findings suggested that more social support and compassionate care should be provided to enrich the personal social capital and thus to reduce loneliness of widowed older adults, especially those in rural areas.

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“…The response rate for the offline survey was 85.26%. Details of the CHRQLS-OA 2018 are available in a previous work done by our team [26].…”

Section: Study Populationmentioning

confidence: 99%

Socioeconomic status, social capital, health risk behaviors, and health-related quality of life among Chinese older adults

Yang

Wang

Chen

et al. 2020

Health Qual Life Outcomes

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Background: There is limited knowledge on the mediating role of different health risk behavior on the relationship between social capital, socioeconomic status (SES), and health-related quality of life (HRQoL) in Chinese older adults. We conducted this study to (a) investigate the condition of health risk behaviors of the Chinese elderly, and (b) assess the relationship between SES, social capital, health risk behaviors, and HRQoL. Methods: A sample of 4868 adults aged 60 years and older were included in this study, from the China's Healthrelated Quality of Life Survey for Older Adults 2018. Participants' demographic characteristics, SES (education level, family income), health risk behaviors (smoking, alcohol consumption, physical inactivity, unhealthy dietary behavior, unhealthy weight, and sleep disorder) were collected. Social capital and HRQoL were assessed by the 16-item Personal Social Capital Scale (PSCS-16) and WHOQOL-Old, respectively. Structural equation modeling (SEM) was applied to examine the associations between variables. Results: The proportion of smoking, alcohol consumption, physical inactivity, unhealthy dietary behavior, unhealthy weight, and sleep disorder were 32.1, 36.3, 62.5, 45.7, 31.8, and 45.5%, respectively. Significant differences were observed in education level, family income, and social capital between elderly individuals with and without each of the six health risk behavior (all p-values < 0.05). Elderly individuals who reported smoking, physical inactivity, unhealthy dietary behavior, and sleep disorder had significantly lower HRQoL than those without these unhealthy behaviors (all p-values < 0.05). SEM analysis showed that SES and social capital positively associated with alcohol consumption. Social capital negatively associated with smoking, physical inactivity, unhealthy dietary behavior, and sleep disorder. SES negatively associated with smoking, physical inactivity, unhealthy dietary behavior, unhealthy weight, and sleep disorder. Smoking, physical inactivity, unhealthy dietary behavior, and sleep disorder correlated with poorer HRQoL. Conclusions: Chinese older adults demonstrated a high incidence of health risk behaviors, especially for physical inactivity (62.5%) and unhealthy dietary behavior (45.7%). Social capital and SES were correlated with the elderly's HRQoL, as well as with the health risk behaviors. Health risk behaviors played potential mediating role on the relationship between social capital, SES, and HRQoL in Chinese older adults.

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The Relationship between the Number of Daily Health-Related Behavioral Risk Factors and Sleep Health of the Elderly in China

Cited by 15 publications

References 35 publications

Association of healthy lifestyle with risk of obstructive sleep apnea: a cross-sectional study

Association of healthy lifestyle with risk of obstructive sleep apnea: a cross-sectional study

Association between Personal Social Capital and Loneliness among Widowed Older People

Socioeconomic status, social capital, health risk behaviors, and health-related quality of life among Chinese older adults

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