The impact of socioeconomic status and sleep quality on the prevalence of multimorbidity in older adults

Xue, Bai; Xue, Yaqing; Dong, Fang; Zheng, Xiao; Shi, Lei; Xiao, Shujuan; Zhang, Jiachi; Ou, Weiyan; Wang, Qi; Zhang, Chichen

doi:10.3389/fpubh.2022.959700

Cited by 12 publications

(8 citation statements)

References 47 publications

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“…These unhealthy habits are recognized as factors associated with chronic diseases (27). Moreover, an increased risk of chronic diseases was associated with more medical visits.…”

Section: Discussionmentioning

confidence: 99%

Association of Adverse Childhood Experiences and Catastrophic Health Expenditures in China: Evidence from the China Health and Retirement Longitudinal Study (CHARLS)

Yu,

Xie,

et al. 2024

Preprint

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Background: Associations between adverse childhood experiences (ACEs) and catastrophic health expenditures (CHEs) among middle-aged or older Chinese individuals have not been well documented. In addition, the role of chronic diseases is not entirely clear. This study was conducted using data from the China Health and Retirement Longitudinal Study (CHARLS) to examine association of ACEs with hospital visits and medical expenditures and the mediating effect of chronic diseases. Methods: Negative binomial regression models were used to assess associations of the ACEs with the number of outpatient visits and inpatient hospital days. Logistic regression models were used to assess associations between the ACEs and catastrophic health expenditures (CHEs). The influence of chronic diseases is discussed by mediating analysis. Results: The prevalence of each ACE indicator ranges from 0.27% (incarcerated household member) to 31.5% (emotional neglect). Moreover, 75.18% were exposed to at least one ACE. Our main analysis identified a significant dose–response relationship for the cumulative ACE scores and the number of outpatient visits (p-trend < 0.001), inpatient hospital days (p-trend < 0.001), and CHEs (p-trend < 0.001). After adjusting for chronic diseases, the dose-response relationship between ACEs and inpatient hospital days was not significant (p-trend = 0.305), but was still significant with outpatient visits and catastrophic health expenditures. Conclusions:Populations with more ACEs are predisposed to chronic diseases, which consequently lead to higher medical expenditures and incur greater economic burdens. It is necessary to formulate corresponding policies to provide catastrophe health services and financial risk protection for different numbers and types of chronic diseases.

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“…These unhealthy habits are recognized as factors associated with chronic diseases (27). Moreover, an increased risk of chronic diseases was associated with more medical visits.…”

Section: Discussionmentioning

confidence: 99%

Association of Adverse Childhood Experiences and Catastrophic Health Expenditures in China: Evidence from the China Health and Retirement Longitudinal Study (CHARLS)

Yu,

Xie,

et al. 2024

Preprint

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“…Previous authors had analysed a unidirectional association between sleep quality and multimorbidity, and a majority of their studies were congruent with our study. For example, a cross-sectional study on 3250 individuals aged 60 years and older in Shanxi Province of China showed that poor sleep quality was associated with the prevalence of multimorbidity (OR = 2.445; 95% CI, 2.043–2.927) [ 21 ], and a recent longitudinal study also indicated that poor sleep quality correlated with an increased risk of multimorbidity (RR: 1.750; 95% CI, 1.476–2.076) [ 18 ]. Regarding sleep duration and multimorbidity, previous studies have shown that short sleep duration increased the risk of cardiovascular diseases [ 22 ], hypertension [ 23 ], and asthma [ 24 ].…”

Section: Discussionmentioning

confidence: 99%

Bidirectional associations between sleep quality/duration and multimorbidity in middle-aged and older people Chinese adults: a longitudinal study

Wang,

Zhang

2024

BMC Public Health

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Background Multimorbidity and sleep disorder possess high incidence rates in the middle-aged and older people populations, posing a significant threat to quality of life and physical and mental health. However, investigators have previously only analysed the unidirectional association between sleep status and multimorbidity. We aimed to investigate bidirectional associations between sleep quality or duration and multimorbidity in middle-aged and older Chinese adults from a longitudinal perspective. Method We enrolled a total of 9823 participants 45 years and older from the China Health and Retirement Longitudinal Study from 2015 to 2018 in our study. Multimorbidity was defined as two or more coexisting chronic diseases in the same individual based on 14 self-reported disease questions. Sleep quality was classified as “good” (restless < 1 day per week) and “poor” (restless ≥ 1 days per week); and sleep duration was divided into short (< 6 h), medium (6–9 h), and long (> 9 h). The bidirectional association between multimorbidity and sleep condition was examined using multivariate logistic regression models with adjustments for covariates. Results Individuals with poor sleep quality showed a significantly higher prevalence of multimorbidity in the future. The adjusted OR (95% CI) values of individuals with poor sleep quality with respect to developing two diseases, three diseases, and ≥ 4 diseases were 1.39 (1.19, 1.63), 1.56 (1.23, 2.03), and 2.36 (1.68, 3.33), respectively. In addition, individuals with multimorbidity exhibited a significantly higher risk of poor sleep quality in the future. Short sleep duration led to multimorbidity in the future (OR = 1.49; 95 CI%, 1.37–1.63), while multimorbidity contributed to short sleep duration (< 6 h) in the future (OR = 1.39; 95% CI, 1.27–1.51) after full adjustment. Conclusions There was a bidirectional association between sleep quality or short sleep duration and multimorbidity in middle-aged and older Chinese adults. We recommend that greater attention be given to clinical management among adults with sleep disorders or physical multimorbidities.

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“…At the socioeconomic characteristic layer, having a primary education and below was considered to be risk factors for multimorbidity. The association between lower education and multimorbidity is unsurprising, given the well-established evidence that the knowledge and awareness of chronic disease prevention and the control of less educated people may be even lower, increasing the risk of developing multimorbidity [ 62 ]. At the macro-environmental characteristic layer, our study did not find an impact of the policy environment on older people with multimorbidity.…”

Section: Discussionmentioning

confidence: 99%

Patterns and Determinants of Multimorbidity in Older Adults: Study in Health-Ecological Perspective

Chen

Shi

Zheng

et al. 2022

IJERPH

Self Cite

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(1) Background: Multimorbidity has become one of the key issues in the public health sector. This study aims to explore the patterns and health-ecological factors of multimorbidity in China to propose policy recommendations for the management of chronic diseases in the elderly. (2) Methods: A multi-stage random sampling method was used to conduct a questionnaire survey on 3637 older adults aged 60 and older in Shanxi, China. Association rule mining analysis (ARM) and network analysis were applied to analyze the patterns of multimorbidity. The health-ecological model was adopted to explore the potential associated factors of multimorbidity in a multidimensional perspective. A hierarchical multiple logistic model was employed to investigate the association strengths reflected by adjusted odds ratios and 95% confidence. (3) Results: Multimorbidity occurred in 20.95% of the respondents. The graph of network analysis showed that there were 6 combinations of chronic diseases with strong association strengths and 14 with moderate association strengths. The results of the ARM were similar to the network analysis; six dyadic chronic disease combinations and six triadic ones were obtained. Hierarchical multiple logistic regression indicated that innate personal traits (age, history of genetics, and body mass index), behavioral lifestyle (physical activity levels and medication adherence), interpersonal network (marital status), and socioeconomic status (educational level) were the common predictors of multimorbidity for older adults, among which, having no family history was found to be a relative determinant as a protective factor for multimorbidity after controlling the other covariates. (4) Conclusions: multimorbidity was prevalent in older adults and most disease combinations are associated with hypertension, followed by diabetes. This shows that diabetes and hypertension have a high prevalence among older adults and have a wide range of associations with other chronic diseases. Exploring the patterns and associated factors of multimorbidity will help the country prevent complications and avoid the unnecessary use of the health service, adopting an integrated approach to managing multimorbidity rather than an individual disease-specific approach and implementing different strategies according to the location of residence.

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The impact of socioeconomic status and sleep quality on the prevalence of multimorbidity in older adults

Cited by 12 publications

References 47 publications

Association of Adverse Childhood Experiences and Catastrophic Health Expenditures in China: Evidence from the China Health and Retirement Longitudinal Study (CHARLS)

Association of Adverse Childhood Experiences and Catastrophic Health Expenditures in China: Evidence from the China Health and Retirement Longitudinal Study (CHARLS)

Bidirectional associations between sleep quality/duration and multimorbidity in middle-aged and older people Chinese adults: a longitudinal study

Patterns and Determinants of Multimorbidity in Older Adults: Study in Health-Ecological Perspective

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