Association between Overweight, Obesity and the Prevalence of Multimorbidity among the Elderly: Evidence from a Cross-Sectional Analysis in Shandong, China

Hu, Fangfang; Xu, Lingzhong; Zhou, Jian; Zhang, Jiao; Gao, Zhaorong; Hong, Zhuang

doi:10.3390/ijerph17228355

Cited by 20 publications

(11 citation statements)

References 32 publications

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“…The rate of BMI ≥ 24 among older adults in China is 37.2%; this estimate is consistent with that recently reports ( 25 ) and is alarming ( 9 , 26 , 27 ). The prevalence rate of BMI ≥ 24 in this group is affected by sex, age, residence, marital status, per capita annual household income, years of education, and lifestyle choices.…”

Section: Discussionsupporting

confidence: 91%

Lifestyle choices mediate the association between educational attainment and BMI in older adults in China: A cross-sectional study

Wang

Ren

Chen

et al. 2022

Front. Public Health

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As the Chinese population ages, unhealthfully high body mass index (BMI) levels in older adults are becoming a public health concern as an unhealthfully high BMI is an ill-being condition and can contribute to the risk of disease. Education and lifestyle choices affect BMI; however, the evidence on the relationships and interactions among these factors remains unclear. This study aimed to investigate the mediating effect of lifestyle choices on educational attainment and BMI among older adults in China. Using the Chinese Family Panel Studies (CFPS) 2018 panel data, this study integrated personal- and family-level economic data libraries, including 7,359 adults aged ≥60 years. Lifestyle parameters included smoking amount and screen time. Height and weight values were used to calculate BMI. The chi-square test, binary logistic regression analysis, stepwise regression analysis, and bootstrapping mediating effect tests were used for data analysis. Single-factor chi-square test revealed differences in BMI levels among groups defined by sex, age, residence, marital status, per capita annual household income, education years, and lifestyle choices. Binary logistic regression showed that age, residence, education years, smoking amount, and screen time influenced BMI. Stepwise regression results showed that education years, smoking amount, and screen time were associated with BMI (t = 3.907, −4.902, 7.491, P < 0.001). The lifestyle variables had partial mediating effects on BMI. The mediating effect of lifestyle on BMI was 0.009, while smoking amount was 0.003, and screen time was 0.006. Unhealthfully high BMI levels are increasing among older adults in China and are affected by many factors. Lifestyle factors and educational attainment can interact, affecting BMI. Interventions should consider lifestyle factors and education attainment to help maintain healthy BMI and reduce unhealthfully high BMI incidence.

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Section: Discussionsupporting

confidence: 91%

Lifestyle choices mediate the association between educational attainment and BMI in older adults in China: A cross-sectional study

Wang

Ren

Chen

et al. 2022

Front. Public Health

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“…The current study focused on the prevalence, patterns, and determinants of multimorbidity in older adults based on the health-ecological model. The results of the study show that the prevalence of multimorbidity among the older population in our study was 20.95%, higher than the rate reported in the United Kingdom (19.0%) [ 40 ] and Nepal (14.0%) [ 41 ], generally consistent with the prevalence reported in the Canada Community Health Survey (27.4%) [ 26 ], but lower than that of a study from Shandong, China (34.7%) [ 42 ]. These disparities can be explained by different sociodemographic structures and disease patterns [ 43 ].…”

Section: Discussionsupporting

confidence: 89%

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

Chen

Shi

Zheng

et al. 2022

IJERPH

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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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“…While not well studied in the US, this association is robust across other populations. Studies in Canada and China have demonstrated a significant association between obesity in older adults and MM 8,11 . MM is also strongly associated with a decline in physical function, 12 cognitive status 13 and leads to a lower quality of life 14 .…”

Section: Introductionmentioning

confidence: 99%

The relationship between multimorbidity, obesity and functional impairment in older adults

Lynch

Petersen

Fanous

et al. 2022

J American Geriatrics Society

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Background Declining mortality rates and an aging population have contributed to increasing rates of multimorbidity (MM) in the United States. MM is strongly associated with a decline in physical function. Obesity is an important risk factor for the development of MM, and its prevalence continues to rise. Our study aimed to evaluate the associations between obesity, MM, and rates of functional limitations in older adults. Methods We analyzed body mass index (BMI) and self‐reported comorbidity data from 7261 individuals aged ≥60 years from the National Health and Nutrition Examination Surveys 2005–2014. Weight status was defined based on standard BMI categories. MM was defined as 2 or more comorbidities, while functional limitations were self‐reported. Adjusted logistic regression quantified the association between standard BMI categories and MM. We also examined the difference in the prevalence of limitations between those with and without MM. Results The overall proportion of individuals with concomitant MM and obesity was 27.0%. Compared to a normal BMI, older adults with obesity had higher odds of MM (Prevalence odds ratio 1.79, 95% CI 1.49, 2.12). Overall, 67.5% of patients with MM also reported a functional limitation, with rates of functional limitation increasing with increasing BMI. When evaluating functional limitations in those with MM by BMI class, 90% of patients classified as severely obese (BMI ≥40 kg/m2) with MM also had a concomitant functional limitation. Conclusions Compared to normal weight status, obesity is associated with an increased burden of MM and functional limitation among older adults. Our results underscore the importance of identifying and addressing obesity, MM, and functional limitation patterns and the need for evidence‐based interventions that address all three conditions in this population.

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Association between Overweight, Obesity and the Prevalence of Multimorbidity among the Elderly: Evidence from a Cross-Sectional Analysis in Shandong, China

Cited by 20 publications

References 32 publications

Lifestyle choices mediate the association between educational attainment and BMI in older adults in China: A cross-sectional study

Lifestyle choices mediate the association between educational attainment and BMI in older adults in China: A cross-sectional study

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

The relationship between multimorbidity, obesity and functional impairment in older adults

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