Dataset Information

Sex- and Age-Specific Associations Between Metabolic Syndrome and Future Functional Disability in the Japanese Older Population.

ABSTRACT: Whether the association between metabolic syndrome (MetS) and functional disability differs depending on sex or age remains unknown. To determine the association between MetS and functional disability in older people separately by sex and age groups. A total of 11 083 participants (4407 men and 6676 women) aged 65 years or over without functional disability were enrolled. MetS was defined according to the revised NCEP ATP III guidelines. Functional disability was defined by a new certification in the long-term care insurance in Japan. Cox proportional hazards models were used to assess the risk of functional disability with adjustment for possible confounding factors. Over the mean observation period of 10.5 years, 1282 men and 2162 women experienced functional disability. For those aged 65 to 74 years, HRs (95% CIs) for functional disability in the MetS group were 1.33 (1.07-1.66) in men and 1.15 (1.000-1.32) in women. For those aged 75 years or older, there was no significant association in men or women. In subjects with a severe care need level, there was a marginal significant association in men aged 65 to 74 years. Among the MetS components that independently increased the risk of functional disability were glucose intolerance and elevated blood pressure (men and women aged 65-74 years), obesity (women aged 65-74 years), and glucose intolerance (women aged 75 years or older). MetS contributed to an increase in a high risk of future functional disability among individuals aged 65 to 74 years. In this age group, improvement of lifestyle, health promotion and interventions for MetS from middle age may prevent future functional disability.

SUBMITTER: Takahashi N

PROVIDER: S-EPMC11348345 | biostudies-literature | 2024 Jan-Dec

REPOSITORIES: biostudies-literature

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Sex- and Age-Specific Associations Between Metabolic Syndrome and Future Functional Disability in the Japanese Older Population.

Takahashi Naomi N Tsubota-Utsugi Megumi M Takahashi Shuko S Yonekura Yuki Y Ohsawa Masaki M Kuribayashi Toru T Onoda Toshiyuki T Takanashi Nobuyuki N Sakata Kiyomi K Yamada Takehiko T Ogasawara Kuniaki K Omama Shinichi S Tanaka Fumitaka F Asahi Koichi K Ishigaki Yasushi Y Itabashi Ryo R Itamochi Hiroaki H Takahashi Fumiaki F Okayama Akira A Tanno Kozo K

Inquiry : a journal of medical care organization, provision and financing 20240101

Whether the association between metabolic syndrome (MetS) and functional disability differs depending on sex or age remains unknown. To determine the association between MetS and functional disability in older people separately by sex and age groups. A total of 11 083 participants (4407 men and 6676 women) aged 65 years or over without functional disability were enrolled. MetS was defined according to the revised NCEP ATP III guidelines. Functional disability was defined by a new certification i ...[more]

PMID: 39183635

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Project description:BackgroundThe prevalence of metabolic syndrome (MetS) in Japan, a super-aged society, is increasing and poses a major public health issue. Several studies have reported sex differences in the association between age and MetS prevalence. This study aimed to examine the association between age and the prevalence of MetS based on multiple screening criteria and MetS components by sex.MethodsWe used 6 years of individual-level longitudinal follow-up data (June 2012 to November 2018; checkup year: 2012-2017) of middle-aged and older adults aged 40-75 years in Japan (N = 161,735). The Joint Interim Statement criteria, International Diabetes Federation criteria, and another set of criteria excluding central obesity were used as the screening criteria for MetS. The prevalence of MetS and MetS components was cross-sectionally analyzed according to sex and age. A longitudinal association analysis of age, MetS, and MetS components by sex was performed using a multilevel logistic model, adjusted for lifestyle- and regional-related factors.ResultsSex differences were observed in the prevalence and association of MetS and MetS components. In all age groups, the prevalence of central obesity was higher among women, and the prevalence of high blood pressure and fasting glucose was higher among men (P < 0.001). The prevalence of high triglyceride and low high-density lipoprotein cholesterol was higher among women aged > 60 years (P < 0.05). Based on the criteria of the Joint Interim Statement and International Diabetes Federation, the prevalence of MetS was higher among women than in men aged > 55 years (P < 0.001). Men had a higher prevalence of MetS without central obesity than women in all age groups (P < 0.001). The odds ratio for MetS and MetS components with aging was greater among women than in men.ConclusionsMedical management should be based on the prevalence of MetS and its components according to sex and age. In particular, the high prevalence of MetS without central obesity in middle-aged and older Japanese men suggests that the adoption of the Joint Interim Statement criteria, which do not precondition central obesity, should be considered.

Project description:BackgroundIt is important to identify older adults at high risk of functional disability and to take preventive measures for them at an early stage. To our knowledge, there are no studies that predict functional disability among community-dwelling older adults using machine learning algorithms.ObjectiveTo construct a model that can predict functional disability over 5 years using basic machine learning algorithms.DesignA cohort study with a mean follow-up of 5.4 years.ParticipantsWe used data from the Japan Gerontological Evaluation Study, which involved 73,262 people aged ≥ 65 years who were not certified as requiring long-term care. The baseline survey was conducted in 2013 in 19 municipalities.Main measuresWe defined the onset of functional disability as the new certification of needing long-term care that was ascertained by linking participants to public registries of long-term care insurance. All 183 candidate predictors were measured by self-report questionnaires.Key resultsDuring the study period, 16,361 (22.3%) participants experienced the onset of functional disability. Among machine learning-based models, ridge regression (C statistic = 0.818) and gradient boosting (0.817) effectively predicted functional disability. In both models, we identified age, self-rated health, variables related to falls and posture stabilization, and diagnoses of Parkinson's disease and dementia as important features. Additionally, the ridge regression model identified the household characteristics such as the number of members, income, and receiving public assistance as important predictors, while the gradient boosting model selected moderate physical activity and driving. Based on the ridge regression model, we developed a simplified risk score for functional disability, and it also indicated good performance at the cut-off of 6/7 points.ConclusionsMachine learning-based models showed effective performance prediction over 5 years. Our findings suggest that measuring and adding the variables identified as important features can improve the prediction of functional disability.

Dataset Information

Sex- and Age-Specific Associations Between Metabolic Syndrome and Future Functional Disability in the Japanese Older Population.

Publications

Sex- and Age-Specific Associations Between Metabolic Syndrome and Future Functional Disability in the Japanese Older Population.

Similar Datasets

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