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A Machine Learning Approach to Design an Efficient Selective Screening of Mild Cognitive Impairment
Published on: January 11, 2020
Occupational gaps and mild cognitive impairment among older workers
Shoma Akaida1,2, Osamu Katayama3, Ryo Yamaguchi3
1Department of Preventive Gerontology, Center for Gerontology and Social Science, National Center for Geriatrics and Gerontology, 7-430 Morioka-cho, Obu City, Aichi, 474-8511, Japan. akaida@ncgg.go.jp.
Purpose:
This study aimed to investigate the association between currently employed but unwilling to remain employed (occupational gaps) and mild cognitive impairment (MCI) in older workers.
Methods:
A cross-sectional analysis was conducted on 2272 workers aged 65 years and older (mean age: 71.2 years, 52.2% male) who participated in a large community-based cohort study from 2017 to 2018. MCI was assessed using the National Center for Geriatrics and Gerontology-Functional Assessment Tool, which measures four cognitive domains: memory, attention, executive function, and processing speed. Participants with a decline ≥ 1.5 standard deviations below the age- and education-adjusted norms in one or more domains were classified as having MCI. Occupational gaps were categorized into two groups based on self-reported willingness to work. Logistic regression analysis was performed with MCI as the dependent variable and occupational gaps as the independent variable, and adjusted for covariates.
Results:
Among older workers, 18.0% experienced MCI and 46.1% experienced occupational gaps. The proportion of individuals with occupational gaps was 44.2% in the non-MCI group and 54.6% in the MCI group, with a significantly higher proportion in the MCI group (p < 0.001). Logistic regression analysis revealed a significant association between occupational gaps and MCI (odds ratio 1.44, 95% confidence interval 1.15-1.80).
Conclusion:
The findings suggest that occupational gaps may be associated with MCI in older workers.
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