Chronic disease profiles of subjective memory complaints: a latent class analysis of older people in a rural Malaysian community

Yap, Kwong Hsia, Allotey, Pascale, Reidpath, Daniel D. and Warren, Narelle, (2020). Chronic disease profiles of subjective memory complaints: a latent class analysis of older people in a rural Malaysian community. Aging and Mental Health, 24(5), 709-716

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  • Sub-type Journal article
    Author Yap, Kwong Hsia
    Allotey, Pascale
    Reidpath, Daniel D.
    Warren, Narelle
    Title Chronic disease profiles of subjective memory complaints: a latent class analysis of older people in a rural Malaysian community
    Appearing in Aging and Mental Health
    Volume 24
    Issue No. 5
    Publication Date 2020
    Place of Publication London
    Publisher Taylor & Francis
    Start page 709
    End page 716
    Language eng
    Abstract Background: Subjective memory complaints (SMC) are common in the elderly and have been suggested as the first subtle sign of decline which can predict dementia. Cognitive decline is thought to be related to inflammatory processes similarly found in other chronic diseases and conditions such as stroke, heart disease and arthritis. This study aimed to examine the association of SMC with chronic diseases and the profile of these health conditions reported by a group of older adults. Methods: Data from a cross-sectional survey conducted from August 2013 and March 2014 was drawn from 6179 individuals aged 56 years and above. Multivariable logistic regression analyses were used to examine SMC’s relationship with individual chronic diseases (asthma, kidney disease, heart disease, stroke, arthritis, hypertension and diabetes) and multimorbidity. Latent class analysis (LCA) was used to identify the profile of health conditions. The effect of SMC was estimated in a multinomial logistic regression as part of the latent class model. Results: SMC was statistically significant in its association with asthma, stroke, heart disease, arthritis and multimorbidity in the fully controlled multivariable logistic regression models. Three health profiles were identified: low comorbidity (n = 4136, low rates in all health conditions), arthritis group (n = 860) and diabetes and hypertension group (n = 1183). SMC was associated with arthritis group (OR = 2.04, 95% CI = 1.51–2.75) and diabetes and hypertension group (OR = 1.22, 95% CI = 1.03–1.46). Conclusion: Adapting a combination of analytical approaches allows a better understanding in the assessment of SMC’s relationship with chronic diseases and the patterns of distribution of these health conditions.
    Keyword Health profile
    Subjective memory complaints
    Latent class analysis
    Population-based study
    Copyright Holder Taylor & Francis
    Copyright Year 2020
    Copyright type All rights reserved
    ISSN 13646915
    DOI https://doi.org/10.1080/13607863.2018.1550632
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    Created: Fri, 08 May 2020, 12:21:17 JST by Chido Nyaruwata on behalf of UNU IIGH