Trends of Multimorbidity Patterns over 16 Years in Older Taiwanese People and Their Relationship to Mortality

Ho, Hsin-En; Yeh, Chih‐Jung; Wei, James Cheng‐Chung; Chu, Wei‐Min; Lee, Meng-Chih

doi:10.3390/ijerph19063317

Cited by 10 publications

(15 citation statements)

References 36 publications

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“…We called the four multimorbidity patterns from our previous work, which showed the comorbidity components of each multimorbidity pattern and the consistency through following years. 21 Table 1 shows the demographic and clinical characteristics of the participants with their distinct multimorbidity patterns and frailty status in 1996. The mean age was highest for those in the Arthritis-cataract group with frailty.…”

Section: Resultsmentioning

confidence: 99%

“…Both model fit (lower AIC or BIC values) and interpretability were used to select the most appropriate model. We called the four multimorbidity patterns from our previous work, which showed the comorbidity components of each multimorbidity pattern and the consistency through following years 21 …”

Section: Resultsmentioning

confidence: 99%

“…However, in our previous study we examined the trends of multimorbidity patterns over a period of 16 years and found that disease patterns remained similar in five waves of data. 21 Thus, we assumed that the constructure of disease groups would be similar in the following years. Second, data from the TLSA were self-reported, which could lead to report bias.…”

Section: Discussionmentioning

confidence: 99%

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Additive effect of frailty with distinct multimorbidity patterns on mortality amongst middle‐aged and older adults in Taiwan: A 16‐year population‐based study

Chu

Yeh

et al. 2023

Geriatrics Gerontology Int

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AimThis study aimed to explore the association between multimorbidity patterns with/without frailty and future mortality among Taiwanese middle‐aged and older adults through a population‐based cohort study design.MethodsData were collected from the Taiwan Longitudinal Study on Aging. The data were obtained from Wave 3, with the multimorbidity patterns in the years of 1996 being analyzed through latent class analysis. Frailty was defined using the modified Fried criteria. The association between each disease group with/without frailty and mortality was examined using logistic regression, with the reference group as the Relatively healthy group without frailty. Survival analysis was performed using Cox regression, and the follow‐up period of mortality was from 1 January 1996 to 31 December 2012.ResultsA total of 4748 middle‐aged and older adults with an average age of 66.3 years (SD: 9.07 years) were included. Four disease patterns were identified in 1996, namely the Cardiometabolic (21.0%), Arthritis‐cataract (11.9%), Relatively healthy (61.6%), and Multimorbidity (5.5%) groups. After adjusting for all covariates, the Relatively healthy group with frailty showed the highest risk for mortality (odds ratio: 3.66, 95% confidence interval [95% CI]: 2.24–5.95), followed by the Cardiometabolic group with frailty (odds ratio: 3.58, 95% CI: 1.96–6.54), Multimorbidity group with frailty (odds ratio: 2.28, 95% CI: 1.17–4.44), Multimorbidity group without frailty (odds ratio: 1.44, 95% CI: 1.01–2.04), and the Cardiometabolic group without frailty (odds ratio: 1.24, 95% CI: 1.04–1.49).ConclusionsFrailty plays an important role in mortality among middle‐aged and older adults with distinct multimorbidity patterns. Middle‐aged and older adults with a relatively healthy multimorbidity pattern or a cardiometabolic multimorbidity pattern with frailty encountered dismal outcomes. Geriatr Gerontol Int 2023; ••: ••–••.

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Section: Resultsmentioning

confidence: 99%

Section: Resultsmentioning

confidence: 99%

Section: Discussionmentioning

confidence: 99%

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Additive effect of frailty with distinct multimorbidity patterns on mortality amongst middle‐aged and older adults in Taiwan: A 16‐year population‐based study

Chu

Yeh

et al. 2023

Geriatrics Gerontology Int

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“…This finding suggests that there is a clear geographic concentration in sports technology research on older adults’ technology acceptance models. Ho et al’s research showed that Taiwan became an aging society in 2018, and it is expected that it will become a super-aging society in 2025 [ 38 ]. The aging population is growing rapidly, and health problems will also increase.…”

Section: Discussionmentioning

confidence: 99%

The Technology Acceptance Model and Older Adults’ Exercise Intentions—A Systematic Literature Review

Yau

Hsiao

2022

Geriatrics

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Aging is a global phenomenon, and the use of exercise technology by older adults can help them to prevent disease, achieve good health, and ultimately achieve successful aging. In the past, there literature compilation studies have been conducted on sports technology and young people or on the use of technology by the older adults; however, no studies have determined the attitudes of older adults toward sports technology. This review applied a systematic literature analysis to determine the factors that correlate the technology acceptance model with the older population’s exercise attitudes. A total of 10 studies were identified as contributing to the use of exercise technology by older adults. The main findings of this review are that, of the 28 factors identified in the 10 studies, only 18 were identified as factors influencing older adults’ use of sports technology in the technology acceptance model (TAM). Among these, fifteen factors affected intention, four factors affected perceived ease of use, three factors affected perceived usefulness, and two factors affected attitudes. Finally, discussing the related factors affecting TAM allows us to provide suggestions for future research directions.

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“…These disease combinations could be named the cardio-metabolic pattern, cardio-degenerative pattern, and metabolic-degenerative pattern. It had been established in previous studies that the above multimorbidity pattern had similar risk factors and pathophysiology [ 48 , 49 , 50 ]. It could be hypothesized that if individuals are affected by HTN or DM, they are more likely to accumulate other metabolic or degenerative morbidities, such as high cholesterol, CAD, osteoporosis, etc.…”

Section: Discussionmentioning

confidence: 99%

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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Trends of Multimorbidity Patterns over 16 Years in Older Taiwanese People and Their Relationship to Mortality

Cited by 10 publications

References 36 publications

Additive effect of frailty with distinct multimorbidity patterns on mortality amongst middle‐aged and older adults in Taiwan: A 16‐year population‐based study

Additive effect of frailty with distinct multimorbidity patterns on mortality amongst middle‐aged and older adults in Taiwan: A 16‐year population‐based study

The Technology Acceptance Model and Older Adults’ Exercise Intentions—A Systematic Literature Review

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

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