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Geriatric Health Charts for Individual Assessment and Prediction of Care Needs: A Population-Based Prospective Study
Stockholm University, Faculty of Social Sciences, Aging Research Center (ARC), (together with KI).ORCID iD: 0000-0001-9064-9222
Stockholm University, Faculty of Social Sciences, Aging Research Center (ARC), (together with KI). Catholic University of Rome, Italy.
Stockholm University, Faculty of Social Sciences, Aging Research Center (ARC), (together with KI). Karolinska University Hospital, Sweden; Stockholm Gerontology Research Center, Sweden.ORCID iD: 0000-0001-5819-8724
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Number of Authors: 62020 (English)In: The journals of gerontology. Series A, Biological sciences and medical sciences, ISSN 1079-5006, E-ISSN 1758-535X, Vol. 75, no 1, p. 131-138Article in journal (Refereed) Published
Abstract [en]

Background: Geriatric health charts that are similar to pediatric growth charts could facilitate monitoring health changes and predicting care needs in older adults. We aimed to validate an existing composite score (Health Assessment Tool [HAT]) and provide provisional age-specific reference curves for the general older population.

Methods: Data came from the Swedish National study on Aging and Care in Kungsholmen (N = 3,363 participants aged 60 years and over examined clinically at baseline and 3 years later). HAT was validated by exploring its relationship with health indicators (logistic regression) and comparing its ability to predict care consumption with that of two of its components, morbidity and disability (receiver operating characteristic curve areas). A flowchart was developed to obtain individual-level HAT scores (nominal response method). Sex-specific health charts were derived by graphing seven percentile curves of age-related HAT change (logistic quantile regression).

Results: HAT scores above the age- and sex-specific median were related to good performance in chair-stand tests (odds ratio [OR] = 2.62, 95% confidence interval [CI]: 2.07-3.31), balance and grip tests (interaction balance grip test, OR = 1.15, 95% CI: 1.05-1.25), and good self-rated health (OR = 2.19, 95% CI: 1.77-2.71). Receiver operating characteristic curve areas (HAT vs number of chronic disorders) were formal care, 0.76 versus 0.58 (p value < .001); informal care, 0.74 versus 0.59 (p value < .001); hospital admission, 0.70 versus 0.66 (p value < .001); primary care visits, 0.71 versus 0.69 (p value > .05); and specialty care visits, 0.62 versus 0.65 (p value < .001). HAT consistently predicted medical and social care service use better than disability.

Conclusions: HAT is a valid tool that predicts care consumption well and could be useful in developing geriatric health charts to better monitor health changes in older populations.

Place, publisher, year, edition, pages
2020. Vol. 75, no 1, p. 131-138
Keywords [en]
Health assessment tool, Physical function, Cognitive function, Multimorbidity, Disability
National Category
Geriatrics
Identifiers
URN: urn:nbn:se:su:diva-182930DOI: 10.1093/gerona/gly272ISI: 000537440300019PubMedID: 30517610OAI: oai:DiVA.org:su-182930DiVA, id: diva2:1446652
Available from: 2020-06-24 Created: 2020-06-24 Last updated: 2022-03-23Bibliographically approved

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Calderón-Larrañaga, AmaiaWelmer, Anna-Karin

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