4.7 Article

Predictors of Covid-19 level of concern among older adults from the health and retirement study

Journal

SCIENTIFIC REPORTS
Volume 12, Issue 1, Pages -

Publisher

NATURE PORTFOLIO
DOI: 10.1038/s41598-022-08332-8

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This longitudinal study aims to construct a prediction model for Covid-19 level of concern among U.S. older adults using socio-demographic, lifestyle, and health risk characteristics, and to examine the contributions of obesity-related cardiometabolic health characteristics. The study analyzed data from 2,872 participants in the Health and Retirement Study from 2006 to 2020. The results showed that diabetes, stroke, cardiometabolic risk factors and/or chronic conditions were associated with higher Covid-19 level of concern, while factors such as female sex, birth cohort, minority race, Hispanic ethnicity, total wealth, depressive symptoms, and education were associated with different levels of Covid-19 concern.
The purpose of this longitudinal study is to construct a prediction model for Covid-19 level of concern using established Covid-19 socio-demographic, lifestyle and health risk characteristics and to examine specific contributions of obesity-related cardiometabolic health characteristics as predictors of Covid-19 level of concern among a representative sample of U.S. older adults. We performed secondary analyses of existing data on 2872 2006-2020 Health and Retirement Study participants and examined 19 characteristics in relation to the outcome of interest using logistic regression and machine learning algorithms. In mixed-effects ordinal logistic regression models, a history of diabetes, stroke as well as 1-2 cardiometabolic risk factors and/or chronic conditions were associated with greater Covid-19 level of concern, after controlling for confounders. Female sex, birth cohort, minority race, Hispanic ethnicity and total wealth as well as depressive symptoms were associated with higher level of Covid-19 concern, and education was associated with lower level of Covid-19 concern in fully adjusted mixed-effects ordinal logistic regression models. The selected socio-demographic, lifestyle and health characteristics accounted for < 70% of the variability in Covid-19 level of concern based on machine learning algorithms. Independent risk factors for Covid-19 level of concern among U.S. older adults include socio-demographic characteristics and depressive symptoms. Advanced research is needed to identify relevant predictors and elucidate underlying mechanisms of observed relationships.

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