{"database":"biostudies-literature","file_versions":[],"scores":null,"additional":{"omics_type":["Unknown"],"volume":["12(1)"],"submitter":["Beydoun HA"],"pubmed_abstract":["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 great"],"journal":["Scientific reports"],"pagination":["4396"],"full_dataset_link":["https://www.ebi.ac.uk/biostudies/studies/S-EPMC8921703"],"repository":["biostudies-literature"],"pubmed_title":["Predictors of Covid-19 level of concern among older adults from the health and retirement study."],"pmcid":["PMC8921703"],"pubmed_authors":["Weiss J","Hossain S","Zonderman AB","Beydoun MA","Beydoun HA","Gautam RS","Alemu BT"],"additional_accession":[]},"is_claimable":false,"name":"Predictors of Covid-19 level of concern among older adults from the health and retirement study.","description":"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 great","dates":{"release":"2022-01-01T00:00:00Z","publication":"2022 Mar","modification":"2025-04-18T13:46:15.449Z","creation":"2025-02-18T23:27:13.936Z"},"accession":"S-EPMC8921703","cross_references":{"pubmed":["35292672"],"doi":["10.1038/s41598-022-08332-8"]}}