Diabetes, Heart Disease, and Dementia: National Estimates of Functional Disability Trajectories

ObjectivesTo estimate the associations between diabetes, heart disease, and dementia, which may increase the difficulty of self-care; model functional disability trajectories jointly with attrition (death or dropout) over 5 years. DesignPopulation-based complex survey design. SettingNational Health and Aging Trends Study. ParticipantsCommunity-dwelling Medicare beneficiaries aged 65 and older (N=7,609). MeasurementsNational estimates were generated using sampling weights. Sociodemographic characteristics, self-reported physician-diagnosed chronic conditions, six activities of daily living (ADL), and cognitive status were ascertained in annual in-person interviews. A joint model using group-based trajectory modeling was used to estimate the number of ADL disabilities and attrition probability. Multinomial logistic regression with survey weights was used to estimate the association between diabetes, heart disease, and dementia and resultant trajectories of disability, with the least disabled trajectory used as a reference. ResultsThree functional disability trajectories were identified: 26.9 million (76.3%) individuals with no disability and a constant study attrition of 14.3%, 4.9 million (13.9%) with mild and increasing disability and 12% attrition in 2012 and 27.2% in 2015, and 3.4 million (9.7%) with severe and increasing disability and 25.4% attrition in 2012 and 35% in 2015. Persons with possible dementia, possible dementia and diabetes, or possible dementia with diabetes and heart disease had significantly greater odds of being on the mild disability trajectory than those with no disability. Persons with probable dementia, representing more than 1.5 million persons, regardless of concurrent conditions, had significantly greater odds of being on the severe disability trajectory than on the no disability trajectory. ConclusionsMethods that generate national estimates and account for attrition and for multiple chronic conditions and cognitive status may be useful for health policy-makers to make decisions on care provisions and services.