Date of Conferral

2022

Degree

Ph.D.

School

Public Health

Advisor

Clarence Schumaker

Abstract

A few promising studies have indicated that activities of daily life (ADL) may be a useful way of predicting Alzheimer’s Disease (AD). However, the existing cross-sectional studies fail to show how ADLs in early years predict AD, and how social factors influence health either in addition to or in interaction with individual risk factors. Using a social epidemiology framework, this study examined the relationship between early years’ ADL and the development of AD in later years. This quantitative study included 4,526 participants derived from the Health and Retirement Study (HRS) dataset. The dependent variable was whether the participant has been diagnosed with AD. The independent variables were the ADL indices and changes in ADL indices. A four-step multilevel regression model approach was used to address the research questions. The results suggested that the only significant predictor of the onset of AD was changes in early years’ ADL (b = 20.253, z = 2.761, p < .05). However, the result of the sensitivity analysis (b = 7.562, z = 1.900, p = .058), which included more control variables and increased the observation period of ADL, did not support this finding. The results suggested that the variances of random effects varied by Level-2 variables associated with random slopes were approximately zero; thus, early years’ ADL variable was not influenced by sociodemographic factors. Findings indicated that an increase in changes in ADL leads to an increase in the probability of onset AD in the future. Implications for positive social change include identifying the predictors of AD that may help isolate causes and target screening to those at the highest risk.

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