Longitudinal Patterns of Multiple Behavioral Risk Factors and Their Joint Effects on Cognitive Aging: Evidence from a 24-Year National Cohort - Project Summary/Abstract Dementia is a major and growing public health burden, affecting over 55 million people worldwide, with projections to nearly triple by 2050. Roughly one-third of dementia cases are attributable to modifiable lifestyle behaviors, emphasizing the need to clarify how multiple behaviors jointly shape risk. Physical inactivity, smoking, and obesity are established risk factors, yet evidence on alcohol use and social isolation remains inconsistent, often limited by single-timepoint measures, inadequate control for confounders, and failure to account for lifecourse dynamics. Health behaviors change across decades, influenced by aging, social context, and cohort effects, and interact in complex ways—for example, smoking cessation may increase BMI, while social isolation reinforces unhealthy trajectories. These interdependencies create cumulative behavioral pathways with long-term consequences for cognitive reserve and dementia risk, but few studies have examined such patterns over extended follow-up. This R03 project will leverage the Health and Retirement Study (HRS), a nationally representative longitudinal survey of U.S. adults age 51+, linked with neighborhood contextual data, to investigate how physical activity, smoking, alcohol use, BMI, and social isolation—coevolve and influence cognitive aging. Aim 1 will model longitudinal trajectories of individual behaviors and their demographic and neighborhood determinants. Aim 2 will identify joint multibehavioral trajectories to capture both protective and high-risk clusters. Aim 3 will evaluate cumulative and bidirectional associations between behavioral trajectories and cognitive decline, mild cognitive impairment (MCI), and dementia incidence (1998–2022). This study is innovative in applying a life-course perspective, integrating multiple behaviors simultaneously, incorporating heterogeneity by individual and residential characteristics, and employing a suite of complementary longitudinal and causal methods. By elucidating how behavioral patterns unfold and cluster over two decades, and how these trajectories differentially predict cognitive decline and dementia, this project will identify protective behavioral constellations, highlight high risk subgroups, and reveal critical windows for intervention. Findings will directly inform multi-domain strategies for dementia prevention and public health policy.
