Modeling approaches for estimating the effects of risk factors using longitudinal lifecourse exposure data in dementia research

Longitudinal data on risk factors at different ages across the lifecourse are essential for gaining important insights into how the timing and accumulation of exposure to risk factors influence the risk of Alzheimer's disease and related dementias (dementia). With increased interest in the exposome and lifecourse research questions, there have been commensurate increases in data sources and methodological approaches for answering these questions using empirical data. Methodological approaches developed within specific disciplines have largely remained within disciplinary silos, despite their potential for broader applications. By enumerating these approaches in a single place, we aim to expand discovery in lifecourse dementia research and help investigators align their research questions with appropriate analytic methods. In doing so, we seek to guide methodological decision-making and ensure that researchers use appropriate statistical tools to answer important questions about the exposome and lifecourse risk factors for dementia. HIGHLIGHTS: Longitudinal exposure data are valuable for exposome and lifecourse research on dementia. Multiple methodological approaches exist to analyze such data, with different assumptions, advantages, and disadvantages. Some methodological approaches have been used predominantly in specific disciplines but may have wider utility. Additional research is needed to integrate added complexity from the co-occurrence of multiple exposures into existing methods. Comparisons between methods help researchers make informed decisions on the appropriate method for a specific research question.