# Statistical approaches for causal effect analysis of mid-life exposures on Alzheimer's disease and Alzheimer's disease related dementia

> **NIH NIH R03** · UNIVERSITY OF CALIFORNIA, SAN DIEGO · 2020 · $147,125

## Abstract

PROJECT SUMMARY/ABSTRACT
 This highly responsive R03 from a new investigator proposes to apply contemporary causal in-
ference methods to research in Alzheimer's disease (AD) and Alzheimer's disease related dementia
(ADRD), which are complex conditions whose causes and risk factors over a person's life time are not
well understood by the scientific community. This one will be a demonstration project using causal
inference methods to investigate the complex relationship between time-varying mid-life exposures
and late-life cognitive outcomes that are potentially related to Alzheimer's disease, in the presence of
time-varying confounders, and with time-varying mediators. As illustration we will consider the mid-
life alcohol exposure collected from the Honolulu Heart Program (HHP) and the cognitive outcomes
collected from the Honolulu-Asia Aging Study (HAAS), where a number of time-varying confounders
and time-varying mediator variables were also collected in both studies. Under this project we will
develop and implement statistical approaches to study: 1) the causal effect of time-varying mid-life
exposure on late-life cognitive outcomes; 2) the effects of time-varying mid-life exposure on late-life
cognitive outcomes mediated by time-varying physical well being variables; 3) the causal effect of
time-varying mid-life exposure on time to late-life moderate or severe cognitive impairment; 4) the
effects of time-varying mid-life exposure on time to late-life moderate or severe cognitive impairment
mediated by time-varying physical well being variables. Successful application of these methods will
shed light on the research field of causal effects of various life style and other exposures on the out-
comes of Alzheimer's disease and Alzheimer's disease related dementia, where the literature currently
presents inconsistent findings using traditional statistical approaches such as direct applications of tra-
ditional regression models. Statistical approaches developed under this proposal will be published in
scientific journals. In cases where software for certain analysis are not yet available, open source R
software packages will be implemented and made freely available to the public.

## Key facts

- **NIH application ID:** 9932870
- **Project number:** 5R03AG062432-02
- **Recipient organization:** UNIVERSITY OF CALIFORNIA, SAN DIEGO
- **Principal Investigator:** RONGHUI XU
- **Activity code:** R03 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2020
- **Award amount:** $147,125
- **Award type:** 5
- **Project period:** 2019-06-01 → 2022-03-31

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/9932870

## Citation

> US National Institutes of Health, RePORTER application 9932870, Statistical approaches for causal effect analysis of mid-life exposures on Alzheimer's disease and Alzheimer's disease related dementia (5R03AG062432-02). Retrieved via AI Analytics 2026-05-26 from https://api.ai-analytics.org/grant/nih/9932870. Licensed CC0.

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