# Project 5 - Retention-Early Warniing

> **NIH NIH U19** · UNIVERSITY OF WISCONSIN-MADISON · 2020 · $638,322

## Abstract

ABSTRACT - Project 5 – Retention-Early Warning Project
This project builds on two lines of inquiry that are rarely integrated. First, we draw on prior research that has
investigated the impact of attrition in longitudinal studies of aging. Second, we incorporate research that has
probed the impact of “early warning” signs for later life health decline. Putting these together, we submit that
those lost to attrition over time are likely to have worse cross-time health profiles compared to continuing
participants (CP). The reasons for predicting greater decline among attriters are that: (a) they had more
extensive profiles of early warning markers at baseline – something we demonstrate with preliminary studies,
and (b) these starting vulnerabilities are expected to increase their risk for subsequent stress exposures as
well as worsening psychosocial profiles across time, the combination of which we hypothesize will account for
their greater mental and physical health decline over time compared to continuing participants (CP) in MIDUS.
To examine these issues, our specific aims are to: (1) locate and reinstate attriters from MIDUS 2 and 3 using
proven survey methods; (2) characterize longitudinal change in physical (including biomarkers) and mental
health between attriters and CP; and (3) test hypotheses about early warning vulnerabilities, subsequent stress
exposures, and worsening psychosocial profiles to account for differences in cross-time health between
attriters and CP. These aims will be accomplished by using high incentives and state of the art methods for
tracking and contacting attriters who will be given a condensed battery of psychosocial, cognitive, and health
assessments via personal home visits. We have excellent current contact information on 85% of MIDUS
attriters and expect to collect new data from about 20% (500–600 individuals) of the full attrition sample. Our
work stands in contrast to other longitudinal aging studies, which have concluded (using multiple imputation
methods) that attrition is not biasing obtained findings. We submit that these assertions may be problematic
when those lost to attrition are not missing at random, the case for which we seek to test. To sharpen
understanding of these differing accounts, we will examine findings on cross-time health from reinstated
attriters to CP to alternative findings derived from multiple imputation methods that adjust for attrition using
observed baseline data. We predict that multiple imputation will under-represent the magnitude of health
decline observed among reinstated attriters. Further, we will explore an alternative imputation strategy that
uses newly collected data on reinstated attriters to multiply impute values for attriters not reinstated. All such
comparisons will be preceded by analyses to assess the degree to which the 20% reinstated attriters are
representative of all attriters, and if necessary, correct for bias between the 20% and the 80%. To facilitate this
...

## Key facts

- **NIH application ID:** 9955140
- **Project number:** 5U19AG051426-05
- **Recipient organization:** UNIVERSITY OF WISCONSIN-MADISON
- **Principal Investigator:** CAROL D. RYFF
- **Activity code:** U19 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2020
- **Award amount:** $638,322
- **Award type:** 5
- **Project period:** — → 2022-09-29

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/9955140

## Citation

> US National Institutes of Health, RePORTER application 9955140, Project 5 - Retention-Early Warniing (5U19AG051426-05). Retrieved via AI Analytics 2026-05-28 from https://api.ai-analytics.org/grant/nih/9955140. Licensed CC0.

---

*[NIH grants dataset](/datasets/nih-grants) · CC0 1.0*