# Network for Advancing Methodological Research in Longitudinal Studies of Aging

> **NIH NIH U24** · UNIVERSITY OF MICHIGAN AT ANN ARBOR · 2024 · $388,052

## Abstract

Longitudinal studies of the population near, through and after the retirement stage, such as the Health
and Retirement Study (HRS), play an important role in aging research because they provide data from a life
course perspective, allowing researchers to make population-level causal inference. Because such data
collection is a social interaction between researchers and the population, the methods employed to collect
data in these studies need to accommodate societal changes. The aging population in the U.S. is
experiencing rapid changes. First, its racial, ethnic, and linguistic composition is being shifted by the
growing Hispanic and Asian American populations. Second, the reliance of this aging population on new
mobile and video technologies has been accelerated by the COVID-19 pandemic. At the same time, the
research environment for population-based data collection has also evolved, with an increased availability
of administrative records that can be integrated with survey data and the increased use of modern devices
for collecting anthropometric and biomarker data that can complement traditional, self-report survey data.
Researchers can capitalize on these naturally occurring trends and shape methodological innovations for
future longitudinal studies. For example, as the population has become accustomed to communicating via
electronic devices during the COVID-19 pandemic, population-based studies have transitioned from using
one interview mode to mixing modes, including web-based data collection and virtual interviewing.
Unfortunately, the methodological research on optimal data collection approaches for aging populations
that has been performed to date has several critical shortcomings: there is a notable lack of data on
minority subgroups, optimal approaches to obtaining consent for administrative record linkage and
biomarker data collection are unknown, methods for combatting increasing rates of attrition are needed,
and there is an absence of methodological research on the use of new technologies for data collection.
 We propose to form a network of internationally-renowned methodological and substantive experts who
are actively researching the benefits of new data collection methodologies in response to these societal
developments. The proposed network will meet regularly to shape methodological innovations specifically
for the measurement of aging populations and design studies that will produce evidence-based best
practices for this type of longitudinal measurement. There are a large number of influential longitudinal
studies of aging in the field at present that would stand to benefit from this type of coordinated, rigorous
methodological investigation of more efficient approaches to collecting longitudinal measures from (and for)
aging populations. Via a coordinated international program of training, consulting, thematic working group
meetings, and pilot research projects, we aim to set the agenda for methodological research on longi...

## Key facts

- **NIH application ID:** 10832595
- **Project number:** 5U24AG077012-03
- **Recipient organization:** UNIVERSITY OF MICHIGAN AT ANN ARBOR
- **Principal Investigator:** Sung-Hee Lee
- **Activity code:** U24 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2024
- **Award amount:** $388,052
- **Award type:** 5
- **Project period:** 2022-06-01 → 2027-03-31

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/10832595

## Citation

> US National Institutes of Health, RePORTER application 10832595, Network for Advancing Methodological Research in Longitudinal Studies of Aging (5U24AG077012-03). Retrieved via AI Analytics 2026-05-24 from https://api.ai-analytics.org/grant/nih/10832595. Licensed CC0.

---

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