# Reducing cardiometabolic risk and promoting functional health in community-based elders with obesity and pre-diabetes: evaluating sustainable DPP follow-up strategies

> **NIH NIH R01** · UNIVERSITY OF PITTSBURGH AT PITTSBURGH · 2020 · $647,119

## Abstract

ABSTRACT
The confluence of obesity and pre-diabetes in older adults substantially increases the risk of diabetes, and
accelerates functional decline, multimorbidity, disability, and death. More research is needed to refine and
extend preventive interventions to reduce burden for elders and society. For over a decade efficacious 6- and
12-month Diabetes Prevention Program (DPP) lifestyle interventions have been translated successfully and
demonstrated positive impact. However, efforts to develop and evaluate potentially scalable programs
conforming to current guidelines for longer term DPP interventions (up to 24 months) and help a greater
proportion of enrollees achieve and sustain the recommended weight loss target of ≥ 5% are lacking. Our
scientific premise is that the evaluation of translational DPP interventions, which has centered largely on
strategies for weight loss induction, must be extended to include longer-term interventions that clearly
demonstrate durable weight, cardiometabolic and functional health benefits especially for vulnerable elders in
community-based settings. Our previous DPP-based research has documented the utility of telephone follow-
up after a 6-month DPP weight loss induction and shown that 63% of a 65-80 year old volunteer sample with
obesity and other risk factors were able to sustain ≥ 5% weight loss at 12-months. Despite good evidence that
longer duration lifestyle interventions yield better outcomes (reflected in the latest Medicare ruling) there are no
translational studies of 24-month long DPP interventions with older adults. We now propose to utilize
community based settings to examine whether we can sustain the impact of an elder-focused DPP approach
using potentially scalable treatment components over a 24-month period. We will recruit and enroll 65-80 year
old adults with obesity and pre-diabetes (N = 360) from a network of senior community centers that provide
aging services. The intervention program sequencing will be aligned with current Medicare policy. First, from 0-
6 months, experienced lifestyle coaches will administer a DPP-video intervention anchored primarily by
telephone coaching for all participants, at least 25% from ethnic/racial minority groups. Next, participants, will
be randomized (N = 180 per arm; stratified by weight loss of < or ≥ 5%) to one of two 18-month follow-up
conditions conducted between 6-24 months. We will compare the effects of (1) DPP-Sustained (DPP-S) and
(2) DPP-Minimal (DPP-M) on measures of weight/adiposity (the primary outcome) at 12, 18, and 24 months. In
addition, we will collect cardiometabolic, physical activity, physical function, psychosocial, behavioral and other
age-sensitive quality of life measures at 12 and 18 and 24 months. Medicare claims data will also be examined
for a proportion of the sample regarding medication use, outpatient, inpatient, and emergency visits and
enrollment/participation in elder-focused activity programs. This work, if successful, ...

## Key facts

- **NIH application ID:** 9843992
- **Project number:** 5R01DK114115-03
- **Recipient organization:** UNIVERSITY OF PITTSBURGH AT PITTSBURGH
- **Principal Investigator:** Elizabeth Mary Venditti
- **Activity code:** R01 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2020
- **Award amount:** $647,119
- **Award type:** 5
- **Project period:** 2018-01-01 → 2022-12-31

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/9843992

## Citation

> US National Institutes of Health, RePORTER application 9843992, Reducing cardiometabolic risk and promoting functional health in community-based elders with obesity and pre-diabetes: evaluating sustainable DPP follow-up strategies (5R01DK114115-03). Retrieved via AI Analytics 2026-05-23 from https://api.ai-analytics.org/grant/nih/9843992. Licensed CC0.

---

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