Abstract MPTU12: Impact of the DASH4D Diet on Post-prandial Glucose Patterns assessed by Continuous Glucose Monitoring in Adults with Type 2 Diabetes

J Joseph Sartini (Johns Hopkins University, Baltimore, Maryland, United States) M Mary Rooney (Johns Hopkins University, Baltimore, Maryland, United States) D Dan Wang C Casey Rebholz (JOHNS HOPKINS UNIVERSITY, Baltimore, Maryland, United States) J Justin Echouffo (Johns Hopkins Hospital, Baltimore, Maryland, United States) C Christine Mitchell (Johns Hopkins University, Baltimore, Maryland, United States) H Hsin-Chieh Yeh (Johns Hopkins University, Baltimore, Maryland, United States) L Lawrence Appel (Johns Hopkins University, Baltimore, Maryland, United States) S Scott Pilla (Johns Hopkins University, Baltimore, Maryland, United States) S Scott Zeger (Johns Hopkins University, Baltimore, Maryland, United States) E Elizabeth Selvin (Johns Hopkins Bloomberg School of Public Health, Baltimore) M Michael Fang (Johns Hopkins Bloomberg School of Public Health, Baltimore)

Abstract

Introduction: In a recent randomized trial, we showed that a DASH-style diet optimized for adults with type 2 diabetes (DASH4D) reduced mean glucose assessed by continuous glucose monitoring (CGM). However, the impact of DASH4D on postprandial glycemic response (PPGR), or glucose dynamics following meal taking, is unclear. Objective: Quantify the effect of the DASH4D diet on the PPGR time series and evaluate the proportion of the overall glycemic benefit of the DASH4D diet attributable to PPGR. Methods: The DASH4D trial had a 4-period crossover design. Adults with type 2 diabetes were randomized to an order of four diets: DASH4D or a typical American dietary pattern (comparison), each with lower or higher sodium. Calories were adjusted to maintain a stable weight. As sodium was not expected to impact PPGR, we combined the lower and higher sodium arms within each diet. Feeding periods were 5 weeks, with ≥ 1 week break between periods. CGM devices were worn from the 3 rd to 5 th weeks, recording up to 14 days of data. In a subset of participants, staff recorded meal timing during CGM wear. We fit a functional model regressing the PPGR time series (CGM glucose 1 hour before to 4 hours after meal start time) on diet type, including participant-specific random effects and adjustment for age, sex, body mass index (BMI), and time of day. We also applied functional regression-based mediation analyses to estimate the proportion of the diet effect on mean glucose that was mediated by differences in PPGR. Results: We collected PPGR data from 768 meals across the 65 participants who consented to meal monitoring (median age 68 years, 66% female). The DASH4D diet reduced PPGR, ranging from a difference -4.5 mg/dL at meal onset to -14.7 mg/dL from 1-2 hours after the start of the meal ( Fig. 1a ). There was a significant difference in PPGR between the DASH4D and comparison diets over the entire observation period ( Fig. 1b ). Differences in PPGR mediated 88% of the overall effect of the DASH4D diet on CGM mean glucose ( Fig. 2 ). Conclusion: Among adults with type 2 diabetes, the DASH4D diet improved glycemic control primarily by reducing PPGR.

Article Details

Journal Circulation
Volume / Issue Vol. 153, Issue Suppl_1
Published March 24, 2026
ISSN 0009-7322
Publisher Lippincott Williams & Wilkins

Journal Info

Circulation

Lippincott Williams & Wilkins

ISSN: 0009-7322 Health Sciences

Authors (12)

J

Joseph Sartini

Johns Hopkins University, Baltimore, Maryland, United States

M

Mary Rooney

Johns Hopkins University, Baltimore, Maryland, United States

D

Dan Wang

C

Casey Rebholz

JOHNS HOPKINS UNIVERSITY, Baltimore, Maryland, United States

J

Justin Echouffo

Johns Hopkins Hospital, Baltimore, Maryland, United States

C

Christine Mitchell

Johns Hopkins University, Baltimore, Maryland, United States

H

Hsin-Chieh Yeh

Johns Hopkins University, Baltimore, Maryland, United States

L

Lawrence Appel

Johns Hopkins University, Baltimore, Maryland, United States

S

Scott Pilla

Johns Hopkins University, Baltimore, Maryland, United States

S

Scott Zeger

Johns Hopkins University, Baltimore, Maryland, United States

E

Elizabeth Selvin

Johns Hopkins Bloomberg School of Public Health, Baltimore

M

Michael Fang

Johns Hopkins Bloomberg School of Public Health, Baltimore