Lauren Thomas Berube

Clinical Assistant Professor of Public Health Nutrition

Professional overview

Lauren Berube, PhD, MS, RDN, is a nutrition and behavioral scientist. With clinical training as a dietitian, she has expertise in medical nutrition therapy and dietary assessment. Her research identifies predictors and outcomes of prenatal, postpartum, and childhood health behaviors, with a focus on understanding how dietary patterns contribute to cardiometabolic health outcomes. She uses technology and personalized approaches to engage clinical populations in self-management and lifestyle behavior change. She has worked on several clinical trials and implementation studies related to maternal and child health, including a primary healthcare-based child obesity prevention intervention beginning in pregnancy, a mobile health intervention for management of gestational diabetes in Nepal, and an observational study that used continuous glucose monitoring to measure the glycemic profiles of individuals with gestational diabetes. During her postdoctoral training, she was engaged in clinical trials that utilized behavioral methods and technology to deliver personalized nutrition interventions for adults with prediabetes and type 2 diabetes.  

Prior to joining GPH, she worked as an Associate Research Scientist at the Institute for Excellence in Health Equity at New York University Grossman School of Medicine, where she managed a maternal health community implementation project delivered digitally by community health workers using culturally responsive text messaging and video links.

Dr. Berube received her PhD from New York University and completed postdoctoral training at New York University Grossman School of Medicine.

Education

BS, Biology, Roanoke College

MS, Food Science and Technology, Cornell University

PhD, Nutrition and Dietetics, New York University

Postdoctoral Fellow, Population Health Science Scholars Program, New York University

Honors and awards

Ruth L. Kirschstein Institutional National Research Service Award, National Institute of Health (2021202220232024)

Outstanding Dissertation Award Nominee, New York University (2019)

Research and Travel Grant, New York University (2018)

Steinhardt Graduate Scholarship, New York University (201320142015)

Gary Wesley Leonard Memorial Award in Biology, Roanoke College (2010)

Publications

Publications

Baseline Characteristics of Weight-Loss Success in a Personalized Nutrition Intervention: A Secondary Analysis

Weight loss is associated with improved daytime time in range in adults with prediabetes and non-insulin-treated type 2 diabetes undergoing dietary intervention

Development and Testing of a Mobile App for Management of Gestational Diabetes in Nepal: Protocol for a User-Centered Design Study and Exploratory Randomized Controlled Trial

Diabetes Telemedicine Mediterranean Diet (DiaTeleMed) Study: study protocol for a fully remote randomized clinical trial evaluating personalized dietary management in individuals with type 2 diabetes

Prenatal Dietary Patterns and Associations With Weight-Related Pregnancy Outcomes in Hispanic Women With Low Incomes

A randomized clinical trial comparing low-fat with precision nutrition–based diets for weight loss: impact on glycemic variability and HbA1c

Effect of a Personalized Diet to Reduce Postprandial Glycemic Response vs a Low-fat Diet on Weight Loss in Adults with Abnormal Glucose Metabolism and Obesity: A Randomized Clinical Trial

Popp, C. J., Hu, L., Kharmats, A. Y., Curran, M., Berube, L., Wang, C., Pompeii, M. L., Illiano, P., St-Jules, D. E., Mottern, M., Li, H., Williams, N., Schoenthaler, A., Segal, E., Godneva, A., Thomas, D., Bergman, M., Schmidt, A. M., & Sevick, M. A. (n.d.).

Publication year

2022

Journal title

JAMA network open

Volume

5

Issue

9

Page(s)

E2233760

10.1001/jamanetworkopen.2022.33760

Abstract

Abstract

Importance: Interindividual variability in postprandial glycemic response (PPGR) to the same foods may explain why low glycemic index or load and low-carbohydrate diet interventions have mixed weight loss outcomes. A precision nutrition approach that estimates personalized PPGR to specific foods may be more efficacious for weight loss. Objective: To compare a standardized low-fat vs a personalized diet regarding percentage of weight loss in adults with abnormal glucose metabolism and obesity. Design, Setting, and Participants: The Personal Diet Study was a single-center, population-based, 6-month randomized clinical trial with measurements at baseline (0 months) and 3 and 6 months conducted from February 12, 2018, to October 28, 2021. A total of 269 adults aged 18 to 80 years with a body mass index (calculated as weight in kilograms divided by height in meters squared) ranging from 27 to 50 and a hemoglobin A1clevel ranging from 5.7% to 8.0% were recruited. Individuals were excluded if receiving medications other than metformin or with evidence of kidney disease, assessed as an estimated glomerular filtration rate of less than 60 mL/min/1.73 m2using the Chronic Kidney Disease Epidemiology Collaboration equation, to avoid recruiting patients with advanced type 2 diabetes. Interventions: Participants were randomized to either a low-fat diet (<25% of energy intake; standardized group) or a personalized diet that estimates PPGR to foods using a machine learning algorithm (personalized group). Participants in both groups received a total of 14 behavioral counseling sessions and self-monitored dietary intake. In addition, the participants in the personalized group received color-coded meal scores on estimated PPGR delivered via a mobile app. Main Outcomes and Measures: The primary outcome was the percentage of weight loss from baseline to 6 months. Secondary outcomes included changes in body composition (fat mass, fat-free mass, and percentage of body weight), resting energy expenditure, and adaptive thermogenesis. Data were collected at baseline and 3 and 6 months. Analysis was based on intention to treat using linear mixed modeling. Results: Of a total of 204 adults randomized, 199 (102 in the personalized group vs 97 in the standardized group) contributed data (mean [SD] age, 58 [11] years; 133 women [66.8%]; mean [SD] body mass index, 33.9 [4.8]). Weight change at 6 months was -4.31% (95% CI, -5.37% to -3.24%) for the standardized group and -3.26% (95% CI, -4.25% to -2.26%) for the personalized group, which was not significantly different (difference between groups, 1.05% [95% CI, -0.40% to 2.50%]; P =.16). There were no between-group differences in body composition and adaptive thermogenesis; however, the change in resting energy expenditure was significantly greater in the standardized group from 0 to 6 months (difference between groups, 92.3 [95% CI, 0.9-183.8] kcal/d; P =.05). Conclusions and Relevance: A personalized diet targeting a reduction in PPGR did not result in greater weight loss compared with a low-fat diet at 6 months. Future studies should assess methods of increasing dietary self-monitoring adherence and intervention exposure. Trial Registration: ClinicalTrials.gov Identifier: NCT03336411.

Associations between chronic cigarette smoking and taste function: Results from the 2013–2014 national health and nutrition examination survey

Self-reported olfactory dysfunction and diet quality: Findings from the 2011–2014 national health and nutrition examination survey (nhanes)

Predictors of gestational weight gain in a low-income hispanic population: Sociodemographic characteristics, health behaviors, and psychosocial stressors

Total and trimester-specific gestational weight gain and infant anthropometric outcomes at birth and 6 months in low-income Hispanic families

Correlates of Prenatal Diet Quality in Low-Income Hispanic Women

Concerns About Current Breast Milk Intake Measurement for Population-Based Studies

Diet quality of individuals with rheumatoid arthritis using the healthy eating index (HEI)-2010

Lifestyle behaviors affecting bone health in young hispanic and Non-Hispanic white women