# Identifying Mechanisms of Peer Influence on Youth Weight-Related Behaviors

> **NIH NIH R01** · UNIVERSITY OF MASSACHUSETTS AMHERST · 2021 · $570,854

## Abstract

Summary
The United States has experienced a two to three fold increase in pediatric obesity since the 1970’s. To date,
school-based interventions to prevent and treat overweight and obesity have realized only limited success.
Many of these interventions are guided by health behavior theories and change strategies that address the
issue from multiple levels of influence. There is, however, limited information regarding peer influence on youth
weight status and weight-related behaviors, such as physical activity, screen time, and dietary patterns. A
growing body of literature suggests that such weight-related behaviors are similar among friends, but the
mechanisms underlying this clustering of behaviors remain unclear. Friends may influence each other, but also
similar students may become friends, or friends may be exposed to similar outside influences. A better
understanding of these phenomena would facilitate design of more effective interventions that can leverage the
power of peer influence. Therefore, the purpose of this proposed study is to identify these mechanisms of
action by collecting and analyzing social network and weight-related behavior data in a cohort of diverse young
adolescents during their middle school years (6th to 8th grade). We will distinctly measure networks of
interaction (whom the respondent spends his/her time with), sentiments (whom the respondent likes), and
organized activities (classes, clubs, and teams). Data will be collected several times each academic year
allowing us to analyze these processes in fine time grain and to use external changes in the organized
activities as natural experiments and quasi-experiments on social network structures and weight-related
behaviors. Stochastic Actor-Oriented Models will be used to rigorously analyze the co-evolution of the network
structure and weight-related behaviors. Using findings from those statistical analyses, Agent-Based
(simulation) Models will be developed to incorporate direct causal relationships and feedbacks as well as the
shapes of these effects over time. Such models will be used to simulate potential intervention scenarios on the
behaviors and ultimately, weight status. The proposed research will identify unique leverage points for
targeting and timing of WRB interventions. We anticipate that next generation WRB interventions will be able to
use the information obtained from this study to improve their ability to prevent excess weight gain in youth
thereby reducing the current and future prevalence of related health risk factors and co-morbidities. The project
will produce an empirically calibrated test bed for developing, testing, and evaluating intervention strategies,
which can be shared with the general public along with privacy-protected study data.

## Key facts

- **NIH application ID:** 10194562
- **Project number:** 5R01HD086259-05
- **Recipient organization:** UNIVERSITY OF MASSACHUSETTS AMHERST
- **Principal Investigator:** James A Kitts
- **Activity code:** R01 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2021
- **Award amount:** $570,854
- **Award type:** 5
- **Project period:** 2016-09-16 → 2023-08-31

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/10194562

## Citation

> US National Institutes of Health, RePORTER application 10194562, Identifying Mechanisms of Peer Influence on Youth Weight-Related Behaviors (5R01HD086259-05). Retrieved via AI Analytics 2026-05-24 from https://api.ai-analytics.org/grant/nih/10194562. Licensed CC0.

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