Using predicted marginal effects to assess the impact of rurality and free and reduced lunch eligibility on a school-based nutrition intervention

Natoshia M Askelson; Patrick J Brady; Youn Soo Jung; Phuong Nguyen-Hoang; Grace Ryan; Carrie Scheidel; Patti Delger

doi:10.1016/j.evalprogplan.2022.102072

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Using predicted marginal effects to assess the impact of rurality and free and reduced lunch eligibility on a school-based nutrition intervention

Journal article

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Using predicted marginal effects to assess the impact of rurality and free and reduced lunch eligibility on a school-based nutrition intervention

Natoshia M Askelson, Patrick J Brady, Youn Soo Jung, Phuong Nguyen-Hoang, Grace Ryan, Carrie Scheidel and Patti Delger

Evaluation and program planning, Vol.92, pp.102072-102072

06/2022

DOI: 10.1016/j.evalprogplan.2022.102072

PMID: 35339765

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Abstract

To estimate the impact of a school-based nutrition education intervention in rural schools and schools with high free and reduced lunch (FRL) eligibility rates. As part of the evaluation of the Healthy Schools Healthy Students intervention, 20 schools were randomized to control and intervention conditions. Pre (October 2017) and posttest (April 2018) data were analyzed using multi-level linear regression models to estimate the intervention effect for multiple outcomes controlling for school-level demographic characteristics. We report the predicted marginal effect overall and specifically for rural; high FRL; and rural, high-FRL schools. We observed at least one significant intervention effect for food group knowledge, liking to eat fruit, beliefs about how healthy fruits are, non-taste test fruit preferences, liking to eat vegetables, beliefs about how healthy vegetables are, and taste test vegetable preferences. We observed differential intervention effects for all outcomes except taste test vegetable preferences based on rural and high-FRL status. Interventions do not necessarily have the same impact on all participants. Sub-analyses can reveal these important differential effects, as they have important implications for policymakers, program implementers, and evaluators. Resources and interventions should be allocated where they will have the greatest impact. •Predicted marginal effects were used to examine differential impact of a nutrition intervention.•Rural schools with a higher percent of students eligible for free and reduced lunch were impacted more by the intervention.•Evaluators should consider sub-analyses to examine the impact of interventions on sub-populations.

Intervention

Predicted marginal effects

Rural

School nutrition

Sub-analyses

Details

Title: Subtitle: Using predicted marginal effects to assess the impact of rurality and free and reduced lunch eligibility on a school-based nutrition intervention
Creators: Natoshia M Askelson - University of Iowa College of Public Health, 145N. Riverside Drive, Iowa City, IA 52242, USA
Patrick J Brady - University of Iowa
Youn Soo Jung - University of Iowa
Phuong Nguyen-Hoang - University of Iowa
Grace Ryan - University of Iowa
Carrie Scheidel - Lowa Department of Education, 400 E 14th St., Des Moines, IA, 50319
Patti Delger - Lowa Department of Education, 400 E 14th St., Des Moines, IA, 50319
Resource Type: Journal article
Publication Details: Evaluation and program planning, Vol.92, pp.102072-102072
DOI: 10.1016/j.evalprogplan.2022.102072
PMID: 35339765
NLM abbreviation: Eval Program Plann
ISSN: 0149-7189
eISSN: 1873-7870
Publisher: Elsevier Ltd
Grant note: DOI: 10.13039/100000002, name: NIH; DOI: 10.13039/100000199, name: US Department of Agriculture
Language: English
Date published: 06/2022
Academic Unit: Injury Prevention Research Center; Public Policy Center (Archive); School of Planning and Public Affairs; Community and Behavioral Health
Record Identifier: 9984230609402771

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