Evidence map›Paper›PMID 30278053›Full record

ArticlePLoS medicine2018

Cost-effectiveness of financial incentives and disincentives for improving food purchases and health through the US Supplemental Nutrition Assistance Program (SNAP): A microsimulation study.

Dariush Mozaffarian, Junxiu Liu, Stephen Sy, Yue Huang, Colin Rehm, Yujin Lee, Parke Wilde, Shafika Abrahams-Gessel, Thiago de Souza Veiga Jardim, Tom Gaziano and 1 more

Registry-linked trialAbstract read
In one paragraph

Article in PLoS medicine, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. It is linked to trial NCT05939349 (A Prescription for Health Equity), which is not on this map. Cited by 81 papers, 4 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
81citing papers in PubMed, 4 pooled it
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

NCT05939349 naunknown statusnot on this mapstarted 2023, after this paper: background citation

A Prescription for Health Equity: A Healthcare Provider-based Produce Prescription Program for People With Prediabetes and Type 2 Diabetes

TypeinterventionalSponsorGriffin HospitalRan2023 to 2025Enrolled134ConditionsPre Diabetes, Diabetes Mellitus, Type 2ArmsProduce Prescription Group
3 · Its place in the literature

Who cites it

81 citing papers in PubMed, 4 syntheses or guidelines pooled it.

  1. Pooled it
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  8. Health Center-Based Community-Supported Agriculture: An RCT.American journal of preventive medicine · 2019
    Trial
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  16. Simulated retail food environments: A literature review of systems science approaches to advance equity in access to healthy diets.Obesity reviews : an official journal of the International Association for the Study of Obesity · 2025
    Review
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21 more citing papers are in PubMed but not listed here.

4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

11 authors.

Dariush MozaffarianFriedman School of Nutrition Science and Policy, Tufts University, Boston, Massachusetts, United States of America.ORCID 0000-0001-7958-9492
Junxiu LiuFriedman School of Nutrition Science and Policy, Tufts University, Boston, Massachusetts, United States of America.ORCID 0000-0003-3303-0217
Stephen SyHarvard T.H. Chan School of Public Health, Boston, Massachusetts, United States of America.ORCID 0000-0001-8090-3768
Yue HuangFriedman School of Nutrition Science and Policy, Tufts University, Boston, Massachusetts, United States of America.ORCID 0000-0002-6642-7088
Colin RehmDepartment of Epidemiology and Population Health, Albert Einstein College of Medicine, Bronx, New York, United States of America.ORCID 0000-0002-7644-0040
Yujin LeeFriedman School of Nutrition Science and Policy, Tufts University, Boston, Massachusetts, United States of America.
Parke WildeFriedman School of Nutrition Science and Policy, Tufts University, Boston, Massachusetts, United States of America.ORCID 0000-0002-9596-9230
Shafika Abrahams-GesselHarvard T.H. Chan School of Public Health, Boston, Massachusetts, United States of America.
Thiago de Souza Veiga JardimHarvard T.H. Chan School of Public Health, Boston, Massachusetts, United States of America.ORCID 0000-0002-7750-2792
Tom GazianoHarvard T.H. Chan School of Public Health, Boston, Massachusetts, United States of America.ORCID 0000-0002-5985-345X
Renata MichaFriedman School of Nutrition Science and Policy, Tufts University, Boston, Massachusetts, United States of America.ORCID 0000-0002-3983-1632

Funding

Cost-Effectiveness of Health System and State-Level Strategies to Improve Diet and Reduce Cardiometabolic DiseasesR01HL115189 · NHLBI · TUFTS UNIVERSITY BOSTON · PI DARIUSH MOZAFFARIAN · 2013 to 2026
$8.2M
Economic Analyses of Policy Strategies to Improve Diet and Reduce CVDR01HL130735 · NHLBI · TUFTS UNIVERSITY BOSTON · PI MICHA, EIRINI (RENATA) · 2016 to 2019
$3.1M
NHLBI NIH HHS R01 HL115189NHLBI NIH HHS R01 HL130735
6 · The paper itself

Abstract

backgroundThe Supplemental Nutrition Assistance Program (SNAP) provides approximately US$70 billion annually to support food purchases by low-income households, supporting approximately 1 in 7 Americans. In the 2018 Farm Bill, potential SNAP revisions to improve diets and health could include financial incentives, disincentives, or restrictions for certain foods. However, the overall and comparative impacts on health outcomes and costs are not established. We aimed to estimate the health impact, program and healthcare costs, and cost-effectiveness of food incentives, disincentives, or restrictions in SNAP. METHODS AND

findingsWe used a validated microsimulation model (CVD-PREDICT), populated with national data on adult SNAP participants from the National Health and Nutrition Examination Survey (NHANES) 2009-2014, policy effects from SNAP pilots and food pricing meta-analyses, diet-disease effects from meta-analyses, and policy, food, and healthcare costs from published literature to estimate the overall and comparative impacts of 3 dietary policy interventions: (1) a 30% incentive for fruits and vegetables (F&V), (2) a 30% F&V incentive with a restriction of sugar-sweetened beverages (SSBs), and (3) a broader incentive/disincentive program for multiple foods that also preserves choice (SNAP-plus), combining 30% incentives for F&V, nuts, whole grains, fish, and plant-based oils and 30% disincentives for SSBs, junk food, and processed meats. Among approximately 14.5 million adults on SNAP at baseline with mean age 52 years, our simulation estimates that the F&V incentive over 5 years would prevent 38,782 cardiovascular disease (CVD) events, gain 18,928 quality-adjusted life years (QALYs), and save $1.21 billion in healthcare costs. Adding SSB restriction increased gains to 93,933 CVD events prevented, 45,864 QALYs gained, and $4.33 billion saved. For SNAP-plus, corresponding gains were 116,875 CVD events prevented, 56,056 QALYs gained, and $5.28 billion saved. Over a lifetime, the F&V incentive would prevent approximately 303,900 CVD events, gain 649,000 QALYs, and save $6.77 billion in healthcare costs. Adding SSB restriction increased gains to approximately 797,900 CVD events prevented, 2.11 million QALYs gained, and $39.16 billion in healthcare costs saved. For SNAP-plus, corresponding gains were approximately 940,000 CVD events prevented, 2.47 million QALYs gained, and $41.93 billion saved. From a societal perspective (including programmatic costs but excluding food subsidy costs as an intra-societal transfer), all 3 scenarios were cost-saving. From a government affordability perspective (i.e., incorporating food subsidy costs, including for children and young adults for whom no health gains were modeled), the F&V incentive was of low cost-effectiveness at 5 years (incremental cost-effectiveness ratio: $548,053/QALY) but achieved cost-effectiveness ($66,525/QALY) over a lifetime. Adding SSB restriction, the intervention was cost-effective at 10 years ($68,857/QALY) and very cost-effective at 20 years ($26,435/QALY) and over a lifetime ($5,216/QALY). The combined incentive/disincentive program produced the largest health gains and reduced both healthcare and food costs, with net cost-savings of $10.16 billion at 5 years and $63.33 billion over a lifetime. Results were consistent in probabilistic sensitivity analyses: for example, from a societal perspective, 1,000 of 1,000 iterations (100%) were cost-saving for all 3 interventions. Due to the nature of simulation studies, the findings cannot prove the health and cost impacts of national SNAP interventions.

conclusionsLeveraging healthier eating through SNAP could generate substantial health benefits and be cost-effective or cost-saving. A combined food incentive/disincentive program appears most effective and may be most attractive to policy-makers.

Indexed as

Choice BehaviorMotivationAdultAgedAged, 80 and overBeveragesCardiovascular DiseasesComputer SimulationCost-Benefit AnalysisCost SavingsDiet, HealthyFemaleFoodFood AssistanceGovernment ProgramsHealth Behavior

Identifiers

PMID30278053
PMCPMC6168180

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Registered trials

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.