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Figure 1.  PRISMA Flow Diagram of Study Selection
PRISMA Flow Diagram of Study Selection

a After deduplication.

b Not mutually exclusive.

Exclusion terminology: metrics refers to how food insecurity was measured; out-of-scope studies were those of hospitalized patient populations, indigenous populations in Canada, or populations that were non-Canada/US; linkage refers to screening and referral with the outcome being how many patients completed the referral process; blended SDOH were interventions addressing multiple social determinants with no separate outcome for food insecurity; healthy eating defines interventions and/or primary outcomes that promote healthy eating; SDOH denotes the Social Determinants of Health; SIREN, Social Interventions Research and Evaluation Network database; and SNAP, Supplemental Nutrition Assistance Program.

Figure 2.  Association Between Food Insecurity and Intervention Type, by Studya
Association Between Food Insecurity and Intervention Type, by Studya

Odds ratios indicate the difference in the odds of being food insecure in the intervention vs the control group. The diamond marker indicates the pooled estimate and 95% CI for each type of intervention; RCT denotes randomized clinical trial.

a The study by Aiyer et al36 was an outlier and was not included in the pooled analysis.

Figure 3.  Association Between Food Insecurity Interventions and Health Outcomes by Study
Association Between Food Insecurity Interventions and Health Outcomes by Study

SMD indicates standardized mean difference for each outcome. The diamond markers indicate pooled estimates and 95% CIs for each health outcome. I2 indicates the I2 statistic, and higher I2 values (closer to 100%) indicate greater study heterogeneity. BMI, denotes body mass index (calculated as weight in kilograms divided by height in meters squared); RCT, randomized clinical trial; HbA1c, hemoglobin A1c; and HRQOL, health-related quality of life.

Table 1.  Studies of Interventions to Address Food Insecurity Among Adults
Studies of Interventions to Address Food Insecurity Among Adults
Table 2.  Certainty of Evidence, by Intervention Type and Outcome
Certainty of Evidence, by Intervention Type and Outcome
1.
Coleman-Jensen  A, Rabbitt  MP, Gregory  CA. Definitions of food security. US Department of Agriculture. Accessed June 29, 2021. https://www.ers.usda.gov/topics/food-nutrition-assistance/food-security-in-the-us/definitions-of-food-security.aspx
2.
Gundersen  C, Ziliak  JP.  Food insecurity and health outcomes.   Health Aff (Millwood). 2015;34(11):1830-1839. doi:10.1377/hlthaff.2015.0645 PubMedGoogle ScholarCrossref
3.
Pooler  JA, Hartline-Grafton  H, DeBor  M, Sudore  RL, Seligman  HK.  Food insecurity: a key social determinant of health for older adults.   J Am Geriatr Soc. 2019;67(3):421-424. doi:10.1111/jgs.15736 PubMedGoogle ScholarCrossref
4.
Berkowitz  SA, Seligman  HK, Meigs  JB, Basu  S.  Food insecurity, healthcare utilization, and high cost: a longitudinal cohort study.   Am J Manag Care. 2018;24(9):399-404.PubMedGoogle Scholar
5.
Berkowitz  SA, Basu  S, Gundersen  C, Seligman  HK.  State-level and county-level estimates of health care costs associated with food insecurity.   Prev Chronic Dis. 2019;16:e90. doi:10.5888/pcd16.180549 PubMedGoogle Scholar
6.
Bauer  L. The COVID-19 crisis has already left too many children hungry in America. Brookings. Published online May 6, 2020. Accessed June 29, 2021. https://www.brookings.edu/blog/up-front/2020/05/06/the-covid-19-crisis-has-already-left-too-many-children-hungry-in-america/
7.
Stenmark  SH, Steiner  JF, Marpadga  S, Debor  M, Underhill  K, Seligman  H.  Lessons learned from implementation of the food insecurity screening and referral program at Kaiser Permanente Colorado.   Perm J. 2018;22:18-093. doi:10.7812/TPP/18-093 PubMedGoogle Scholar
8.
Bresnick  J. Food insecurity becomes focus for population health programs. Published online April 26, 2019. Accessed August 3, 2020. https://healthitanalytics.com/news/food-insecurity-becomes-focus-for-population-health-programs
9.
Heath  S. VA partnership targets food security, social determinants of health. Published June 17, 2020. Accessed August 3, 2020. https://patientengagementhit.com/news/va-partnership-targets-food-security-social-determinants-of-health
10.
Hudak  KM, Racine  EF.  The supplemental nutrition assistance program and child weight status: a review.   Am J Prev Med. 2019;56(6):882-893. doi:10.1016/j.amepre.2019.01.006 PubMedGoogle ScholarCrossref
11.
Andreyeva  T, Tripp  AS, Schwartz  MB.  Dietary quality of Americans by supplemental nutrition assistance program participation status: a systematic review.   Am J Prev Med. 2015;49(4):594-604. doi:10.1016/j.amepre.2015.04.035 PubMedGoogle ScholarCrossref
12.
Heflin  CM, Ingram  SJ, Ziliak  JP.  The effect of the supplemental nutrition assistance program on mortality.   Health Aff (Millwood). 2019;38(11):1807-1815. doi:10.1377/hlthaff.2019.00405 PubMedGoogle ScholarCrossref
13.
University of California San Francisco. Social Interventions Research & Evaluation Network. Accessed June 29, 2021. https://sirenetwork.ucsf.edu/tools/evidence-library
14.
Cochrane Bias Methods Group. RoB 2: a revised Cochrane risk-of-bias tool for randomized trials. Accessed June 29, 2021. https://methods.cochrane.org/bias/resources/rob-2-revised-cochrane-risk-bias-tool-randomized-trials
15.
Sterne  JA, Hernán  MA, Reeves  BC,  et al.  ROBINS-I: a tool for assessing risk of bias in non-randomised studies of interventions.   BMJ. 2016;355:i4919. doi:10.1136/bmj.i4919 PubMedGoogle Scholar
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National Heart, Lung, and Blood Institute. study quality assessment tools. Accessed June 29, 2021. https://www.nhlbi.nih.gov/health-topics/study-quality-assessment-tools
17.
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Higgins  JP, Thompson  SG, Deeks  JJ, Altman  DG.  Measuring inconsistency in meta-analyses.   BMJ. 2003;327(7414):557-560. doi:10.1136/bmj.327.7414.557 PubMedGoogle ScholarCrossref
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23.
Howick  J, Glasziou  P, Aronson  JK.  The evolution of evidence hierarchies: what can Bradford Hill’s ‘guidelines for causation’ contribute?   J R Soc Med. 2009;102(5):186-194. doi:10.1258/jrsm.2009.090020 PubMedGoogle ScholarCrossref
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National Academies of Sciences, Engineering, and Medicine. Evidence-based practice for public health emergency preparedness and response: assessment of and recommendations for the field. Accessed June 29, 2021. https://www.nationalacademies.org/our-work/evidence-based-practices-for-public-health-emergency-preparedness-and-response-assessment-of-and-recommendations-for-the-field
25.
Berkowitz  SA, Delahanty  LM, Terranova  J,  et al.  Medically tailored meal delivery for diabetes patients with food insecurity: a randomized cross-over trial.   J Gen Intern Med. 2019;34(3):396-404. doi:10.1007/s11606-018-4716-z PubMedGoogle ScholarCrossref
26.
Seligman  HK, Smith  M, Rosenmoss  S, Marshall  MB, Waxman  E.  Comprehensive diabetes self-management support from food banks: a randomized controlled trial.   Am J Public Health. 2018;108(9):1227-1234. doi:10.2105/AJPH.2018.304528 PubMedGoogle ScholarCrossref
27.
Ferrer  RL, Neira  LM, De Leon Garcia  GL, Cuellar  K, Rodriguez  J.  Primary care and food bank collaboration to address food insecurity: a pilot randomized trial.   Nutr Metab Insights. 2019;12:1178638819866434. doi:10.1177/1178638819866434 PubMedGoogle Scholar
28.
Feuerstein-Simon  R, Dupuis  R, Schumacher  R, Cannuscio  CC.  A randomized trial to encourage healthy eating through workplace delivery of fresh food.   Am J Health Promot. 2020;34(3):269-276. doi:10.1177/0890117119890804 PubMedGoogle ScholarCrossref
29.
Martin  KS, Wu  R, Wolff  M, Colantonio  AG, Grady  J.  A novel food pantry program: food security, self-sufficiency, and diet-quality outcomes.   Am J Prev Med. 2013;45(5):569-575. doi:10.1016/j.amepre.2013.06.012 PubMedGoogle ScholarCrossref
30.
Gubits  D, Shinn  M, Wood  M, Brown  SR, Dastrup  SR, Bell  SH.  What interventions work best for families who experience homelessness? impact estimates from the family options study.   J Policy Anal Manage. 2018;37(4):735-766. doi:10.1002/pam.22071 PubMedGoogle ScholarCrossref
31.
Eicher-Miller  HA, Mason  AC, Abbott  AR, McCabe  GP, Boushey  CJ.  The effect of Food Stamp Nutrition Education on the food insecurity of low-income women participants.   J Nutr Educ Behav. 2009;41(3):161-168. doi:10.1016/j.jneb.2008.06.004 PubMedGoogle ScholarCrossref
32.
Lohse  B, Belue  R, Smith  S, Wamboldt  P, Cunningham-Sabo  L.  About eating: an online program with evidence of increased food resource management skills for low-income women.   J Nutr Educ Behav. 2015;47(3):265-272. doi:10.1016/j.jneb.2015.01.006 PubMedGoogle ScholarCrossref
33.
Berkowitz  SA, Terranova  J, Randall  L, Cranston  K, Waters  DB, Hsu  J.  Association between receipt of a medically tailored meal program and health care use.   JAMA Intern Med. 2019;179(6):786-793. doi:10.1001/jamainternmed.2019.0198 PubMedGoogle ScholarCrossref
34.
Wright  L, Vance  L, Sudduth  C, Epps  JB.  The impact of a home-delivered meal program on nutritional risk, dietary intake, food security, loneliness, and social well-being.   J Nutr Gerontol Geriatr. 2015;34(2):218-227. doi:10.1080/21551197.2015.1022681 PubMedGoogle ScholarCrossref
35.
Palar  K, Napoles  T, Hufstedler  LL,  et al.  Comprehensive and medically appropriate food support is associated with improved hiv and diabetes health.   J Urban Health. 2017;94(1):87-99. doi:10.1007/s11524-016-0129-7 PubMedGoogle ScholarCrossref
36.
Aiyer  JN, Raber  M, Bello  RS,  et al.  A pilot food prescription program promotes produce intake and decreases food insecurity.   Transl Behav Med. 2019;9(5):922-930. doi:10.1093/tbm/ibz112 PubMedGoogle ScholarCrossref
37.
Cheyne  K, Smith  M, Felter  EM,  et al.  Food bank-based diabetes prevention intervention to address food security, dietary intake, and physical activity in a food-insecure cohort at high risk for diabetes.   Prev Chronic Dis. 2020;17:190210. doi:10.5888/pcd17.190210 PubMedGoogle Scholar
38.
Seligman  HK, Lyles  C, Marshall  MB,  et al.  A pilot food bank intervention featuring diabetes-appropriate food improved glycemic control among clients in three states.   Health Aff (Millwood). 2015;34(11):1956-1963. doi:10.1377/hlthaff.2015.0641 PubMedGoogle ScholarCrossref
39.
Wetherill  MS, Chancellor McIntosh  H, Beachy  C, Shadid  O.  Design and implementation of a clinic-based food pharmacy for food insecure, uninsured patients to support chronic disease self-management.   J Nutr Educ Behav. 2018;50(9):947-949. doi:10.1016/j.jneb.2018.05.014 PubMedGoogle ScholarCrossref
40.
Khan  F, Schiff  A, Mello  M.  Impact of participation in the commodity supplemental food program on food insecurity among low-income elderly Rhode Islanders.   R I Med J (2013). 2019;102(2):32-35.PubMedGoogle Scholar
41.
Durward  CM, Savoie-Roskos  M, Atoloye  A,  et al.  Double up food bucks participation is associated with increased fruit and vegetable consumption and food security among low-income adults.   J Nutr Educ Behav. 2019;51(3):342-347. doi:10.1016/j.jneb.2018.08.011 PubMedGoogle ScholarCrossref
42.
Cueva  K, Lovato  V, Nieto  T, Neault  N, Barlow  A, Speakman  K.  Increasing healthy food availability, purchasing, and consumption: lessons learned from implementing a mobile grocery.   Prog Community Health Partnersh. 2018;12(1):65-72. doi:10.1353/cpr.2018.0007 PubMedGoogle ScholarCrossref
43.
Carney  PA, Hamada  JL, Rdesinski  R,  et al.  Impact of a community gardening project on vegetable intake, food security and family relationships: a community-based participatory research study.   J Community Health. 2012;37(4):874-881. doi:10.1007/s10900-011-9522-z PubMedGoogle ScholarCrossref
44.
Berkowitz  SA, Hulberg  AC, Placzek  H,  et al.  Mechanisms associated with clinical improvement in interventions that address health-related social needs: a mixed-methods analysis.   Popul Health Manag. 2019;22(5):399-405. doi:10.1089/pop.2018.0162 PubMedGoogle ScholarCrossref
45.
Feinberg  AT, Hess  A, Passaretti  M, Coolbaugh  S, Lee  TH. Prescribing food as a specialty drug. NEJM Catal. Published online April 10, 2018. Accessed July 12, 2021. https://catalyst.nejm.org/doi/abs/10.1056/CAT.18.0212
46.
Gurvey  J, Rand  K, Daugherty  S, Dinger  C, Schmeling  J, Laverty  N.  Examining health care costs among MANNA clients and a comparison group.   J Prim Care Community Health. 2013;4(4):311-317. doi:10.1177/2150131913490737 PubMedGoogle ScholarCrossref
47.
Frongillo  EA, Wolfe  WS.  Impact of participation in home-delivered meals on nutrient intake, dietary patterns, and food insecurity of older persons in New York state.   J Nutr Elder. 2010;29(3):293-310. doi:10.1080/01639366.2010.499094 PubMedGoogle ScholarCrossref
48.
Lee  JS, Johnson  MA, Brown  A.  Older Americans Act Nutrition Program improves participants’ food security in Georgia.   J Nutr Gerontol Geriatr. 2011;30(2):122-139. doi:10.1080/21551197.2011.566526 PubMedGoogle ScholarCrossref
49.
Chatterjee  A, Brown  R, Block  JP.  “Feastworthy is something that gives us our dignity back:” feasibility of a delivered prepared meal program for families in motel-shelters.   J Health Care Poor Underserved. 2018;29(4):1333-1355. doi:10.1353/hpu.2018.0099 PubMedGoogle ScholarCrossref
50.
Andrade  FCD, Kramer  KZ, Greenlee  A, Williams  AN, Mendenhall  R.  Impact of the Chicago Earned Income Tax Periodic Payment intervention on food security.   Prev Med Rep. 2019;16:100993-100993. doi:10.1016/j.pmedr.2019.100993 PubMedGoogle ScholarCrossref
51.
Richardson  AS, Ghosh-Dastidar  M, Beckman  R,  et al.  Can the introduction of a full-service supermarket in a food desert improve residents’ economic status and health?   Ann Epidemiol. 2017;27(12):771-776. doi:10.1016/j.annepidem.2017.10.011 PubMedGoogle ScholarCrossref
52.
Roncarolo  F, Bisset  S, Potvin  L.  Short-term effects of traditional and alternative community interventions to address food insecurity.   PLoS One. 2016;11(3):e0150250. doi:10.1371/journal.pone.0150250 PubMedGoogle Scholar
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Sonik  RA, Parish  SL, Mitra  M.  Food insecurity patterns before and after initial receipt of Supplemental Security Income.   Public Health Nutr. 2019;22(10):1909-1913. doi:10.1017/S1368980019000570 PubMedGoogle ScholarCrossref
54.
Phojanakong  P, Welles  S, Dugan  J,  et al.  Trauma-informed financial empowerment programming improves food security among families with young children.   J Nutr Educ Behav. 2020;52(5):465-473. doi:10.1016/j.jneb.2020.02.008Google Scholar
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Wilkinson  M.  Combating food insecurity: addressing health beyond an empty pantry.   J Christ Nurs. 2019;36(2):80-87. doi:10.1097/CNJ.0000000000000590 PubMedGoogle ScholarCrossref
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Brown  EM, Tarasuk  V.  Money speaks: reductions in severe food insecurity follow the Canada child benefit.   Prev Med. 2019;129:105876-105876. doi:10.1016/j.ypmed.2019.105876 PubMedGoogle ScholarCrossref
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Himmelstein  G.  Effect of the Affordable Care Act’s Medicaid expansions on food security, 2010-2016.   Am J Public Health. 2019;109(9):1243-1248. doi:10.2105/AJPH.2019.305168 PubMedGoogle ScholarCrossref
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Li  N, Dachner  N, Tarasuk  V.  The impact of changes in social policies on household food insecurity in British Columbia, 2005-2012.   Prev Med. 2016;93:151-158. doi:10.1016/j.ypmed.2016.10.002 PubMedGoogle ScholarCrossref
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Londhe  S, Ritter  G, Schlesinger  M.  Medicaid expansion in social context: examining relationships between Medicaid enrollment and county-level food insecurity.   J Health Care Poor Underserved. 2019;30(2):532-546. doi:10.1353/hpu.2019.0033 PubMedGoogle ScholarCrossref
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    Original Investigation
    August 6, 2021

    Interventions to Address Food Insecurity Among Adults in Canada and the US: A Systematic Review and Meta-analysis

    Author Affiliations
    • 1Greater Los Angeles Veterans Affairs Healthcare System, Los Angeles, California
    • 2David Geffen School of Medicine, University of California, Los Angeles
    • 3National Clinician Scholars Program, University of California, Los Angeles
    • 4RAND Corporation, Southern California Evidence-based Practice Center, Santa Monica, California
    • 5Humana Inc, Louisville, Kentucky
    JAMA Health Forum. 2021;2(8):e212001. doi:10.1001/jamahealthforum.2021.2001
    Key Points

    Question  Are food insecurity interventions associated with improvements in food insecurity status, health outcomes, or health care utilization?

    Findings  In this systematic review and meta-analysis of 39 randomized and observational studies, including 170 605 participants, direct provision of food and monetary assistance were associated with statistically significant reductions in the prevalence of food insecurity. Health and health care utilization outcomes were reported in less than half of studies with mixed results that were not statistically significant in pooled analyses.

    Meaning  For individuals with food insecurity, interventions that directly address their needs with food or monetary assistance are associated with improvements in food insecurity status, but further work is needed to understand the association with health outcomes and health care utilization.

    Abstract

    Importance  Inadequate access to food is a risk factor for poor health and the effectiveness of federal programs targeting food insecurity, such as the Supplemental Nutrition Assistance Program (SNAP), are well-documented. The associations between other types of interventions to provide adequate food access and food insecurity status, health outcomes, and health care utilization, however, are unclear.

    Objective  To review evidence on the association between food insecurity interventions and food insecurity status, clinically-relevant health outcomes, and health care utilization among adults, excluding SNAP.

    Data Sources  A systematic search for English-language literature was performed in PubMed Central and Cochrane Trials databases (inception to January 23, 2020), the Social Interventions Research and Evaluation Network database (December 10, 2019); and the gray literature using Google (February 1, 2021).

    Study Selection  Studies of any design that assessed the association between food insecurity interventions for adult participants and food insecurity status, health outcomes, and health care utilization were screened for inclusion. Studies of interventions that described addressing participants’ food needs or reporting food insecurity as an outcome were included. Interventions were categorized as home-delivered food, food offered at a secondary site, monetary assistance in the form of subsidies or income supplements, food desert interventions, and miscellaneous.

    Data Extraction and Synthesis  Data extraction was performed independently by 3 reviewers. Study quality was assessed using the Cochrane Risk of Bias Tool, the ROBINS-I (Risk of Bias in Non-Randomized Studies of Interventions) tool, and a modified version of the National Institutes of Health’s Quality Assessment Tool for Before-After Studies With No Control. The certainty of evidence was based on GRADE (Grading of Recommendations Assessment, Development, and Evaluation) criteria and supplemented with mechanistic and parallel evidence. For outcomes within intervention categories with at least 3 studies, random effects meta-analysis was performed.

    Main Outcomes and Measures  Food insecurity (measured through surveys; eg, the 2-item Hunger Vital Sign), health outcomes (eg, hemoglobin A1c), and health care utilization (eg, hospitalizations, costs).

    Results  A total of 39 studies comprising 170 605 participants were included (8 randomized clinical trials and 31 observational studies). Of these, 14 studies provided high-certainty evidence of an association between offering food and reduced food insecurity (pooled random effects; adjusted odds ratio, 0.53; 95% CI, 0.33-0.67). Ten studies provided moderate-certainty evidence of an association between offering monetary assistance and reduced food insecurity (pooled random effects; adjusted odds ratio, 0.64; 95% CI, 0.49-0.84). There were fewer studies of the associations between interventions and health outcomes or health care utilization, and the evidence in these areas was of low or very low certainty that any food insecurity interventions were associated with changes in either.

    Conclusions and Relevance  This systematic review with meta-analysis found that providing food and monetary assistance was associated with improved food insecurity measures; however, whether it translated to better health outcomes or reduced health care utilization was unclear.

    Introduction

    Food insecurity, which is defined as limited or uncertain access to adequate food owing to resource limitations,1 is an important social risk factor for poor health. Food insecurity is linked to a range of health conditions and adverse outcomes among adults, including diabetes, hypertension, worsened depressive symptoms, and greater activity limitations.2,3 Furthermore, individuals with food insecurity are more likely to experience an emergency department visit, inpatient admission, and higher health care costs.4 Food insecure Medicare beneficiaries incur $5527 higher health care expenditures annually compared with those who are food secure.4 Nationally, food insecurity is estimated to contribute nearly $52 billion in excess health care spending.5 The COVID-19 pandemic and its economic consequences have exacerbated the problem, as the prevalence of food insecurity increased from 11.1% of households in 2018 to 22.7% in April 2020.6

    Given the scope of unmet social needs and the growth of value-based payment models that prioritize population health, there is wide interest in addressing food insecurity. For example, integrated delivery systems, hospitals, and payers have invested in programs that identify patients with food insecurity to connect them with resources.7-9 Many have focused on enrolling eligible patients into the Supplemental Nutrition Assistance Program (SNAP), for which a robust evidence base demonstrates strong positive impact.2,10-12 Despite the proliferation of other types of interventions addressing food insecurity, little is known about their effectiveness. To better understand the scope of interventions targeting food insecurity among adults within and outside of health care settings, as well as their association with outcomes, this systematic review with meta-analysis builds on prior work to evaluate the evidence of interventions across all settings, while excluding well-established public food assistance programs, such as SNAP.

    Methods

    This systematic review of randomized clinical trials and observational studies followed the Preferred Reporting Items for Systematic Reviews and Meta-analyses (PRISMA) reporting guideline. The study topic was developed in consultation with the sponsor, Humana Inc. The study was registered in PROSPERO (CRD42020172486). The University of California Los Angeles Institutional Review Board deemed this study exempt and waived informed consent because the study used only previously published research and did not meet the criteria found in the Regulations for the Protection of Human Subjects (45 CFR §46).

    Data Sources and Searches

    The search strategy, detailed in eAppendix 1 of the Supplement, was created by an experienced reference librarian using a broad set of terms related to food insecurity interventions. We conducted English-language searches in PubMed Central, Cochrane Trials, and Academic Search Complete, from inception to January 23, 2020; and in the Social Interventions Research and Evaluation Network (SIREN) database on December 10, 2019. The SIREN database is a University of California San Francisco project to collect, summarize, and disseminate research on interventions that address the social determinants of health.13 For our search of SIREN, we used the social determinant “food/hunger” to filter results. We also performed a supplemental search of the gray literature using Google on February 1, 2021.

    Study Selection

    Three team members (C.I.O., I.M.L., and P.G.S.) independently screened the titles of retrieved citations. For titles deemed relevant by at least 1 person, abstracts were then screened in triplicate by team members. All disagreements were reconciled through group discussion. Full-text review was conducted in triplicate by 3 independent team members (C.I.O., I.M.L., and P.G.S.), with any disagreements being resolved through discussion. To be included, a study had to evaluate a food insecurity intervention and include health outcomes or food insecurity as an outcome measured at the person-level. Food insecurity was measured with self-reported surveys, most often with the US Department of Agriculture Food Security Survey Module or a short form of the module. We defined a food insecurity intervention as a program or policy that either directly addresses food needs or improves the ability to obtain food.

    In consultation with the study sponsor, we did not require that a food insecurity intervention originate in a health care setting as long as it or something similar could be plausibly implemented by the health care system. We excluded studies of SNAP and similar programs, studies with fruit and vegetable intake as the sole outcome, and studies focusing on children and adolescents, as the focus of the sponsor was adults with food insecurity. Because our focus was on interventions applicable to the US, we also excluded studies conducted in low- and middle-income countries. A full description of the exclusion and inclusion criteria is available in the eAppendix 2 and eAppendix 3 of the Supplement.

    Data Extraction and Quality Assessment

    Data extraction was completed in triplicate (C.I.O., I.M.L., and P.G.S.). All discrepancies were resolved with full group discussion. We abstracted data on the following: study design, sample size, enrolled population, intervention, and outcomes measured. To assess risk of bias, we used the Cochrane Risk of Bias Tool,14 ROBINS-I (Risk of Bias in Non-Randomized Studies of Interventions) tool,15 or an adaptation of the National Institutes of Health Quality Assessment Tool for Before-After Studies With No Control.16

    Data Synthesis and Grading

    We grouped interventions into 5 broad categories: (1) food delivered to the home (eg, Meals on Wheels), (2) food offered at a secondary location (eg, a senior center), (3) monetary assistance as means-tested subsidies or similar programs (eg, tax credits or health insurance), (4) programs to address food deserts, and (5) miscellaneous interventions. We grouped outcomes into 3 domains: (1) food insecurity, (2) health outcomes (eg, blood pressure, hemoglobin A1c [HbA1c]), and (3) health care utilization. When study instruments varied, we combined food insecurity results according to the study-defined measures of food insecurity and aggregated the categories of low or very low food security. Summary statistics were extracted for each intervention and control group (or before-after intervention) for each study and outcome. To compare between group differences, results were converted to effect sizes (odds ratios [ORs] for binary outcomes and standardized mean differences [SMDs] for continuous outcomes) and plotted on a common measure. After confirming via meta-regression that 6 studies using a randomized trial design did not report systematically different effect sizes compared with the 24 observational studies, we pooled results within the categories of providing food and monetary assistance, respectively. When sufficient studies existed (≥3 studies) within each outcome and intervention category, studies were pooled using a random effects meta-analysis.17 Outliers were assessed and removed from all pooled results.

    Statistical Analysis

    Tests of heterogeneity were performed using the I2 statistic.18 Values of the I2 statistic close to 100% represent high degrees of heterogeneity. Begg rank correlation19 and Egger regression asymmetry test20 were used to examine publication bias. Exploratory metaregressions, which did not influence our conclusions, are described in the eAppendix 3 of the Supplement. P values were 2-tailed and statistical significance was defined as P = .05. All analyses were conducted in R, version 4.0.2 (The R Foundation for Statistical Computing).21 We based the certainty of the evidence ratings on factors considered in the GRADE (Grading of Recommendations Assessment, Development, and Evaluation) system,22 and supplemented these with other factors (eg, mechanistic and parallel evidence) as proposed by Howick and colleagues23 and used by the National Academy of Medicine.24

    Results
    Description of the Evidence

    We identified 4807 potentially relevant citations, with 150 undergoing full-text review and 111 of these being excluded (see eAppendix 2 of the Supplement). A total of 39 publications, including 170 605 participants, met inclusion criteria (Figure 1). Of these 39 studies, 8 were RCTs,25-32 1 was a quasi-experimental study,33 12 were before-after studies without controls,34-45 9 were before-after studies with controls,46-54 1 was a time-series study,55 and 8 were cross-sectional studies.56-63 Thirty-four studies were of interventions in the US, and 5 were of interventions in Canada.

    Across RCTs, most studies were judged as having a high risk of bias from outcome assessment, incomplete outcome data, and selective reporting of outcomes (eTable 1 in the Supplement). Half of the observational studies were judged to have a high risk of bias owing to missing data (eTable 2 in the Supplement). Most of the 13 before-after studies without controls had small sample sizes and high rates of loss to follow-up and thus were judged to have a high risk of bias (eTable 3 in the Supplement).

    Associations With Food Insecurity
    Food Delivered to Home

    There were 6 studies examining the association between food provision delivered to the participant’s home and food insecurity status25,34,47-49,63 (Table 1). One was a small randomized trial of medically tailored meals in which dieticians designed meals to address patients’ nutritional needs based on their medical conditions (eg, diabetes or HIV). Among those receiving medically tailored meals, 42% were food insecure vs 62% of those who were not receiving home-delivered medically tailored meals, compared with the baseline of 71% to 80%.25 The remaining 5 interventions, which included programs, such as the Older Americans Act Nutrition Program and Meals on Wheels, delivered nonmedically tailored food to participants’ homes or places of shelter.34,47-49,63 Three of these observational studies found that home delivered food interventions were associated with reduced food insecurity,34,47,48 while 2 studies found that they were not.49,63 Full details of these studies are described in the eAppendix 3 of the Supplement.

    Food at a Secondary Site

    Ten studies examined the association between food insecurity status and interventions where food was provided at a secondary location (Table 1). These were differentiated by degree of tailoring toward the patients’ comorbidities—medically tailored meals, medically tailored or appropriate food boxes, or other (no further individualization). One intervention provided medically tailored meals to individuals living with HIV or diabetes, and 4 studies evaluated medically tailored grocery interventions, such as prescriptions to a food pantry and predesigned boxes of fresh groceries and dry goods. Nearly all were tailored to populations with diabetes, prediabetes, or obesity, and were often bundled with other services to support self-management of chronic disease. Aside from 1 RCT,26 these were before-after studies without control groups.35-37,39 The other 5 studies that provided food at a secondary site were heterogeneous in type of intervention (Table 1). Two of these studies evaluated interventions that encouraged healthy food intake (ie, more fruits and vegetables),28,29 1 provided a supplemental food box for older adults,40 and 2 provided meals in congregate settings for older adults.48,63 In general, these interventions were associated with reductions in food insecurity (further details are available in the Supplement).

    Thirteen of 16 interventions (81%) that provided food to participants and reported food insecurity outcomes used measures that were the same or similar. Although interventions differed across studies, we considered them all to be assessing the construct “providing regular food.” The random effects pooled estimate across these 13 interventions was an OR of 0.53 (95% CI, 0.36-0.77) in food insecurity (Figure 2), which shows an association with an absolute reduction in food insecurity of 15% given the weighted baseline average prevalence across these studies. There was significant heterogeneity (I2 statistic = 84.5%). There was disagreement among tests for possible publication bias, with Egger’s regression test being statistically significant (z  = -3.45; P = .001) but Begg’s rank correlation test being insignificant (Kendall τ, -0.359; P = .10).

    Monetary Assistance

    Eleven studies evaluated the association between monetary assistance (eg, Medicaid Expansion, child tax credits) and outcomes (Table 1). Most of these interventions were not designed primarily as food insecurity interventions. In the only RCT, which enrolled 2282 families staying in emergency shelters, long-term rent subsidies were associated with a 10 percentage point increase in food security at 37 months.30 The remainder were observational studies examining expansions or modifications to safety net programs, ranging from child tax credits to Medicaid eligibility. Nine interventions were associated with statistically significant decreases in food insecurity across multiple populations,25,30,41,50,53,57-59,61 while 2 did not observe a difference.56,60 Ten studies had similarly measured outcomes to permit pooling.30,41,50,53,56-61 The random effects pooled estimate across these 10 studies was an OR of 0.64 (95% CI, 0.49-0.84) in food insecurity (Figure 2), which shows an association with an absolute reduction in food insecurity of 8% given the weighted baseline average prevalence across these studies. There was significant heterogeneity (I2 statistic = 98.8%). There was no statistical evidence of publication bias.

    Food Deserts

    Two studies used before-after designs to evaluate interventions to address food deserts.42,51 One of these studies51 was associated with a decrease of 12 percentage points compared with the control after 1 year (Figure 2).

    Miscellaneous

    The miscellaneous category comprised 1 RCT and 5 before-after analyses, which included interventions such as educational programs and community gardens (Table 1).31,32,43,44,52,54 Three of the 5 before-after studies had similar outcomes that were associated with improvements in food insecurity43,52,54 (Figure 2).

    Associations With Health Outcomes

    Studies that reported health outcomes were primarily food provision interventions. Fifteen reported various health outcomes: 6 reported HbA1c among patients with diabetes,25-27,35,38,45 7 reported self-reported quality of life or health status measures,25,34,37,48,49,51,52 6 reported body mass index (calculated as weight in kilograms divided by height in meters squared; BMI),25,27,35,37,49,55 5 reported depressive symptoms,25,26,35,37,63 3 reported blood pressure,25,39,55 and 2 reported lipid panel results25,45 (Table 1).

    The 6 studies examining HbA1c provided food and 3 of these were RCTs. Two of these studies were of medically tailored meals,25,35 2 of diabetes-appropriate food boxes,26,38 and 2 were clinic-based food pantry interventions.27,45 While 5 studies demonstrated associations with small reductions in HbA1c, only 2 reached statistical significance, including a small RCT that provided food with dietician-led patient education and home visits from a community health worker.27 In the random effects pooled analysis, provision of food was associated with an SMD in HbA1c of −0.13 (95% CI, −0.34 to 0.09; Figure 3). There was heterogeneity (I2 statistic = 67.8%). There was no evidence of publication bias.

    Seven studies evaluated interventions with respect to health-related quality of life (HRQOL) or health status measures. Five studies evaluated food provision interventions,25,34,37,48,49 1 was a food desert intervention,51 and 1 was a miscellaneous intervention.52 Four of the 7 studies had similar self-reported HRQOL measures. In the random effects pooled analysis, these interventions were associated with an SMD of −0.28 (95% CI, −0.56 to 0.00) favoring improved health status (Figure 3). There was moderate heterogeneity (I2 statistic = 43.0%). There was no evidence of publication bias. One study reported its outcomes as dichotomous and could not be included in the pooled analysis, observing a significant decrease in fair or poor health from 74% to 60% after 6 months.37

    Six observational studies evaluated the association between food provision interventions and BMI.25,27,35,37,49,55 Four of the 6 studies had data and outcomes that were sufficiently similar to support pooling.35,37,49,55 In the random effects pooled analysis, the provision of food was associated with an SMD in BMI of −0.05 (95% CI, −0.20 to 0.11) (Figure 3). There was no heterogeneity (I2 statistic = 0.0%). There was no evidence of publication bias. The 2 studies excluded from the pooled analysis did not observe a statistically significant association.25,27

    Five studies reporting depressive symptoms included interventions that provided food.25,26,35,37,63 Three of the 5 studies reported similar scales of depressive symptoms sufficient to support pooling.35,41,63 In the random effects pooled analysis, the provision of food was associated with an SMD in depressive symptoms of −0.04 (95% CI, −0.19 to 0.11) (Figure 3). There was no heterogeneity (I2 statistic = 9.8%). There was no evidence of publication bias. The 2 studies excluded from the pooled analysis did not observe an association with depressive symptoms.26,37

    Four studies examined blood pressure or lipid panels.25,39,45,55 Half of these observed a small association with diastolic blood pressure and none with lipid panels.39,55

    Associations With Health Care Utilization and Costs

    Four studies, all of which directly provided food, reported health care utilization, or cost outcomes.33,35,45,46 The heterogeneity in outcomes, such as inpatient admissions and emergency department utilization, limited us from drawing overall conclusions about their findings. Full details of these outcomes are available in eTable 4 of the Supplement.

    Certainty of Evidence

    The evidence that offering direct food provision is associated with reduced food insecurity was deemed to be of high certainty (Table 2). While most studies had methodologic limitations and there was heterogeneity across studies, which lowered the certainty of evidence, the overall pooled estimate strongly favored the intervention. Moreover, there is a strong mechanistic rationale that providing food to people who are worried about running out of food before they have money to buy more would alleviate their worry. We judged with moderate certainty that programs providing monetary assistance were associated with reductions in food insecurity. This was based on the inclusion of an RCT and several observational studies with a pooled estimate favoring the intervention. Furthermore, given the robust parallel evidence supporting the health benefits of SNAP and other programs, such as the Earned Income Tax Credit, there is a moderately strong rationale that providing direct monetary assistance to households would relieve food insecurity.

    The certainty of evidence is low that interventions for food insecurity improve HbA1C, HRQOL, BMI, or depressive symptoms (Table 2). Moreover, the certainty of evidence is very low on any association of food insecurity interventions and measures of health care utilization or costs.

    Discussion

    Providing food or groceries, regardless of setting, has high-certainty evidence that it is associated with reductions in the prevalence of food insecurity, whereas offering income assistance or subsidies has moderate certainty evidence of an association with reduced food insecurity. We believe these associations are much more likely attributable to a causal relationship than to confounding, as these interventions focus on the 2 factors that define food insecurity: worry about inadequate food and lacking money to buy food.

    There was insufficient evidence to support the association between food insecurity interventions and a variety of health outcomes, except HRQOL, although this was low certainty evidence and merits further research. Among the 15 studies that included clinically relevant health outcomes, those that evaluated associations with HbA1c had the strongest evidence (3 RCTs). Although the association was not statistically significant, the pooled analysis suggested a possible association with a modest reduction in HbA1c.

    Our review complements prior work by De Marchis and colleagues,64 which focused on interventions within health care, by including additional studies and broadening the scope of interventions outside of health care settings. We included studies examining monetary assistance and welfare expansions that may not have been initially conceived as interventions for food insecurity. Because this review included more studies than the prior review,64 we were able to perform a meta-analysis on multiple clinical outcomes. The meta-analytic findings of this review are consistent with the narrative conclusions of the prior review. Additionally, we find that the higher risk of bias across the evidence limits the ability to draw firm conclusions regarding these interventions and any associations with health care utilization. With respect to food insecurity as an outcome, we observed that direct provision of food and monetary assistance were associated with 8% to 15% absolute reductions in food insecurity, comparable to the 11% reduction observed with SNAP in a prior evaluation.65

    These findings have important implications as policy makers, payers, and clinicians search for opportunities to address the health-related social needs of patients and populations. First, if alleviating the anxiety and stress regarding access to food (which is intrinsic to the definition of food insecurity) is considered a beneficial health outcome, then there is enough evidence to enact policy changes now. The effectiveness of interventions to address food insecurity can encourage the adoption of the National Quality Forum’s quality measures to monitor food insecurity screening processes.66 Likewise, payers should consider using value-based payment models to encourage data collection on food insecurity and implement interventions to address unmet needs. Expanding current programs, such as SNAP and the Commodity Supplemental Food Program for older adults, would be effective in addressing food insecurity. Additionally, the US Congress could broaden the criteria for the Medicare Special Supplemental Benefits for the Chronically Ill, expanding eligibility to those without chronic conditions if they have social needs with important health consequences, such as food insecurity.

    Alternatively, if alleviating anxiety and stress concerning access to food is not considered a sufficient health outcome to support practice and policy changes, then these results along with the observational evidence that food insecurity is associated with worse health and higher health care costs, should be an urgent call to action for more evidence. In particular, rigorous evidence for interventions addressing the mechanisms that facilitate food insecurity’s health effects should be prioritized. There are many potential opportunities for further evaluation as payers seek to use traditional health care spending for social care interventions.67 For example, recent announcements from the Centers for Medicare & Medicaid Innovation indicate that greater flexibility within the Value-Based Insurance Design model will reduce eligibility limitations in offering social services and should be a source of learning.68 Additionally, North Carolina has implemented a Medicaid section 1115 waiver to allow the state to invest $650 million in pilot programs to address social needs and created a statewide platform to foster a high-value network of community-based organizations.69 Such laboratories of innovation offer great promise in delivering better evidence regarding the influence of these programs on health outcomes and health care utilization.

    Limitations

    The main limitation of this review is the quantity and quality of the existing evidence. Most of the studies were observational and had small sample sizes, limiting the ability to draw conclusions about the effects of the interventions. Moreover, of the 39 studies included, only 15 reported health outcomes, and even fewer reported health care utilization measures. Second, the search strategy excluded interventions that identify and address multiple social determinants of health, which may include food insecurity if it was not measured as an outcome. Some interventions that address food insecurity or improve household resources to attain food may have been overlooked. Also, interventions focused on pediatric populations were excluded; therefore, pediatric-based interventions that improve household food insecurity may have been overlooked. Third, we pooled studies across both observational and RCT study designs, but only after verifying that RCTs did not systematically produce lower estimates of effect than observational studies. Furthermore, while we pooled several outcomes, these must be interpreted in the context of high heterogeneity and potential publication bias for interventions providing food. Finally, we focused on food insecurity interventions that excluded conventional assistance programs that comprise the food safety net (ie, SNAP) to focus on interventions that could be implemented by health systems or health plans.

    Conclusions

    In this meta-analysis, the evidence for providing food and income assistance or subsidies demonstrated a clear association with reduced food insecurity. The evidence that this translated into better health outcomes or reduced health care utilization, as suggested by observational studies, was less clear. Future efforts should prioritize evaluating food insecurity interventions on clinically important health outcomes, health care utilization, and health care spending.

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    Article Information

    Accepted for Publication: June 11, 2021.

    Published: August 6, 2021. doi:10.1001/jamahealthforum.2021.2001

    Open Access: This is an open access article distributed under the terms of the CC-BY-NC-ND License. © 2021 Oronce CIA et al. JAMA Health Forum.

    Corresponding Author: Carlos Irwin A. Oronce, MD, National Clinician Scholars Program, University of California, Los Angeles, 1100 Glendon Ave, Ste 900, Los Angeles, CA 90024 (coronce@mednet.ucla.edu).

    Author Contributions: Drs Oronce and Shekelle had full access to all the data in the study and take responsibility for the integrity of the data and the accuracy of the data analysis.

    Concept and design: Oronce, Miake-Lye, Shrank, Shekelle.

    Acquisition, analysis, or interpretation of data: All authors.

    Drafting of the manuscript: Oronce, Miake-Lye, Begashaw, Shrank, Shekelle.

    Critical revision of the manuscript for important intellectual content: Oronce, Booth, Shrank, Shekelle.

    Statistical analysis: Booth.

    Obtained funding: Shekelle.

    Administrative, technical, or material support: Miake-Lye, Begashaw, Shrank.

    Supervision: Shekelle.

    Conflict of Interest Disclosures: Dr Oronce reports support from the Veterans Affairs Office of Academic Affiliations through the National Clinician Scholars Program, during the conduct of the study. No other disclosures were reported.

    Funding/Support: This study was funded by Humana Inc (Award No. 1529619).

    Role of the Funder/Sponsor: The funder helped set the scope of the review and participated as an author (W.H.S.) in contextualizing results. Humana sponsored this review to understand the published evidence on interventions affecting food insecurity among adults and to inform its population health strategy. The funder had no role in the collection, management, analysis, and interpretation of the data.

    Disclaimer: The contents do not represent the views of the authors’ employer or institution, including those of the US Department of Veteran Affairs and the US government.

    Meeting Presentation: This paper was presented virtually at the Society of General Internal Medicine 2021 Annual Meeting on April 21, 2021, and the Academy Health 2021 Annual Research Meeting on June 15, 2021.

    Additional Contributions: The authors wish to thank Sachi Yagyu, MS (formerly of RAND Corp) for developing the search strategy. She was not compensated for her work beyond her regular salary.

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