Interventions to Address Food Insecurity Among Adults in Canada and the US
Bibliographic record
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: ), 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.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.007 | 0.037 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.003 | 0.003 |
| Bibliometrics | 0.005 | 0.008 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.005 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".