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Clarifying the Association Between Food Insecurity and Chronic Disease: Why Methods Matter
Daniel J Arenas1, Sourik Beltrán2,3, Paul Okoyeh4
1Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA.
Current Nutrition Reports
|July 27, 2026
Summary
Food insecurity is strongly linked to depression and anxiety. However, its connection to heart disease and diabetes is unclear, with inconsistent research findings. Future studies need better methods to clarify these complex relationships.
Area of Science:
- Public Health
- Epidemiology
- Health Services Research
Background:
- Food insecurity (FIS) is a significant public health concern, often associated with chronic health conditions.
- Understanding the relationship between FIS and specific diseases is crucial for informing policy and clinical practice.
Purpose of the Study:
- To critically review and synthesize evidence on the associations between food insecurity and depression, anxiety, hypertension, diabetes, and dyslipidemia.
- To examine methodological insights from systematic reviews and recent studies to clarify these complex relationships.
Main Methods:
- Narrative review synthesizing methodological insights from prior systematic reviews and recent studies.
- Critical examination of the associations between FIS and selected chronic health conditions.
Main Results:
- Consistent evidence shows a significant association between FIS and higher likelihood of depression and anxiety.
- Associations between FIS and cardiometabolic conditions (hypertension, diabetes, dyslipidemia) are inconsistent and less clear.
- Methodological variations, including self-reported diagnoses versus objective measures and population heterogeneity, contribute to inconsistent findings.
Conclusions:
- FIS is strongly linked to mental health conditions like depression and anxiety.
- The relationship between FIS and cardiometabolic diseases is complex and requires further investigation with improved methodologies.
- Future research should prioritize objective disease indicators, consider population heterogeneity, account for covariates, and assess health-related worry.
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