A Systematic Review and Meta-analysis of Depression, Anxiety, and Sleep Disorders in US Adults with Food Insecurity.

Abstract

A large number of peer-reviewed studies, with various methodologies and populations, have addressed the effects of food insecurity (FIS) on mental health conditions such as depression, anxiety, and sleep disorders. There are currently, however, no published systematic assessments or meta-analyses of this literature. A systematic search of the literature was conducted in PubMed, PsycInfo, Embase, Scopus, and Web of Science. Cross-sectional studies assessing the association between food insecurity and depression, anxiety, or sleep disorders were identified. For each of the three health outcomes, we extracted (or calculated when possible) the following effect sizes: odds ratio (OR), Hedges' g, Pearson correlation coefficients r, or bivariate coefficients. Then, for each mental health-outcome/effect-size pair, the available studies were combined using the random effect model. Heterogeneity, publication bias, and subgroup dependence, for each meta-analysis, were also assessed. Fifty-seven studies provided cross-sectional data on the relationship between FIS and depression (n = 169,433), 13 on anxiety and psychological distress (n = 91,957), and 8 studies provided data on sleep disorders (n = 85,788). Meta-analysis showed that FIS is associated with an increased risk of testing positive for depression OR = 2.74 [95% CI 2.52-2.97, n = 135,500, Q(df = 41) = 69, I2= 40%], anxiety OR = 2.41 [95% CI 1.81-3.22, n = 51,541, Q(df = 3) = 8, I2= 63%], and sleep disorders OR = 1.80 [95% CI 1.51-2.15, n = 84,800, Q(df = 5) = 13, I2= 62%]. The highest risks were found for depression and anxiety which had statistically similar values. The results were robust to covariates and population groups. This systematic review and meta-analysis demonstrates a strong association between FIS and depression, anxiety, and sleep disorders, for which more longitudinal studies addressing effect sizes are warranted to further study causation.