INTRODUCTION

Depression and anxiety are leading causes of morbidity in the USA, with significant health and economic impacts. They are also associated with other comorbid conditions such as cardiovascular disease, obesity, and diabetes.1,2,3 Similarly, sleep disorders have strong associations with depression and anxiety, also leading to significant morbidity over time.4

A large body of research has shown that socioeconomic status (SES) in the USA has a significant influence on the health outcomes of populations.5,6,7,8 An important component of SES is household food security—the basic ability to purchase food with nutritional value for oneself and/or one’s family.9 Food insecurity (FIS) is complex, with varying levels of severity, ranging from uncertainty in obtaining food to inability to eat sufficient calories.10, 11 Various questionnaires, with evolving validity, have been developed over the last 30 years to study this complex issue,10, 12, 13 such as the US Household Food Security Survey Module, which contains questions that assess a range of conditions and behaviors due to insufficient availability of food throughout the previous 12 months. Considerable research using these surveys has demonstrated that FIS is prevalent in many subgroups of the US population,14 findings that in turn have resulted in significant efforts to determine the effects of FIS on health outcomes.

Although there have been several reviews on the influence of FIS on various health outcomes,15, 16 to date, there have been few comprehensive systematic reviews in this area.15,16,17 Previous reviews had methodological limitations, including absent subgroup data and individual/group bias analyses. Furthermore, previous reviews also failed to address the association between FIS and mental health outcomes.15,16,17

We therefore conducted a meta-analytic investigation to determine the magnitude, characteristics, and consistency of the relationship between screening positive for FIS and screening positive for depression, anxiety, and sleep disorders. Confirmation of this association would support follow-up screening for depression, anxiety, and sleep disorders in patients screening positive for FIS, and vice versa, which could improve the care provided to marginalized populations.

METHODS

Overall Approach

This report focuses on subjects from the general population or any specific subgroups, with an exposure to FIS and the risk for depression, anxiety, and sleep disorders when compared to subjects without FIS. Here, we define depression as participants’ feelings of sadness and loss of interest or pleasure in life activities during a given amount of time; anxiety as excessive worry occurring on most days for at least 6 months; and sleep disorders as excessive changes in sleep latency, duration, or interruptions. Patients meeting these definitions were identified by standardized screening questionnaires, where responses could be coded for comparative analysis.

Search Strategy

PubMed, PsycINFO, Scopus, Web of Science, and Embase databases were searched for articles up to 15 December 2018. Subsets of these databases have been shown to be sufficient for previous mental health meta-analyses.18,19,20,21 The search targeted US studies that investigated the association of food insecurity with depression, anxiety, and sleep disorders. Search terms for these concepts were tailored for each database and are presented in the S1 Supplemental Documents in their entirety. Filters used such as “journal articles,” “USA,” and others were also specified. Duplicates were removed using the commercial software RefWorks.

Study Eligibility Criteria and Selection

Three authors independently examined each abstract to determine if the article (i) contained primary quantitative data about adults in the USA; (ii) measured food security/insecurity; (iii) assessed a mental health outcome such as depression, anxiety, or sleep disorders; and (iv) compared the health outcome directly to food security and not through a third variable. For the latter criterion, the raters were instructed to examine the text of the manuscript if the information was not clear from the abstract. Interrater reliability was analyzed using the group Fleiss kappa and Cohen kappa permutated through different raters.39,40,41,42,43,44 Most studies had a wide age range, while only a few studies provided data on age-specific groups: five studies on 50+-year-old adults and six on young adults/college freshmen. There were no male-inclusive studies, while ten studies provided women-specific data. Other specific groups included HIV+ patients, veterans, and Hispanics. The major results of the meta-analyeses are summarized in Table 1.

Table 1 Major Results from the Seven Meta-analyses
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Results of Individual Studies and Synthesis of Results

Depression

Depression was measured using several validated scales including the Burnam Depression Scale (BDS) (n = 183), Center for Disease Control Healthy Days Measure (CDC-HDM) (n = 1956), Center for Epidemiological Studies Depression Scale (CESD) (n = 8439), Composite International Diagnostic Interview (CIDI) (n = 4347), Geriatric Depression Scale (GDS) (n = 938), Patient Health Questionnaire (PHQ) (n = 70,575), and others.

Among the studies with sufficient odds ratio data (42 studies, n = 135,550) (Fig. 2), the OR was 2.74 [95% CI 2.52–2.97, Q(df = 41) = 69, I2 = 40%].40, 41, 45,46,47,48,49,50,51,52,53,54,55,56,57,58,59,60,61,62,63,64,65,66,67,68,69,70,71,72,73,74,75,76,77,78,79,80,81,82,83,84 One study was divided into two groups for the meta-analysis.76 Thirteen studies (n = 5837) (Fig. 3) provided sufficient data to calculate a corrected standardized mean difference of g = 0.63 [95% CI 0.54–0.71, Q(df = 12) = 19, I2 = 36%].47, 70, 85,86,87,88,89,90,91,92,93,94,95 As for the three studies (n = 28,706) with sufficient data to determine the Pearson’s correlation coefficient r,96,97,98 the results were r = 0.29 [95% CI 0.18–0.39, Q(df = 2) = 28, I2 = 93%] (S2 Supplemental Document, Fig. S2–1).

Figure 2
figure 2

Statistical summary and forest plot of OR for the association between FIS and depression.

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Figure 3
figure 3

Statistical summary and forest plot of Hedges’ g for the association between FIS and depression.

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Anxiety and Psychological Distress

The most common scale (or subset of) for measuring anxiety and psychological distress were the 7-item anxiety scale (GAD-7) (n = 50,321) and the Kessler scale (n = 37,389), respectively. Other commonly used scales included the caretaker portion of the Child Behavior Check List (CBCL) (n = 724) and the Short Form 12-item Health Survey (n = 683). Four studies (n = 51,541) (Fig. 4) provided sufficient data to calculate an odds ratio of 2.41 [95% CI 1.81–3.22, Q(df = 3) = 8, I2 = 63%],39, 52, 77, 82 while three (n = 825) (Fig. 5) yielded a Hedges’ g = 0.50 [95% CI 0.34–0.66, Q(df = 2) = 1.2, I2 = 0%].47, 95 For psychological distress, five studies (n = 39,439) (Fig. 6) were combined and produced an odds ratio of 2.28 [95% CI 1.14–4.56, Q(df = 4) = 150, I2 = 97%].99,100,101,102,103

Figure 4
figure 4

Statistical summary and forest plot of OR for the association between FIS and anxiety.

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Figure 5
figure 5

Statistical summary and forest plot of Hedges’ g for the association between FIS and anxiety.

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Figure 6
figure 6

Statistical summary and forest plot of OR for the association between FIS and psychological distress.

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Sleep Disorders

Sleep disorders were mostly measured using various custom questions about difficulties falling or maintaining sleep (n = 11,577) and insufficient sleep (n = 73,243).52, 104,105,106,107,108 Combining the six studies (n = 84,800) (Fig. 7) with sufficient data to calculate the OR of sleep disorders yielded an OR = 1.80 [95% CI 1.51–2.15, Q(df = 5) = 13, I2 = 62%]. Two studies (n = 988) (Fig. 8) with data about sleep duration and quality were combined to calculate the standardized mean difference, g = − 0.44 [95% CI (− 0.78)–(− 0.09), Q(df = 1) = 3, I2 = 66%].107

Figure 7
figure 7

Statistical summary and forest plot of OR for the association between FIS and sleep disorders.

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Figure 8
figure 8

Statistical summary and forest plot of g for the association between FIS and sleep disorders.

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Further Analyses

Risk of Bias Across Studies

Among the 42 studies reporting the odds of depression with FIS, there was no evidence of bias using either funnel plots or statistical tests (Begg’s p = 0.45, Egger’s p = 0.3). Similar results were obtained for the assessment of depression using Hedges’ g (Begg’s p = 1.0, Egger’s p = 0.88). The other five major meta-analyses had fewer than six studies and would therefore provide very low statistical power for the Begg’s and Egger’s publication bias tests109, 110 (see the S3 Supplemental Document).

Subgroup Analysis

Table 2 shows the results for meta-analysis of subgroups for ORDep. Subgroup analyses of studies that adjusted the odds ratio (AOR) in terms of covariates yielded a combined result that did not differ significantly from the OR for all manuscripts. Similarly, analysis of the studies that did not correct for covariates did not differ either. Studies involving only women had results lower than the total. Studies involving Hispanics had the highest OR and senior citizens had the lowest. However, the 95% confidence interval of all subgroups contained the average found for all studies.

Table 2 Subgroup Analysis for the Depression Studies with Reported (or Calculable) OR
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DISCUSSION

These large standardized meta-analyses show that FIS is associated with an increased risk of depression, anxiety, and sleep disorders. For physicians caring for diverse or marginalized populations of patients, individuals screening positive for FIS may warrant follow-up screening for depression, anxiety, and sleep disorders. Similarly, for patients manifesting evidence of depression, anxiety, and sleep disorders, it may be appropriate to assess for the presence of FIS, especially given the link between nutrition and emotional well-being.

The evidence for the FIS–depression association is perhaps the most significant, with 57 studies and 169,433 participants. The studies spanned several populations such as college freshmen, seniors, veterans, HIV+ individuals, low-income caretakers, and the general population. This is among the largest pool of participants for a meta-analysis of mental health outcomes.18, 32, 111, 112

Subgroup analysis suggests the association between FIS and depression was smaller for women; unfortunately, there were not enough men-only studies for subgroup analysis and so the comparison was done with respect to all-gender studies. The results also showed that the FIS/depression association was consistent for veterans, seniors, HIV+ individuals, and Latinos. Furthermore, the agreement between studies with or without covariate analysis suggests that covariates are not responsible.97

The similarity between the increased risks for depression and anxiety was also remarkable. This suggests that anxiety and depression from FIS may be interconnected in their mechanism or predisposing factors. Also interesting, however, was that the risk of sleep disorders was smaller than the former two, although there were too few studies on sleep disorders to be definitive.

Analysis of the studies by the g effect size also showed a significant and considerable association. (g = 0.63 for depression and g = 0.50 for anxiety). In Cohen’s scale, this corresponds to a medium-to-large effect size; although it should be noted that this scale is subjective. Cohen himself, and several following authors, have pointed out that relevant comparisons are more important than the suggested scale.113 As more authors report effect sizes, we can develop better scales to assess the effects of certain variables on outcome measures.

Another useful characteristic of the g effect size is that it allows the Z-score interpretation of results. An effect size of 0.63 means that we expect the average FIS individual to have a depression score higher than 75% of food-secure individuals. Similarly, the average FIS individual would be expected to have an anxiety score higher than 69%. The effect sizes are consistent for different depression screening scales, and even subscales. This is beneficial because it may be difficult to choose cutoff scores for a smaller subset of the original scale. Finally, for sleep, the g of − 0.44 corroborates a smaller association to FIS than that of depression and anxiety.

Several limitations are noted. First, this analysis focused only on cross-sectional studies, and therefore, our results and conclusions cannot speak to causation.

Second, we only included studies about populations in the USA. As this work represents the initial analysis of this literature, we believe it was necessary to have this restriction given that poverty and markers of it such as FIS are contextual, varying in meaning and impact from one country to another. Situations in which individuals may be able to eat three meals per day, with high caloric content but poor nutritional quality, may be more prevalent in the USA compared to other countries where individuals are unable to purchase enough food to meet basic caloric needs. Therefore, limiting this review to studies conducted in the USA minimized the confounding influence of varying contextual definitions of FIS. Despite this, we were still able to assemble a large number of studies for our analysis. The diversity of the US population offered numerous opportunities for subgroup analyses.

Third, caution should be exercised in interpreting the significance of the effect sizes g and r, as there are an insufficient number of published studies on the effect of other SES markers on depression, anxiety, and sleep disorders. The standard definitions of “small” or “large” effect sizes were originally proposed with the suggestion to carefully consider context.114 Therefore, it is difficult to state if these effect sizes are large or small given the paucity of other data on other makers of SES for comparison. It may be that other components of low SES have a stronger association with depression, anxiety, and sleep disorders. Fourth, we did not register the project in a protocol database. As this is becoming the norm, all future systematic reviews in this topic, including from the authors, should follow this emerging guideline.

Finally, it should be noted that “depression” was identified by questionnaires assessing symptoms of depression. This analysis does not speak to associations with clinical diagnoses of depression made by a healthcare provider such as major depressive episodes, dysthymic disorders, bipolar episodes, or even substance-induced mood or adjustment disorders.

CONCLUSIONS

This systematic review and meta-analysis demonstrates a strong association of FIS with depression, anxiety, and sleep disorders, that provides further rationale for the screening of patients for FIS.