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. Author manuscript; available in PMC: 2021 Aug 1.
Published in final edited form as: Soc Sci Med. 2020 May 17;258:113033. doi: 10.1016/j.socscimed.2020.113033

Examining associations of food insecurity with major depression among older adults in the wake of the Great Recession

Rachel S Bergmans 1, Riley Wegryn-Jones 2
PMCID: PMC7363549  NIHMSID: NIHMS1595355  PMID: 32535473

Abstract

As a psychosocial stressor, the degree to which food insecurity impacts major depression may be dependent on macro-level context, which can be examined in the wake of the Great Recession. The objective of this study was to determine (1) whether food insecurity transition status (i.e. initially food insecure, becoming food insecure, and remaining food insecure vs. not food insecure) was associated with major depression in older adults and; (2) whether this association was moderated by macro-level context. Data came from the United States Health and Retirement Study, 2008–2016. Multivariable logistic regression across all years revealed that major depression was associated with any exposure to food insecurity, however; this association was moderated by time period. Remaining food insecure was associated with major depression during all time periods. In contrast, becoming food insecure was associated with major depression in the years during and immediately following the Recession, but not in later time periods. Findings suggest that associations of food insecurity with major depression among older adults are moderated by macro-level context, consistent with theories of social comparison and relative disadvantage. Food insecurity may represent an important risk factor for major depression and mental health disparities across socioeconomic strata in old age. Thus, policies that increase access to food assistance programs or improve the quality of local food environments may buffer against the impact of food insecurity on depression and associated complications among older adults.

INTRODUCTION

Do macro-level factors—the large-scale economic, cultural, and social contexts where people live and age—moderate associations of psychosocial stressors with major depression? Food insecurity, defined as unreliable access to food of sufficient quantity or quality due to limited money or other financial resources (Gundersen and Ziliak 2015), is a psychosocial stressor that has been repeatedly associated with depression among adults over age 50 (Bergmans, Zivin, and Mezuk 2019; Jung et al. 2018; K. Kim and Frongillo 2007). As a psychosocial stressor, the degree to which food insecurity influences depression in older adults may be affected by the broader, macro-level context, which can be examined in the wake of the Great Recession.

Food Insecurity Is a Psychosocial Stressor Associated with Depression among Older Adults

Major depression is a leading cause of morbidity and mortality among older adults (Fiske, Wetherell, and Gatz 2009). For example, depressive symptoms including anhedonia and fatigue can complicate management of medical comorbidities and accelerate cognitive decline (Jorm 2000; Lin et al. 2004). Furthermore, late-life depression (i.e. depression diagnosed after age 50) represents half of all first-onset cases and is more closely associated with suicide-related behavior than depression in younger age groups (Fiske, Wetherell, and Gatz 2009).

Risk of depression among older adults is especially high for those with low socioeconomic status, in part due to a greater burden of psychosocial stressors (Koster et al. 2006). The stress process model posits that adverse events and conditions (i.e. psychosocial stressors) over the short or long term can challenge a person’s adaptive capacity (Haley et al. 1987; Pearlin 1999). In the presence of a psychosocial stressor, individuals will appraise the nature of the threat and their capacity to adjust. A person’s subsequent emotional and/or behavioral response stimulates physiological pathways (e.g. neuroendocrine and immune-inflammatory) that can be deleterious to health, including mental health (Dale, Bang-Andersen, and Sánchez 2015).

For older adults, food insecurity is an important psychosocial stressor that contributes to disparities in major depression across socioeconomic strata. Prior work consistently demonstrates associations of food insecurity with depression in older adults (Bergmans, Zivin, and Mezuk 2019; Jung et al. 2018; Kim, Park, and Kim 2019; Kim and Frongillo 2007; Vilar-Compte et al. 2016). Food insecurity challenges access to a vital resource, eliciting unique emotional and behavioral changes that can have physiological consequences implicated in the etiology of depression (Kloet, Joels, and Holsboer 2005; Miller and Raison 2016). Older adults may be particularly vulnerable to the impact of food insecurity. For example, some evidence indicates that food insecurity is more likely to result in poor diet quality among older adults than younger age groups (Bergmans, Palta, et al. 2018). Poor diet quality is in turn associated with depression, potentially as a source of chronic systemic inflammation (Bergmans and Malecki 2017). Food insecurity also exacerbates management of medical conditions that are common in older age, like diabetes (Bergmans, Zivin, and Mezuk 2019; Seligman et al. 2014). And, poor health status and medical morbidity are considered risk factors for late-life depression (Cole and Dendukuri 2003). Additionally, social isolation, loss of independence, and frailty—which increase with age (Fitzpatrick, Greenhalgh-Stanley, and Ver Ploeg 2016)—may make it more difficult to seek out alternative food sources through food assistance programs, food banks, or social networks. Therefore, older adults may feel particularly helpless when confronted with food insecurity, thus increasing the likelihood of depression (Davison et al. 2012).

Macro-Level Context may Moderate Associations of Food Insecurity with Major Depression

Multiple sociological theories articulate that older adults do not experience psychosocial stressors like food insecurity in a vacuum. For one, the social comparison theory states that individuals consider not only the presence or absence of a psychosocial stressor, but also their personal circumstance relative to their community (Schieman and Pearlin 2006). Social comparison may play an important role in the mental health of older adults. For example, among older adults with functional limitations, depression was less common in those > 75 years than those 55–64 years (Choi and Kim 2007). This is possibly because adults > 75 with functional limitations do not consider themselves to be worse off than their peers for whom functional limitations are common. Therefore, despite the potential challenges of food insecurity in old age, the impact of food insecurity on major depression may be weaker for those who do not consider themselves worse off than others in their social environment, including at the macro-level.

Other sociological research highlights that the ability or inability to tap into certain coping resources may drive the intensity of associations between psychosocial stressors and depression (Wheaton 1990; Wheaton and Montazer 2010). When considering food insecurity to be a source of psychosocial stress, the intersection of macro-level factors with food systems could determine which coping strategies are accessible to older adults. Food assistance programs and the local food environment offer two examples. First, older adults are less likely to participate in food assistance programs even when accounting for socioeconomic differences (Cunnyngham 2018), a disparity that has puzzled researchers for decades (Stavrianos 1997). However, among older adults who do participate, food assistance programs can reduce the association of food insecurity with depression (Kim and Frongillo 2007). Second, other work indicates that the association of food insecurity with poor mental health is attenuated for those who live in areas with greater access to fruits and vegetables (Bergmans et al. 2019). Nearby proximity to food retailers may be particularly important for older adults, who face a greater prevalence of reduced independence (Anstey et al. 2006) and functional limitations (Kuh 2007), than younger adults. Therefore, macro-level factors that affect enrollment in food assistance programs or the quality of local food environments could have a moderating influence on the relationship of food insecurity with major depression.

The Great Recession as an Indicator of Macro-Level Context

The Great Recession provides a novel opportunity to examine whether macro-level context modifies associations of food insecurity with major depression in older adults. The Recession was a global economic crisis that occurred from December 2007 to June 2009 (Jenkins et al. 2012), initiated by the collapse of the U.S. real-estate market (Verick and Islam 2010). From 2007 to 2009, the U.S. unemployment rate increased from 4.4 to 10.1% (Grusky, Western, and Wimer 2011). For older adults, the Recession was associated with delays in retirement expectations (McFall 2011), decreases in net worth (Sabelhaus et al. 2012), and housing instability (Trawinski 2012). Given that food insecurity is often driven by a lack of financial resources, rates of food insecurity also increased in response to the Recession (Coleman-Jensen 2012). The prevalence of food insecurity in the U.S. rose from 11.1% in 2007, to 14.6% in 2008 (Nord, Coleman-Jensen, and Gregory 2014). The prevalence of food insecurity did not stop rising until 2011, when it reached 14.9% (Coleman-Jensen et al. 2019). Recent estimates indicate that U.S. food insecurity rates returned to pre-Recession levels in 2018 (Coleman-Jensen et al. 2019).

Psychosocial stressors that accompanied the Great Recession negatively impacted the mental health of older adults. Job loss and home foreclosure among older Americans during the Recession was associated with depression (Cagney et al. 2014; Riumallo-Herl et al. 2014; Pruchno, Heid, and Wilson-Genderson 2017). While a majority of research is based on cross-sectional analyses (Frasquilho et al. 2016), some evidence indicates that associations may be sensitive to macro-level context. For example, one study examined whether being personally burdened by the economic slowdown was associated with depression among older adults in Australia (Sargent-Cox, Butterworth, and Anstey 2011). Findings indicated that the association of personal economic burden with depressive symptoms was weaker in the months immediately following the Recession, and stronger during a later time period. Sargent-Cox and colleagues (2011) articulated that a possible explanation for the lagged association is the protective effect of social comparison, which may have dissipated with time as media salience concerning the Recession declined.

The objective of this study was to build on prior work examining associations of food insecurity with depression among older adults by considering potential moderation by macro-level context. While several studies have tested associations with depressive symptoms, fewer have used diagnostic criteria for major depression. Additionally, a majority of research treats food insecurity as a static experience. However, both life transitions and cumulative experiences can impact depression in old age (Vergare 1997; Murayama et al. 2020). For example, food insecurity could be a temporary source of psychosocial stress following extenuating circumstances (e.g. lost wages due to temporary medical leave or economic shock), or more consistent for those with low socioeconomic status across the life course.

Specific aims of this study were to determine (1) whether food insecurity transition status (i.e. initially food insecure, becoming food insecure, and remaining food insecure) was associated with major depression in older adults and; (2) whether this association was moderated by macro-level context. Considering food insecurity to be a psychosocial stressor, we hypothesized that those who became food insecure and those who remained food insecure would be more likely to have major depression than those who did not experience food insecurity. Additionally, we hypothesized that individuals who experienced food insecurity during and immediately following the Great Recession would put their experience within the context of poor economic circumstances at the macro-level, and perceive themselves to be no worse-off than their peers. Thus, we expected associations of food insecurity with major depression to be blunted in the years during and immediately following the Recession (i.e. 2008 to 2010, and 2010 to 2012) when compared to later years of economic growth (i.e. 2012 to 2014, and 2014 to 2016).

METHODS

SAMPLE

This study used data from the United States Health and Retirement Study (HRS). Using a multi-stage area probability design (Heeringa and Connor 1995), HRS is a longitudinal, nationally representative sample of adults > 50 years (Sonnega and Weir 2014). U.S. Metropolitan Statistical Areas (MSA) and non-MSA counties represent the primary and secondary stages of sampling. The third stage of sampling systematically selects housing units within sampled areas, and the final stage selects a financial unit within housing units. HRS also includes supplements that oversample those who are Black, those who are Hispanic, and those who reside in the state of Florida. HRS collects information every two years on socioeconomic status, financial assets, health status, and social relationships. HRS has been fielded since 1992, replenishing their sample with new, younger participants every 6 years to maintain a representative sample of American adults in mid- and late-life. HRS was approved by the University of Michigan Institutional Review Board and; informed consent was obtained from participants prior to data collection for each wave.

Data for this study came from five HRS waves collected in 2008–2016, which provided information for all variables of interest. The analysis sample was limited to those who participated in at least two consecutive HRS waves so that we could determine food insecurity transition status. Additionally, primary analyses were limited to individuals with complete-case data for each 2-wave study period (i.e. 2008 to 2010, 2010 to 2012, etc.). The complete-case analysis sample included 20,415 unique subjects. Missingness over the four 2-wave time periods ranged from 10 to 11 %.

MEASURES

Food insecurity transition status

During each HRS wave, respondents were asked, “In the last two years, have you always had enough money to buy the food you need?”. Those who responded “No”, “Don’t Know” or refused to answer were then asked, “In the last 12 months, did you ever eat less than you felt you should because there wasn’t enough money to buy food?” Those who did not always have money to buy enough food or ever ate less because of a lack of money were considered food insecure over the past 2 years. Those who always had enough money to buy food and did not eat less because of a lack of money were considered food secure. This definition of food insecurity is comparable to the 2-item food insecurity screen (Hager et al. 2010), and was previously used to test associations of food insecurity with diabetic morbidity, depression symptomatology, and smoking cessation (Bergmans 2019; Bergmans, Zivin, and Mezuk 2019).

Next, food insecurity transition status was determined by how food insecurity status changed within each 2-wave time period in HRS. Respondents were grouped into one of four categories: (1) Not Food Insecure: not food insecure in either the baseline wave or follow-up wave; (2) Initially Food Insecure: food insecure in the baseline wave and not food insecure in the follow-up wave; (3) Became Food Insecure: not food insecure in the baseline wave and food insecure in the follow-up wave, and; (4) Remained Food Insecure: food insecure in both the baseline wave and follow-up wave.

Major depression

HRS used the Composite International Diagnostic Interview short form (CIDI-SF) to assess major depression at each wave over the previous 12 months. The CIDI-SF is designed to be compatible with diagnostic criteria established by the Diagnostic and Statistical Manual of Mental Disorders (DSM; American Psychiatric Association 2013). Consistent with the scoring method established by Walters and colleagues (2002), two stem questions determined whether respondents experienced symptoms of dysphoria or anhedonia for most of the day, and for the majority of days in a 2-week period or more. Those who did not meet this criterion were not considered to have major depression and received a CIDI-SF score of 0. Those who met this criterion were scored on a total of seven symptoms: anhedonia, appetite change, fatigue, sleep problems, trouble concentrating, feelings of worthlessness, and thoughts of death. CIDI-SF scores range from 0 to 7. Using a 90% caseness cutoff based on work by Kessler and colleagues (1998), those with a score ≥ 5 were considered to meet criteria for major depression in the previous 12 months. Additionally, those who volunteered that they were taking antidepressants when asked the CIDI-SF stem questions were also considered to have major depression (Kessler 2002). In our study, respondents were categorized by major depression status in the second wave of each 2-wave time period (i.e. in 2010 for the 2008 to 2010 time period, etc.). Additionally, baseline major depression status was assigned for the first wave of each 2-wave time period (i.e. in 2008 for the 2008 to 2010 time period, etc.).

Time period

The time period for HRS survey waves was used to indicate macro-level context during and following the Great Recession. We used four 2-wave time periods: (1) 2008 to 2010, (2) 2010 to 2012, (3) 2012 to 2014, and (4) 2014 to 2016.

Covariates

Analyses accounted for potential confounding due to demographics, socioeconomic status, and health status. Demographic covariates included age (continuous measure), gender (male; female), race/ethnicity (non-Hispanic White; non-Hispanic Black; other race/ethnicity or more than one race/ethnicity), and marital status (married; never married; separated or divorced; widowed). Socioeconomic covariates included educational attainment (≥ high school degree; < high school degree), poverty status (household income-to-poverty ratio ≤ 1.0; household income-to-poverty ratio > 1.0), work status (works for pay; does not work for pay), retirement status (retired; not retired), and wealth. Wealth was measured at the household level as the sum net value of checking accounts, savings accounts, money market accounts, term deposits, government savings bonds, treasury bills, bonds or bond funds, retirement plans, stocks and mutual funds, primary residence, secondary residence, real estate, vehicles, businesses, and all other savings; minus the net value of the balance on an equity line of credit, all mortgages, other home loans, and any other debt. Health status covariates included having a chronic medical condition and functional limitations. Respondents were considered to have a chronic condition if they reported a lifetime diagnosis of hypertension, diabetes, cancer or malignant tumor of any kind except skin cancer, chronic lung disease except asthma, a heart problem (e.g. heart attack, coronary heart disease, congestive heart failure), stroke, transient ischemic attack, a psychiatric condition, arthritis, or rheumatism. Functional limitations were defined as having at least some difficulty with one or more activities of daily living, including eating, getting in or out of bed, walking across a room, dressing, and bathing.

For each of the 2-wave time periods, most covariates were measured during the first wave. Educational attainment was assessed when respondents initially enrolled in HRS. Additionally, we considered important life transitions and role changes that occurred over the four 2-wave time periods. These included becoming divorced or widowed (yes vs. no); change in household income-to-poverty ratio (continuous measure); employment loss (became unemployed or retired vs. did not become unemployed or retire) and; receiving a diagnosis for a new chronic condition (yes vs. no).

STATISTICAL APPROACH

All analyses were conducted using SAS version 9.4 (SAS Institute Inc., Cary, NC, USA). First, X2 and F tests compared respondent characteristics by food insecurity transition status. Next, logistic regression determined associations of food insecurity transition status with major depression. Model 1 accounted for time period and baseline major depression status. Model 2 accounted for all covariates in Model 1, plus demographic factors (i.e. age, gender, race/ethnicity, and marital status). Model 3 accounted for all covariates in Model 2, plus socioeconomic factors (i.e. educational attainment, poverty status, wealth, work status, and retirement status). Model 4 accounted for all covariates in Model 3, plus health status (i.e. having a chronic condition and functional limitations). Model 5 accounted for all covariates in Model 4, plus life transitions (i.e. becoming divorced or widowed, change in household income-to-poverty-ratio, employment loss, and new diagnosis for a chronic condition).

Analyses used robust variance estimates and accounted for HRS’s complex survey design by including sample weights provided by HRS in SAS survey procedures (i.e. SURVEYLOGISTIC). Weights corresponded to the initial wave of each 2-wave time period (e.g. 2008 survey weights for the 2008 to 2010 time period, etc.). When modeling logistic regression, SAS provides the ability to account for either complex survey design (SURVEYLOGISTIC) or repeated measures (GENMOD), but not both. The primary analyses of our study were conducted using SURVEYLOGISTIC since it provides robust estimates of odds ratios (ORs) and 95% confidence intervals (CIs) that would be generated if associations were only tested within a single time period. Sensitivity analyses accounted for repeated measures in our data when testing associations of food insecurity transitions with major depression across all years.

Finally, to test whether the association of food insecurity transition status with major depression was moderated by macro-level context, an interaction term between time period and food insecurity transition status was included in Model 5. In the event that an interaction was observed, stratified analyses using the DOMAIN statement in SURVEYLOGISTIC provided associations of food insecurity with major depression for each time period.

RESULTS

Table 1 describes the study sample by food insecurity transition status. During HRS 2008–2016, for at least one of the 2-wave time periods, 17,455 persons did not experience food insecurity (73% of persons, 86% of observations); 2,544 persons experienced initial food insecurity (11% of persons, 5% of observations); 2,416 persons experienced becoming food insecure (10% of persons, 4% of observations) and; 1,545 persons experienced remaining food insecure (6% of persons, 5% of observations). Overall, experiencing any food insecurity over a 2-wave time period was more common in 2008 to 2010, among those who were not non-Hispanic White, and among those who were divorced, separated, or never married, and less common with increasing age. Experiencing any food insecurity was also more common among those with low socioeconomic status (e.g. less household wealth and living at or below the poverty level), and those with functional limitations, a chronic condition, or major depression.

Table 1.

Sample characteristics by 2-wave food insecurity transition status, Health and Retirement Study 2008–2016a

Food Insecurity Transition
Characteristics Not Food Insecure (FI)
n = 49,526
(unique n = 17,455)		 Initially FI
n = 2,713
(unique n = 2,544)		 Became FI
n = 2,559
(unique n = 2,416)		 Remained FI
n = 2,732
(unique n = 1,545)		 Pb
Time Period <0.001
2008–2010 11,342 (21.7) 395 (15.9) 502 (22.0) 328 (14.4)
2010–2012 13,965 (27.6) 825 (29.2) 863 (32.1) 894 (30.2)
2012–2014 12,844 (26.3) 800 (29.7) 679 (25.9) 846 (30.7)
2014–2016 11,375 (24.5) 693 (25.1) 515 (20.0) 664 (24.7)
At Baseline Wave
Have major depression 2,509 (5.4) 379 (13.9) 315 (14.2) 620 (23.7) <0.001
Age, mean, (95% CI) 65.7 (65.2, 66.1) 62.4 (61.9, 62.9) 62.6 (62.0, 63.1) 60.7 (60.1, 61.3) <0.001
Female 28,503 (54.4) 1,677 (57.9) 1,603 (57.9) 1,894 (65.9) <0.001
Race/Ethnicity <0.001
 Non-Hispanic White 35,460 (82.0) 1,134 (59.2) 1,048 (57.4) 1,005 (56.3)
 Non-Hispanic Black 7,531 (8.2) 906 (20.1) 841 (19.8) 1,114 (24.4)
 Other 6,535 (9.8) 673 (20.8) 670 (22.8) 613 (19.2)
Marital Status <0.001
 Married 30,842 (64.8) 1,171 (47.0) 1,112 (47.2) 863 (33.1)
 Divorced or separated 6,046 (12.8) 674 (24.5) 633 (24.0) 876 (33.7)
 Widowed 8,469 (13.1) 459 (13.7) 456 (13.8) 504 (15.6)
 Never married 4,169 (9.4) 409 (14.8) 358 (15.0) 489 (17.6)
≥ High school degree 41,931 (88.86) 1,919 (76.82) 1,725 (73.90) 1,890 (74.04) <0.001
Wealth, mean $1,000 (95% CI) 594 (549, 638) 219 (164, 274) 189 (144, 234) 34 (27, 41) <0.001
Live in poverty 3,541 (5.8) 732 (21.3) 633 (20.3) 992 (34.3)
Work for pay 20,017 (47.9) 991 (41.2) 881 (39.3) 829 (33.5) <0.001
Retired 30,856 (55.4) 1,492 (52.2) 1,389 (50.9) 1,465 (51.5) 0.0011
Functional limitations 5,828 (10.2) 704 (24.1) 648 (23.3) 1,031 (38.0) <0.001
Have a chronic condition 42,256 (82.5) 2,364 (87.4) 2,242 (87.8) 2,485 (91.5) <0.001
At Follow-Up Wave
Became divorced or widowed 1,450 (2.5) 81 (3.0) 93 (3.1) 57 (2.2) 0.15
Employment loss 6,994 (14.7) 429 (16.4) 501 (20.1) 507 (18.8) <0.001
Change in income-to-poverty ratio, mean (95% CI) −0.19 (−0.46, 0.07) −0.20 (−0.75, 0.34) −0.37 (−0.63, −0.12) −0.04 (−0.15, 0.08) 0.09
New chronic condition 8,734 (17.1) 545 (20.5) 606 (23.5) 629 (23.2) <0.001
Have major depression 2,416 (5.1) 324 (11.7) 343 (14.6) 579 (20.9) <0.001
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a

Unique subject n=20,415

b

X2 or F test

When comparing persons across food insecurity transition status, those who remained food insecure had distinct characteristics. These individuals were more likely to be women, non-Hispanic Black, and younger. They were also more likely to have more depression symptoms at baseline, major depression at follow-up, lower socioeconomic status, and poorer health status. Those who were either initially food insecure or became food insecure appeared the most similar across demographic factors, socioeconomic status, and health status.

Table 2 presents ORs and 95% CIs for the association of food insecurity transition status with major depression across all years (2008–2016). When compared to those who did not experience food insecurity over a 2-wave time period, those who were initially food insecure had a 1.2 (95% CI = 1.0, 1.5) times greater odds of major depression in fully adjusted models. Additionally, those who became food insecure had a 1.7 (95% CI = 1.4, 2.0) times greater odds of major depression, as did those who remained food insecure (OR = 1.7; 95% CI = 1.4, 2.0). Other factors associated with major depression were baseline major depression status, gender, race/ethnicity, marital status, household wealth, work and retirement status, functional limitations, having a chronic condition, becoming divorced or widowed, employment loss, and receiving a new diagnosis for a chronic condition (Supplemental Table 1). Associations of food insecurity transitions with major depression were consistent when accounting for repeated measures across all years (Supplemental Table 2).

Table 2.

Odds ratios (ORs) and 95% confidence intervals (CIs) for the association of food insecurity transition status with major depression, Health and Retirement Study 2008–2016a

Model 1b
Year and Baseline Mental Health 		Model 2c
Model 1 + Demographics 		Model 3d
Model 2 + Socioeconomic Status 		Model 4e
Model 3 + Health Status 		Model 5f
Model 4 + Life Transitions
Characteristics OR (95% CI) P OR (95% CI) P OR (95% CI) P OR (95% CI) P OR (95% CI) P
Food Insecurity Transition <0.001 <0.001 <0.001 <0.001 <0.001
Not food insecure Reference Reference Reference Reference Reference
Initially food insecure 1.8 (1.5, 2.1) 1.6 (1.4, 2.0) 1.4 (1.2, 1.8) 1.3 (1.1, 1.6) 1.2 (1.0, 1.5)
Became food insecure 2.4 (2.0, 2.9) 2.3 (1.9, 2.7) 2.0 (1.6, 2.4) 1.8 (1.5, 2.2) 1.7 (1.4, 2.0)
Remained food insecure 2.8 (2.4, 3.4) 2.5 (2.1, 3.0) 2.1 (1.7, 2.5) 1.8 (1.5, 2.2) 1.7 (1.4, 2.0)
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a

Unique subjects n=20,415

b

Model 1 accounts for baseline major depression status and time period

c

Model 2 accounts for all variables in Model 1, plus age, gender, race/ethnicity, and marital status

d

Model 3 accounts for all variables in Model 2, plus educational attainment, wealth, poverty status, work status, and retirement status

e

Model 4 accounts for all variables in Model 3, plus functional limitations and having a chronic condition

f

Model 5 accounts for all variables in Model 4, plus becoming divorced or widowed, employment loss, change in income, and being diagnosed with a new chronic condition

Time period moderated the association of food insecurity transition status with major depression (interaction p-value = 0.007; Supplemental Table 3). Figure 1 presents associations of food insecurity transition status with major depression, stratified by the four 2-wave time periods from 2008–2016. ORs and 95% CIs are also provided in Supplemental Table 4. Those who were initially food insecure had higher odds of major depression than those who were not food insecure in 2012 to 2014. For all other time periods confidence intervals for the association of initial food insecurity with major depression crossed 1.0. Those who became food insecure had higher odds of major depression than those who were not food insecure in 2008 to 2010, and in 2010 to 2012. During later time periods (2012–2016), confidence intervals for the association of becoming food insecure with major depression crossed 1.0. Remaining food insecure was associated with greater odds of major depression during all time periods.

Figure 1.

Figure 1.

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Odds ratios (ORs) and 95% confidence intervals (CIs) for the association of food insecurity transitions with major depression by time period among older adults, HRS 2008–2016

IFI = Initially food insecure; BFI = Became food insecure; RFI = Remained food insecure. Those who were not food insecure within a 2-year time period served as the reference group.

* indicates 95% confidence interval does not cross 1.0

Adjusted for major depression status at baseline, time period, age, race/ethnicity, gender, marital status, educational attainment, wealth, poverty status, work status, retirement status, functional limitations, having a chronic condition, employment loss, change in income, change in marital status and receiving a diagnosis for a new chronic condition.

Unique subjects = 20,415

Interaction p-value = 0.007

DISCUSSION

In a nationally-representative, longitudinal cohort of Americans aged > 50 years, we determined the association of food insecurity transition status with major depression and; whether this association was moderated by macro-level context. When examining associations for all years (2008–2016), those who experienced initial food insecurity, becoming food insecure, and remaining food insecure were more likely to have major depression than those who did not experience food insecurity. Additionally, time period moderated the association of food insecurity transition status with major depression. This suggests that macro-level context plays an important role in the relationship of food insecurity with major depression.

We initially hypothesized that the impact of becoming food insecure and remaining food insecure on major depression would be blunted in the years during and immediately following the Great Recession. Our hypothesis was rooted in prior work which indicated that greater media salience of poor economic conditions surrounding the Great Recession could buffer against individual psychosocial stress and subsequent depressive symptoms (Sargent-Cox, Butterworth, and Anstey 2011). However, while time period moderated the association of food insecurity transition status with major depression, findings were inconsistent with our hypothesis.

Becoming food insecure was associated with major depression in the time periods during and immediately following the Great Recession, but not in later years. This suggests that social comparison related to socioeconomic status and psychosocial stressors has a negative impact on mental health among older adults, which is consistent with prior work on relative disadvantage. For example, one study observed that older Americans who lost a considerable amount of wealth during the Recession (i.e. nearly $250,000 in non-housing wealth) were 50% more likely to feel depressed and 35% more likely to use antidepressants than those without considerable wealth loss (McInerney, Mellor, and Nicholas 2013). Similar findings were observed in Icelandic adults who felt that they had suffered more than others during the 2010 financial crisis (Ragnarsdottir, Bernburg, and Olafsdottir 2013). Additional insight comes from work by Wheaton and colleagues (1990; 2010), who observe that the mental health impact of psychosocial stressors can depend on an individual’s preceding circumstances and ability to tap into specific coping strategies. It is possible that those who became food insecure around the time of the Recession never expected it based on their prior socioeconomic status, thus making coping more difficult. Additionally, the depth and severity of food insecurity that people experienced during the Recession may have been worse compared to other time periods (Balistreri 2016).

Alternatively, it is also possible that macro-level context in later years (2012–2016) attenuated the stress of becoming food insecure. In the U.S., the Supplemental Nutrition Assistance Program (SNAP) is a federal food assistance program administered at the state level. SNAP provides a supplemental benefit for households with low-income to purchase food resources from authorized retailers, often via an electronic benefits transfer card that is automatically reloaded each month (Bartfeld et al. 2015). Participation in SNAP has been associated with fewer depressive symptoms and less psychological distress among those with a high risk of food insecurity (Kim and Frongillo 2007; Oddo and Mabli 2015; Bergmans, Berger, et al. 2018). During the Great Recession, SNAP participation rates reached record highs (Pavetti and Rosenbaum 2010). This trend continued in the following years, with 75% of eligible-households participating in 2011, compared to 54% of eligible-households participating in 2002 (Rosenbaum 2013). As SNAP participation increased following the Recession, so did the number and density of authorized food retailers from 2007 to 2014 (Shannon et al. 2016). The Recession also sparked changes within SNAP. Specifically, payment accuracy (i.e. avoiding under- and over-payment) improved (Rosenbaum 2013) and policy changes at the federal and state level (e.g. the American Recovery and Reinvestment Act of 2009) contributed to greater enrollment (Ganong and Liebman 2018). These macro-level policy and social changes in the wake of the Recession may have improved local food environments and increased social acceptance of receiving food assistance. Thus, individuals who became food insecure in later years after the Recession may have perceived their initial circumstance to be less dire given a greater ability to access effective coping strategies.

Findings also indicated that remaining food insecure was associated with major depression across all time periods. There are a number of reasons why consistent food insecurity could increase the risk of major depression among older adults. The longer food insecurity lasts the more likely it is to disrupt emotional and behavioral responses that increase risk of major depression (Miller and Raison 2016; Kloet, Joëls, and Holsboer 2005). For example, while temporary food insecurity is a source of psychosocial stress, it may not result in lasting changes of pathways associated with major depression, like poor diet quality (Bergmans and Malecki 2017) or poor management of medical conditions (Cole and Dendukuri 2003). Additionally, it may take time for other mediating pathways to lead to major depression. For example, food insecurity is associated with a number of poor health outcomes among older adults including functional impairments (Lee and Frongillo 2001), frailty (Perez-Zepeda et al. 2016), and poorer cognitive function (Gao et al. 2009), which are considered risk factors for major depression in late-life (Aziz and Steffens 2013).

It is not readily apparent why an association between initial food insecurity and major depression may have occurred in 2012 to 2014, but not in earlier or later time periods. In the U.S., 2012 marked the beginning of food insecurity rates declining, and eventually returning to pre-Recession levels in 2018 (Coleman-Jensen et al. 2019). It is possible that “turning of the tide” represents a unique vulnerability to psychosocial stressors. Perhaps escaping food insecurity during a time when many others are experiencing the effects of economic growth is uniquely challenging, or requires a certain set of coping behaviors that are subsequently harmful to mental health. However, this hypothesis requires further study.

While not the focus of this study, life transitions that are common in old age were associated with major depression in our analyses. Specifically, becoming widowed or divorced, leaving the workforce, and receiving a new medical diagnosis were associated with greater odds of major depression. These life transitions could provide opportunities for targeted intervention or early detection.

STRENGTHS AND LIMITATIONS

This study leveraged longitudinal data collected over eight years from a nationally representative sample of American adults aged > 50 years to determine associations of food insecurity transitions with major depression. While several studies have examined associations of food insecurity with depressive symptoms, our study is among the few to use clinical diagnostic criteria for major depression. Additionally, these data came from time periods during and after the Great Recession, which enabled us to examine moderation by macro-level context. Results provide a valuable contribution regarding the impact of food insecurity on disparities in major depression among older adults across socioeconomic strata.

Results of this study should be interpreted in light of its limitations. First, since analyses were limited to complete-case data, missingness of 10–11% in the 2-year time periods may have introduced bias. However, when repeating analyses using multiple imputation (unique subject n = 22,238), findings remained consistent for the most part (Supplemental Table 4). The only difference when using multiple imputation was that confidence intervals for the association of becoming food insecure with major depression no longer crossed 1.0 during the 2014–2016 time period. Second, two HRS core survey questions made it possible to determine food insecurity status as a binary measure. However, examining associations across a broader range of food insecurity severity (e.g. worrying about having enough food to eat vs. experiencing hunger pains) was not possible. Future work may consider addressing this limitation by using the 6- or 18-item USDA Food Security Survey Module (Bickel et al. 2000). Third, our analyses adjusted for whether respondents were diagnosed with a new chronic medical condition. This could attenuate associations since it would include those who received a new diagnosis for major depression. However, in sensitivity analyses that excluded these persons from being considered as having a new diagnosis, associations of food insecurity with major depression did not change (data not shown). Fourth, confounding due to unobserved covariates is possible (e.g. area-level access to food and health services). It is also possible that the association of food insecurity with major depression is moderated by other covariates in addition to time period that could inform strategies for intervention.

Finally, major depression was assessed over the previous twelve months, and change in food insecurity status was assessed over the previous two years. Therefore, it is possible that in some cases, major depression onset preceded the experience of food insecurity. Adjusting for baseline major depression status and examining food insecurity transitions helps mitigate this. For example, among those who remained food insecure, their experience of food insecurity was a preexisting condition before the onset of major depression. Nevertheless, this is still a limitation particularly for those who became food insecure over the 2-year time periods. While other approaches are possible using HRS data, they also have drawbacks. HRS includes the Center for Epidemiologic Studies Depression Scale (CESD), which is a measure of depression over the past 2 weeks instead of over the past 12 months. However, the CESD is not consistent with diagnostic criteria for major depression and considered a poor substitute for the CIDI-SF (Dang, Dong, and Mezuk 2019). Additionally, use of the CESD would not avoid the possibility that depressive symptoms preceded food insecurity during the same wave. A second option would be using the CIDI-SF score from the HRS wave that occurred two years later, however; since major depression is only assessed over the previous twelve months, this would exclude an entire year of observation from follow-up.

CONCLUSIONS

Findings indicate that food insecurity is associated with major depression among older adults and; both preventing food insecurity and mitigating existing food insecurity may be important targets for intervention. Additionally, results suggest that associations of food insecurity transitions with major depression are moderated by macro-level context. For example, older adults who became food insecure during the Great Recession may have benefited from policies that expanded SNAP enrollment among beneficiaries and program participation among food retailers. In sum, food insecurity could represent an important risk factor for major depression and mental health disparities across socioeconomic strata in old age. Thus, policies that increase access to food assistance programs or improve the quality of local food environments may buffer against the impact of food insecurity on depression and associated complications among older adults.

Supplementary Material

Supplemental Table 1
Supplemental Table 2
Supplemental Table 3
Supplemental Table 4

HIGHLIGHTS.

  • We determined associations of food insecurity with major depression (MD) in older adults.

  • We also tested moderation by time period during and after the Great Recession.

  • Becoming food insecure was associated with MD during the Recession.

  • Remaining food insecure was associated with MD during all time periods.

  • Findings are consistent with theories of social comparison and relative disadvantage.

Acknowledgments

DECLARATION OF INTEREST: RSB is supported by the United States National Institute of Mental Health (NIMH T32 MH73553).

Footnotes

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Associated Data

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Supplementary Materials

Supplemental Table 1
NIHMS1595355-supplement-Supplemental_Table_1.docx (21KB, docx)
Supplemental Table 2
NIHMS1595355-supplement-Supplemental_Table_2.docx (12.8KB, docx)
Supplemental Table 3
NIHMS1595355-supplement-Supplemental_Table_3.docx (15.6KB, docx)
Supplemental Table 4
NIHMS1595355-supplement-Supplemental_Table_4.docx (22.8KB, docx)

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