have to write bibliography Write an Outline for your paper. From the articles you’ve looked at, what are some ideas/arguments you can make about the topic? What about a main thesis? Introduction — es

Conclusions:The study shows the extent to which food insecurity results in erratic stress among vul- nerable populations and how high levels of hunger may lead to a more inconsistent stress response.

Findings reinforce the need for more mental health services and food programs for young adults who have experienced homelessness.

Keywords:hunger, stress, ecological momentary assessment, homeless persons, young adults A limited but growing body of research has examined food inse- curity among young adults who experience homelessness (Crawford et al., 2014;Haskettetal.,2021;Johnson et al., 2019;Tucker et al., 2022). For example, a series of studies have found food insecurity prevalence estimates in this population to range between 28% and 85% (Bowen & Irish, 2018;Crawford et al., 2015;Goldman-Hasbun et al., 2019;Tarasuk et al., 2009;Whitbeck et al., 2006)andthat food insecurity persists even after a young adult has exited home- lessness through programs such as permanent supportive housing (Johnson et al., 2019). Studies have also identified increased risk behaviors among young adults experiencing homelessness thatresult from food insecurity including exchange sex, stealing, and scavenging in dumpsters for food (Bowen & Irish, 2018;Crawford et al., 2015;Goldman-Hasbun et al., 2019;Whitbeck et al., 2006).

Even when food programs such as food stamps and soup kitchens are available, young adults may not access them due to feelings of stigma (Johnson et al., 2019).

Resulting hunger from experiencing homelessness and food insecurity could lead to increased levels of stress that add to cumu- lative health risk (Hernandez et al., 2019). Biologically, stress results in an increase in cortisol levels, which is thought to pro- mote hunger through an increase in the amount of insulin, leptin, Eldin Dzubur https://orcid.org/0000-0002-3248-5327 Sara Semborski https://orcid.org/0000-0003-3295-0759 Brian Redline https://orcid.org/0000-0002-0694-1106 Donald Hedeker https://orcid.org/0000-0001-8134-6094 Genevieve F. Dunton https://orcid.org/0000-0002-4129-3829 Benjamin F. Henwood https://orcid.org/0000-0001-8346-3569 Eldin Dzubur served as lead for conceptualization, formal analysis, and writing—original draft. Sara Semborski contributed equally to project administration, validation, writing—original draft, and writing—review and editing and served in a supporting role for formal analysis. Brian Redline served as lead for project administration and contributed equally to data curation, writing—original draft, and writing—review and editing.

Donald Hedeker served as lead for validation, contributed equally to formal analysis, and served in a supporting role for writing—review and editing.Genevieve F. Dunton contributed equally to formal analysis and served in a supporting role for validation and writing—review and editing. Benjamin F.

Henwood served as lead for funding acquisition, resources, and supervision and contributed equally to writing—original draft and writing—review and editing.

The study was funded by grants from the National Institute of Mental Health (1R01 MH110206 and F31MH126641). We thank the study participants, the homelessness services agencies that helped with recruitment, and Danielle Madden for her contributions to the team. We have no conflicts of interest to disclose.

Correspondence concerning this article should be addressed to Sara Semborski, Suzanne Dworak-Peck School of Social Work, University of Southern California, 669 West 34th Street, Montgomery Ross Fisher (MRF) Building, Suite 203, Los Angeles, CA 90089, United States. Email:

[email protected] 559 Health Psychology ©2022 American Psychological Association2022, Vol. 41, No. 8, 559–565 ISSN: 0278-6133https://doi.org/10.1037/hea0001214 This document is copyrighted by the American Psychological Association or one of its allied publishers.

This article is intended solely for the personal use of the individual user and is not to be disseminated broadly. and neuropeptide (Brownell & Walsh, 2017). Furthermore, evi- dence from human and animal models suggests that eating reduces the physiological stress response, acting as a negative feedback loop in the presence of stress (Finch & Tomiyama, 2014), and may thus be worsened under conditions of chronic stress, leading to excess calorie consumption. In addition to biological models that have identified a temporally plausible causal mechanism to hunger as a result of stress, studies using real-time sampling have substantiated thesefindings in situ. For example, a 10-day ecologi- cal momentary assessment (EMA) protocol using a sample of chil- dren and adults found that reasons for eating were primarily hunger-driven under conditions of higher stress (Reichenberger et al., 2018). Still, the relationship between hunger and stress is thought to vary in the general population due to individual factors (e.g., body mass index), environmental factors, and time of day (Block et al., 2009;Brownell & Walsh, 2017). For instance, time- varying effects models using EMA data from young adult college students showed a nonlinear relationship between hunger and stress, suggesting that the relationship between hunger and stress was stronger in the late afternoons and evenings (Huh et al., 2015). Further, there is an established relationship between the number of stressful events and deterioration of mental health (Kar- atekin, 2018), making those who experience homelessness particu- larly vulnerable. In fact, data have shown up to 98% of young adults experiencing homelessness meet criteria for a mental health disorder (Hodgson et al., 2013).

Yet compared to the effects of stress on hunger, the temporal effect of hunger on stress levels is less understood, especially in the context of everyday lives of vulnerable populations with unsta- ble access to food. Qualitative research has revealed how hunger has impacted mental health and contributed to chronic stress of parents, often also impacting their children’s well-being (Knowles et al., 2016). Negative developmental effects related to hunger have also been documented in younger populations, particularly regarding self-control, attentiveness, and task persistence, all of which contributed to poorer social skills (Howard, 2011). Simi- larly, population-level studies, especially in children, have found significant associations between hunger and psychiatric morbid- ities, including suicidal ideation (McIntyre et al., 2013;Muldoon et al., 2013). However, such qualitative and population-level stud- ies are limited by recall biases, the inability to understand temporal processes, and poor ecological validity.

The current study used EMA to better understand the relation- ship between hunger and stress among young adults who have experienced homelessness and food insecurity. In particular, this study investigated the less examined effects of hunger on stress, rather than the commonly explored impact stress has on hunger.

These methods provide an ability to delineate the microtemporal order of the association between hunger and stress. Further, research examining the experience of homelessness among young adults often focuses on those actively experiencing homelessness while neglecting the increasing population of formerly homeless young adults being placed in supportive housing, a primary inter- vention being applied to homelessness (National Academies of Sciences, Engineering, and Medicine, 2018). Using a sample of young adults who are either currently homeless or formerly home- less and now in stable housing, the specific study questions we sought to answer included the following: Are there differences in food insecurity, hunger, and stress based on current housingstatus? Does food insecurity and/or hunger lead to increased stress? And how does food insecurity and/or hunger affect vari- ability in stress? It is expected that those in supportive housing will feel more food secure than those actively experiencing home- lessness, but this may not translate into greater momentary hunger.

Additionally, hunger was expected to increase momentary stress such that those in housing were expected to be less stressed, on av- erage, than those who were unhoused. Method The study used an intensive longitudinal repeated-measures design to examine how a time-lagged primary predictor, prior hun- ger, is associated with mean and variability of stress. This study used a baseline questionnaire and EMA data from a larger obser- vational, mixed-methods geographically explicit EMA study investigating health risk behaviors in a sample of young adults who have experienced homelessness in Los Angeles County, Cali- fornia. Of the 230 participants in the study, 109 were currently homeless (i.e., street-based or living in a dwelling not meant for human habitation or couch surfing in temporary locations), en- rolled via drop-in centers and shelters, and 121 were formerly homeless and residing in supportive housing at the time of the study. The complete procedures for the Log My Life study are available elsewhere (Henwood et al., 2019).

Participants Those who were recruited and enrolled in the study were asked to complete a baseline questionnaire consisting of person-level measures such as demographics and food insecurity, followed by a 7-day EMA protocol querying hunger, stress, and other variables.

Participants were allowed to use their own smartphones or a study phone with a data plan for the duration of the study. A custom application was installed on the devices, and EMA prompts were delivered at 2-hour intervals throughout the day, excluding times that participants identified as sleep. Participants receivedfive prompts per day, on average, and took approximately 60 s to com- plete each prompt. Participants were compensated up to $130 for the study. All protocols were approved by the institutional review board at the University of Southern California. Data are not cur- rently publicly available but may be available upon request.

Measures Demographics for the study were collected at the onset of the study, including age and self-identified gender, race, and ethnicity.

Participants completed the Household Food Insecurity Access Scale (HFIAS), a nine-item (a= .91) questionnaire indicating both the occurrence and frequency of food scarcity events in the past 4 weeks, such as worry about access to food, limiting eating, or going to bed hungry (Coates et al., 2007). Previous research sug- gests the HFIAS to be most preferred measure of food insecurity among individuals experiencing homelessness and more appropri- ate for use with this population than other measures (Holland et al., 2011). The HFIAS was scored using published guidelines, and participants were identified as either food secure, mildly food inse- cure, moderately food insecure, or severely food insecure (Coates et al., 2007). Stress and hunger were queried using single-item 560 DZUBUR ET AL. This document is copyrighted by the American Psychological Association or one of its allied publishers.

This article is intended solely for the personal use of the individual user and is not to be disseminated broadly. EMA questions (“Just before the phone went off, how STRESSED were you feeling?”and“Just before the phone went off, how HUNGRY were you feeling?”respectively), with a 5-point Likert- style scaling as follows:slightly/not at all,a little,moderately, quite a bit, andextremely. The stress measure has been validated and used in other EMA studies with child, adolescent, and adult populations as part of a circumplex model of affect (Dunton et al., 2015;O’Reilly et al., 2015).

Data Analysis Each day was divided into 12 two-hour panels (i.e., windows), based on the EMA prompting scheme. The primary predictor, hun- ger, was time-lagged at the prior 2-hour interval (t-1) to establish temporal precedence. For the purpose of this analysis, gender (male vs. female or other gender), race (Black or African Ameri- can vs. any other race), and food insecurity (food secure or mildly food insecure vs. moderately or severely food insecure) were dichotomized based on the distribution of responses and to aid in interpretation of the model. Age was grand mean centered, and hunger (lagged;t-1) was disaggregated into between- and within- subject components using person-centered and grand-centered means. MixWILD, a statistical software program designed for lon- gitudinal data (Dzubur et al., 2020), was used to run all analyses.

A mixed-effects multiple location (i.e., intercept and slope) and scale (i.e., within-subject variance) model (Nordgren et al., 2020) was used to examine the effects of hunger and food insecurity on mean levels of stress and within- and between-subjects variability of stress. Within-subject variability of stress captures the extent to which a participant’s stress differed from their own mean during the study period and may represent instability of life or repeated occurrences of stressful events; both high mean levels of stress and high variability of stress are associated with poor health out- comes (Shields & Slavich, 2017). A subsequent mixed-effectsmultiple location and scale model tested for the interaction of hun- ger and food insecurity on both mean levels of stress and stress variability. MixWILD also allows for second-stage models (e.g., logistic regressions) using subject specific random effects found at thefirst stage; hence, a second-stage model was used to examine the association of subjective-specific mean stress and stress vari- ability with housing status. The following terms are used inter- changeably to describe models produced by MixWILD: random location: between-subjects variance of stress; random location effects: variance-covariance matrix of the random intercept and slope; random scale: within-subject variance of stress; and random slope: relationship between current stress and prior hunger. Results Data Availability and Descriptive Statistics A total of 187 participants completed the enrollment (i.e., base- line) questionnaire with food insecurity measures, of which 176 completed at least some portion of the EMA protocol. Participants completed 28 prompts on average, ranging from one to 54 prompts for the duration of the study period (Mdn= 30 prompts). Partici- pants were excluded from the analysis if they had no variance in the outcome across all EMA prompts (N= 4) or if they had miss- ing values for covariates in the model (N= 3). Descriptive statis- tics of the analytic sample (Level-2N= 169, Level-1n= 5,737) are presented inTable 1, with bivariate analyses testing for differ- ences based on housing status. Participants were approximately 22 years of age, with 59% of the sample currently homeless and 41% residing in supportive housing. There was a significant difference in gender distribution between unhoused and housed participants, with a greater proportion of men in the unhoused sample and a smaller proportion of other identified genders compared to the housed sample (p,.05). Race was associated with housing status Table 1 Descriptive Statistics of a Sample of Currently and Formerly Homeless Young Adults VariablesUnhoused (N= 100)Housed (N= 69)Total (N= 169)pvalue Age (in years),M(SD) 21.90 (2.00) 22.07 (2.16) 21.97 (2.06) 0.594 Gender0.016 Male only 60 (60.0%) 27 (39.1%) 87 (51.5%) Female only 30 (30.0%) 27 (39.1%) 57 (33.7%) Other 10 (10.0%) 15 (21.7%) 25 (14.8%) Race0.010 Another race 8 (8.0%) 9 (13.0%) 17 (10.1%) Multiracial 9 (9.0%) 8 (11.6%) 17 (10.1%) Black or African American 54 (54.0%) 19 (27.5%) 73 (43.2%) Unknown or no race 17 (17.0%) 24 (34.8%) 41 (24.3%) White 12 (12.0%) 9 (13.0%) 21 (12.4%) Ethnicity0.005 Not Hispanic 73 (73.0%) 36 (52.2%) 109 (64.5%) Hispanic 27 (27.0%) 33 (47.8%) 60 (35.5%) Food insecurity0.003 Food secure 27 (27.0%) 24 (34.8%) 51 (30.2%) Mildly food insecure 4 (4.0%) 9 (13.0%) 13 (7.7%) Moderately food insecure 15 (15.0%) 17 (24.6%) 32 (18.9%) Severely food insecure 54 (54.0%) 19 (27.5%) 73 (43.2%) Stress (momentary),M(SD) 2.03 (0.83) 1.94 (0.78) 2.00 (0.81) 0.460 Hunger (momentary),M(SD) 2.20 (0.86) 2.02 (0.65) 2.13 (0.78) 0.131FOOD INSECURITY, HUNGER, STRESS, AND HOMELESSNESS 561 This document is copyrighted by the American Psychological Association or one of its allied publishers.

This article is intended solely for the personal use of the individual user and is not to be disseminated broadly. such that participants who were currently homeless were predomi- nantly Black or African American, whereas housed participants largely did not identify as any specific race (p,.05). Similarly, participants in the housed group were more likely to be of His- panic ethnicity as compared to the unhoused group (p,.01).

Last, housing status was associated with food insecurity such that participants who were experiencing homeless were more likely to report being severely food insecure compared to housed partici- pants (p,.01). Mean levels for momentary stress and momentary hunger did not differ based on housing status.

Effects of Hunger and Food Insecurity on Momentary Stress Table 2presents results from the mixed-effects multiple loca- tion scale model predicting stress as a function of food insecurity.

Participants with greater-than-average mean levels of hunger (i.e., between-subjects effect) reported higher levels of momentary stress (p,.001). Similarly, participants reported higher momen- tary stress at the current prompt when hunger at the prior prompt was greater than one’s own average (i.e., within-subject effect; p,.001). After adjusting for the effects of hunger and all other covariates on the mean of stress, moderate or severe food insecur- ity at baseline was associated with an increase in mean levels of momentary stress (p,.01). Furthermore, those participants iden- tifying as Black or African American reported lower mean levels of momentary stress compared to participants identifying as another race after adjusting for all covariates (p,.05). Random location effect estimates (i.e., variances and covariances of the random location effects—intercept and slope) indicated that sub- jects differed significantly from each other in their levels of stress(z= 8.32,p,.001). As indicated by the random slope estimate of hunger, the relationship between prior hunger and current stress varied significantly across subjects (z= 2.58,p,.05). The rela- tionship between random slope and random location was statisti- cally significant (z= 2.69,p,.05), indicating that participants with higher mean levels of stress had greater slopes (i.e., relation- ship between current stress and prior hunger). Effects of Hunger and Food Insecurity on Stress Variability Random scale effects indicated that subjects differed from each other significantly in their variability of stress (SD= .92,SE= .05, z= 16.35,p,.001). Additionally, participants with greater-than- average levels of hunger had greater variability in stress (z= 2.45, p,.05). Likewise, participants reporting higher than usual levels of hunger at the prior prompt had increased variability in stress at the subsequent prompt compared to their mean variability (z= 3.01,p,.01). Compared to participants who were food secure or mildly food insecure, those who were moderately or severely food insecure had greater variability in stress (z= 2.21,p,.05). The interaction of random location and random scale revealed that par- ticipants with greater mean levels of stress also had greater vari- ability in reported stress (z= 4.94,p,.001). However, there was no statistically significant effect of random slope (i.e., relationship between current stress and prior hunger) and random scale (i.e., the variability of stress;z= .55,p= .58). An additional model revealed a statistically significant interaction between moderate or severe food insecurity (as compared to low food insecurity) and hunger at the prior prompt (i.e., within-subject effect) on variabili- ty of stress (z= 2.17,p= .03) but not on mean levels of stress Table 2 Results of a Mixed-Effects Multiple Location Scale Model Predicting Stress in a Sample of Young Adults Experiencing Homelessness Predictors EstimateSE z p Mean model effects Intercept 1.87 0.13 14.07 0.00 Age 0.01 0.02 0.39 0.69 Food insecure (ref = food secure) 0.32 0.10 3.05 0.00 Housed (ref = unhoused) 0.02 0.10 0.19 0.85 Black (ref = not Black) 0.28 0.11 2.57 0.01 Hispanic (ref = not Hispanic) 0.01 0.11 0.09 0.93 Male (ref = not male) 0.01 0.10 0.10 0.92 Hunger (within subject) 0.08 0.01 5.46 0.00 Hunger (between subject) 0.46 0.06 7.37 0.00 Random location effects a Intercept 0.38 0.05 8.32 0.00 Hunger (within subject) 0.01 0.01 2.58 0.01 Covariance 0.02 0.01 2.69 0.01 Within-subject variance effects Intercept 0.68 0.13 5.18 0.00 Hunger (within subject) 0.06 0.02 3.01 0.00 Hunger (between subject) 0.37 0.17 2.45 0.01 Food insecure (ref = food secure) 0.26 0.10 2.21 0.03 Random Location3Scale Effects b Intercept 0.40 0.08 4.94 0.00 Hunger (within subject) 0.07 0.13 0.55 0.58 Note. Analytic sample size isn= 5,737 at Level 1 andN= 169 at Level 2. Ref = reference.

aRandom location effects are the variance-covariance matrix of the random intercept and slope. bThis interac- tion is the effects of the random intercept and slope on within-subject variance. 562 DZUBUR ET AL. This document is copyrighted by the American Psychological Association or one of its allied publishers.

This article is intended solely for the personal use of the individual user and is not to be disseminated broadly. (z= .71,p= .41). As indicated inFigure 1, participants who were food secure or mildly food insecure had more stress variabili- ty at lower levels of hunger compared to those who were moder- ately or severely food insecure. Conversely, participants who were food secure or mildly food insecure had less stress variability at higher levels of hunger compared to those who were moderately or severely food insecure.

Association Between Housing Status and Mean Stress and Stress Variability Second-stage logistic regressions using subject-specific random effects found that, after adjusting for all covariates in previous models and average stress variability (i.e., random scale), mean levels of stress were not associated with housing status (z= .28, p= .78). Similarly, after adjusting for all covariates and average mean stress (i.e., random location), stress variability was not asso- ciated with housing status (z= .13,p= .90). However, the logistic regression found a significant interaction between stress variability and mean stress, as depicted inFigure 2(z= 2.77,p,.01).

Mean levels of stress were found to be a moderator of the relation- ship between stress variability and housing status. The odds of being housed were lower for individuals with greater-than-average stress variability when mean stress levels were also high. How- ever, the odds of being housed were higher for individuals with greater-than-average stress variability when mean stress levels were low. Discussion Results show that those who were more food insecure experi- enced greater stress variability across the EMA week. This indi- cates that food secure individuals were less affected by hunger compared to those who felt they were more food insecure. Simi- larly, when individuals experienced greater-than-average hunger (i.e., hunger greater than their average rate of hunger), they then experienced greater stress variability at the next prompt, showing the impact of hunger on stress at the momentary level.Other mainfindings centered on the significance of stress.

Those with higher average levels of stress, regardless of hunger, became substantially more stressed when becoming hungry com- pared to their generally less stressed counterparts. High mean lev- els of stress with no variability, often referred to as allostatic load, has been proven highly problematic as it is linked to increased dis- ease over time (McEwen, 1998). However, individuals with greater mean levels of stress in this sample were also found to have greater variability in reported stress, and these individuals were also less likely to be housed.

Young adults currently experiencing homelessness were more food insecure than those who now reside in housing programs.

Specifically, results indicated that over half of the unhoused young adults were severely food insecure, compared to only a quarter of young adults in housing programs. This is largely consistent with existing studies that found that between 28% and 85% of unhoused young adults experience food insecurity (Bowen & Irish, 2018;Crawford et al., 2015;Goldman-Hasbun et al., 2019;Tara- suk et al., 2009;Whitbeck et al., 2006), but this is thefirst known study that has compared those who are currently and formerly homeless (Johnson et al., 2019). It should be noted, however, that there were no differences in mean levels of reported stress or hun- ger between young adults who were experiencing homelessness or those who now reside in supportive housing. In addition, the rela- tionship between hunger, stress, and food insecurity did not depend on one’s housing status. This suggests that food insecurity and heightened levels of momentary hunger may be a better indi- cator of irregular stress than the housing environment (Businelle et al., 2013).

Findings from this study provide evidence for the influence of both food insecurity and hunger on the variability of stress, with greater levels of momentary hunger or food insecurity resulting in variability of perceived stress. Momentary hunger predicted subse- quent stress in young adults who have experienced homelessness, even after adjusting for variables like food insecurity and demo- graphics. As self-reported hunger increased, the association between prior hunger and subsequent perceived stress increased, indicating a potentially curvilinear relationship. Stress variability was higher among food-secure young adults at lower-than-average Figure 1 Interaction Plot of Food Insecurity and Momentary Hunger on Stress Variability Figure 2 Interaction Plot of Mean Stress and Stress Variability on Housing Status Note. Low = 1 standard deviation, high =þ1 standard deviation, mod- erate = mean. FOOD INSECURITY, HUNGER, STRESS, AND HOMELESSNESS 563 This document is copyrighted by the American Psychological Association or one of its allied publishers.

This article is intended solely for the personal use of the individual user and is not to be disseminated broadly. hunger levels compared to food-insecure young adults. Inversely, stress variability was higher among food-insecure young adults at greater-than-average hunger levels. Environments related to home- lessness are already stressful such that homelessness can disrupt the normative development associated with young adulthood and increase adverse outcomes (Masten et al., 1993). Results suggest the simultaneous experience of hunger in already stressful contexts exacerbates stress levels, and those who reported higher average stress levels also experienced greater variability in stress. Ulti- mately, individuals with higher mean stress and greater stress vari- ability were less likely to be housed. Thesefindings are novel but also merit caution as food-secure young adults may simply not have sufficient variance of higher-than-average hunger scores to il- licit stress variability, and similarly, food-insecure young adults may not have sufficient variance at lower-than-average levels of hunger.

Limitations Thefindings from this study were limited in generalizability as a result of design. The study took place in a dense, urban city, which may not adequately generalize to rural areas where food access and the cost of food may vary. Additionally, there was no item examining food access (e.g.,“Could you eat right now, if you wanted to?”) that could establish a more ecologically valid rela- tionship between food insecurity and hunger at the momentary level. Last, the study used a novel single-item hunger measure that has not been used in previous studies. However, the measure shows preliminary convergent validity with food insecurity as measured in the context of this study (r= .15).

Conclusion The study sought to address gaps in the context of food insecur- ity by examining the effects of momentary hunger on mean and variability of momentary stress in a sample of current and for- merly homeless young adults. The study showed, in situ, the extent to which food insecurity results in variability of stress among vul- nerable populations and how high levels of hunger may lead to a stronger and more consistent stress response. Findings can be interpreted as reinforcing the need for mental health services and food programs for young adults even after they access housing programs. That is, feelings of hunger and stress may continue even after young adults are placed in supportive housing, but additional longitudinal research is warranted on young adults transitioning from homelessness into housing to establish causal effects. In addition, future research may seek to examine what happens to young adults with extended periods of food insecurity to determine how long-term exposure to hunger-related stress impacts health outcomes, mental health, other health behavior (e.g., drug and alcohol use) and whether the relationship between hunger and stress changes as a result of allostatic load or similar processes (Kim et al., 2017). Of course, givenfindings that unhoused youth are highly food insecure, this study also provides more evidence to the literature that has consistently found food insecurity to be neg- atively associated with health and supports calls for the eradication of hunger and food insecurity entirely as a detrimental and danger- ous national health problem (Gundersen & Ziliak, 2015;Thomas et al., 2019). References Block, J. P., He, Y., Zaslavsky, A. M., Ding, L., & Ayanian, J. Z. (2009).

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(2022). Late adolescent predictors of homelessness and food insecurity during emerging adulthood.Journal of Adolescent Health,70(5), 736– 742.https://doi.org/10.1016/j.jadohealth.2021.10.035 Whitbeck, L. B., Chen, X., & Johnson, K. D. (2006). Food insecurity among homeless and runaway adolescents.Public Health Nutrition, 9(1), 47–52.https://doi.org/10.1079/PHN2005764 Received August 28, 2021 Revision received May 4, 2022 Accepted May 9, 2022 n FOOD INSECURITY, HUNGER, STRESS, AND HOMELESSNESS 565 This document is copyrighted by the American Psychological Association or one of its allied publishers.

This article is intended solely for the personal use of the individual user and is not to be disseminated broadly.