Prospective Associations of Childhood Housing Insecurity With Anxiety and Depression Symptoms During Childhood and Adulthood

Ryan Keen; Jarvis T Chen; Natalie Slopen; Megan Sandel; William E Copeland; Henning Tiemeier

doi:10.1001/jamapediatrics.2023.1733

. 2023 Jun 20;177(8):818–826. doi: 10.1001/jamapediatrics.2023.1733

Prospective Associations of Childhood Housing Insecurity With Anxiety and Depression Symptoms During Childhood and Adulthood

Ryan Keen ^1,^✉, Jarvis T Chen ¹, Natalie Slopen ^1,², Megan Sandel ^3,⁴, William E Copeland ⁵, Henning Tiemeier ^1,⁶

¹Department of Social and Behavioral Sciences, Harvard T.H. Chan School of Public Health, Boston, Massachusetts

²Center on the Developing Child, Harvard University, Boston, Massachusetts

³Department of Environmental Health, Boston University School of Public Health, Boston, Massachusetts

⁴Department of Pediatrics, School of Medicine, Boston University, Boston, Massachusetts

⁵Department of Psychiatry, University of Vermont, Burlington

⁶Department of Epidemiology, Harvard T.H. Chan School of Public Health, Boston, Massachusetts

Accepted for Publication: April 20, 2023.

Published Online: June 20, 2023. doi:10.1001/jamapediatrics.2023.1733

^✉

Corresponding Author: Ryan Keen, PhD, Department of Social and Behavioral Sciences, Harvard T.H. Chan School of Public Health, 677 Huntington Ave, Kresge 7th Floor, Boston, MA 02115-0000 (ryankeen@g.harvard.edu).

Author Contributions: Dr Keen had full access to all of the data in the study and takes responsibility for the integrity of the data and the accuracy of the data analysis.

Concept and design: Keen, Sandel, Copeland, Tiemeier.

Acquisition, analysis, or interpretation of data: All authors.

Drafting of the manuscript: Keen, Chen.

Critical revision of the manuscript for important intellectual content: All authors.

Statistical analysis: Keen, Chen.

Obtained funding: Keen, Copeland.

Supervision: Chen, Sandel, Copeland, Tiemeier.

Conflict of Interest Disclosures: Dr Slopen reported receiving funding from the National Heart, Lung, and Blood Institute, the National Cancer Institute, the Eunice Kennedy Shriver National Institute of Child Health and Human Development (NICHD), the National Institute on Drug Abuse (NIDA), and the W. K. Kellogg Foundation outside the submitted work. Dr Sandel reported receiving nonfinancial support from and serving as an unpaid board member of Enterprise Community Partners and the National Low Income Housing Coalition. Dr Copeland reported receiving funding from the National Institute of Mental Health (NIMH), the National Institute on Aging, the NICHD, NIDA, and the University of Vermont Research Center for Children, Youth, and Families outside the submitted work. Dr Tiemeier reported receiving funding from the NICHD, the National Institute of Environmental Health Sciences, and the Dutch Medical Research Council outside the submitted work. No other disclosures were reported.

Funding/Support: This study was supported by the Science and Innovation Fellowship at the Center on the Developing Child, Harvard University (Dr Keen) and grant R01MH117559 from the NIMH.

Role of the Funder/Sponsor: The funders had no role in the design and conduct of the study; collection, management, analysis, and interpretation of the data; preparation, review, or approval of the manuscript; and decision to submit the manuscript for publication.

Data Sharing Statement: See Supplement 2.

Additional Contributions: Marilyn Winkleby, PhD (Stanford University), provided mentorship and support during the study. There was no financial compensation for these contributions.

^✉

Corresponding author.

PMCID: PMC10282957 PMID: 37338896

This cohort study examines the association of childhood housing insecurity with anxiety and depression symptoms during childhood and adulthood.

Key Points

Question

Is childhood housing insecurity prospectively associated with higher anxiety and depression symptom scores during both childhood and adulthood after adjusting for childhood poverty?

Findings

In this cohort study of 1339 participants, those who experienced housing insecurity during childhood were significantly more likely to have higher anxiety and depression symptom scores during later childhood and higher depression symptom scores during adulthood. These associations remained statistically significant after adjustment for childhood poverty.

Meaning

In this study, childhood housing insecurity was associated with short- and long-term mental health outcomes after adjustment for childhood poverty, suggesting that efforts to increase housing security may be protective for mental health.

Abstract

Importance

Childhood housing insecurity has dramatically increased in the US in recent decades, but whether an association with adverse mental health outcomes exists after adjusting for repeated measures of childhood poverty is unclear.

Objective

To test whether childhood housing insecurity is associated with later anxiety and depression symptoms after adjusting for time-varying measures of childhood poverty.

Design, Setting, and Participants

This prospective cohort study included individuals aged 9, 11, and 13 years at baseline from the Great Smoky Mountains Study in western North Carolina. Participants were assessed up to 11 times from January 1993 to December 2015. Data were analyzed from October 2021 to October 2022.

Exposure

Participants and their parents reported social factors annually when participants were 9 to 16 years of age. A comprehensive measure of childhood housing insecurity was constructed based on frequent residential moves, reduced standard of living, forced separation from home, and foster care status.

Main Outcomes and Measures

Between ages 9 and 16 years, the Child and Adolescent Psychiatric Assessment was used up to 7 times to evaluate childhood anxiety and depression symptoms. Adult anxiety and depression symptoms were assessed at ages 19, 21, 26, and 30 years using the Young Adult Psychiatric Assessment.

Results

Of the 1339 participants (mean [SD] age, 11.3 [1.63] years), 739 (55.2%; 51.1% weighted) were male; 1203 individuals assessed up to 30 years of age were included in the adulthood outcome analyses. Standardized mean (SD) baseline anxiety and depression symptom scores were higher among children who experienced housing insecurity than among those who never experienced housing insecurity (anxiety: 0.49 [1.15] vs 0.22 [1.02]; depression: 0.20 [1.08] vs −0.06 [0.82]). Individuals who experienced childhood housing insecurity had higher anxiety symptom scores (fixed effects: standardized mean difference [SMD], 0.21; 95% CI, 0.12-0.30; random effects: SMD, 0.25; 95% CI, 0.15-0.35) and higher depression symptom scores (fixed effects: SMD, 0.18; 95% CI, 0.09-0.28; random effects: SMD, 0.26; 95% CI, 0.14-0.37) during childhood. In adulthood, childhood housing insecurity was associated with higher depression symptom scores (SMD, 0.11; 95% CI, 0.00-0.21).

Conclusions and Relevance

In this cohort study, housing insecurity was associated with anxiety and depression during childhood and with depression during adulthood. Because housing insecurity is a modifiable, policy-relevant factor associated with psychopathology, these results suggest that social policies that support secure housing may be an important prevention strategy.

Introduction

Childhood housing insecurity is a construct often referring to a lack of safe and stable housing and occurs for a variety of reasons.^1,2,3,4,5,6 Across the literature, operationalizations of housing insecurity have included frequent residential moves, living in overcrowded or doubled-up spaces, involuntary familial separation, and homelessness.^3,4,5,6,7 Despite consensus that housing insecurity is relevant to child development, the lack of a formal definition makes it challenging to characterize,³ and studies seeking to elucidate the association of housing insecurity with developmental or well-being outcomes across the life course have yielded inconsistent results.^8,9

Given this challenge, Cox et al⁶ conducted a cross-field literature review examining the multidimensional facets of housing insecurity. Notably, the authors included housing stability, or “the ability of a household to stay in a housing unit of its choosing, for a duration of its choosing, without interruption or complication,”⁶ and housing affordability among these facets. They contextualized housing insecurity through aspects of quality and safety, emphasizing housing characteristics associated with reduced quality of life and direct health risks, such as inconsistent and inadequate heat, electricity, and plumbing.⁶

Despite cross-sectional literature suggesting that children in low-income and housing-insecure families are at increased risk of poor health problems,^7,10,11,12 longitudinal research suggests that direct increases to household income are associated with minimal reductions to this risk.¹³ For example, a 2014 UK-based prospective study found that while family income, a marker of poverty, was associated with child health, potential mediating factors, such as housing, medical care, and nutrition, were associated with a greater likelihood of affecting child outcomes.¹³ By better understanding the specific longitudinal impact of housing insecurity, policy makers and practitioners may be better positioned to act on amenable targets for interventions supporting children experiencing housing insecurity.

To date, few longitudinal studies have examined childhood housing insecurity as a factor associated with anxiety and depression.^4,8,9 Gilman and colleagues⁴ analyzed data from the Providence, Rhode Island, site of the National Collaborative Perinatal Project and found that early childhood residential instability was prospectively associated with increased risk of major depression during childhood, adolescence, and adulthood. Similarly, using 3 waves of data from the National Longitudinal Study of Adolescent Health, Fowler et al⁸ found that increased residential mobility during adolescence was associated with depression in adulthood. While these studies contributed to understanding the associations between residential movement and psychopathology, they did not consider childhood housing insecurity as a broad construct.^4,8

Using longitudinal data from the Great Smoky Mountains Study (GSMS), we investigated the associations between childhood housing insecurity and anxiety and depression symptoms during later childhood and adulthood.¹⁴ We hypothesized that childhood housing insecurity would be associated with higher anxiety and depression symptom scores during both later childhood and adulthood after adjusting for childhood poverty and across multiple modeling approaches.

Methods

Data

Data for this cohort study were drawn from the GSMS, an ongoing, longitudinal, population-based cohort study of child psychiatric and developmental epidemiologic characteristics.¹⁴ The GSMS began assessing participants in January 1993, by enrolling 1420 youths at ages 9, 11, and 13 years from 11 counties of the Appalachian region of North Carolina,¹⁴ and ended in December 2015. By using public or reservation school records to identify eligible American Indian participants, approximately one-quarter (n = 349) of the sample included enrolled members of the Eastern Band of the Cherokee Nation.¹⁴ This oversampling was designed to address underrepresentation of American Indian children in most cohort studies in the US. A screening questionnaire was used to select children for the GSMS with a high probability of mental health service use.¹⁴ All covariates, exposures, and outcomes were evaluated using the Child and Adolescent Psychiatric Assessment (CAPA) and the Young Adult Psychiatric Assessment (YAPA) through structured, in-person interviews conducted annually through 16 years of age (CAPA) and subsequently at ages 19, 21, 26, and 30 years (YAPA).^14,15,16 These assessments were based on the latest edition of the Diagnostic and Statistical Manual of Mental Disorders (Third Edition Revised) (DSM-III-R)¹⁷ and DSM (Fourth Edition) (DSM-IV)¹⁸ at the time of the corresponding interview and included various measures of other social and demographic characteristics.^14,15,16 Ethical approval for the GSMS was obtained from Duke University Medical Center and extended to the present study; all participants provided written informed consent, which extended to secondary use of data in the present study.¹⁶ This study followed the Strengthening the Reporting of Observational Studies in Epidemiology (STROBE) reporting guideline.¹⁹

Childhood Housing Insecurity

We created a composite measure of childhood housing insecurity based on extant literature,^{1,4,6,7,8,9,20} expert input, and characterizations from the US Department of Housing and Urban Development and the US Department of Education.²¹ Specifically, the childhood housing insecurity covariate was based on responses to the following CAPA variables: (1) Has the child moved more than 4 times in the past 5 years? (2) Has the child experienced a reduced standard of living in the past 3 months? (3) Has the child experienced a forced separation from their home in the past 3 months? (4) Is the child currently living in foster care? (eTable 1 in Supplement 1). We included a report of a reduced standard of living, as the measure was contextualized with examples of needing to move and inadequate heat.⁶ We determined that separation from their home and living in foster care were forced moves⁶ that reflected housing instability (as a facet of housing insecurity).⁶

An affirmative response to any of the 4 dichotomous measures indicated childhood housing insecurity during that assessment. Depending on enrollment age, participants may have had up to 7 measures of childhood housing insecurity by age 16 years (mean [SD], 4.9 [1.40] years). Childhood housing insecurity was then coded as contemporaneous (ie, measured during the same assessment as the outcome) or lagged (ie, measured during the assessment preceding the outcome). The lagged coding ensured that the modeled exposure preceded the outcome and thus provided stronger evidence for potential prospective associations. To assess adult outcomes, we categorized participants as ever vs never having housing insecurity during childhood. Alternative operationalizations of housing insecurity were also assessed to allow flexible interpretations of the exposure.

Anxiety and Depression

Time-varying childhood anxiety and depression symptom scores were measured annually via structured, in-person interviews using the CAPA; time-varying adulthood symptom scores were later measured using the YAPA.¹⁴ Symptom scores were based on DSM-III-R¹⁷ and DSM-IV¹⁸ criteria. Depression symptom scores ranged from 0 to 10, and anxiety symptom scores ranged from 0 to 22, with higher scores indicating worse symptoms of depression and anxiety, respectively; these scores were standardized.

Covariates and Confounding Variables

Measures of covariates and potential confounders were obtained using the CAPA¹⁴ (eTable 2 in Supplement 1). Time-invariant covariates and potential confounders included child sex, race and ethnicity (American Indian, Black, or White, ascertained by investigator-defined categories based on definitions from the federal government), age at enrollment, maternal age at birth, and maternal anxiety and depression at baseline (defined using clinical thresholds). Time-varying covariates and potential confounders included child age, poverty (defined according to the federal poverty threshold based on family income and size), parental separation or divorce, and physical violence between parents. Poverty was coded analogously to housing insecurity (ie, contemporaneous, lagged, and ever vs never). Race and ethnicity and poverty were also examined as potential modifiers. Parent separation or divorce and physical violence between parents could function as either mediating factors or confounders; accordingly, analyses with and without adjustments for these covariates were performed.

Statistical Analysis

Data were analyzed from October 2021 to October 2022. First, we calculated the distributions of key demographic characteristics for the analytic samples. Second, we estimated a series of multivariable, multilevel, fixed-effects (FE) regression models to investigate the associations between childhood housing insecurity and anxiety and depression during childhood. Fixed-effects models rely on within-person variation both to identify the effect of a time-varying exposure while limiting potential confounding by measured and unmeasured time-invariant factors and to account for correlations that arise between repeated measures.^22,23,24 Therefore, our FE models were only informed by participants whose housing insecurity changed across waves of observation. When time-varying covariates were explicitly included, FE estimates represent the participant-specific association of changing childhood housing insecurity status across assessments with childhood anxiety or depression.

Third, we estimated multivariable, multilevel, random-effects (RE) regression models to triangulate the results of our FE models for childhood outcomes and to evaluate the associations between housing insecurity and anxiety and depression during adulthood.^22,23,24 To account for correlations between repeated measures, the RE models included random intercepts and slopes (for time and housing insecurity) at the individual level. Unlike FE models, RE models use both between-person and within-person variation but cannot adjust for unmeasured time-invariant covariates.²⁴ Thus, RE regression estimates represent the average association of childhood housing insecurity with the outcome after explicit adjustment for time-invariant and time-varying covariates. All models incorporated sampling weights to reflect each participant’s probability of selection into the study, ensuring that the results reflect unbiased estimates for the original population of the 11 counties from which the sample was selected.^14,25 Estimates are reported as standardized mean differences (SMDs), meaning that the presence of childhood housing insecurity shifted the distribution of anxiety and depression symptom scores by the associated number of SDs²⁶; a positive SMD indicates that exposure to housing insecurity was associated with higher anxiety and depression symptom scores.

To address missingness across covariates (Table 1), we assumed data were missing at random and used multivariate imputation by chained equations to impute missing data among participants who met the study’s inclusion criteria.^27,28,29 Exposure and outcome data were not imputed. The imputation models included the covariates used in the main analyses, and we generated 20 imputed data sets.²⁹ Sampling weights were incorporated in the imputation models based on recommendations to incorporate interaction terms between weights and covariates.^28,30,31 The distributions of the observed and imputed covariates were similar.

Table 1. Characteristics for the Overall Study Sample and Stratified by Experiences of Housing Insecurity During Childhood^a.

Characteristic	Never housing insecure (n = 984)^b	Ever housing insecure (n = 355)^b	Overall (N = 1339)
Child covariates
Sex
Female	444 (49.6)	156 (46.8)	600 (48.9)
Male	540 (50.4)	199 (53.2)	739 (51.1)
Race and ethnicity
American Indian	257 (3.8)	78 (3.6)	335 (3.8)
Black	48 (6.0)	33 (9.7)	81 (6.9)
White	679 (90.2)	244 (86.7)	923 (89.4)
Age at baseline, y
Mean (SD)	11.3 (1.6)	10.9 (1.6)	11.2 (1.6)
9-10	331 (33.7)	147 (44.0)	478 (36.2)
11-12	341 (34.8)	129 (33.3)	470 (34.5)
13-15	312 (31.5)	79 (22.7)	391 (29.3)
Experience of childhood poverty at baseline
Without poverty	664 (79.0)	183 (57.1)	847 (73.6)
With poverty	282 (18.1)	156 (40.1)	438 (23.5)
Missing	38 (2.9)	16 (2.8)	54 (2.9)
Experience of poverty during childhood
Never reported experiencing poverty	577 (71.2)	127 (45.5)	704 (64.9)
Ever reported experiencing poverty	407 (28.8)	228 (54.5)	635 (35.1)
Covariate response rate, mean (SD)^c	91.9 (11.9)	87.6 (17.7)	90.7 (13.9)
Anxiety symptom score at baseline, standardized, mean (SD)	0.22 (1.02)	0.49 (1.15)	0.29 (1.06)
Depression symptom score at baseline, standardized, mean (SD)	−0.06 (0.82)	0.20 (1.08)	0.01 (0.90)
Parent covariates
Mother’s age at child’s birth, y
≥18	877 (92.2)	292 (81.1)	1169 (89.5)
<18	28 (2.4)	19 (8.8)	47 (3.9)
Missing	79 (5.6)	44 (10.0)	123 (6.6)
Physical violence between parents at baseline
Without violence	749 (79.7)	233 (66.7)	982 (76.5)
With violence	30 (3.0)	12 (3.4)	42 (3.1)
Missing	205 (20.8)	110 (31.0)	315 (23.5)
Parent separation or divorce at baseline
Without separation or divorce	960 (97.6)	333 (93.8)	1293 (96.6)
With separation or divorce	24 (2.3)	22 (2.0)	46 (2.2)
Maternal anxiety disorder in biological mother at baseline
Without anxiety disorder	349 (40.7)	104 (29.8)	453 (38.0)
With anxiety disorder	164 (15.9)	82 (20.8)	246 (17.1)
Missing	471 (43.4)	169 (49.3)	640 (44.8)
Maternal depression in biological mother at baseline
Without depression	744 (81.3)	226 (63.3)	970 (76.9)
With depression	73 (4.8)	52 (12.2)	125 (6.6)
Missing	167 (13.9)	77 (24.4)	244 (16.5)

Open in a new tab

^{^a}

Fixed-effects models relied exclusively on within-person variation and therefore only included individuals whose childhood housing insecurity status changed between waves of observation. Means and absolute numbers are unweighted; SDs and percentages are weighted. Data are presented as number (weighted percentage) of participants unless otherwise indicated.

^{^b}

Never indicates that participants never experienced housing insecurity across all childhood assessments. Ever indicates that participants experienced housing insecurity at least once across all childhood assessments.

^{^c}

Covariate response rates were obtained by dividing the number of waves in which each participant was observed and responded by the total number of waves in which each participant was observed, averaging these values across all participants, and multiplying by 100.

To assess potential unmeasured confounding, E-values were calculated for each estimate. E-values represent the minimum strength of association that an unmeasured confounder would need to have with both housing insecurity and the respective outcome (ie, anxiety or depression) to fully explain the modeled association.³² We also conducted sensitivity analyses using alternative operationalizations of housing insecurity to test the robustness of the results. These operationalizations included (1) frequent moves, reduced standard of living, and forced separation from home; (2) frequent moves, forced separation from home, and foster care; (3) frequent moves, reduced standard of living, and foster care; (4) forced separation from home, reduced standard of living, and foster care; (5) frequent moves and forced separation from home; (6) frequent moves; (7) reduced standard of living; and (8) forced separation from home. Foster care was not analyzed independently because it was only observed 18 times across all childhood assessments (eTable 1 in Supplement 1) and would result in an underpowered analysis. Furthermore, we estimated FE and RE models in which we omitted childhood housing insecurity to characterize the overall association between poverty and anxiety and depression during childhood. We used logistic regression to test whether childhood housing insecurity was associated with loss to follow-up. Finally, we tested for effect modification by race and ethnicity and poverty.

All analyses were conducted in R, version 4.2.2 (R Project for Statistical Computing) using the plm, lmer, and mice packages. We reported 2-sided P values based on Wald tests with a threshold of α = .05 and included 95% CIs for all estimates.

Results

Descriptive Results

By 2015, an average of 80% of the surviving sample of the GSMS had been interviewed at each assessment.¹⁴ Participant inclusion in each of the analytic samples is detailed in the eFigure in Supplement 1. The analytic sample for the RE regression models examining anxiety and depression during childhood included 1339 participants. Since FE regression models require within-person variation in the exposure, these analyses included only the 350 of the 1339 participants whose housing insecurity status changed across waves. The analytic sample to examine adult anxiety and depression symptoms included 1203 of the 1339 participants who also had at least 2 measures of anxiety and depression during adulthood.

Of the 1339 participants in the overall sample (mean [SD] age, 11.2 [1.63] years), 600 (44.8%; 48.9% weighted) were female, 739 (55.2%; 51.1% weighted) were male, 335 (3.8% weighted) were American Indian, 81 (6.9% weighted) were Black, and 923 (89.4% weighted) were White. A total of 355 participants (26.5%) had experienced childhood housing insecurity, with higher rates of housing insecurity among Black vs White participants (33 of 81 [40.7%] vs 244 of 923 [26.4%]) (Table 1). Participants who experienced childhood housing insecurity were younger at baseline (mean [SD] age, 10.9 [1.6] years) than were those who never experienced childhood housing insecurity (mean [SD] age, 11.3 [1.6] years). Importantly, 127 participants (35.8%; 45.5% weighted) who experienced housing insecurity never reported experiencing poverty during childhood. Standardized mean (SD) baseline anxiety and depression symptom scores were higher among children who experienced housing insecurity than among those who never experienced housing insecurity (anxiety: 0.49 [1.15] vs 0.22 [1.02]; depression: 0.20 [1.08] vs −0.06 [0.82]). As shown in eTable 3 in the Supplement, the distributions of baseline demographic characteristics for the sample in the FE analyses (350 whose housing insecurity status changed across waves) were similar to the overall sample.

Anxiety During Childhood

Contemporaneous childhood housing insecurity was associated with higher anxiety symptom scores after adjustment for contemporaneous poverty and all child and parental characteristics (FE: SMD, 0.21; 95% CI, 0.12-0.30; RE: SMD, 0.25; 95% CI, 0.15-0.35) (Table 2). In contrast, there was no association between contemporaneous poverty and childhood anxiety in the adjusted FE model (SMD, 0.09; 95% CI, −0.01 to 0.20), but there was an association in the adjusted RE model (SMD, 0.07, 95% CI, 0.01-0.13). The RE models to test the association between lagged housing insecurity and anxiety yielded similar findings (SMD, 0.24; 95% CI, 0.10-0.38). Lagged poverty was not associated with anxiety in either of the specified models. These prospective findings did not vary significantly by race and ethnicity or poverty (eTables 4 and 5 in Supplement 1). All modeling adjustments for anxiety during childhood can be found in eTable 6 in Supplement 1.

Table 2. Longitudinal Associations of Childhood Housing Insecurity and Childhood Poverty With Anxiety Symptom Scores During Childhood.

Childhood experience (yes vs no)	Child anxiety symptom score, SMD (95% CI)^a
	Fixed-effects model (n = 350)^b	Random-effects models^c
	Fixed-effects model (n = 350)^b	Model 2a (n = 1339)^d	Model 2b (n = 1339)^e	Model 3a (n = 1339)^d	Model 3b (n = 1339)^e
Contemporaneous housing insecurity^f	0.21 (0.12 to 0.30)^g	0.26 (0.16 to 0.36)^g	0.25 (0.15 to 0.35)^g	NA	NA
Contemporaneous poverty^f	0.09 (−0.01 to 0.20)	0.08 (0.02 to 0.14)^h	0.07 (0.01 to 0.13)ⁱ	NA	NA
Housing insecurity, lagged^j	NA	NA	NA	0.25 (0.10 to 0.39)^g	0.24 (0.10 to 0.38)^g
Poverty, lagged^j	NA	NA	NA	−0.01 (−0.08 to 0.06)	−0.03 (−0.09 to 0.04)

Open in a new tab

Abbreviations: NA, not applicable; SMD, standardized mean difference.

^{^a}

The SMD reflects the number of SDs by which the covariate shifted the distribution of anxiety and depression symptoms; a positive SMD indicates that the covariate was associated with higher anxiety and depression symptom scores.

^{^b}

The fixed-effects model (model 1) relied exclusively on within-person variation and therefore only analyzed the participants in the analytic sample whose housing insecurity status changed across waves of assessment. By design, the model was adjusted for all time-invariant covariates and included additional adjustments for age, poverty, parent separation or divorce, and physical violence between parents.

^{^c}

Random-effects models included random intercepts and slopes (for time and housing insecurity).

^{^d}

Models 2a and 3a were adjusted for age and wave, sex, age at baseline, race and ethnicity, baseline outcome (anxiety), either contemporaneous poverty or lagged poverty, and mother being younger than age 18 years at child’s birth. Random intercepts and slopes (for time and housing insecurity) were used.

^{^e}

Models 2b and 3b included all of the adjustments from models 2a and 3a, respectively, as well as adjustments for parental separation or divorce, biological mother anxiety, physical violence between parents, and mother being younger than age 18 years at child’s birth. Random intercepts and slopes (for time and housing insecurity) were used.

^{^f}

Contemporaneous indicates that the variable was measured at the same assessment as the outcome.

^{^g}

P < .001.

^{^h}

P < .01.

^ⁱ

P < .05.

^{^j}

Lagged indicates that the variable was coded using the value of the variable 1 assessment prior to the outcome.

Depression During Childhood

Contemporaneous childhood housing insecurity was associated with higher depression symptom scores after adjustment for contemporaneous poverty and all child and parental characteristics (FE: SMD, 0.18; 95% CI, 0.09-0.28; RE: SMD, 0.26; 95% CI 0.14-0.37) (Table 3). In contrast, the there was no association between contemporaneous poverty and childhood depression in the adjusted FE model (SMD, 0.09; 95% CI, −0.02 to 0.19), but there was an association in the adjusted RE model (SMD, 0.07; 95% CI, 0.00-0.14). Similar results were obtained with lagged housing insecurity (SMD, 0.19; 95% CI, 0.05-0.33). Lagged poverty was not associated with depression symptoms in either of the specified models. These prospective findings varied neither by race and ethnicity nor by poverty (eTables 4 and 5 in Supplement 1). All modeling adjustments for depression during childhood can be found in eTable 7 in Supplement 1.

Table 3. Longitudinal Associations of Childhood Housing Insecurity and Childhood Poverty With Depression Symptom Scores During Childhood.

Childhood experience (yes vs no)	Child depression symptom score, SMD (95% CI)^a
	Fixed-effects model (n = 350)^b	Random-effects models^c
	Fixed-effects model (n = 350)^b	Model 2a (n = 1339)^d	Model 2b (n = 1339)^e	Model 3a (n = 1339)^d	Model 3b (n = 1339)^e
Contemporaneous housing insecurity^f	0.18 (0.09 to 0.28)^g	0.28 (0.16 to 0.39)^g	0.26 (0.14 to 0.37)^g	NA	NA
Contemporaneous poverty^f	0.09 (−0.02 to 0.19)	0.10 (0.03 to 0.16)^h	0.07 (0.00 to 0.14)	NA	NA
Housing insecurity, laggedⁱ	NA	NA	NA	0.20 (0.06 to 0.33)^j	0.19 (0.05 to 0.33)^j
Poverty, laggedⁱ	NA	NA	NA	−0.04 (−0.11 to 0.04)	−0.06 (−0.13 to 0.02)

Open in a new tab

Abbreviations: NA, not applicable; SMD, standardized mean difference.

^{^a}

^{^b}

The fixed-effects model (model 1) relied exclusively on within-person variation and therefore only analyzed the participants in the analytic sample whose housing insecurity status changed across waves of assessment. By design, the model adjusted for all time-invariant covariates and included additional adjustments for age, poverty, parent separation or divorce, and physical violence between parents.

^{^c}

Random-effects models included random intercepts and slopes (for time and housing insecurity).

^{^d}

Models 2a and 3a were adjusted for age/wave, sex, age at baseline, race and ethnicity, baseline outcome (depression), either contemporaneous poverty or lagged poverty, and mother being younger than 18 years at child’s birth. Random intercepts and slopes (for time and housing insecurity) were used.

^{^e}

Models 2b and 3b included all of the adjustments from models 2a and 3a, respectively, as well as adjustments for parental separation or divorce, biological mother depression, and physical violence between parents. Random intercepts and slopes (for time and housing insecurity) were used.

^{^f}

Contemporaneous indicates that the variable was measured at the same assessment as the outcome.

^{^g}

P < .001.

^{^h}

P < .05.

^ⁱ

Lagged indicates that the variable was coded using the value of the variable 1 assessment prior to the outcome.

^{^j}

P < .01.

Anxiety and Depression During Adulthood

Participants who experienced childhood housing insecurity had higher depression symptom scores (SMD, 0.11; 95% CI, 0.00-0.21) but not higher anxiety symptom scores (SMD, 0.08; 95% CI, −0.03 to 0.18) as adults than did those who never experienced childhood housing insecurity (Table 4). Childhood poverty was not associated with adult anxiety or depression. All modeling adjustments for depression during childhood can be found in eTable 8 in Supplement 1.

Table 4. Longitudinal Associations of Childhood Housing Insecurity and Childhood Poverty With Anxiety and Depression Symptom Scores During Adulthood.

Childhood experience (ever vs never)^a	SMD (95% CI)^b
	Adult anxiety symptom score		Adult depression symptom score
	Model 1a (n = 1203)^c	Model 1b (n = 1203)^d	Model 1a (n = 1203)^c	Model 1b (n = 1203)^d
Housing insecurity	0.10 (0.00 to 0.21)^e	0.08 (−0.03 to 0.18)	0.14 (0.04 to 0.25)^f	0.11 (0.00 to 0.21)^e
Poverty	0.07 (−0.03 to 0.16)	0.04 (−0.06 to 0.14)	0.08 (−0.01 to 0.17)	0.04 (−0.06 to 0.13)

Open in a new tab

Abbreviation: SMD, standardized mean difference.

^{^a}

Ever indicates that participants experienced housing insecurity at least once across all childhood assessments. Never indicates that participants never experienced housing insecurity across all childhood assessments.

^{^b}

^{^c}

Model 1a was adjusted for age and wave, sex, age at baseline, race and ethnicity, baseline outcome (anxiety or depression), and childhood poverty. Random intercepts and slopes (for time and housing insecurity) were used.

^{^d}

Model 1b was adjusted for age and wave, sex, age at baseline, race and ethnicity, baseline outcome (anxiety or depression), childhood poverty, parental separation or divorce, biological mother depression during childhood, biological mother anxiety during childhood, physical violence between parents during childhood, and mother being younger than 18 years at child’s birth. Random intercepts and slopes (for time and housing insecurity) were used.

^{^e}

P < .05.

^{^f}

P < .01.

Sensitivity Analysis

The E-values suggest that an unmeasured confounder would need to be strongly associated (SMD≥1.35 across models and outcomes) (eTable 9 in Supplement 1) with both childhood housing insecurity and the psychiatric outcome to explain the results. The alternative operationalizations of housing insecurity showed similar findings for anxiety and depression during childhood (Table 5) and were consistent with the results of the main analyses. In models omitting childhood housing insecurity, the results of the analysis of poverty and anxiety (FE: SMD, 0.10; 95% CI, −0.01 to 0.21; RE: SMD, 0.07; 95% CI, 0.00-0.14) and depression (FE: SMD, 0.09; 95% CI, −0.01 to 0.19; RE: SMD, 0.08; 95% CI, 0.00-0.15) were similar. Loss to follow-up during adulthood was not associated with childhood housing insecurity (SMD, 0.04; 95% CI, −0.37 to 0.43) (eTable 10 in Supplement 1).

Table 5. Sensitivity Analyses of Different Operationalizations of Housing Insecurity.

Housing insecurity operationalization (yes vs no)^a	SMD (95% CI)^b
	Child anxiety symptom score		Child depression symptom score
	Fixed-effects model (n = 350)^c	Random-effects model (n = 1339)^d	Fixed-effects model (n = 350)^c	Random-effects model (n = 1339)^d
Frequent moves, reduced standard of living, and forced separation from home	0.22 (0.12 to 0.31)^e	0.26 (0.15 to 0.36)^e	0.18 (0.08 to 0.28)^e	0.27 (0.15 to 0.39)^e
Frequent moves, forced separation from home, and foster care	0.35 (0.21 to 0.48)^e	0.28 (0.12 to 0.44)^e	0.37 (0.23 to 0.51)^e	0.34 (0.17 to 0.51)^e
Frequent moves, reduced standard of living, and foster care	0.19 (0.09 to 0.29)^e	0.25 (0.14 to 0.36)^e	0.09 (−0.02 to 0.19)	0.22 (0.11 to 0.34)^e
Forced separation from home, reduced standard of living, and foster care	0.13 (0.03 to 0.23)^f	0.28 (0.15 to 0.41)^e	0.16 (0.05 to 0.27)^g	0.30 (0.16 to 0.44)^e
Frequent moves and forced separation from home	0.35 (0.22 to 0.49)^f	0.29 (0.13 to 0.45)^e	0.37 (0.23 to 0.51)^e	0.35 (0.18 to 0.53)^e
Frequent moves	0.42 (0.24 to 0.59)^e	0.22 (0.03 to 0.40)^f	0.24 (0.06 to 0.42)^g	0.25 (0.06 to 0.44)^g
Reduced standard of living	0.07 (−0.05 to 0.19)	0.27 (0.12 to 0.42)^e	−0.02 (−0.15 to 0.10)	0.22 (0.08 to 0.36)^g
Forced separation from home	0.27 (0.06 to 0.48)^f	0.34 (0.03 to 0.65)^f	0.52 (0.30 to 0.74)^e	0.58 (0.22 to 0.93)^g

Open in a new tab

Abbreviation: SMD, standardized mean difference.

^{^a}

All operationalizations of housing insecurity were derived from contemporaneous measures; contemporaneous indicates that the variable was measured at the same assessment as the outcome. Foster care was not modeled independently, as the number of exposures across all waves (n = 18) was too small to produce meaningful results.

^{^b}

^{^c}

The fixed-effects model was adjusted for all time-invariant covariates, age and wave, poverty, parental separation or divorce, and physical violence between parents.

^{^d}

The random-effects model was adjusted for age and wave, sex, age at baseline, race and ethnicity, baseline depression, contemporaneous poverty, parental separation or divorce, maternal depression, physical violence between parents, and maternal age at child’s birth. These models contained random intercepts and slopes (for time and housing insecurity).

^{^e}

P < .001.

^{^f}

P < .05.

^{^g}

P < .01.

Discussion

In this cohort study using GSMS data, experiencing housing insecurity from 9 to 16 years of age was associated with higher anxiety and depression symptom scores during later childhood and with higher depression symptom scores during adulthood. These associations were maintained with (1) FE and RE models; (2) contemporaneous and lagged versions of housing insecurity; (3) adjustment for potential confounders, including poverty status; and (4) alternative operationalizations of housing insecurity. These results align with previous work demonstrating that childhood housing insecurity was associated with higher risk of anxiety and depression symptoms.^4,8 We advanced the literature by using a large, prospective, population-based cohort with high retention rates and limited missing data and by creating a broad measure of childhood housing insecurity. By triangulating FE and RE models, we were able to control for a variety of biases and include lagged covariates that ensured the correct underlying temporal orderings of modeled associations. The results demonstrating that the associations between childhood housing insecurity and anxiety and depression remained after adjustment for poverty are consistent with a 2015 meta-analysis focused on childhood homelessness,¹¹ the “most severe form of housing insecurity.”³³ Specifically, the 2015 study found that school-aged children (ages 6-11 years) experiencing homelessness had nearly twice the prevalence of internalizing problems as their counterparts with low-income housing, suggesting that homelessness may be more closely associated with anxiety and depression symptoms than income status.¹¹ Clinically, the associations reported in another study³⁴ were similar to those of factors previously shown to be associated with childhood anxiety and depression, such as maternal psychopathology.

Our FE models suggested that transitioning from housing secure to housing insecure was associated with more anxiety and depression than transitioning from living above to living below the federal poverty level; this finding was supported by the RE models demonstrating that the SMDs for the associations between poverty and anxiety and depression during childhood were smaller than those for childhood housing insecurity. One potential explanation for these results is that our housing insecurity measure was composed of palpable events directly experienced by the child. Considering mechanisms, housing insecurity can involve displacing children from their social environments, which can disrupt social networks and routines.^35,36,37 Consequently, children with housing insecurity may be increasingly exposed to stressors, such as social isolation,³⁶ bullying,³⁸ physical and sexual violence,³⁹ food insecurity,⁴⁰ and parental mental distress, and may experience disruptions in education and social programming,³⁵ sleep patterns,⁴¹ health care,^1,7 and caregiving.^1,7 Unlike housing insecurity, formal poverty status may provide access to public benefits (eg, health care, early childhood education^10,42,43), which may reduce its relative effects on mental health outcomes.

A previous longitudinal investigation with the GSMS found that transitioning out of poverty was associated with reduced externalizing symptoms and with marginally reduced anxiety and depression symptoms in children in families with low income.⁴⁴ Improved parental supervision was identified as a mediating factor that accounted for approximately 77% of the improvement in total psychiatric symptoms.⁴⁴ While the housing insecurity constructs were not assessed in the previous investigation, future studies may benefit from considering the potential mediating role of housing security. By improving our understanding of the impact of housing insecurity as both a broad construct and in terms of its various dimensions, policy makers may more appropriately and efficiently allocate resources to minimize social costs and practitioners may work more collaboratively to maximize the benefits to children and their families affected by housing insecurity.

Limitations

This study has several limitations. First, the sample was representative of the population of western North Carolina but not the entire US; participants were mostly White, and American Indian individuals were oversampled. While the GSMS sampled a large geographic region, the selected counties did not represent metropolitan areas; together, these aspects limited generalizability to more urban, racially and ethnically diverse populations. Second, our measure of housing insecurity was not completely objective, as reduction in the standard of living was based on the parent’s and/or child’s perception; however, the validity of this measure was strengthened because the pertinent CAPA item contained several housing-specific prompts (eTable 2 in Supplement 1). Moreover, as shown in sensitivity analyses (Table 5), our results were robust to exclusion of this component of the measure. Third, confounding by unmeasured time-varying covariates (eg, dynamic housing policies) could have occurred. Fourth, although there was loss to follow-up, our analyses indicated that it was not associated with childhood housing insecurity.

Conclusions

In this longitudinal cohort study that assessed the short- and long-term associations between childhood housing insecurity and anxiety and depression, after adjustment for poverty, childhood housing insecurity was prospectively associated with higher anxiety and depression symptom scores in childhood and higher depression symptom scores during adulthood. Our results underscore the importance of interventions that optimize services and resources to ensure safe and secure housing for all children.

Supplement 1.

eTable 1. Underlying Measures Contributing to Childhood Housing Insecurity Construct

eTable 2. Measured Covariates Included in Multilevel Regression Analyses

eTable 3. Characteristics of the Study Sample Used in the Fixed-Effects Analysis of the Associations Between Childhood Housing Insecurity and Childhood Anxiety and Depression

eTable 4. Longitudinal Associations of Childhood Housing Insecurity With Depression Symptom Scores During Childhood Testing-Effect Measure Modification by Race

eTable 5. Longitudinal Associations of Childhood Housing Insecurity With Depression Symptom Scores During Childhood Testing Interaction With Poverty

eTable 6. Longitudinal Associations of Childhood Housing Insecurity With Anxiety Symptom Scores During Childhood, All Modeling Adjustments

eTable 7. Longitudinal Associations of Childhood Housing Insecurity With Depression Symptom Scores During Childhood, All Modeling Adjustments

eTable 8. Longitudinal Associations of Childhood Housing Insecurity With Anxiety and Depression Symptom Scores During Adulthood, All Modeling Adjustments

eTable 9. E-values for Modeled Associations Between Housing Insecurity and Anxiety and Depression

eTable 10. Characteristics of the Study Sample Used to Analyze the Association Between Childhood Housing Insecurity and Anxiety and Depression During Adulthood and Participants Excluded Due to Missing or Insufficient Data

eFigure. Study sample flow diagram

Click here for additional data file.^{(366.1KB, pdf)}

Supplement 2.

Data Sharing Statement

Click here for additional data file.^{(14.3KB, pdf)}

References

1.Cutts DB, Meyers AF, Black MM, et al. US housing insecurity and the health of very young children. Am J Public Health. 2011;101(8):1508-1514. doi: 10.2105/AJPH.2011.300139 [DOI] [PMC free article] [PubMed] [Google Scholar]
2.Marçal K. Pathways from food and housing insecurity to adolescent behavior problems: the mediating role of parenting stress. J Youth Adolesc. 2022;51(4):614-627. doi: 10.1007/s10964-021-01565-2 [DOI] [PubMed] [Google Scholar]
3.Kushel MB, Gupta R, Gee L, Haas JS. Housing instability and food insecurity as barriers to health care among low-income Americans. J Gen Intern Med. 2006;21(1):71-77. doi: 10.1111/j.1525-1497.2005.00278.x [DOI] [PMC free article] [PubMed] [Google Scholar]
4.Gilman SE, Kawachi I, Fitzmaurice GM, Buka L. Socio-economic status, family disruption and residential stability in childhood: relation to onset, recurrence and remission of major depression. Psychol Med. 2003;33(8):1341-1355. doi: 10.1017/S0033291703008377 [DOI] [PubMed] [Google Scholar]
5.Phinney R, Danziger S, Pollack HA, Seefeldt K. Housing instability among current and former welfare recipients. Am J Public Health. 2007;97(5):832-837. doi: 10.2105/AJPH.2005.082677 [DOI] [PMC free article] [PubMed] [Google Scholar]
6.Cox R, Wenzel SC, Rice E. Roadmap to a unified measure of housing insecurity. CESR-Schaeffer working paper 2016-013. SSRN. January 1, 2017. Accessed March 31, 2023. https://ssrn.com/abstract=2817626
7.Sandel M, Sheward R, Ettinger de Cuba S, et al. Unstable housing and caregiver and child health in renter families. Pediatrics. 2018;141(2):e20172199. doi: 10.1542/peds.2017-2199 [DOI] [PubMed] [Google Scholar]
8.Fowler PJ, Henry DB, Marcal KE. Family and housing instability: longitudinal impact on adolescent emotional and behavioral well-being. Soc Sci Res. 2015;53:364-374. doi: 10.1016/j.ssresearch.2015.06.012 [DOI] [PMC free article] [PubMed] [Google Scholar]
9.Hatem C, Lee CY, Zhao X, Reesor-Oyer L, Lopez T, Hernandez DC. Food insecurity and housing instability during early childhood as predictors of adolescent mental health. J Fam Psychol. 2020;34(6):721-730. [DOI] [PMC free article] [PubMed]
10.Council on Community Pediatrics . Poverty and child health in the United States. Pediatrics. 2016;137(4):e20160339. doi: 10.1542/peds.2016-0339 [DOI] [PubMed] [Google Scholar]
11.Bassuk EL, Richard MK, Tsertsvadze A. The prevalence of mental illness in homeless children J Am Acad Child Adolesc Psychiatry. 2015;54(2):86-96.e2. doi: 10.1016/j.jaac.2014.11.008 [DOI] [PubMed] [Google Scholar]
12.Aurand A, Emmanuel D, Threet D, Rafi I, Yentel D. The gap: a shortage of affordable homes. National Low Income Housing Coalition. March 2021. Accessed November 10, 2022. https://reports.nlihc.org/sites/default/files/gap/Gap-Report_2021.pdf?aid=8c3b6e3c-0805-4a4a-8900-c79e66adb0e2
13.Kuehnle D. The causal effect of family income on child health in the U.K. J Health Econ. 2014;36:137-150. doi: 10.1016/j.jhealeco.2014.03.011 [DOI] [PubMed] [Google Scholar]
14.Costello EJ, Copeland W, Angold A. The Great Smoky Mountains Study: developmental epidemiology in the southeastern United States. Soc Psychiatry Psychiatr Epidemiol. 2016;51(5):639-646. doi: 10.1007/s00127-015-1168-1 [DOI] [PMC free article] [PubMed] [Google Scholar]
15.Duke Psychiatry & Behavioral Sciences, Duke University School of Medicine. The Young Adult Psychiatric Assessment (YAPA). Accessed June 12, 2022. https://psychiatry.duke.edu/research/research-programs-areas/assessment-intervention/developmental-epidemiology-instruments-3
16.Duke Psychiatry & Behavioral Sciences, Duke University School of Medicine. Developmental epidemiology instruments. Accessed September 20, 2022. https://devepi.duhs.duke.edu/studies/great-smoky-mountains-study/gsms-summary/
17.American Psychiatric Association . Diagnostic and Statistical Manual of Mental Disorders. 3rd ed, revised. American Psychiatric Association; 1987. [Google Scholar]
18.American Psychiatric Association . Diagnostic and Statistical Manual of Mental Disorders. 4th ed. American Psychiatric Association; 1994. [Google Scholar]
19.von Elm E, Altman DG, Egger M, Pocock SJ, Gøtzsche PC, Vandenbroucke JP; STROBE Initiative . The Strengthening the Reporting of Observational Studies in Epidemiology (STROBE) statement: guidelines for reporting observational studies. Lancet. 2007;370(9596):1453-1457. doi: 10.1016/S0140-6736(07)61602-X [DOI] [PubMed] [Google Scholar]
20.National Center for Homeless Education . The McKinney-Vento definition of homeless. Accessed March 1, 2023. https://nche.ed.gov/mckinney-vento-definition/
21.US Interagency Council on Homelessness. Key federal terms and definitions of homelessness among youth. Accessed June 12, 2022. https://www.usich.gov/resources/uploads/asset_library/Federal-Definitions-of-Youth-Homelessness.pdf
22.Imai K, Kim IS. When should we use unit fixed effects regression models for causal inference with longitudinal data? Am J Pol Sci. 2019;63(2):467-490. doi: 10.1111/ajps.12417 [DOI] [Google Scholar]
23.Clark TS, Linzer DA, Should I. Use fixed or random effects? Political Sci Res Methods. 2015;3(2):399-408. doi: 10.1017/psrm.2014.32 [DOI] [Google Scholar]
24.Wilson JR, Lorenz KA. Modeling Binary Correlated Responses Using SAS, SPSS and R. Springer Cham; 2015. doi: 10.1007/978-3-319-23805-0 [DOI] [Google Scholar]
25.Carle AC. Fitting multilevel models in complex survey data with design weights: recommendations. BMC Med Res Methodol. 2009;9(1):49. doi: 10.1186/1471-2288-9-49 [DOI] [PMC free article] [PubMed] [Google Scholar]
26.Austin PC. An Introduction to propensity score methods for reducing the effects of confounding in observational studies. Multivariate Behav Res. 2011;46(3):399-424. doi: 10.1080/00273171.2011.568786 [DOI] [PMC free article] [PubMed] [Google Scholar]
27.Azur MJ, Stuart EA, Frangakis C, Leaf PJ. Multiple imputation by chained equations: what is it and how does it work? Int J Methods Psychiatr Res. 2011;20(1):40-49. doi: 10.1002/mpr.329 [DOI] [PMC free article] [PubMed] [Google Scholar]
28.Quartagno M, Carpenter JR, Goldstein H. Multiple imputation with survey weights: a multilevel approach. J Surv Stat Methodol. 2020;8(5):965-989. doi: 10.1093/jssam/smz036 [DOI] [Google Scholar]
29.Sterne JAC, White IR, Carlin JB, et al. Multiple imputation for missing data in epidemiological and clinical research: potential and pitfalls. BMJ. 2009;338:b2393. doi: 10.1136/bmj.b2393 [DOI] [PMC free article] [PubMed] [Google Scholar]
30.Seaman SR, White IR, Copas AJ, Li L. Combining multiple imputation and inverse-probability weighting. Biometrics. 2012;68(1):129-137. doi: 10.1111/j.1541-0420.2011.01666.x [DOI] [PMC free article] [PubMed] [Google Scholar]
31.Kim JK, Brick JM, Fuller WA, Kalton G. On the bias of the multiple-imputation variance estimator in survey sampling. J R Stat Soc Series B Stat Methodol. 2006;68(3):509-521. doi: 10.1111/j.1467-9868.2006.00546.x [DOI] [Google Scholar]
32.VanderWeele TJ, Ding P. Sensitivity analysis in observational research: introducing the E-value. Ann Intern Med. 2017;167(4):268-274. doi: 10.7326/M16-2607 [DOI] [PubMed] [Google Scholar]
33.Gabbay JM, Stewart AM, Wu AC. Housing instability and homelessness—an undertreated pediatric chronic condition. JAMA Pediatr. 2022;176(11):1063-1064. doi: 10.1001/jamapediatrics.2022.3258 [DOI] [PubMed] [Google Scholar]
34.Wesseldijk LW, Dieleman GC, van Steensel FJA, et al. Do parental psychiatric symptoms predict outcome in children with psychiatric disorders? J Am Acad Child Adolesc Psychiatry. 2018;57(9):669-677.e6. doi: 10.1016/j.jaac.2018.05.017 [DOI] [PubMed] [Google Scholar]
35.Leventhal T, Newman S. Housing and child development. Child Youth Serv Rev. 2010;32(9):1165-1174. doi: 10.1016/j.childyouth.2010.03.008 [DOI] [Google Scholar]
36.Adam EK. Beyond quality: parental and residential stability and children’s adjustment. Curr Dir Psychol Sci. 2004;13(5):210-213. doi: 10.1111/j.0963-7214.2004.00310.x [DOI] [Google Scholar]
37.Marçal KE. Perceived instrumental support as a mediator between maternal mental health and housing insecurity. J Child Fam Stud. 2021;30(12):3070-3079. doi: 10.1007/s10826-021-02132-w [DOI] [Google Scholar]
38.McCallops K, Aviles AM, Earnshaw VA, Palkovitz R. Homelessness and suicidality: the role of bullying and parental support. Fam Relat. 2021;70(4):1150-1161. doi: 10.1111/fare.12437 [DOI] [Google Scholar]
39.Li C, Liang Z, Yin X, Zhang Q. Family social capital mediates the effect of poverty on children’s anxiety and depression. J Community Psychol. 2018;46(8):983-995. doi: 10.1002/jcop.22086 [DOI] [PubMed] [Google Scholar]
40.Yousefi-Rizi L, Baek JD, Blumenfeld N, Stoskopf C. Impact of housing instability and social risk factors on food insecurity among vulnerable residents in San Diego County. J Community Health. 2021;46(6):1107-1114. doi: 10.1007/s10900-021-00999-w [DOI] [PMC free article] [PubMed] [Google Scholar]
41.McMakin DL, Alfano CA. Sleep and anxiety in late childhood and early adolescence. Curr Opin Psychiatry. 2015;28(6):483-489. doi: 10.1097/YCO.0000000000000204 [DOI] [PMC free article] [PubMed] [Google Scholar]
42.Toro PA. Toward an international understanding of homelessness. J Soc Issues. 2007;63(3):461-481. doi: 10.1111/j.1540-4560.2007.00519.x [DOI] [Google Scholar]
43.Toro PA, Bellavia CW, Daeschler CV, et al. Distinguishing homelessness from poverty. J Consult Clin Psychol. 1995;63(2):280-289. doi: 10.1037/0022-006X.63.2.280 [DOI] [PubMed] [Google Scholar]
44.Costello EJ, Compton SN, Keeler G, Angold A. Relationships between poverty and psychopathology. JAMA. 2003;290(15):2023-2029. doi: 10.1001/jama.290.15.2023 [DOI] [PubMed] [Google Scholar]

Associated Data

This section collects any data citations, data availability statements, or supplementary materials included in this article.

Data Citations

US Interagency Council on Homelessness. Key federal terms and definitions of homelessness among youth. Accessed June 12, 2022. https://www.usich.gov/resources/uploads/asset_library/Federal-Definitions-of-Youth-Homelessness.pdf

Supplementary Materials