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Journal of General Internal Medicine logoLink to Journal of General Internal Medicine
. 2025 Jul 3;40(13):3013–3022. doi: 10.1007/s11606-025-09709-x

Unmet Subsistence and Mental Health Needs in Women Experiencing Homelessness: Rethinking Care Models for Improved Outcomes

Thye Peng Ngo 1,✉, Torsten B Neilands 2, Annesa Flentje 3, Samantha E Dilworth 2, Elise Riley 2
PMCID: PMC12508409  NIHMSID: NIHMS2136973  PMID: 40610668

Abstract

Background

Women experiencing homelessness or unstable housing (WEH) exhibit disproportionately high rates of depression and anxiety. While existing research links unmet subsistence needs (e.g., housing and food insecurity) to mental health (MH), the intersection of these unmet needs with health and social factors on MH disparities remains underexplored.

Objective

We examined associations between unmet subsistence needs and MH symptoms among WEH, focusing on interactions with health and social-related factors, including sleep disturbances, pain, and HIV status.

Design

Cross-sectional analysis using baseline data from the PULSE cohort study.

Participants

245 women recruited from shelters, free meal programs, and street encampments.

Main Measures

We measured anxiety with the Generalized Anxiety Disorder 7-item (GAD-7) and depression with the Patient Health Questionnaire (PHQ-9). Unmet subsistence needs included insufficient access to shelter, food, clothing, and hygiene resources.

Key Results

Nearly half (49%) of WEH had moderate to severe depression, 36% had moderate to severe anxiety, and nearly 40% had at least one unmet subsistence need. WEH with ≥ 2 unmet needs had almost four times the odds of depression (AOR = 3.96, 95% CI = 1.84, 8.51) and nearly three times the odds of anxiety (AOR = 2.83, 95% CI = 1.39, 5.77) than those without unmet needs. Sleep disturbance and pain were also associated with higher odds of depression (AOR = 4.46, 95% CI = 2.28, 8.71; AOR = 7.01, 95% CI: 3.40, 14.44) and anxiety (AOR = 5.01, 95% CI = 2.70, 9.31; AOR = 3.60, 95% CI = 1.73, 7.50). HIV modified the effect of unmet needs, with seven times higher odds of anxiety among women with HIV who also had ≥ 2 unmet needs (AOR = 7.11, 95% CI = 1.06, 48.00).

Conclusion

Unmet subsistence needs, sleep disturbances, and pain contribute to depression and anxiety among WEH, particularly those living with HIV. Low-barrier care models that address social needs alongside medical care may improve MH outcomes in WEH.

KEY WORDS: unmet subsistence needs, mental health, women experiencing homelessness

INTRODUCTION

Ninety-percent of women experiencing homelessness or unstable housing (WEH) have at least one mental health (MH) diagnosis,1 significantly surpassing the 27.2% in the general U.S. adult female population.2 Compared to men, WEH report higher rates of psychiatric hospitalizations.3

Depression and anxiety are among the most prevalent MH conditions in this demographic.4–6 They frequently co-occur, sharing several risk factors and potentially influencing each other.7–9 Approximately half of WEH experience both depression and anxiety,10 with and substantial overlap with substance-related disorders.1

Unmet subsistence needs (inability to access housing, food, clothing, and hygiene)11 exacerbate MH challenges. For example, unmet subsistence needs are associated with worse overall health status among WEH.12 Housing instability13 and food insecurity14,15 are consistently linked to worse MH outcomes; recent studies have highlighted the growing impact of clothing and hygiene deprivation on MH.16,17 Additionally, unmet needs significantly increase the likelihood of conditions like anxiety and depression in this population,10 and such disparities are more common among racial and ethnic minorities, including African American and Hispanic unhoused women.18

While existing research focuses on the direct impact of unmet subsistence needs on MH, less attention has been given to how these needs interact with other health (e.g., HIV) and social-related factors (e.g., race, age, and sexual orientation). This is important because overlapping effects of health and social-related issues can compound vulnerabilities, leading to unique disadvantages and health outcomes among WEH.19 For example, both identifying as a sexual minority and experiencing homelessness may intersect and exacerbate MH challenges in ways that differ from other demographic groups.20,21 Exploring how unmet needs intersect with other social determinants of health may provide important insight for identifying the full scope of MH disparities among WEH and informing care models or interventions. This may be particularly useful for “low-barrier” care models, which began placing a strong emphasis on removing social and structural barriers to care seven years ago in the context of HIV care (e.g., no appointments, financial incentives, and assistance with transportation),22,23 and have since been adapted for other types of care.24–26

Prior research investigating depression and anxiety among people who experience homelessness has largely focused on their prevalence,4,5 with sub-analyses regarding age, gender, and geographic region.4 Few studies have rigorously examined multiple competing factors that intersect to shape MH outcomes. Our research on social and psychological changes among WEH during the COVID-19 pandemic found a strong association between unmet subsistence needs and depression; however, that study did not include predisposing factors like substance use or co-occurring conditions like sleep disturbance and pain, which disproportionately impact people who experience homelessness. The current study extends prior research by examining associations between unmet subsistence needs and MH outcomes among WEH, focusing on how these relationships are influenced by other intersecting demographic, socioeconomic, and health-related factors.

METHODS

Study Design

This secondary analysis used data from the “Polysubstance Use and Health Outcomes Evaluation” (PULSE) study, which examined substance use on cardiac dysfunction among WEH.27 Data were collected between June 2016 and January 2019. Participants completed monthly confidential study visits for six consecutive months, including interviews, blood draws, and urine collections. The current study used baseline data only.

Consistent with our prior research among people who experience homelessness,28,29 we used the Behavioral Model for Vulnerable Populations as a heuristic to guide this study. The model posits that predisposing factors (e.g., age and gender), enabling resources (e.g., access to housing and food), and health needs (e.g., pain interference and sleep disturbances) shape health outcomes and health services use in underserved populations like WEH.30,31

Participants and Recruitment

Participants were recruited from San Francisco shelters, free meal programs, single occupancy hotels, and street encampments. Women with HIV were over-sampled to address HIV-specific aims of the main study from safety net HIV clinics and provider referrals.27 Inclusion criteria were (1) female sex at birth, (2) age ≥ 18 years, and (3) a lifetime history of housing instability (i.e., slept in public, a place not meant for human habitation, or a homeless shelter; or stayed with a series of associates because there was no other place to sleep [“couch-surfed”]). HIV testing was conducted at screening for participants who did not already have an HIV diagnosis.

This study was approved by the Institutional Review Board at the University of California, San Francisco. Informed consent was obtained prior to study participation, and compensation was $40 per study visit.

Outcome Measures

The outcomes of this study were symptoms consistent with anxiety and depression. We dichotomized the Generalized Anxiety Disorder 7-item (GAD-7) scale, with scores ≥ 10 indicating moderate to severe anxiety.32 Similarly, we dichotomized the Patient Health Questionnaire (PHQ) 9, with scores ≥ 10 indicating moderate to severe depression.33

Primary Exposure Measures: Unmet Subsistence Needs

We assessed unmet subsistence needs11 as insufficient access to shelter, food, clothing, personal hygiene needs, and sanitation facilities within the past month. Due to the distribution in the number of unmet needs, this variable was coded as 0, 1, or ≥ 2.

Additional Covariates

Social-related Covariates

Demographics were age, race, ethnicity, sexual orientation, and relationship status, while socioeconomic status included education, previous month’s income, and health insurance status. Instrumental support reflected whether participants knew anyone who would lend them money or give them a place to sleep in the previous month;34 responses were dichotomized as yes (support available) or no (support unavailable).

Health-related Covariates

Health-related covariates included HIV status at baseline, postmenopausal status (> 12 months since last menstrual period), sleep disturbance, and pain, based on their associations with MH in individuals experiencing homelessness in the literature.35–38 We measured sleep disturbance with the Patient-Reported Outcomes Measurement Information System (PROMIS) Sleep Disturbance Scale39,40 and dichotomized it as none to mild (< 60) and moderate to severe sleep disturbance (≥ 60).41 We quantified pain using the PEG-3 scale, a three-item measure that evaluates average pain intensity (P) and how it interferes with life enjoyment and general activity (G) on a scale of 0–10, where higher scores indicate greater pain severity.42 Following prior research, we dichotomized the sum of the PEG-3 score as none to mild (0–3) and moderate to severe (≥ 4) pain intensity and interference in daily activities and enjoyment of life.43

Given prior research on substance use and MH among WEH,44 including those living with HIV,45 we included multiple substance use (i.e., using ≥ 2 substances) to isolate the potential influence of unmet subsistence needs on depression and anxiety. Substance use included self-reported use in the prior 30 days or toxicology-confirmed use of alcohol (ethyl glucuronide), tobacco (urinary cotinine, serum nicotine), stimulants (cocaine, amphetamine, methamphetamine), opioids (heroin, opioids, fentanyl), or cannabis (THC).

Analysis

We used chi-square statistics and logistic regression to test whether study factors were significantly associated with symptoms of depression and anxiety. Variable selection for adjusted models was conducted using the best subset variable selection method (‘gvselect’ command in STATA), which tests all possible subsets of predictors and selects the best-fitting model based on the Bayesian Information Criterion (BIC), balancing model complexity with predictive accuracy to obtain a parsimonious yet informative model.46 In addition to the main effects, we tested interactions between unmet subsistence needs and key sociodemographic and health-related factors (i.e., age, race, ethnicity, sexual orientation, HIV status, postmenopausal status, multiple substance use, sleep disturbance, and pain interference) using the cross-fit partialing-out model. All analyses were conducted using STATA, v18.

RESULTS

Participant Characteristics

Nearly one-third of participants were living with HIV (31.4%), mean age was 51.6 years, and the majority identified as Black/African American (40%), followed by White/European-American (27.8%), and multiracial (19.2%) (Table 1). Over two-thirds (69.8%) had completed high school, more than 90% had health insurance, and 83.3% reported having instrumental social support. Approximately 40% reported at least one unmet subsistence need in the prior month, with 22.2% having two or more.

Table 1.

Participant Characteristics at Baseline by Moderate to Severe Symptoms of Anxiety and Depression among Homeless and Unhoused Women Living in San Francisco (N = 245)

Characteristics Total Sample
N (%) or Mean (SD*, range)		 Depression Anxiety
No to Mild
N (%) or Mean (SD*) 		Moderate to Severe
N (%) or Mean (SD*) 		p-value No to Mild
N (%) or Mean (SD*) 		Moderate to Severe
N (%) or Mean (SD*) 		p-value
Primary Exposures: Unmet Subsistence Needs (prior month)†
  0 unmet needs 146 (59.6%) 91 (72.8%) 55 (45.8%)  < 0.001 106 (67.9%) 39 (44.3%) 0.001
  1 unmet need 44 (18.0%) 18 (14.4%) 26 (21.7%) – 25 (16.0%) 19 (21.6%) –
  2 or more unmet needs 55 (22.4%) 16 (12.8%) 39 (32.5%) – 25 (16.0%) 30 (34.1%) –
Demographics
Age (years) 51.6 (10.8, 28.8–71) 52.1 (10.5) 51.1 (11.1) 0.666 52.9 (10.7) 49.2 (10.5) 0.010
Race 0.004 0.174
  Alaskan/Native American 16 (6.5%) 7 (5.6%) 9 (7.5%) – 11 (7.1%) 5 (5.7%) –
  Asian/Pacific Islander 8 (3.3%) 7 (5.6%) 1 (0.8%) – 8 (5.1%) 0 (0.0%) –
  Black/African American 97 (40.0%) 51 (40.8%) 46 (38.3%) – 60 (38.5%) 36 (40.9%) –
  White/European-American 68 (27.8%) 40 (32.0%) 28 (23.3%) – 46 (29.5%) 22 (25.0%) –
  Other 9 (3.7%) 0 (0.0%) 9 (7.5%) – 3 (1.9%) 6 (6.8%) –
  Multiracial 47 (19.2%) 20 (16.0%) 27 (22.5%) – 28 (18.0%) 19 (21.6%) –
Latina ethnicity 37 (15.1%) 13 (10.4%) 24 (20.0%) 0.036 20 (12.8%) 17 (19.3%) 0.174
Sexual orientation 0.394 0.120
  Heterosexual 181 (73.9%) 95 (76.0%) 86 (71.7%) – 119 (76.3%) 61 (73.8) –
  Homosexual 16 (6.5%) 10 (8.0%) 6 (5.0%) – 12 (7.7%) 4 (4.6%) –
  Bisexual 39 (15.9%) 17 (13.6%) 22 (18.3%) – 22 (14.1%) 17 (19.3%) –
  Other 9 (3.7%) 3 (2.4%) 6 (5.0%) – 3 (1.9%) 6 (6.8%) –
Relationship status 0.603 0.515
  Single 164 (66.9) 81 (64.8%) 83 (69.2%) – 106 (68.0%) 57 (64.8%) –
  Legally married 36 (14.7%) 18 (14.4%) 18 (15.0%) – 20 (12.8%) 16 (18.2%) –
  In a relationship 45 (18.4%) 26 (20.8%) 19 (15.8%) – 30 (19.2%) 15 (17.1%) –
Socioeconomic Status and Social Support
Completed high school 171 (69.8%) 95 (76.6%) 76 (63.9%) 0.030 114 (73.1%) 56 (64.4%) 0.134
Income (dollars, prior month) 935.4 (662.1) 920.6 (587.7) 950.9 (733.7) 0.614 957.1 (735.0) 892.6 (512.3) 0.935
Health insurance (prior month) 227 (92.6%) 118 (94.4%) 109 (90.8%) 0.297 147 (94.2%) 79 (89.8%) 0.197
Instrumental social support (prior month) 204 (83.3%) 107 (85.6%) 97 (80.8%) 0.318 132 (84.6%) 71 (80.7%) 0.430
Health-Related Characteristics
HIV-positive 77 (31.4%) 42 (33.6%) 35 (29.2%) 0.455 52 (33.3%) 24 (27.3%) 0.326
Postmenopausal‡ 154 (62.9%) 75 (60.0%) 79 (66.4%) 0.301 99 (63.5%) 54 (62.1%) 0.829
Multiple Substance Use (≥ 2 substances)§ 207 (84.5%) 99 (79.2%) 107 (89.2%) 0.033 126 (80.8%) 79 (89.8%) 0.065
Single Substance Use 27 (11.0%) 18 (14.4%) 9 (7.5%) 0.085 21 (13.5%) 6 (6.8%) 0.112
  Alcohol 157 (64.1%) 73 (58.4%) 84 (70.0%) 0.059 90 (57.7%) 66 (75.0%) 0.007
  Tobacco 183 (74.7%) 85 (68.0%) 98 (81.7%) 0.014 111 (71.2%) 72 (81.8%) 0.065
  Stimulant‖ 162 (66.1%) 74 (59.2%) 88 (73.3%) 0.019 100 (64.1%) 61 (69.3%) 0.409
  Opioid 107 (43.7%) 46 (36.8%) 61 (50.8%) 0.027 62 (39.7%) 44 (50.0%) 0.121
  Cannabis 169 (67.0%) 84 (67.2%) 85 (70.8%) 0.539 101 (64.7%) 67 (76.1%) 0.065
Moderate to severe sleep disturbance (prior week)# 76 (31.0%) 19 (15.2%) 57 (47.5%)  < 0.001 27 (17.3%) 48 (54.6%)  < 0.001
Moderate to severe pain and interference (prior week)** 170 (69.4%) 65 (52.0%) 105 (87.5%)  < 0.001 94 (60.3%) 75 (85.2%)  < 0.001
Mental Health Symptoms (Outcomes)
Moderate to severe depression (prior two weeks)†† 120 (49.0%) – – – – – –
Moderate to severe anxiety (prior two weeks)‡‡ 88 (35.9%) – – – – – –
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*SD = standard deviation

†Including shelter, food, clothing, sanitation facilities, and personal hygiene

‡More than 1 year since last menstrual period

§Including self-report or toxicology-confirmed alcohol, tobacco, stimulants, opioids, and cannabis

‖Including cocaine, amphetamine, and methamphetamine

Including fentanyl and heroin

#Patient-Reported Outcomes Measurement Information System (PROMIS) Sleep Disturbance Scale

**PEG-3 Scale

††Patient Health Questionnaire (PHQ-9)

‡‡Generalized Anxiety Disorder 7-item (GAD-7) scale

Almost one-third of participants reported moderate to severe sleep disturbances (31.0%), approximately two-thirds were postmenopausal (62.9%), and a majority experienced moderate to severe pain (69.4%). The most commonly used substances were tobacco (74.4%), followed by cannabis (67.0%), stimulants (66.1%), alcohol (64.1%), and opioids (43.7%). The vast majority of participants used two or more substances (84.5%).

Associations Between Study Factors and Moderate to Severe Depression

Almost half of the participants reported moderate to severe depression (49.0%). Unadjusted analyses indicated the odds of experiencing depression were twice as high for participants with one unmet need (unadjusted odds ratio [UOR] = 2.39, 95% CI = 1.20, 4.75) and four times as high for those with two or more unmet needs (UOR = 4.03, 95% CI = 2.06, 7.89) compared to participants with no unmet needs (Table 2). The odds of experiencing depression were also twice as high for Latina women (UOR = 2.15, 95% CI = 1.04, 4.46) and those who used multiple substances (UOR = 2.16, 95% CI = 1.05, 4.44), while the odds were five times higher for those who experienced sleep disturbance (UOR = 5.05, 95% CI = 2.75, 9.25) and six times higher for those with moderate to severe pain (UOR = 6.46, 95% CI = 3.39, 12.31). The odds of experiencing depression were 46% lower for those who completed high school (UOR = 0.54, 95% CI = 0.31, 0.94).

Table 2.

Associations Between Study Factors and Moderate and Severe Depression (N = 245)

Characteristics Unadjusted Odds Ratio
(95% CI),* p-value 		Adjusted Odds Ratio
(Full Model)
(95% CI), p-value 		Adjusted Odds Ratio
(Final Model)
(95% CI),† p-value
Primary Exposure: Unmet Subsistence Needs
 0 unmet needs (reference) (reference) (reference)
  1 unmet need 2.39 (1.20, 4.75), p = 0.013 2.92 (1.22, 6.97), p = 0.016 2.36 (1.07, 5.21), p = 0.034
  2 or more unmet needs 4.03 (2.06, 7.89), p < 0.001 3.96 (1.65, 9.51), p = 0.002 3.96 (1.84, 8.51), p < 0.001
Demographics
Age (years) 0.99 (0.97, 1.01), p = 0.453 0.97 (0.93, 1.02), p = 0.240 –
Race
  White/European-American (reference) (reference) –
  Alaskan/Native American 1.84 (0.61, 5.51), p = 0.278 1.96 (0.50, 7.70), p = 0.334 –
  Asian/Pacific Islander 0.20 (0.24, 1.75), p = 0.147 0.20 (0.02, 2.54), p = 0.213 –
  Black/African American 1.29 (0.69, 2.41), p = 0.428 1.15 (0.51, 2.56), p = 0.738 –
  Other ‡ ‡ –
  Multiracial 1.93 (0.91, 4.10), p = 0.088 1.60 (0.57, 4.48), p = 0.375 –
Latina ethnicity 2.15 (1.04, 4.46), p = 0.039 0.82 (0.29, 2.35), p = 0.712 –
Sexual orientation
  Heterosexual (reference) (reference) –
  Homosexual 0.66 (0.23, 1.90), p = 0.444 0.48 (0.12, 1.90), p = 0.297 –
  Bisexual 1.43 (0.71, 2.87), p = 0.315 1.06 (0.39, 2.83), p = 0.913 –
  Other 2.21 (0.54, 9.11), p = 0.273 0.32 (0.05, 1.94), p = 0.214 –
Relationship status
  Single (reference) (reference) –
  Married or in relationship 0.98 (0.47, 2.01), p = 0.947 0.75 (0.29, 1.96), p = 0.557 –
  In a relationship 0.71 (0.37, 1.39), p = 0.320 0.58 (0.22, 1.51), p = 0.263 –
Socioeconomic Status and Social Support
Completed high school 0.54 (0.31, 0.94), p = 0.031 0.63 (0.30, 1.34), p = 0.231 –
Income (dollars) 1.00 (1.00, 1.00), p = 0.720 1.00 (1.00, 1.00), p = 0.431 –
Health insurance 0.75 (0.46, 1.22), p = 0.242 0.87 (0.44, 1.73), p = 0.700 –
Instrumental social support 0.71 (0.36, 1.39), p = 0.319 0.86 (0.37, 2.00), p = 0.724 –
Health-Related Characteristics
HIV-positive 0.81 (0.47, 1.40), p = 0.455 0.60 (0.29, 1.24), p = 0.168 –
Postmenopausal 1.32 (0.78, 2.22), p = 0.302 2.32 (0.84, 6.44), p = 0.106 –
Multiple Substance Use (≥ 2 substances) 2.16 (1.05, 4.44), p = 0.036 1.94 (0.75, 5.03), p = 0.174 –
Moderate to severe sleep disturbance 5.05 (2.75, 9.25), p < 0.001 5.29 (2.56, 10.92), p < 0.001 4.46 (2.28, 8.71), p < 0.001
Moderate to severe pain and interference 6.46 (3.39, 12.31), p < 0.001 5.28 (2.39, 11.68), p < 0.001 7.01 (3.40, 14.44), p < 0.001
Open in a new tab

*CI = confidence interval

†The adjusted model includes unmet subsistence needs as the primary exposure. Covariates include moderate to severe pain and interference and moderate to severe sleep disturbance based on Bayesian Information Criteria

‡This category predicts failure perfectly (i.e., all participants reporting “other” race had depression). Thus, it was omitted from the adjusted analysis

In adjusted analysis, the association between unmet subsistence needs and depression remained significant for women with one (AOR = 2.36, 95% CI = 1.07, 5.21) or ≥ 2 unmet needs (AOR = 3.96, 95% CI = 1.84, 8.51). Also, the adjusted odds ratios for sleep disturbance (AOR = 4.46, 95% CI = 2.28, 8.71) and pain interference (AOR = 7.01, 95% CI = 3.40, 14.44) also remained strong for depression, consistent with the unadjusted findings.

We did not observe significant interactions between unmet subsistence needs and other key sociodemographic and health-related factors in analyses regarding depression.

Associations Between Study Factors and Moderate to Severe Anxiety

Over one-third of participants reported moderate to severe anxiety (35.9%). The unadjusted analyses revealed that participants with one unmet need had twice the odds of experiencing anxiety (UOR = 2.07, 95% CI = 1.03, 4.16), while those with ≥ 2 unmet needs had over three times the odds (UOR = 3.26, 95% CI = 1.71, 6.22) relative to women with no unmet needs (Table 3). Additionally, the odds of experiencing anxiety were almost six times higher for women who reported sleep disturbance (UOR = 5.73, 95% CI = 3.18, 10.34) and almost four times higher for those with moderate to severe pain (UOR = 3.81, 95% CI = 1.95, 7.44). Younger women had lower odds of experiencing anxiety than their older counterparts, with each additional year being associated with a 3% decrease in the odds (UOR = 0.97, 95% CI = 0.95, 0.99).

Table 3.

Associations Between Study Factors and Moderate and Severe Anxiety (N = 245)

Characteristics Unadjusted Odds Ratio (95% CI),* p-value Adjusted Odds Ratio
(Full Model)
(95% CI), p-value 		Adjusted Odds Ratio
(Final Model)
(95% CI),† p-value
Primary Exposures: Unmet Subsistence Needs
  0 unmet needs (reference) (reference) (reference)
  1 unmet need 2.07 (1.03, 4.16), p = 0.042 1.98 (0.85, 4.62), p = 0.113 1.79 (0.82, 3.91), p = 0.141
  2 or more unmet needs 3.26 (1.71, 6.22), p < 0.001 2.38 (1.06, 5.36), p = 0.037 2.83 (1.39, 5.77), p = 0.004
Demographics
Age (years) 0.97 (0.95, 0.99), p = 0.012 0.94 (0.90, 0.98), p = 0.008 –
Race
  White/European-American (reference) (reference) –
  Alaskan/Native American 0.95 (0.29, 3.07), p = 0.932 0.91 (0.22, 3.84), p = 0.897 –
  Asian/Pacific Islander ‡ ‡ –
  Black/African American 1.25 (0.65, 2.41), p = 0.497 1.43 (0.62, 3.35), p = 0.407 –
  Other 4.18 (0.96, 18.30), p = 0.057 1.76 (0.27, 11.48), p = 0.553 –
  Multiracial 1.42 (0.65, 3.07), p = 0.375 1.09 (0.38, 3.11), p = 0.870 –
Latina ethnicity 1.63 (0.80, 3.30), p = 0.177 –
Sexual orientation
  Heterosexual (reference) (reference) –
  Homosexual 0.65 (0.20, 2.10), p = 0.472 0.62 (0.15, 2.52), p = 0.501 –
  Bisexual 1.51 (0.75, 3.05), p = 0.253 1.62 (0.63, 4.17), p = 0.315 –
  Other 3.90 (0.94, 16.14), p = 0.060 1.06 (0.18, 6.19), p = 0.953 –
Relationship status
  Single (reference) (reference) –
  Married or in relationship 1.49 (0.72, 3.09), p = 0.287 1.53 (0.61, 3.84), p = 0.363 –
  In a relationship 0.93 (0.46, 1.87), p = 0.838 0.92 (0.36, 2.35), p = 0.863 –
Socioeconomic Status and Social Support
Completed high school 0.65 (0.37, 1.14), p = 0.135 0.75 (0.36, 1.57), p = 0.443 –
Income (dollars) 1.00 (1.00, 1.00), p = 0.469 1.00 (1.00, 1.00), p = 0.712 –
Health insurance 0.79 (0.49, 1.27), p = 0.327 1.05 (0.56, 1.99), p = 0.872 –
Instrumental social support 0.76 (0.38, 1.51), p = 0.431 1.02 (0.41, 2.51), p = 0.973 –
Health-Related Characteristics
HIV-positive 0.75 (0.42, 1.33), p = 0.327 0.59 (0.28, 1.22), p = 0.154 –
Postmenopausal 0.94 (0.55, 1.62), p = 0.012 2.66 (0.95, 7.47), p = 0.062 –
Multiple Substance Use (≥ 2 substances) 2.09 (0.94, 4.63), p = 0.070 1.35 (0.50, 3.65), p = 0.553 –
Moderate to severe sleep disturbance 5.73 (3.18, 10.34), p < 0.001 5.94 (3.00, 11.82), p < 0.001 5.01 (2.70, 9.31), p < 0.001
Moderate to severe pain and interference 3.81 (1.95, 7.44), p < 0.001 3.03 (1.33, 6.89), p = 0.008 3.60 (1.73, 7.50), p = 0.001
Open in a new tab

*CI = confidence interval

†The adjusted model includes unmet subsistence needs as the primary exposure. Covariates include moderate to severe pain and interference and moderate to severe sleep disturbance based on Bayesian Information Criteria

‡This category predicts failure perfectly (i.e., all participants reporting “other” race had depression). Thus, it was omitted from the adjusted analysis

Adjusted analysis for anxiety showed that women with ≥ 2 unmet needs still had significantly higher odds (AOR = 2.83, 95% CI = 1.39, 5.77) compared to those without unmet needs. The adjusted odds ratios for moderate to severe sleep disturbances (AOR = 5.01, 95% CI = 2.70, 9.31) and pain interference (AOR = 3.60, 95% CI = 1.73, 7.50) were consistent after the adjustment. After adjusting for unmet needs, the association between age and anxiety weakened, and age was not included in the final model.

In assessing potential interactions, we observed that HIV status modified the effect of unmet subsistence needs on anxiety. Specifically, the odds of experiencing anxiety were substantially higher for HIV-positive women with two or more unmet needs compared to those without unmet needs and HIV-negative status (AOR = 7.11, 95% CI = 1.06, 48.00).

DISCUSSION

Almost half of WEH in this study had symptoms of depression, and over a third had symptoms of anxiety, which is 47% higher than the general population.5 One-third had unmet subsistence needs, one-third had sleep disturbance, 70% experienced severe pain, and each factor was associated with both depression and anxiety. More unmet needs were associated with higher odds of experiencing both anxiety and depression, and the effect was greater among women living with HIV. Younger women had more unmet needs, but experiencing unmet needs, rather than age, was the stronger predictor of anxiety. While current guidelines recommend cognitive behavioral therapy (CBT) and self-help manuals for treating depression and anxiety in the general population,47 additional strategies addressing unmet needs are necessary. Attending to basic survival needs, pain management, and sleep improvements are all critical for improving MH outcomes, especially for WEH with HIV.

Unmet subsistence needs tend to co-occur, compounding their effects on MH. For example, individuals who experience food insecurity are more likely to develop depressive symptoms when they also face housing instability and live with HIV.48 Furthermore, poorly maintained single-room occupancy hotels can exacerbate MH conditions.49 Deprivation of basic necessities, such as food and clothing, irrespective of income, is associated with increased anxiety and stress, emphasizing the importance of addressing both financial and non-financial factors.​17 Using the Behavioral Model for Vulnerable Populations,30,31 this study identified unmet needs as enabling factors and sleep disturbance and pain as health conditions associated with depression and anxiety. Our prior work informed by this model suggested that enabling factors such as unmet needs predict sexually transmitted infections,50 overall health status,12 and viral load among WEH with HIV.29 Similar to the current study’s findings with regard to MH outcomes, our prior work also showed a strong relationship between pain and hospitalization, but not HIV and hospitalization, among WEH.51

This study extends prior research that examined the cumulative effect of a wider range of co-occurring unmet subsistence needs on MH symptoms.52 Specifically, this study includes additional critical factors, such as access to clothing, sanitation, and hygiene, which are persistent challenges often faced by unhoused individuals.53 These findings emphasize the compounded impact of multiple, co-occurring needs and the necessity of integrated care. Collaboration between social workers with primary and emergency care providers is crucial in ensuring access to supportive housing with adequate water and sanitation, which positively improve MH outcomes among unhoused individuals.54,55 Medical practitioners can incorporate screenings for unmet needs into routine assessments and partner with community organizations to provide housing, hygiene, and MH support. By leveraging low-barrier, wraparound care models that facilitate the use of collocated services, such as San Francisco’s “POP UP” clinic for people with HIV56,57 and the “Health Access Point” clinic, general practitioners can address the intertwined medical and social needs of WEH.

We observed that sleep disturbances and pain interference were associated with both MH outcomes among WEH. Cognitive behavioral therapy (CBT) has been recommended for the simultaneous management of both chronic pain and insomnia.58 In terms of each individual condition, prior research suggests that non-pharmacological sleep interventions such as those involving the use of earplugs, eye masks, white noise, music, aromatherapy, massage, light intensity, and a sleep hygiene protocol can have a positive influence on sleep quality.59–61 Similarly, pain management requires a multimodal approach, including individualized physical therapy,62 mindfulness-based stress reduction,63 and even battlefield acupuncture for unhoused Veterans.64 Findings from this study further suggest that addressing basic subsistence needs should be a foundational step in sleep and pain interventions. A stepwise, research-informed approach by addressing basic needs first before targeted interventions (e.g., CBT) may optimize outcomes.65,66 Whether integrating substance use interventions into a stepwise multimodal approach enhances effectiveness remains unclear; however, given the high prevalence in this population, future research is warranted.

Prior research shows a high prevalence of MH disorders among individuals living with HIV, especially among marginalized populations,67 and substantially overlap with social/structural factors, including food and housing insecurity.68 Results presented here indicate that these factors do not simply co-exist, but rather that they interact with HIV. The odds of experiencing anxiety were almost three times higher for women with multiple unmet subsistence needs, and seven times higher for women with HIV and multiple unmet needs. While connecting women with social services is crucial, individuals with HIV who experience unmet needs are not only more likely to have depression and anxiety, but also less likely to remain in care.69 Recent HIV care models address complex medical and social needs among patients who are not well-engaged in traditional HIV care22 by providing low-barrier, wrap-around services–including MH support and addiction treatment–and incentives to make clinic visits.57 Such clinics are showing significant improvements in care engagement and virologic suppression.23,56 Results from this study suggest that similar low-barrier and wrap-around care may also improve MH conditions, particularly anxiety, among WEH. Future research should explore whether these models for MH care would yield better outcomes than current guidelines.

LIMITATIONS

Several limitations should be noted. First, this study’s cross-sectional design precludes assessing changes over time or establishing causality between unmet subsistence needs and MH outcomes. Longitudinal studies are needed to clarify these dynamics. Second, the study is based on a single city, limiting generalizability to other urban areas. However, the distribution of participant characteristics and outcomes were similar to studies of WEH in other cities, including racial composition and a higher prevalence of substance use and MH,70–72 suggesting broader applicability. Third, while HIV was not associated with either outcome, oversampling WEH living with HIV may limit the generalizability of our findings to all WEH and amplify the observed influence of HIV on the relationship between unmet needs and anxiety, warranting caution in interpretation. Fourth, while this study examined the cumulative impact of unmet needs, future sensitivity analyses could separate specific needs to refine insights. Additionally, participants were not screened for psychotic disorders, which are common in this population and strongly correlated with depression and anxiety. Future studies should consider them as potential modifiers or outcomes. Lastly, data were collected between 2016 and 2019, before the COVID-19 pandemic. While the pandemic has influenced housing and health outcomes, it is unlikely to have changed the fundamental relationships between unmet needs and MH.73 Nevertheless, post-pandemic research is needed to examine whether these associations persist. Despite these limitations, this study enhances understanding of unmet subsistence needs and mental health in among WEH, highlighting the interaction between overlapping factors.

CONCLUSION

WEH with unmet subsistence needs, sleep disturbance, and severe pain are much more likely to have anxiety and depression, which may make current treatment guidelines insufficient. Women with HIV are even more likely to live with anxiety. The expansion of low-barrier wrap-around care models to both HIV and non-HIV clinics, which include MH care but also provide an infrastructure that specifically addresses unmet social needs and tailored care, may improve care and ultimately lower the high levels of mental illness experienced among WEH.

Author Contributions:

Conception and design: TPN, ER.

Analysis and interpretation: TPN, TBN, AF, SED, ER.

Drafting of the article: TPN, ER.

Critical revision of the article for important intellectual content: TPN, TBN, AF, SED, ER.

Final approval of the article: TPN, TBN, AF, SED, ER.

Administrative, technical, or logistic support: SED, ER.

Funding

Funding sources are non-commercial and include grants from the National Institute on Drug Abuse (R01 DA037012, R01 DA049648, and K24 DA039780).

Data Availability

Due to the sensitive nature of the data analyzed here, as well as the relatively small sample, which could compromise participant anonymity, data from this study are not publicly available. De-identified data sets are available upon request.

Declarations:

Human Ethics and Consent to Participate:

UCSF IRB #14–13868.

Conflict of Interest:

The authors report no conflicts of interest.

Prior Presentations:

Not applicable.

Footnotes

Publisher's Note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

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Associated Data

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

Data Availability Statement

Due to the sensitive nature of the data analyzed here, as well as the relatively small sample, which could compromise participant anonymity, data from this study are not publicly available. De-identified data sets are available upon request.

Articles from Journal of General Internal Medicine are provided here courtesy of Society of General Internal Medicine

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