Skip to main content
NCBI home page
JAMA Network logoLink to JAMA Network
. 2026 Sep 30;9(9):e2636988. doi: 10.1001/jamanetworkopen.2026.36988

Geographic and Sociodemographic Disparities in Pediatric Mental Health Care Need and Access

Yiting Chen 1, Mengjie Lu 2, Yunyu Xiao 3, Li Niu 4,5, Angela Diaz 5, Yan Li 6,7,✉
PMCID: PMC13628320  PMID: 42814466

Abstract

This survey study evaluates associations between respondent and household characteristics and 3 household-reported pediatric mental health treatment measures.

Introduction

The pediatric mental health crisis in the US has intensified over the past decades. Between 2009 and 2019, the proportion of adolescents reporting persistent sadness or hopelessness increased by approximately 40%.1 In 2024, an estimated 11.3% of adolescents experienced a major depressive episode with severe impairment,2 and nearly half of US children with mental health conditions did not receive treatment or counseling from a mental health professional.3,4

Despite growing recognition of disparities in pediatric mental health care, contemporary evidence characterizing household-reported treatment need and barriers to accessing care remains limited. Using pooled data from the Household Pulse Survey (HPS), this study examined associations between respondent and household characteristics and 3 household-reported pediatric mental health treatment (MHT) measures: reported treatment need, nonreceipt of needed treatment, and perceived difficulty obtaining treatment. We also characterized geographic variation in these measures across US states.

Methods

This repeated cross-sectional study used data from the US Census Bureau’s HPS, a survey designed to monitor social and economic conditions among US households.5 We pooled 9 survey cycles conducted between January 9 and September 16, 2024; later cycles were excluded because state identifiers were unavailable. The study followed Strengthening the Reporting of Observational Studies in Epidemiology (STROBE) and American Association for Public Opinion Research (AAPOR) reporting guidelines. In accordance with 45 CFR §46, this survey study was exempt from review because it used publicly available, deidentified datasets.

There were 3 primary household-reported measures. The first was whether at least 1 child in the household needed MHT in the past 4 weeks (yes vs no). The second was whether needed treatment was received among households reporting need (all or some received vs none received). The third was perceived difficulty obtaining MHT among households reporting need (not difficult, difficult [including somewhat difficult, very difficult, or unable to access], or did not try).

Because MHT information was reported by an adult household respondent, all analyses were interpreted at the household level. Survey-weighted proportions were calculated using official HPS household weights. Survey-weighted logistic regression models estimated associations between household characteristics and each measure, adjusting for census region, respondent race and ethnicity, educational attainment, annual household income, marital status, food sufficiency, financial difficulty, housing type, housing tenure, and health insurance type. Analyses were conducted using R version 4.4.0 (R Project for Statistical Computing). Statistical significance was defined as a 2-sided P < .05.

Results

The analytic sample included 167 421 responding households with children younger than 18 years. Among adult household respondents, 97 076 (55.6% weighted) were female; 115 129 (54.3% weighted) were non-Hispanic White, 15 542 (14.2% weighted) non-Hispanic Black, 9214 (5.5% weighted) non-Hispanic Asian, 19 231 (21.1% weighted) Hispanic, and 8305 (4.9% weighted) other races and ethnicities. In weighted analyses, 15.6% (95% CI, 15.3%-15.8%) of households reported pediatric MHT need. Among households reporting need, 13.7% (95% CI, 13.1%-14.3%) reported nonreceipt of needed treatment, and 59.6% (95% CI, 58.6%-60.6%) reported difficulty obtaining treatment. State-level weighted estimates varied from 9.6% (95% CI, 8.0%-11.2%) in Hawaii to 21.1% (95% CI, 18.5%-23.7%) in Vermont for reported MHT need, 7.4% (95% CI, 4.8%-10.0%) in West Virginia to 24.5% (95% CI, 15.5%-33.6%) in the District of Columbia for nonreceipt of MHT care, and 43.4% (95% CI, 37.0%-49.8%) in Arkansas to 72.3% (95% CI, 66.6%-78.0%) in New Hampshire for access difficulty (Figure).

Figure. Map of State-Level Variation in Household-Reported Pediatric Mental Health Treatment Need, Nonreceipt of Needed Treatment, and Difficulty Obtaining Treatment.

Three-panel U S choropleth maps of pediatric mental health treatment access measures. Three vertically stacked choropleth maps of the United States, each labeled at the upper left with a boxed panel letter and a title. Panel A label A with title Need. Each state and the District of Columbia is outlined in black and filled with one of four blue-gray shades from very light to dark. State postal abbreviations appear centered within states. At the right of panel A, a legend titled Survey-weighted proportion, percent lists four color bins: 9.6–15.2, 15.3–17.1, 17.2–18.4, and 18.5–21.1, with darker shading corresponding to higher values. Small northeastern states are labeled with leader lines to abbreviations at the far right, including N H, V T, M A, R I, C T, N J, D E, M D, and D C; M E and N Y are labeled within their shapes. Alaska and Hawaii appear as inset outlines at the lower left, with A K filled and H I unfilled white. Panel B label B with title Nonreceipt of needed treatment. The same U S state layout and labeling style repeats. The legend at right again reads Survey-weighted proportion, percent with bins 7.4–10.2, 10.3–12.9, 13.0–15.2, and 15.3–24.5. Northeastern leader-line labels repeat for the small states and D C. Panel C label C with title Difficulty obtaining treatment. The same map layout repeats with a legend titled Survey-weighted proportion, percent listing bins 43.8–54.8, 54.9–60.7, 60.8–65.6, and 65.7–73.5. Across all panels, darker fills appear in multiple western and northeastern states, while several central and southern states appear in lighter bins; unfilled white states are present in each panel.

Open in a new tab

Survey-weighted proportions were categorized into quartiles separately for each measure across the 50 states and the District of Columbia, with darker shading indicating higher proportions. Map shows the weighted proportion of households with children reporting that at least 1 child needed mental health treatment during the previous 4 weeks. Analyses were restricted to households reporting such need, and maps show the weighted proportions reporting nonreceipt of needed treatment and difficulty obtaining treatment, respectively.

Compared with households with non-Hispanic White respondents, households with non-Hispanic Asian respondents had lower odds of reported MHT need (adjusted odds ratio [aOR], 0.42; 95% CI, 0.37-0.48; P < .001) but higher odds of nonreceipt (aOR, 2.47; 95% CI, 1.80-3.37; P < .001) and not attempting to obtain treatment (aOR, 7.58; 95% CI, 3.80-15.10; P < .001) (Table). Households with non-Hispanic Black respondents had higher odds of nonreceipt (aOR, 2.02; 95% CI, 1.68-2.42; P < .001). Compared with households reporting sufficient food, households experiencing frequent food insufficiency had higher odds of nonreceipt (aOR, 3.21; 95% CI, 2.42-4.26; P < .001), difficulty obtaining treatment (aOR, 2.46; 95% CI, 1.91-3.18; P < .001), and not attempting to obtain treatment (aOR, 3.53; 95% CI, 2.02-6.17; P < .001).

Table. Associations of Sociodemographic Characteristics With Household-Reported Pediatric Mental Health Treatment (MHT) Need, Receipt of Needed Treatment, and Difficulty Obtaining Treatment.

Characteristic Need MHTa Not received MHTa Difficulty obtaining MHTa
Difficult Not tried
aOR (95% CI)b P value aOR (95% CI)b P value aOR (95% CI)b P value aOR (95% CI)b P value
US Census region
Northeast 1 [Reference] NA 1 [Reference] NA 1 [Reference] NA 1 [Reference] NA
South 0.85 (0.80-0.91) <.001 1.07 (0.86-1.34) .55 0.81 (0.72-0.92) .002 1.30 (0.80-2.11) .29
Midwest 0.98 (0.92-1.04) .52 0.98 (0.78-1.24) .88 0.82 (0.73-0.91) <.001 1.37 (0.81-2.30) .25
West 0.91 (0.85-0.98) .01 1.32 (1.07-1.64) .02 1.10 (0.98-1.25) .13 2.04 (1.13-3.68) .02
Race and ethnicity
Hispanic 0.72 (0.67-0.77) <.001 1.33 (1.11-1.58) .004 1.01 (0.87-1.18) .88 1.31 (0.87-1.97) .20
Non-Hispanic Asian 0.42 (0.37-0.48)c <.001 2.47 (1.80-3.37)c <.001 1.02 (0.79-1.31)c .91 7.58 (3.80-15.10)c <.001
Non-Hispanic Black 0.63 (0.58-0.68) <.001 2.02 (1.68-2.42)c <.001 0.74 (0.63-0.86) <.001 3.05 (1.90-4.90)c <.001
Non-Hispanic White 1 [Reference] NA 1 [Reference] NA 1 [Reference] NA 1 [Reference] NA
Otherd 0.91 (0.84-0.98) .02 1.46 (1.16-1.83) .003 1.03 (0.86-1.23) .80 1.60 (0.94-2.72) .09
Respondent’s education level
Less than high school 0.85 (0.72-1.02) .09 0.82 (0.53-1.28) .39 0.38 (0.27-0.54)c <.001 1.42 (0.72-2.82) .32
Some high school 0.63 (0.55-0.72) <.001 0.90 (0.62-1.31) .60 0.40 (0.31-0.52)c <.001 0.51 (0.22-1.14) .11
High school graduate or equivalent 0.61 (0.56-0.65) <.001 0.64 (0.53-0.77) <.001 0.46 (0.40-0.53)c <.001 0.64 (0.37-1.10) .12
Some college 0.81 (0.75-0.87) <.001 0.71 (0.59-0.84) <.001 0.64 (0.58-0.71) <.001 0.65 (0.41-1.02) .07
Associate’s degree 0.86 (0.81-0.93) <.001 0.78 (0.63-0.96) .03 0.67 (0.58-0.78) <.001 0.56 (0.30-1.06) .08
College degree 0.84 (0.80-0.89) <.001 0.91 (0.79-1.06) .24 0.83 (0.75-0.91) <.001 0.97 (0.60-1.57) .91
Doctoral, professional, or master’s degree 1 [Reference] NA 1 [Reference] NA 1 [Reference] NA 1 [Reference] NA
Annual household income level, US $
<25 000 0.88 (0.78-0.99) .04 1.14 (0.86-1.51) .39 0.59 (0.48-0.74) <.001 0.85 (0.36-2.04) .72
25 000–49 999 0.79 (0.72-0.88) <.001 1.09 (0.82-1.44) .56 0.75 (0.63-0.88) .002 1.12 (0.58-2.15) .74
50 000–99 999 0.78 (0.72-0.84) <.001 1.24 (0.99-1.55) .07 0.86 (0.76-0.97) .02 0.58 (0.30-1.12) .11
100 000–199 999 0.88 (0.84-0.93) <.001 1.10 (0.89-1.34) .38 0.92 (0.83-1.03) .15 0.81 (0.47-1.39) .44
≥200 000 1 [Reference] NA 1 [Reference] NA 1 [Reference] NA 1 [Reference] NA
Unreported 0.75 (0.64-0.87) <.001 1.36 (0.69-2.68) .38 0.66 (0.47-0.93) .02 1.17 (0.37-3.68) .80
Respondent’s marital status
Now married 1 [Reference] NA 1 [Reference] NA 1 [Reference] NA 1 [Reference] NA
Widowed 1.72 (1.48-1.99) <.001 1.64 (1.12-2.40) .02 0.91 (0.72-1.14) .41 2.69 (1.16-6.25) .03
Divorced 1.70 (1.60-1.82) <.001 1.12 (0.95-1.31) .18 0.93 (0.83-1.05) .27 1.28 (0.84-1.95) .26
Separated 1.69 (1.47-1.94) <.001 1.21 (0.88-1.67) .24 1.10 (0.89-1.37) .39 0.96 (0.41-2.26) .92
Never married 1.25 (1.16-1.34) <.001 1.27 (1.07-1.51) .01 1.01 (0.88-1.16) .86 1.86 (1.18-2.92) .01
Unreported 1.64 (0.93-2.91) .10 4.20 (1.93-9.14)c <.001 0.95 (0.27-3.42) .94 1.12 (0.10-12.67) .93
Household food sufficiency
Enough 1 [Reference] NA 1 [Reference] NA 1 [Reference] NA 1 [Reference] NA
Enough, but not always 1.18 (1.11-1.26) <.001 1.59 (1.30-1.94) <.001 1.55 (1.37-1.74) <.001 2.15 (1.41-3.27) .001
Sometimes not enough 1.41 (1.28-1.54) <.001 2.09 (1.63-2.70)c <.001 1.83 (1.50-2.24) <.001 2.16 (1.25-3.72) .01
Often not enough 1.79 (1.56-2.06) <.001 3.21 (2.42-4.26)c <.001 2.46 (1.91-3.18)c <.001 3.53 (2.02-6.17)c <.001
Unreported 1.05 (0.78-1.40) .77 1.51 (0.70-3.26) .30 0.98 (0.54-1.77) .95 3.23 (0.95-10.98) .07
Financial difficulty
Not at all difficult 1 [Reference] NA 1 [Reference] NA 1 [Reference] NA 1 [Reference] NA
A little difficult 1.20 (1.12-1.28) <.001 1.28 (1.05-1.55) .02 1.26 (1.12-1.43) <.001 1.01 (0.59-1.72) .98
Somewhat difficult 1.28 (1.18-1.40) <.001 1.50 (1.20-1.88) .001 1.51 (1.31-1.76) <.001 1.38 (0.74-2.56) .32
Very difficult 1.59 (1.45-1.75) <.001 1.97 (1.56-2.49) <.001 2.00 (1.72-2.31)c <.001 2.36 (1.38-4.05) .004
Unreported 2.23 (1.70-2.91) <.001 1.77 (0.89-3.53) .11 1.80 (1.03-3.16) .05 1.16 (0.37-3.70) .80
Housing type
Mobile housing 1.04 (0.93-1.17) .49 0.96 (0.76-1.21) .71 0.72 (0.62-0.83) <.001 1.16 (0.65-2.07) .61
Single-family house detached from any other house 1 [Reference] NA 1 [Reference] NA 1 [Reference] NA 1 [Reference] NA
Single-family house attached to ≥1 houses 0.97 (0.88-1.07) .52 0.90 (0.70-1.16) .42 1.25 (1.03-1.50) .03 0.81 (0.39-1.71) .59
Multiunit apartment 0.86 (0.79-0.93) <.001 1.28 (1.01-1.61) .05 1.13 (0.93-1.38) .22 1.43 (0.81-2.50) .23
Boat, RV, van, or other nontraditional housing 2.15 (1.61-2.87)c <.001 3.21 (1.95-5.27)c <.001 0.93 (0.52-1.66) .81 6.19 (2.35-16.29)c <.001
Unreported 0.74 (0.59-0.91) .01 0.94 (0.52-1.68) .83 1.01 (0.65-1.56) .97 0.77 (0.19-3.11) .71
Housing tenure
Owned free and clear 1 [Reference] NA 1 [Reference] NA 1 [Reference] NA 1 [Reference] NA
Owned with mortgage or loan 1.05 (0.99-1.12) .11 1.08 (0.90-1.31) .41 1.04 (0.92-1.18) .50 1.25 (0.77-2.01) .38
Rented 1.05 (0.96-1.15) .32 1.13 (0.89-1.45) .32 0.83 (0.70-1.00) .06 0.90 (0.53-1.51) .69
Occupied without payment 1.10 (0.90-1.35) .37 2.43 (1.68-3.52)c <.001 0.78 (0.52-1.15) .22 1.88 (0.72-4.91) .21
Unreported 1.27 (0.95-1.70) .12 1.18 (0.62-2.25) .63 0.99 (0.61-1.62) .97 1.70 (0.37-7.75) .50
Household health insurance type
Uninsured 0.76 (0.67-0.86) <.001 1.89 (1.49-2.38) <.001 1.64 (1.26-2.11) <.001 2.49 (1.35-4.60) .006
Private 1 [Reference] NA 1 [Reference] NA 1 [Reference] NA 1 [Reference] NA
Public 1.20 (1.11-1.30) <.001 0.83 (0.70-0.98) .03 1.13 (0.98-1.30) .11 0.56 (0.33-0.95) .04
Other insurance 0.77 (0.56-1.04) .10 2.62 (1.18-5.84) .02 1.19 (0.60-2.37) .62 1.30 (0.37-4.63) .69
Unreported 0.78 (0.66-0.91) .004 1.14 (0.58-2.24) .70 1.36 (0.95-1.94) .10 0.80 (0.28-2.32) .69
Open in a new tab

Abbreviations: aOR, adjusted odds ratio; NA, not applicable; RV, recreational vehicle.

a

Models were survey-weighted logistic regressions using Household Pulse Survey household weights and the Fay balanced repeated replication method for variance estimation. For need MHT, the model compared households reporting that at least 1 child needed MHT with households reporting that no child needed MHT. For not received MHT, the model compared households in which no children received needed MHT with households in which all or some children received MHT. For difficulty getting MHT, separate binary models compared difficult vs not difficult and not tried vs not difficult.

b

All models were adjusted for US Census region, respondent race and ethnicity, educational attainment, annual household income, marital status, household food sufficiency, financial difficulty, housing type, housing tenure, and household health insurance type. All measures were reported by an adult household respondent. Collinearity was assessed using variance inflation factors, with mean values below 2 indicating no serious multicollinearity.

c

Indicates aORs of 2.00 or greater or 0.50 or lower with P < .001.

d

Other race indicates any other race alone, or race in combination.

Discussion

In this national analysis of household-reported survey data, approximately 1 in 6 households with children reported pediatric MHT need, and nearly 60% of households reporting need perceived difficulty obtaining treatment. The strongest associations involved respondent race and ethnicity and household material hardship. Higher odds of nonreceipt among households with non-Hispanic Black and Asian respondents are consistent with documented racial and ethnic disparities in pediatric mental health care.6,7 These disparities may reflect multiple barriers, including differences in access, affordability, cultural responsiveness, and care-seeking experiences.

Households experiencing food insufficiency and financial hardship had substantially higher odds of unmet treatment need and access barriers. These findings highlight the importance of considering social and economic circumstances when designing strategies to improve pediatric mental health care access.8 Efforts to expand equitable care may require coordinated approaches addressing financial barriers, insurance coverage, culturally responsive services, and geographic variation in available resources.9,10

Because the HPS relies on adult household respondents and captures cross-sectional associations, these findings should be interpreted as household-reported patterns rather than individual-level clinical estimates or causal relationships. Nevertheless, the large national sample provides timely evidence of disparities in reported pediatric mental health treatment need and access barriers.

Supplement.

Data Sharing Statement

jamanetwopen-e2636988-s001.pdf (20.5KB, pdf)

References

  • 1.Youth Risk Behavior Survey: data summary and trends report 2009-2019. 2020. Accessed August 26, 2026. https://stacks.cdc.gov/view/cdc/115813
  • 2.Mental Health America . The state of mental health in America 2025. October 1, 2025. Accessed June 24, 2026. https://mhanational.org/the-state-of-mental-health-in-america/
  • 3.Whitney DG, Peterson MD. US national and state-level prevalence of mental health disorders and disparities of mental health care use in children. JAMA Pediatr. 2019;173(4):389-391. doi: 10.1001/jamapediatrics.2018.5399 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 4.Lee D, Dusetzina SB, Patrick SW, Graves JA, Fry CE. Adolescent treatment landscape of depression, suicidality, and substance use disorder in the US. JAMA Health Forum. 2025;6(8):e252647. doi: 10.1001/jamahealthforum.2025.2647 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 5.US Census Bureau . Household pulse survey: measuring emergent social and economic matters facing U.S. Households. Accessed June 24, 2026. https://www.census.gov/programs-surveys/household-pulse-survey.html
  • 6.Alegria M, Vallas M, Pumariega AJ. Racial and ethnic disparities in pediatric mental health. Child Adolesc Psychiatr Clin N Am. 2010;19(4):759-774. doi: 10.1016/j.chc.2010.07.001 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 7.Thomeer MB, Moody MD, Yahirun J. Racial and ethnic disparities in mental health and mental health care during the COVID-19 pandemic. J Racial Ethn Health Disparities. 2023;10(2):961-976. doi: 10.1007/s40615-022-01284-9 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 8.Verhoog S, Eijgermans DGM, Fang Y, Bramer WM, Raat H, Jansen W. Contextual determinants associated with children’s and adolescents’ mental health care utilization: a systematic review. Eur Child Adolesc Psychiatry. 2024;33(7):2051-2065. doi: 10.1007/s00787-022-02077-5 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 9.Grant KL, Simmons MB, Davey CG. Three nontraditional approaches to improving the capacity, accessibility, and quality of mental health services: an overview. Psychiatr Serv. 2018;69(5):508-516. doi: 10.1176/appi.ps.201700292 [DOI] [PubMed] [Google Scholar]
  • 10.Foster AA, Hoffmann JA, Douglas MD, et al. Comprehensiveness of state insurance laws and perceived access to pediatric mental health care. JAMA Netw Open. 2024;7(8):e2426402. doi: 10.1001/jamanetworkopen.2024.26402 [DOI] [PMC free article] [PubMed] [Google Scholar]

Associated Data

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

Supplementary Materials

Supplement.

Data Sharing Statement

jamanetwopen-e2636988-s001.pdf (20.5KB, pdf)

Articles from JAMA Network Open are provided here courtesy of American Medical Association

RESOURCES