Association of Childhood Area-Level Ethnic Density and Psychosis Risk Among Ethnoracial Minoritized Individuals in the US

Deidre M Anglin; Adriana Espinosa; Jean Addington; Kristin S Cadenhead; Tyrone D Cannon; Barbara A Cornblatt; Matcheri Keshavan; Daniel H Mathalon; Diana O Perkins; William Stone; Ming Tsuang; Scott W Woods; Elaine Walker; Carrie E Bearden; Benson S Ku

doi:10.1001/jamapsychiatry.2023.2841

. 2023 Aug 16;80(12):1226–1234. doi: 10.1001/jamapsychiatry.2023.2841

Association of Childhood Area-Level Ethnic Density and Psychosis Risk Among Ethnoracial Minoritized Individuals in the US

Deidre M Anglin ^1,^2,^✉, Adriana Espinosa ^1,², Jean Addington ³, Kristin S Cadenhead ⁴, Tyrone D Cannon ^5,⁶, Barbara A Cornblatt ^7,⁸, Matcheri Keshavan ⁹, Daniel H Mathalon ¹⁰, Diana O Perkins ¹¹, William Stone ⁹, Ming Tsuang ⁴, Scott W Woods ⁵, Elaine Walker ¹², Carrie E Bearden ^13,¹⁴, Benson S Ku ¹⁵

¹Department of Psychology, The City College of New York, City University of New York, New York

²The Graduate Center, City University of New York, New York

³Department of Psychiatry, Hotchkiss Brain Institute, University of Calgary, Calgary, Alberta, Canada

⁴Department of Psychiatry, University of California, San Diego

⁵Department of Psychiatry, Yale University, New Haven, Connecticut

⁶Department of Psychology, Yale University, New Haven, Connecticut

⁷Division of Psychiatry Research, The Zucker Hillside Hospital, Northwell Health, Glen Oaks, New York

⁸Department of Psychiatry, Donald and Barbara Zucker School of Medicine at Hofstra/Northwell, Hempstead, New York

⁹Department of Psychiatry, Harvard Medical School at Beth Israel Deaconess Medical Center, Boston, Massachusetts

¹⁰Department of Psychiatry, University of California, and San Francisco Veterans Affairs Medical Center, San Francisco

¹¹Department of Psychiatry, University of North Carolina, Chapel Hill

¹²Department of Psychology, Emory University, Atlanta, Georgia

¹³Department of Psychiatry and Biobehavioral Sciences, Semel Institute for Neuroscience and Human Behavior, UCLA, Los Angeles, California

¹⁴Department of Psychology, Semel Institute for Neuroscience and Human Behavior, UCLA, Los Angeles, California

¹⁵Department of Psychiatry and Behavioral Sciences, Emory University School of Medicine, Atlanta, Georgia

Accepted for Publication: June 13, 2023.

Published Online: August 16, 2023. doi:10.1001/jamapsychiatry.2023.2841

^✉

Corresponding Author: Deidre M. Anglin, PhD, Department of Psychology, The City College of New York, North Academic Center, Room 7/120, 160 Convent Ave, New York, NY 10031 (danglin@ccny.cuny.edu).

Author Contributions: Drs Anglin and Ku had full access to all of the data in the study and take responsibility for the integrity of the data and the accuracy of the data analysis.

Concept and design: Anglin, Espinosa, Cadenhead, Cannon, Perkins, Tsuang, Walker, Ku.

Acquisition, analysis, or interpretation of data: Anglin, Espinosa, Addington, Cadenhead, Cannon, Cornblatt, Keshavan, Mathalon, Perkins, Stone, Woods, Walker, Bearden, Ku.

Drafting of the manuscript: Anglin, Espinosa, Tsuang, Bearden, Ku.

Critical review of the manuscript for important intellectual content: Anglin, Espinosa, Addington, Cadenhead, Cannon, Cornblatt, Keshavan, Mathalon, Perkins, Stone, Woods, Walker, Bearden, Ku.

Statistical analysis: Anglin, Espinosa, Ku.

Obtained funding: Addington, Cadenhead, Cannon, Cornblatt, Mathalon, Perkins, Woods, Walker, Bearden, Ku.

Administrative, technical, or material support: Cadenhead, Cannon, Keshavan, Walker, Bearden, Ku.

Supervision: Walker, Bearden, Ku.

Conflict of Interest Disclosures: Dr Cannon has served as a consultant for Boehringer Ingelheim and Lundbeck A/S. Dr Mathalon reported personal fees from Neurocrine Biosciences outside the submitted work and has served as a consultant for Aptinyx, Boehringer Ingelheim, Cadent Therapeutics, and Greenwich Biosciences. Dr Perkins reported grants from the National Institute of Mental Health during the conduct of the study, has served as a consultant for Sunovion and Alkermes, has received research support from Boehringer Ingelheim, and has received royalties from American Psychiatric Association Publishing. Dr Woods reported grants from National Institute of Mental Health during the conduct of the study; personal fees from American Psychiatric Association and Medscape outside the submitted work; had a patent for US patent no. 8492418 B2 issued; has received investigator-initiated research support from Pfizer and sponsor-initiated research support from Auspex and Teva; served as a consultant for Biomedisyn (unpaid), Boehringer Ingelheim, and Merck; served as an unpaid consultant to DSM-5; and received royalties from Oxford University Press. Dr Bearden reported grants from National Institute of Mental Health during the conduct of the study and from National Institute of Health outside the submitted work. No other disclosures were reported.

Funding/Support: This work was supported in part by the National Institute of Mental Health (grants U01 MH081902 to Dr Cannon, P50 MH066286 to Dr Bearden, U01 MH081857 to Dr Cornblatt, U01 MH82022 to Dr Woods, U01 MH066134 to Dr Addington, U01 MH081944 to Dr Cadenhead, R01 U01 MH066069 to Dr Perkins, R01 MH076989 to Dr Mathalon, U01 MH081988 to Dr Walker, and K23 MH129684 to Dr Ku).

Role of the Funder/Sponsor: The funder 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.

^✉

Corresponding author.

PMCID: PMC10433142 PMID: 37585191

This cohort study examines the association between area-level ethnic density during childhood, perceived discrimination, and psychosis risk outcomes among ethnoracial minoritized individuals at clinical high risk for psychosis.

Key Points

Question

Is area-level ethnic density during childhood associated with clinical outcomes among ethnoracial minoritized individuals with clinical high risk for psychosis (CHR-P) syndrome in the US?

Findings

In this cohort study of 193 ethnoracial minoritized individuals with CHR-P syndrome, greater area-level minoritized ethnic density during childhood was associated with a higher likelihood of remission at 2-year follow-up compared with staying symptomatic and getting progressively worse. This association between ethnic density and the probability of remission was partly explained by lower lifetime exposure to discrimination in high minoritized ethnic density areas.

Meaning

The sociocultural environment during childhood may play a pivotal role in the development of clinical outcomes among minoritized youth at risk for psychosis.

Abstract

Importance

The protective ethnic density effect hypothesis, which suggests that minoritized individuals who grow up in neighborhoods with a high proportion of ethnoracial minoritized groups are protected from the effects of perceived discrimination, has not been examined among individuals at clinical high risk of psychosis (CHR-P). This level of examination may help identify intervention targets for preventing psychosis among high-risk individuals.

Objective

To examine the association between area-level ethnic density during childhood, perceived discrimination, and psychosis risk outcomes among ethnoracial minoritized individuals with CHR-P.

Design, Setting, and Participants

Data were collected as part of the North American Prodrome Longitudinal Study-2 (NAPLS 2) between November 2008 and March 2013. Participants included ethnoracial minoritized youth with CHR-P. Area-level ethnoracial minoritized density pertained to the percent of ethnoracial minoritized individuals within the participant’s county during childhood. Generalized mixed-effects models with random intercepts for participants, NAPLS 2 site, and county estimated the associations between area-level ethnic density and the risk of psychosis risk outcomes. Self-reported experience of discrimination was assessed. Mediation analyses computed the indirect association of perceived discrimination in the prospective correlation between ethnic density and psychosis risk outcomes. Analyses took place between December 2021 and June 2023.

Main Outcomes and Measures

Psychosis risk outcomes included remission, symptomatic, progression, and conversion to psychosis and were assessed throughout 24-month follow-up.

Results

Of 193 individuals, the mean (SD) age was 17.5 (3.4) years and 113 males (58.5%) were included. Participants self-identified as Asian (29 [15.0%]), Black (57 [29.0%]), Hispanic (any race; 87 [45.0%]), or other (First Nations, Middle Eastern, and interracial individuals; 20 [10.4%]). Greater area-level minoritized density was associated with a lower likelihood of remaining symptomatic (relative risk [RR], 0.54 [95% CI, 0.33-0.89]) and having progressively worsening symptoms (RR, 0.52 [95% CI, 0.32-0.86]) compared with being in remission. More perceived discrimination was associated with a higher risk of staying symptomatic (RR, 1.43 [95% CI, 1.09-1.88]) and progressively worsening (RR, 1.34 [95% CI, 1.02-1.78]) compared with being in remission. Perceived discrimination significantly mediated 21.7% (95% CI, 4.1%-67.0%; P = .02) of the association between area-level minoritized density and the likelihood of being in remission.

Conclusions and Relevance

This study found that among ethnoracial minority youth with CHR-P, growing up in communities with a greater proportion of ethnically minoritized individuals was associated with remission of psychosis risk symptoms partly through lower levels of perceived discrimination. Understanding how the social environment impacts early psychosis risk may help develop effective interventions to prevent psychosis, especially for vulnerable minoritized youth.

Introduction

Ethnoracial disparities in psychosis outcomes exist across the extended psychosis phenotype, from psychotic disorders¹ to less severe expressions of psychotic symptoms that may not meet clinical threshold, ie, psychotic experiences.^2,3 In the US, Black and Hispanic groups are overrepresented in the clinical patient population with schizophrenia^4,5,6 and are more likely than White ethnoracial groups to self-report psychotic experience.^2,7 These psychosis-related ethnoracial disparities are associated with inequitable physical and social environments, ie, social determinants of health largely driven by structural racism.^8,9

Vargas and colleagues¹⁰ describe how chronic stress in social environments that foster a sense of social exclusion, isolation, or lack of belonging can trigger biological mechanisms most associated with psychotic symptoms, eg, aberrant dopamine and glutamate transmission and chronic inflammation through the oxytocinergic system, which has been preliminarily demonstrated in neuroimaging and animal studies. One such indicator of potential social isolation is neighborhood ethnic density: the degree to which one’s ethnoracial group is represented in their neighborhood.¹¹ Studies have demonstrated that ethnoracial minoritized individuals living in neighborhoods with higher representation of a White majority (ie, low ethnic density) have higher rates of psychotic experiences and disorders than those living in neighborhoods with higher ethnic density.^12,13 This association holds even after accounting for area-level economic deprivation.^13,14 European epidemiologic studies¹⁵ provide empirical support for the protective ethnic density effect hypothesis, which indicates that ethnoracial minoritized individuals living in high ethnically dense neighborhoods are protected from the effects of racial discrimination by way of higher social support, community networks, and social cohesion.¹⁶

Yet, the degree to which the protective ethnic density effect can generalize to ethnoracial minoritized populations in the US remains unexplored, to our knowledge.¹⁷ The role of area-level risk factors for psychosis risk may be dependent on the sociopolitical context, for which the US has a unique sociopolitical racialized history.¹⁸ To our knowledge, no study in the US has examined the potentially protective effect of ethnic density across developmental stages of psychotic illness prospectively. The social environment within one’s neighborhood can provide social experiences including a sense of belonging, cohesion, and support,^19,20 which during childhood are integral for shaping one’s mental health in adulthood. In contrast, neighborhood social fragmentation during young school-aged years is a documented developmental risk factor for psychosis.²¹

The present study examines the degree to which ethnoracial minoritized area-level ethnic density during childhood in the North American Prodromal Longitudinal Study-2 (NAPLS 2) cohort is associated with the following psychosis risk outcomes among a clinical high-risk ethnoracial minoritized subsample: (1) remission, (2) staying symptomatic, (3) getting progressively worse, and (4) conversion to psychosis. We hypothesize that high area-level minoritized ethnic density in childhood (ie, high concentration of ethnoracial minoritized groups) is associated with a higher probability of remission compared with other psychosis risk outcomes, controlling for area-level socioeconomic status (SES) and degree of urbanicity/rurality. We also hypothesize that the association between area-level ethnoracial minoritized childhood ethnic density and psychosis risk outcomes is in part explained by differences in discrimination.

Methods

Participants

Data corresponded to baseline assessments from the NAPLS 2, the largest multisite, prospective cohort study of help-seeking participants at clinical high risk for psychosis (CHR-P). Participants were recruited from November 2008 to March 2013.²² The NAPLS 2 consortium of 8 programs includes 764 CHR-P help-seeking adolescents and young adults, 613 of which were followed up repeatedly during a 24-month period.²³ Participants were deemed to be at CHR-P if they met criteria for a psychosis risk syndrome based on the Structured Interview for Psychosis-Risk Syndromes²⁴ or if they were younger than 19 years and met criteria for schizotypal personality disorder.²⁵ Participants were excluded from the CHR-P designation if they already met criteria for a psychotic disorder or a central nervous system disorder, had IQ scores below 70, or had substance dependence over the past 6 months. The present study focused on participants with CHR-P who were followed up and identified with a non-White ethnoracial or Hispanic group (n = 299). Of the 299 participants, 80 had missing geocodable data, 37 of which were because they were from the Canada site, and another 26 were missing baseline individual-level sociodemographic data (eFigure in Supplement 1). Excluding these cases resulted in a final sample of 193.²⁶ eTable 2 in Supplement 1 lists site characteristics. The larger sample of 299 and final sample of 193 differed on age and ethnoracial group. The final sample had a smaller percentage of individuals in the other non-Hispanic group and specifically 22 years and older, and were on average younger at baseline (eTable 1 in Supplement 1). There were no significant differences in psychosis risk outcomes by site (χ² = 29.88; df = 21; P = .09). All participants provided written consent/assent. The study protocol and consent form were approved by the institutional review boards at all 8 sites, and all procedures comply with the ethical standards of the relevant committees.

Baseline Measures

The Structured Interview for Psychosis-Risk Syndromes was administered at baseline to rate symptom severity along positive, negative, and disorganization symptom dimensions.²⁴ Individual items were summed to produce a total score for each dimension. Assessments were performed by trained personnel, with high interrater reliability.^25,27

Information regarding race and ethnicity were collected via self-report and during baseline clinical interview procedures. Respondents selected their racial identification among several options, including Black, Central/South American, East Asian, First Nations, Native Hawaiian or Pacific Islander, South Asian, Southeast Asian, West/Central Asian and Middle East, White, and interracial. A second question assessed Hispanic ethnicity (yes/no). Herein, we consolidated racial identification and Hispanic ethnicity into the following categories: non-Hispanic Asian, non-Hispanic Black, non-White Hispanic, White Hispanic, and non-Hispanic other (includes First Nations, Middle Eastern, and interracial individuals). The majority of the non-White Hispanic group identified racially as interracial (30 [54%]) or Central/South American (17 [30%]). Other sociodemographic variables included age and sex assigned at birth.

Area-Level Variables

Respondents indicated the city or town in which they spent the most time during childhood. This information was transformed into county-level codes according to the 1990 and 2000 US Decennial Censuses.²⁸ Cities/towns where individuals lived for the longest time during childhood, along with states, were linked to the primary county 5-digit Federal Information Processing Standards codes.²⁹ Then, 1990 and 2000 county-level characteristics were linked to these Federal Information Processing Standards codes for those born between 1985 and 1994 and between 1995 and 2000, respectively. Census records from these 2 time periods captured the area (county) characteristics during childhood.

Area-level ethnoracial minoritized childhood ethnic density corresponded to the percent of all minoritized racial groups (ie, other than non-Hispanic White) among all individuals in a county. Area-level SES corresponded to the Z score average of the following percentages: residents living above the poverty level and residents who completed high school or obtained GED or above. This method is consistent with previous studies.^30,31 Higher values correspond to higher area-level SES.

Area-level Rural-Urban Continuum Codes (RUCCs) captured degree of rurality/urbanicity and population density in a county by distinguishing metropolitan counties by population size and nonmetropolitan counties by degree of urbanicity/rurality and adjacency to a metropolitan area.³² It was coded from 1 (completely metropolitan with high population density) to 9 (completely rural with low population density). Higher values correspond with higher degrees of rurality and lower degrees of population density.

Perceived Discrimination

At baseline, participants completed a modified self-report measure used in previous studies on discrimination and psychosis³³ reporting if they had experienced discrimination over their lifetime due to skin color, ethnicity, gender, age, appearance, disability, sexual orientation, religion, and other. Participants could check up to all 9 of the reasons that were summed into a total count of the types of discrimination experienced over the lifetime.

Clinical Outcome at Follow-Up

Participants with CHR-P were followed up for up to 2 years to determine illness progression based on Current Clinical State criteria of the Structured Interview for Psychosis-Risk Syndromes.³⁴ Generalized mixed-effects models with random effects for each participant estimated the relative risk of the clinical outcome. The random effects reduce attrition-related bias because they use any participant data available at each follow-up without relying on imputation.³⁵ This approach yielded findings using 590 follow-up observations from 193 participants. The resulting clinical outcomes were (1) remission (no longer meeting Scale of Psychosis-Risk Symptoms clinical high-risk criteria, ie, scored below the prodromal risk threshold on each of the positive symptom subscale items on the Scale of Psychosis-Risk Symptoms), (2) symptomatic (continues to exhibit psychosis risk symptoms, but not meeting clinical high risk syndrome criteria), (3) psychosis risk progression (continues to meet clinical high-risk syndrome criteria), or (4) psychotic (converted to psychosis). Participants’ scores could go up, down, or stay the same across follow-up time points (eg, go from remission to symptomatic and vice versa).

Data Analysis

Depending on the measurement of the variables, Pearson correlation coefficients, Cramér V, and point biserial correlations are presented as effect sizes for the associations between area-level ethnoracial minoritized childhood ethnic density, area-level own group ethnic density, perceived discrimination, and psychosis risk outcomes. Generalized mixed-effects models estimated the associations between area-level ethnic density and the risk of psychosis risk outcomes, holding constant age, sex, area-level SES, RUCC, and ethnoracial group (ie, Asian, non-Hispanic Black, non-White Hispanic, White Hispanic, and other). The models included random intercepts for participants, site, and county to address potential biases due to attrition and correlated errors within site and county. The discrimination score distribution was right skewed, so to avoid heteroskedasticity, scores of 7 to 9 were rescored to 6, compressing the scale 0 to 6.³⁶ We used SPSS statistical software version 24 (SPSS Inc) and R version 4.4.2 (R Foundation) to conduct the analyses. We estimated the indirect association of perceived discrimination in the prospective correlation between area-level childhood ethnic density and psychosis risk outcomes using the R package mediation.³⁷ The package estimates 2 separate models, one in which the mediator is regressed on the predictor and the covariates and the second, in which the outcome is regressed on mediator, predictor, and the covariates. The indirect association (ie, average causal mediation association) is then estimated using a general procedure based on Monte Carlo simulations, which produces 95% CIs. All data were standardized prior to running the analyses. Two-sided P values were statistically significant at .05. Analysis took place between December 2021 and June 2023.

Results

Descriptive Statistics

Table 1 presents participant sociodemographic information. Over half of the sample was either non-Hispanic Black or non-White Hispanic, male, and adolescents 17 years and younger. The mean (SD) count of types of perceived discriminatory experiences was 2.9 (2.3) with 54.9% (n = 106) of the sample reporting discrimination because of skin color or ethnicity and 76.7% (n = 148) skin color, ethnicity, or appearance. Mean discrimination scores varied between ethnoracial groups (F_4,192 = 2.51; P = .04), whereby Black individuals (mean [SD], 3.6 [2.3]) reported significantly higher mean perceived discrimination than White Hispanic individuals (mean [SD], 2.2 [2.3]). For area-level SES variables, the sample predominantly grew up in resourced counties; a mean (SD) of 12.0% (4.8%) lived below poverty level and 25.2% (4.6%) had a high school diploma or GED or above. The mean (SD) percent ethnic minoritized density was 39.1 (19.0). Over the course of the 2-year follow-up, approximately 18% (n = 34) of the sample converted, 25% (n = 48) progressed but did not convert, 30% (n = 57) remained symptomatic but did not progress, and 28% (n = 54) went into remission.

Table 1. Sociodemographic Characteristics (N = 193).

Characteristic	No. (%)
Age at baseline, y
12.0-17.0	105 (54.4)
17.1-22.0	69 (35.8)
22.1-27.0	19 (9.8)
Sex
Male	113 (58.5)
Female	80 (41.5)
Race and ethnicity
Asian non-Hispanic	29 (15.0)
Black non-Hispanic	57 (29.5)
Non-White Hispanic	56 (29.0)
White Hispanic	31 (16.1)
Other non-Hispanic^a	20 (10.4)
Psychosis risk outcomes
Remission	54 (28.0)
Symptomatic	57 (29.5)
Progression	48 (24.9)
Conversion	34 (17.6)
Percentage of individuals living below poverty level in area level, mean (SD) [range]	12.0 (4.8) [3.7-28.7]
Percentage of individuals with high school diploma or GED or above in area level, mean (SD) [range]	25.2 (4.6) [15.9-35.8]
Percentage of area-level minority individuals, mean (SD) [range]	39.1 (19.0) [1.9-77.1]
Area-level Rural-Urban Continuum Code, mean (SD) [range]	1.39 (0.93) [1-8]
Perceived discrimination, mean (SD) [range]	2.87 (2.34) [0-9]

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^{^a}

Other non-Hispanic includes First Nations, Middle Eastern, and interracial individuals.

Bivariate Correlations

As shown in Table 2, age, sex, specific ethnoracial group, area-level SES, and RUCC were not significantly associated with psychosis risk outcomes. Area-level SES was significantly negatively associated with area-level minoritized childhood ethnic density such that more ethnoracial minoritized individuals represented in a county was associated with lower area-level SES (eg, higher poverty, less education). Area-level minoritized childhood ethnic density was significantly higher among those who were in remission at 2-year follow-up compared with those in any of the other 3 psychosis risk outcomes combined and was significantly negatively associated with perceived discrimination and RUCC. Higher ethnic density was associated with less perceived discrimination and less degrees of rurality/more population density.

Table 2. Correlations Between Sociodemographic Characteristics, Perceived Discrimination, and Psychosis Risk Outcomes^a.

Characteristic	Age	Female	White Hispanic	Non-White Hispanic	Non-Hispanic			Area-level SES	Area-level minoritized childhood ethnic density	RUCC	Perceived discrimination	Remission vs other outcomes	Symptomatic vs other outcomes	Progression vs other outcomes
Characteristic	Age	Female	White Hispanic	Non-White Hispanic	Black	Asian	Other^b	Area-level SES	Area-level minoritized childhood ethnic density	RUCC	Perceived discrimination	Remission vs other outcomes	Symptomatic vs other outcomes	Progression vs other outcomes
Female	−0.079
White Hispanic	−0.094	−0.053
Non-White Hispanic	−0.087	−0.005	−0.280^c
Black non-Hispanic	0.098	0.078	−0.283^c	−0.414^c
Asian non-Hispanic	0.106	−0.059	−0.184^d	−0.269^c	−0.272^c
Other non-Hispanic^b	−0.029	0.024	−0.149^d	−0.217^c	−0.220^c	−0.143^d
Area-level SES	0.068	−0.040	−0.071	−0.053	0.090	0.061	−0.041
Area-level minoritized childhood ethnic density	−0.247^c	0.071	0.13	0.021	−0.092	−0.01	−0.039	−0.738^c
RUCC	0.157^d	0.010	−0.107	−0.059	0.219^c	−0.051	−0.051	0.132	−0.343^c
Perceived discrimination	0.337^c	0.162^d	−0.132	−0.012	0.203^c	−0.044	−0.075	0.056	−0.213^c	0.166^d
Remission vs other outcomes	−0.124	0.038	−0.053	0.136	−0.024	−0.068	−0.023	−0.117	0.212^c	0.038	−0.177^d
Symptomatic vs other outcomes	−0.011	0.101	−0.005	−0.064	0.104	0.014	−0.071	0.045	−0.066	−0.026	0.150^d	−0.404^c
Progression vs other outcomes	0.095	−0.119	0.107	−0.024	−0.083	−0.007	0.04	−0.004	−0.061	−0.086	−0.034	−0.359^c	−0.372^c
Converter vs other outcomes	0.051	−0.03	−0.054	−0.056	−0.001	0.072	0.066	0.089	−0.102	0.085	0.068	−0.288^c	−0.299^c	−0.266^c

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Abbreviations: RUCC, Rural-Urban Continuum Code; SES, socioeconomic status.

^{^a}

Pearson correlations identify associations between continuous variables. Cramér V identifies associations between categorical variables (eg, sex, race and ethnicity, and prodromal outcomes). Point-biserial correlations present associations between continuous and binary variables.

^{^b}

Other non-Hispanic includes First Nations, Middle Eastern, and interracial individuals.

^{^c}

P < .01 (2-tailed).

^{^d}

P < .05.

Generalized Mixed-Effects Model

Results from the generalized mixed-effects model appear in Table 3. Holding constant age, sex, ethnoracial group, area-level SES, and RUCC, a higher degree of area-level minoritized childhood ethnic density significantly associated with a higher likelihood of being in remission at 2-year follow-up compared with progression or staying symptomatic. Area-level minoritized childhood ethnic density was not associated with the likelihood of conversion vs progression or staying symptomatic or progression vs staying symptomatic. The pattern of results from generalized mixed-effects models analyzing psychosis risk outcomes on an ordinal scale was similar, such that higher area-level minoritized childhood ethnic density was associated with lower severity in psychosis outcomes (eTable 3 in Supplement 1).

Table 3. Adjusted Generalized Mixed-Effects Model With Random Intercepts for Participants, Site, and County Identifying the RR of Psychosis Risk Outcomes vs Remission^a.

Parameter	Symptomatic		Progression		Conversion
Parameter	RR (95% CI)	P value	RR (95% CI)	P value	RR (95% CI)	P value
Age	0.33 (0.01-8.23)	.50	0.43 (0.01-14.69)	.64	0.02 (0.00-0.53)^b	.02
Female	1.24 (0.67-2.30)	.49	0.80 (0.43-1.50)	.49	0.77 (0.29-2.00)	.59
Asian non-Hispanic	0.89 (0.32-2.52)	.83	0.85 (0.32-2.26)	.75	1.66 (0.41-6.83)	.48
Non-White Hispanic	0.44 (0.20-1.00)	.051	0.52 (0.23-1.17)	.11	0.56 (0.17-1.87)	.34
White Hispanic	0.82 (0.31-2.14)	.68	0.93 (0.33-2.64)	.90	0.85 (0.18-3.94)	.83
Other non-Hispanic^c	0.39 (0.12-1.21)	.10	0.58 (0.17-2.03)	.40	0.97 (0.19-4.84)	.97
RUCC	0.77 (0.60-0.99)^b	.04^b	0.60 (0.41-0.88)^b	.009^b	1.06 (0.63-1.79)	.82
Area-level childhood SES	0.82 (0.46-1.44)	.48	0.71 (0.38-1.33)	.29	0.87 (0.35-2.20)	.77
Area-level minoritized childhood ethnic density	0.54 (0.33-0.89)^b	.02^b	0.52 (0.32-0.86)^b	.01^b	0.61 (0.30-1.24)	.17

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Abbreviations: RUCC, Rural-Urban Continuum Code; RR, relative risk; SES, socioeconomic status.

^{^a}

All the continuous variables in the model including percent ethnic minority density are standardized. A generalized mixed-effects model with random intercepts for participants was used to handle missing clinical outcome data due to attrition during the 2-year follow-up. Models also cluster standard errors by site and county. Non-Hispanic Black was the reference group for ethnoracial group. Remission was the reference outcome.

^{^b}

Significant coefficients (P < .05) are indicated.

^{^c}

Other non-Hispanic includes First Nations, Middle Eastern, and interracial individuals.

Analyses of Perceived Discrimination

The generalized mixed-effects model indicated that perceived discrimination was significantly associated with a higher risk of being symptomatic and progressing compared to being in remission (Table 4). The Figure depicts results from the mediation analyses with remission (1) vs all other psychosis risk outcomes combined (0) as the outcome variable. As shown, there was an indirect association via perceived discrimination in the association between area-level minoritized childhood ethnic density and remission of psychosis risk symptoms during follow-up. Higher area-level minoritized childhood ethnic density was associated with lower perceived discrimination, which in turn was associated with a higher likelihood of being in remission. The indirect association via perceived discrimination captured 21.7% (95% CI, 4.1%-67.0%; P = .02) of the total association.

Table 4. Adjusted Generalized Mixed-Effects Model With Random Intercepts for Participants, Site, and County of Area-Level Ethnoracial Minoritized Density During Childhood With the Addition of Perceived Discrimination Predicting Psychosis Risk Outcomes vs Remission^a.

Parameter	Symptomatic		Progression		Conversion
Parameter	RR (95% CI)	P value	RR (95% CI)	P value	RR (95% CI)	P value
Perceived discrimination	1.43 (1.09-1.88)^b	.01^b	1.34 (1.02-1.78)	.04^b	1.49 (0.87-2.54)	.15
Area-level minoritized childhood ethnic density	0.72 (0.56-0.92)^b	.01^b	0.77 (0.60-1.00)	.050	0.69 (0.40-1.17)	.17

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Abbreviation: RR, relative risk.

^{^a}

All the continuous variables in the model are standardized. A generalized mixed-effects model with random intercepts for participants was used to handle missing clinical outcome data due to attrition during the 2-year follow-up. Models also cluster standard errors by site and county. Remission was the reference outcome.

^{^b}

Significant coefficients (P < .05) are indicated.

Figure. — All paths adjusted for age at visit, female sex, ethnoracial group, Rural-Urban Continuum Code, and area-level socioeconomic status. Random intercept only included unique participants since the mediation package in R version 4.4.2 (R Foundation) does not support more than 2 levels per model.

Discussion

To our knowledge, this is the first US-based study to examine the association between area-level childhood ethnic density and developmental psychosis outcomes using objective census-based data while controlling for indicators of area-level deprivation and urbanicity/rurality and population density and to examine the mediating role of perceived discrimination in said association. Consistent with some European studies,^12,38 we found a connection between high minoritized area-level ethnic density and decreased risk across the extended psychosis phenotype. Among ethnoracial minoritized individuals with CHR-P, growing up in a county with a high proportion of ethnoracial minoritized individuals was associated with a higher likelihood of going into remission compared with staying symptomatic and getting progressively worse. These prospective relations remained significant after controlling for individual-level factors, including ethnoracial group, age, and sex, and area-level SES and rurality/population density. Specifically, our findings indicate that although counties with a higher proportion of ethnoracial minoritized individuals had lower resources and were more population dense, growing up in such counties was associated with lower psychosis risk severity over time among those with CHR-P. These findings have implications for prevention and early intervention, as area-level ethnic density in childhood was salient for understanding the risk of remission compared with other psychosis outcomes rather than highlighting differences in the degree to which someone at CHR-P is at risk of progressing or converting to psychosis.

Our results also indicated that lower lifetime exposure to experiences of discrimination in areas with higher minoritized individuals is a mechanism that can explain some of the lower risk of staying symptomatic, progressing, or converting to psychosis vs going into remission among ethnoracial minoritized individuals with CHR-P. These findings are consistent with studies conducted globally (eg, Northern Europe, US, Canada), which demonstrate that racial discrimination is positively associated with psychosis across the extended phenotype.^39,40,41,42 Discrimination increases cumulative stress⁴³ and can increase social exclusion, which could be worse when more culturally isolated in your environment—isolation purported to be linked with brain mechanisms connected to psychosis.^10,44,45 Neighborhoods with high ethnoracial diversity have the capacity to attenuate the stress and isolation associated with discrimination by fostering an inclusive atmosphere that discourages discrimination while also providing more opportunities to process everyday discriminatory experiences and more subtle microaggressions, which are associated with psychotic experiences in minoritized young people.⁴⁶ In addition, high ethnoracial diversity in schools may provide ethnically minoritized children and adolescents more tools to cope with subsequent discriminatory experiences, which could improve mental well-being.

In general, these findings support social determinant models of psychosis risk^8,44 that postulate social factors at the neighborhood level promote risk for psychosis among ethnoracial minoritized individuals directly and through intervening mechanisms at the individual level.⁸ These findings expand on these existing models by emphasizing the importance of the developmental timing of social environmental exposures on psychosis outcomes and risk.

Our findings regarding the association between ethnic density and psychosis are consistent with a previous US-based urban study that found a connection between perceived ethnic density growing up before age 12 years and psychosis-like experiences in young adulthood.⁴⁷ Unlike that study, the present study included help-seeking individuals across a broader area of the US including nonurban and more rural counties, factors that Oh and colleagues⁴⁸ found are relevant for psychotic experience risk especially among Black individuals in the US. Future work should examine the degree of protection that own-ethnic group density confers for psychosis in the US racialized context, as it may vary for different ethnoracial groups; this variability has been demonstrated in European contexts.⁴⁹

Limitations

Despite its novel contributions, the present study has several limitations. First, county-level geographic coding misses important neighborhood dynamics at the census tract block level that may provide additional insight into the results. In particular, our findings suggest the need to explore additional factors within higher minoritized areas that can explain why in spite of having lower SES, participants from these areas had on average a higher likelihood of remission, especially in light of how much more variance is still left unexplained (78%) after accounting for discrimination. Second, we do not know the residential history of participants and whether exposure of living conditions at other developmental time periods may differ in their impact on psychosis risk outcomes. Likewise, lifetime discrimination could have happened before, during, or after one’s childhood neighborhood experience, which precludes us from establishing directionality and causality in the mediation model. Finally, some associations estimated might have been underpowered to detect small associations such as examine specific interactions by ethnoracial group, and the sample was not representative of more lower-SES area counties. Future studies should replicate these analyses by using census tract-level exposures during childhood as well as larger and more diverse samples, especially measuring more precise factors relevant to mental health for Hispanic individuals such as age at immigration, nativity and generation status, and country of origin.⁵⁰

Conclusions

In conclusion, our findings suggest that area-level ethnic minority density during childhood is important for understanding remission of psychosis risk symptoms. In addition, our findings highlight perceived discrimination as a factor that can explain some of the association between ethnic density and remission among ethnoracial minoritized individuals with CHR-P. Our results may have clinical implications for prevention of schizophrenia, whereby strategies to reduce discrimination in less ethnically dense areas can be an effective early intervention strategy among minority at-risk youth.

Supplement 1.

eTable 1. Comparison of characteristics for ethnoracial minoritized CHR-P follow-up sample (N=299) and final ethnoracial minoritized sample (N=193)

eTable 2. Comparison of demographic and area-level characteristics in final sample by site

eTable 3. Adjusted generalized mixed effects model with random intercepts for participants, site, and county identifying the relative risk of psychosis risk severity for area-level minoritized group ethnic density during childhood (N = 193)

eFigure. Missing data Flowchart

Click here for additional data file.^{(98.7KB, pdf)}

Supplement 2.

Data sharing statement.

Click here for additional data file.^{(13.9KB, pdf)}

References

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Associated Data

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

Supplementary Materials

Supplement 1.

eTable 1. Comparison of characteristics for ethnoracial minoritized CHR-P follow-up sample (N=299) and final ethnoracial minoritized sample (N=193)

eTable 2. Comparison of demographic and area-level characteristics in final sample by site

eFigure. Missing data Flowchart

Click here for additional data file.^{(98.7KB, pdf)}

Supplement 2.

Data sharing statement.

Click here for additional data file.^{(13.9KB, pdf)}

[yoi230063r1] 1.Olbert CM, Nagendra A, Buck B. Meta-analysis of Black vs. White racial disparity in schizophrenia diagnosis in the United States: Do structured assessments attenuate racial disparities? J Abnorm Psychol. 2018;127(1):104-115. doi: 10.1037/abn0000309 [DOI] [PubMed] [Google Scholar]

[yoi230063r2] 2.Cohen CI, Marino L. Racial and ethnic differences in the prevalence of psychotic symptoms in the general population. Psychiatr Serv. 2013;64(11):1103-1109. doi: 10.1176/appi.ps.201200348 [DOI] [PubMed] [Google Scholar]

[yoi230063r3] 3.Olfson M, Lewis-Fernández R, Weissman MM, et al. Psychotic symptoms in an urban general medicine practice. Am J Psychiatry. 2002;159(8):1412-1419. doi: 10.1176/appi.ajp.159.8.1412 [DOI] [PubMed] [Google Scholar]

[yoi230063r4] 4.Barnes A. Race, schizophrenia, and admission to state psychiatric hospitals. Adm Policy Ment Health. 2004;31(3):241-252. doi: 10.1023/B:APIH.0000018832.73673.54 [DOI] [PubMed] [Google Scholar]

[yoi230063r5] 5.Barr PB, Bigdeli TB, Meyers JL. Prevalence, comorbidity, and sociodemographic correlates of psychiatric disorders reported in the All of Us research program. JAMA Psychiatry. 2022;79(6):622-628. doi: 10.1001/jamapsychiatry.2022.0685 [DOI] [PMC free article] [PubMed] [Google Scholar]

[yoi230063r6] 6.Schwartz RC, Blankenship DM. Racial disparities in psychotic disorder diagnosis: a review of empirical literature. World J Psychiatry. 2014;4(4):133-140. doi: 10.5498/wjp.v4.i4.133 [DOI] [PMC free article] [PubMed] [Google Scholar]

[yoi230063r7] 7.DeVylder J, Anglin D, Munson MR, et al. Ethnoracial variation in risk for psychotic experiences. Schizophr Bull. 2023;49(2):385-396. [DOI] [PMC free article] [PubMed] [Google Scholar]

[yoi230063r8] 8.Anglin DM, Ereshefsky S, Klaunig MJ, et al. From womb to neighborhood: a racial analysis of social determinants of psychosis in the United States. Am J Psychiatry. 2021;178(7):599-610. doi: 10.1176/appi.ajp.2020.20071091 [DOI] [PMC free article] [PubMed] [Google Scholar]

[yoi230063r9] 9.Bailey ZD, Krieger N, Agénor M, Graves J, Linos N, Bassett MT. Structural racism and health inequities in the USA: evidence and interventions. Lancet. 2017;389(10077):1453-1463. doi: 10.1016/S0140-6736(17)30569-X [DOI] [PubMed] [Google Scholar]

[yoi230063r10] 10.Vargas T, Conley RE, Mittal VA. Chronic stress, structural exposures and neurobiological mechanisms: a stimulation, discrepancy and deprivation model of psychosis. Int Rev Neurobiol. 2020;152:41-69. doi: 10.1016/bs.irn.2019.11.004 [DOI] [PMC free article] [PubMed] [Google Scholar]

[yoi230063r11] 11.Faris REL, Dunham HW. Mental Disorders in Urban Areas: An Ecological Study of Schizophrenia and Other Psychoses. University of Chicago Press; 1939. [Google Scholar]

[yoi230063r12] 12.Kirkbride JB, Morgan C, Fearon P, Dazzan P, Murray RM, Jones PB. Neighbourhood-level effects on psychoses: re-examining the role of context. Psychol Med. 2007;37(10):1413-1425. doi: 10.1017/S0033291707000499 [DOI] [PubMed] [Google Scholar]

[yoi230063r13] 13.Veling W, Susser E, van Os J, Mackenbach JP, Selten JP, Hoek HW. Ethnic density of neighborhoods and incidence of psychotic disorders among immigrants. Am J Psychiatry. 2008;165(1):66-73. doi: 10.1176/appi.ajp.2007.07030423 [DOI] [PubMed] [Google Scholar]

[yoi230063r14] 14.Boydell J, van Os J, McKenzie K, et al. Incidence of schizophrenia in ethnic minorities in London: ecological study into interactions with environment. BMJ. 2001;323(7325):1336-1338. doi: 10.1136/bmj.323.7325.1336 [DOI] [PMC free article] [PubMed] [Google Scholar]

[yoi230063r15] 15.Baker SJ, Jackson M, Jongsma H, Saville CWN. The ethnic density effect in psychosis: a systematic review and multilevel meta-analysis. Br J Psychiatry. 2021;219(6):632-643. doi: 10.1192/bjp.2021.96 [DOI] [PMC free article] [PubMed] [Google Scholar]

[yoi230063r16] 16.Bécares L, Nazroo J, Stafford M. The buffering effects of ethnic density on experienced racism and health. Health Place. 2009;15(3):670-678. doi: 10.1016/j.healthplace.2008.10.008 [DOI] [PubMed] [Google Scholar]

[yoi230063r17] 17.Anglin DM. Advancing the study of local ethnic density and psychosis. Lancet Psychiatry. 2020;7(4):293-294. doi: 10.1016/S2215-0366(20)30101-2 [DOI] [PubMed] [Google Scholar]

[yoi230063r18] 18.Robinson C. Black Marxism: The Making of the Black Radical Tradition. University of North Carolina Press; 1983. [Google Scholar]

[yoi230063r19] 19.Zammit S, Lewis G, Rasbash J, Dalman C, Gustafsson JE, Allebeck P. Individuals, schools, and neighborhood: a multilevel longitudinal study of variation in incidence of psychotic disorders. Arch Gen Psychiatry. 2010;67(9):914-922. doi: 10.1001/archgenpsychiatry.2010.101 [DOI] [PubMed] [Google Scholar]

[yoi230063r20] 20.Morgan P. Towards a developmental theory of place attachment. J Environ Psychol. 2010;30:11-22. doi: 10.1016/j.jenvp.2009.07.001 [DOI] [Google Scholar]

[yoi230063r21] 21.Mason SM, Kaufman JS, Daniels JL, Emch ME, Hogan VK, Savitz DA. Neighborhood ethnic density and preterm birth across seven ethnic groups in New York City. Health Place. 2011;17(1):280-288. doi: 10.1016/j.healthplace.2010.11.006 [DOI] [PMC free article] [PubMed] [Google Scholar]

[yoi230063r22] 22.Addington J, Cadenhead KS, Cornblatt BA, et al. North American Prodrome Longitudinal Study (NAPLS 2): overview and recruitment. Schizophr Res. 2012;142(1-3):77-82. doi: 10.1016/j.schres.2012.09.012 [DOI] [PMC free article] [PubMed] [Google Scholar]

[yoi230063r23] 23.Kline ER, Seidman LJ, Cornblatt BA, et al. Depression and clinical high-risk states: baseline presentation of depressed vs. non-depressed participants in the NAPLS-2 cohort. Schizophr Res. 2018;192:357-363. doi: 10.1016/j.schres.2017.05.032 [DOI] [PMC free article] [PubMed] [Google Scholar]

[yoi230063r24] 24.Miller TJ, McGlashan TH, Rosen JL, et al. Prodromal assessment with the structured interview for prodromal syndromes and the scale of prodromal symptoms: predictive validity, interrater reliability, and training to reliability. Schizophr Bull. 2003;29(4):703-715. doi: 10.1093/oxfordjournals.schbul.a007040 [DOI] [PubMed] [Google Scholar]

[yoi230063r25] 25.Addington J, Liu L, Buchy L, et al. North American Prodrome Longitudinal Study (NAPLS 2): the prodromal symptoms. J Nerv Ment Dis. 2015;203(5):328-335. doi: 10.1097/NMD.0000000000000290 [DOI] [PMC free article] [PubMed] [Google Scholar]

[yoi230063r26] 26.Ku BS, Addington J, Bearden CE, et al. Association between residential instability at individual and area levels and future psychosis in adolescents at clinical high risk from the North American Prodrome Longitudinal Study (NAPLS) consortium. Schizophr Res. 2021;238:137-144. doi: 10.1016/j.schres.2021.09.025 [DOI] [PMC free article] [PubMed] [Google Scholar]

[yoi230063r27] 27.Woods SW, Walsh BC, Powers AR III, McGlashan TH. Reliability, validity, epidemiology, and cultural variation of the Structured Interview for Psychosis-Risk Syndromes (SIPS) and the Scale of Psychosis-Risk Symptoms (SOPS). In: Li H, Shapiro DI, Seidman LJ, eds. Handbook of Attenuated Psychosis Syndrome Across Cultures. Springer; 2019;85-113. [Google Scholar]

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PERMALINK

Association of Childhood Area-Level Ethnic Density and Psychosis Risk Among Ethnoracial Minoritized Individuals in the US

Deidre M Anglin, PhD

Adriana Espinosa, PhD

Jean Addington, PhD

Kristin S Cadenhead, MD

Tyrone D Cannon, PhD

Barbara A Cornblatt, PhD, MBA

Matcheri Keshavan, MD

Daniel H Mathalon, MD, PhD

Diana O Perkins, MD

William Stone, PhD

Ming Tsuang, MD

Scott W Woods, MD

Elaine Walker, PhD

Carrie E Bearden, PhD

Benson S Ku, MD

Key Points

Question

Findings

Meaning

Abstract

Importance

Objective

Design, Setting, and Participants

Main Outcomes and Measures

Results

Conclusions and Relevance

Introduction

Methods

Participants

Baseline Measures

Area-Level Variables

Perceived Discrimination

Clinical Outcome at Follow-Up

Data Analysis

Results

Descriptive Statistics

Table 1. Sociodemographic Characteristics (N = 193).

Bivariate Correlations

Table 2. Correlations Between Sociodemographic Characteristics, Perceived Discrimination, and Psychosis Risk Outcomesa.

Generalized Mixed-Effects Model

Table 3. Adjusted Generalized Mixed-Effects Model With Random Intercepts for Participants, Site, and County Identifying the RR of Psychosis Risk Outcomes vs Remissiona.

Analyses of Perceived Discrimination

Table 4. Adjusted Generalized Mixed-Effects Model With Random Intercepts for Participants, Site, and County of Area-Level Ethnoracial Minoritized Density During Childhood With the Addition of Perceived Discrimination Predicting Psychosis Risk Outcomes vs Remissiona.

Figure. Perceived Discrimination as a Mediator of the Association Between Area-Level Ethnic Minority Density During Childhood and Remission of Psychosis Risk Symptoms at Follow-Up.

Discussion

Limitations

Conclusions

References

Associated Data

Supplementary Materials

ACTIONS

PERMALINK

RESOURCES

Similar articles

Cited by other articles

Links to NCBI Databases

Table 2. Correlations Between Sociodemographic Characteristics, Perceived Discrimination, and Psychosis Risk Outcomes^a.

Table 3. Adjusted Generalized Mixed-Effects Model With Random Intercepts for Participants, Site, and County Identifying the RR of Psychosis Risk Outcomes vs Remission^a.

Table 4. Adjusted Generalized Mixed-Effects Model With Random Intercepts for Participants, Site, and County of Area-Level Ethnoracial Minoritized Density During Childhood With the Addition of Perceived Discrimination Predicting Psychosis Risk Outcomes vs Remission^a.