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Disparities in Referral and Diagnosis in NYC Jail Mental Health Service, AJPH, 2015

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RESEARCH AND PRACTICE

Disparities in Mental Health Referral and Diagnosis in the
New York City Jail Mental Health Service
Fatos Kaba, MA, Angela Solimo, MA, Jasmine Graves, MPH, Sarah Glowa-Kollisch, MPH, Allison Vise, BA, Ross MacDonald, MD, Anthony Waters, PsyD,
Zachary Rosner, MD, Nathaniel Dickey, MA, MPH, Sonia Angell, MD, MPH, and Homer Venters, MD, MS

The care of persons with mental illness in the
United States is inextricably linked to the
criminal justice system. Approximately 12
million people pass through a jail or prison
annually, with the majority cycling through
local jails.1 Approximately one third of these
persons have an identified mental illness diagnosed before or during incarceration. Treatment and discharge planning for this population represent considerable challenges. In some
small jails, a single mental health professional
may only be available for several hours a week,
whereas in larger jails more comprehensive
services may be available.
Research shows that significant health disparities exist for incarcerated persons of color,
including the occurrence of infection, violence,
and mortality.2---5 The distribution of psychiatric morbidity and mortality by race in correctional settings is complex, with studies showing
higher rates of major affective and depressive
disorder diagnoses and suicide among White
patients and higher rates of schizophrenia and
nonschizophrenic psychotic disorder diagnoses
among African American patients.6---10 Similar
disparities exist in the community settings
where these patients originate and for most,
to which they will return.11
In the New York City jail system, the Bureau
of Correctional Health Services of the New
York City Department of Health and Mental
Hygiene is responsible for all aspects of medical
and mental health care and the New York
City Department of Correction is responsible
for security and custody management. The
New York City jail system is the nation’s second
largest, with 70 000 annual admissions and
11 000 persons incarcerated at any given time,
with a median length of incarceration of 9 days.
Unlike most jail settings, which use relatively
cursory intake health screenings, every
person who enters the New York City jail
system undergoes a comprehensive 4- to 6-hour
intake history taking, physical examination, and

Objectives. To better understand jail mental health services entry, we analyzed
diagnosis timing relative to solitary confinement, nature of diagnosis, age, and
race/ethnicity.
Methods. We analyzed 2011 to 2013 medical records on 45 189 New York City
jail first-time admissions.
Results. Of this cohort, 21.2% were aged 21 years or younger, 46.0% were
Hispanic, 40.6% were non-Hispanic Black, 8.8% were non-Hispanic White, and
3.9% experienced solitary confinement. Overall, 14.8% received a mental health
diagnosis, which was associated with longer average jail stays (120 vs 48 days),
higher rates of solitary confinement (13.1% vs 3.9%), and injury (25.4% vs 7.1%).
Individuals aged 21 years or younger were less likely than older individuals to
receive a mental health diagnosis (odds ratio [OR] = 0.86; 95% confidence
interval [CI] = 0.80, 0.93; P < .05) and more likely to experience solitary confinement (OR = 4.99; 95% CI = 4.43, 5.61; P < .05). Blacks and Hispanics were less likely
than Whites to enter the mental health service (OR = 0.57; 95% CI = 0.52, 0.63; and
OR = 0.49; 95% CI = 0.44, 0.53; respectively; P < .05), but more likely to experience
solitary confinement (OR = 2.52; 95% CI = 1.88, 3.83; and OR = 1.65; 95% CI = 1.23,
2.22; respectively; P < .05).
Conclusions. More consideration is needed of race/ethnicity and age
in understanding and addressing the punishment and treatment balance in jails. (Am J Public Health. 2015;105:1911–1916. doi:10.2105/AJPH.
2015.302699)

preventive medicine encounter. Approximately
25% of those admitted to the jails will be
admitted into the mental health service, and
approximately 4% of those admitted will ultimately be designated as seriously mentally ill
(SMI). Although the proportion of SMI patients
has remained stable in recent years, the percentage of admitted persons who become part
of the mental health service has increased from
approximately 12% in 2004 to 25% today.
(Note: Entrance into the mental health service
is based on ever receiving a mental health
diagnosis during incarceration in the New York
City jail system.) In addition, because persons
with mental illness have longer lengths of stay
than others, they now represent approximately
38% of persons in jail at any given time. Entry
into the jail mental health service is typically
described as resulting from a mental health
referral that occurs during the intake history
or physical examination during jail admission.

September 2015, Vol 105, No. 9 | American Journal of Public Health

Nonetheless, we also have patients enter into
the mental health service later in their stay and
our clinical experience is that these later admissions may be associated with environmental
stressors of the jail itself.
Recent Correctional Health Services quality
improvement studies on the issue of selfharm have revealed that SMI patients, in
addition to adolescents and those in solitary
confinement, are significantly more likely to
self-harm while in jail.12 Solitary confinement
refers to the isolation of persons from others
for 22 to 24 hours per day in a locked cell,
which is employed in the New York City jail
system for punishment reasons. To better understand how persons with a mental health
diagnosis initially come to the attention of
the mental health service, we conducted an
epidemiological analysis focused on timing
of diagnosis during jail stay and, where relevant, relative to solitary confinement, nature of

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RESEARCH AND PRACTICE

diagnosis, age, and race/ethnicity of patients.
The overarching goal of this analysis is to
improve the quality of care for patients by
detecting characteristics of our health system
and those of our patients that merit special
attention.

METHODS
This analysis focused on individuals during
their first jail incarceration. Eligible patients
had only 1 incarceration from April 15, 2011,
through November 31, 2013, and no previous
history of incarceration in New York City
since November 2008 when our electronic
health record (EHR) was established. Previous
paper-based diagnoses were not known to
us. To allow patients admitted after December
1, 2013, adequate follow-up time for mental
illness to be expressed and diagnosed, we
extended the observation period until February 28, 2014.

Patients admitted into New York City jails
receive a rigorous medical intake within 4
hours of their arrival. The medical intake can
trigger a mental health referral and assessment, which occurs within 72 hours or immediately, depending on the referral urgency.
Patients may also be referred to mental health
services through Department of Corrections
or other medical staff on the basis of their
observations.
We extracted data on inmate demographics,
jail admission and discharge dates, and placement in solitary confinement from the EHR.
Demographic information is entered directly
by the Department of Correction staff into their
electronic Inmate Information System, which is
automatically transferred into the EHR. The
interface between the Department of Correction information system and the EHR is quite
reliable, although we do not have visibility into
the quality assurance process for Department
of Correction data entry. We defined SMI

patients according to criteria established by the
New York State Office of Mental Health.13 We
also obtained data for medical and mental
health resource use from the EHR during the
study period. We defined use as the number of
visits during which patients had an interaction
with a medical or mental health provider,
including psychiatrists, psychologists, and licensed clinical social workers, and mental
health diagnoses were made consistent with the
Diagnostic and Statistical Manual of Mental
Disorders, Fifth Edition.14
Our dependent variables—entry into mental
health services, late entry into mental health
services, and entry into solitary confinement—
were dichotomous. We identified patients who
were admitted into mental health services from
EHR (0 = no; 1 = yes). Because most mental
health service recipients are identified within
a week of jail admission, we defined those who
were sent to mental health services after 7
or more days of jail admission as late entrants

TABLE 1—Percentage Receiving a Mental Health Diagnosis Among Persons Incarcerated for the First Time, by Timing of the Mental Health
Diagnosis and Selected Demographic, Mental Health Diagnosis, and Incarceration Features: New York City, 2011–2013
MH Dx Admitted £ 7 d

MH Dx
Characteristic
Total

Total No. (%) or Mean

No. (%) or Mean

45 189 (100)

6 673 (14.8)

5 756 (12.7)
39 433 (87.3)

1 625 (24.4)
5 048 (75.6)

% of Total

No. (%) or Mean

% of Total

4 745 (71.1)

MH Dx Admitted > 7 d
No. (%) or Mean

% of Total

1 928 (28.9)

Gender
Female
Male

28.2*
12.8

1 302 (27.4)
3 443 (72.6)

80.1
68.2

323 (16.8)
1 605 (83.2)

19.9
31.8*

Age
£ 21 y

9 584 (21.2)

1 469 (22.0)

849 (17.9)

57.8

620 (32.2)

> 21 y

35 605 (78.8)

5 204 (78.0)

3 896 (82.1)

74.9

1 308 (67.8)

42.2*
25.1

Race/ethnicity
Hispanic

20 778 (46.0)

2 720 (40.8)

13.1

1 905 (40.1)

70.0

815 (42.3)

30.0

Non-Hispanic Black

18 367 (40.6)

2 871 (43.0)

15.6

1 994 (42.0)

69.5

877 (45.5)

30.5

Non-Hispanic White
Other or unknown

3 970 (8.8)
2 064 (4.6)

21.9*
10.3

689 (14.5)
157 (3.3)

79.2
74.1

181 (9.4)
55 (2.9)

20.8*
25.9

49.5*

302 (6.4)

LOS, d
Solitary confinement

48
1 770 (3.9)

MH dx 610 d of solitary confinement
Injured

870 (13.0)
212 (3.2)
120*
876 (13.1)

84

140 (16.0)
3 227 (7.1)

1 698 (25.4)

52.6*

210*
34.5

574 (29.8)

65.5*

43 (14.2)

30.7

97 (16.9)

69.3

867 (18.3)

22.0

831 (43.1)

48.9*

SMI

1 139 (17.5)

982 (20.7)

32.0*

157 (8.1)

13.8

Depression or anxiety dx

1 165 (17.5)

878 (18.5)

29.8*

287 (14.9)

24.6

Mood, adjustment, or antisocial personality
disorder dx

2 343 (35.1)

1 345 (28.3)

21.5

998 (8.0)

42.6*

Note. Dx = diagnosis; LOS = mean length of stay (days); MH = mental health; SMI = diagnosed as seriously mental ill.
*P = .001.

1912 | Research and Practice | Peer Reviewed | Kaba et al.

American Journal of Public Health | September 2015, Vol 105, No. 9

RESEARCH AND PRACTICE

(0 = mental health services entry within 7 days;
1 = mental health services entry after 7 days
or more). We identified patients who were in
solitary confinement from housing placement,
thus creating a dichotomous variable (0 = no;
1 = yes).
The independent variables included ever
being in solitary confinement during incarceration, SMI, age 21 years and younger, gender,
length of stay, and race/ethnicity. We created
a binary variable to indicate patients who were
aged 21 years or younger (0 = older than
21 years; 1 = 21 years or younger). We used
21 years as the cutoff because of the difference
in the epidemiology of young adults and
older adults, as well as the different approaches
that are taken by jail managers in responding
to these 2 groups. Because clinical staff rarely
remove an SMI designation for a patient during their incarceration, we used the presence

of SMI at any time. Gender was another
dichotomous variable (0 = male; 1 = female).
We calculated length of stay (in 6-month
increments) from jail admission and discharge
dates, creating a dummy discharge date for
those patients who were still in jail by February
28, 2014. We created another continuous
variable to show the timing of mental health
service entry in conjunction with solitary confinement, namely, mental health service entry
10 days before or after solitary confinement
(0 = did not enter mental health services
around the time of solitary confinement;
1 = entered into mental health services 10 days
before or after solitary confinement). Our
previous investigations and clinical work indicated strong correlations between the 2,
particularly in relation to evidence of new
mental health symptoms just before or at the
outset of placement in solitary confinement.12

6000

5000

Frequency

4000

3000

2000

The race/ethnicity was categorized as Hispanic,
non-Hispanic Black, non-Hispanic White, and
other or unknown.
Two additional mental health variables included were whether patients were diagnosed
with depression or anxiety (0 = no; 1 = yes),
and if they were diagnosed with mood, adjustment, or antipersonality disorders (0 = no;
1 = yes). We chose these 2 diagnosis combinations on the basis of clinical observations,
mainly that the second set of diagnoses are
often associated with patients who experience
friction in the jail setting and who may elicit less
sympathy for their mental health problems,
whereas the first diagnosis grouping reflects
assessments that are often thought by both
inmates and clinical staff to be more “legitimate” mental health problems.
We conducted 3 logistic regression models
to estimate odds ratios and 95% confidence
intervals for predictors associated with entry
into mental health services, late entry into
mental health services, and entry into solitary
confinement. The first model looked at the
effects of age 21 years or younger or older,
length of stay, gender, and race/ethnicity on
entry into mental health services and the
second model looked at the effects of the same
independent variables on late entry into
mental health services. The third model explored the impact of gender, race/ethnicity, age
21 years or younger or older, and length of
stay on entry into solitary confinement.
We determined statistical significance of
differences in bivariate analysis by using the
v2 test and we determined significance for
bivariate and multivariate analysis at the 5%
level. We used SPSS version 19 (IBM, Somers,
NY) for statistical analysis.

RESULTS
1000

0
0

200

400

600

800

1000

Days
Note. Mean = 24.62 days; SD = 65.929 days. The sample size was n = 6673.

FIGURE 1—Timing of entry into mental health services (n = 6673): New York City jail,
2011–2013.

September 2015, Vol 105, No. 9 | American Journal of Public Health

Of the 129 642 individuals incarcerated
during the study period, there were 45 189
who met the study criteria. Almost 15% received mental health services and close to 30%
(28.9%) of these patients entered mental
health services 7 or more days after admission.
Of this study cohort, 87.3% were male,
21.2% were aged 21 years or younger, 46.0%
were Hispanic, 40.6% were non-Hispanic Black,
8.8% were non-Hispanic White, and 3.9%
spent time in solitary confinement (Table 1).

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RESEARCH AND PRACTICE

Mental health patients were significantly
more likely than non---mental health patients to
be female (28.2% vs 12.8%), non-Hispanic
White (21.9% vs 15.6% non-Hispanic Black
and 13.1% Hispanic), to stay longer in jail (120
days vs 35 days), to be placed in solitary
confinement (13.1% vs 2.3%), and to be injured (25.4% vs 4.0%; Table 1). Of these
patients, 17.5% were diagnosed as SMI, and
the most frequent mental health diagnoses
among all patients were adjustment disorder
(15.1%), depression (9.7%), mood disorder
(6.6%), and bipolar disorder (4.2%).
Most mental health patients (71.1%) received their mental health diagnosis within
7 days of admission (Table 1; Figure 1).
Conversely, findings for the group of patients
who were ever in solitary confinement show
that 65.5% received a diagnosis later in their
stay, compared to 34.5% of patients diagnosed

within 7 days (P < .001) after admission, indicating that later entry into mental health
services might be in the context of solitary
confinement. When we plotted the distribution
of receiving a mental health diagnosis with
respect to timing of entry into solitary confinement, we found a near normal distribution
centered around zero days (Figure 2). Among
those experiencing solitary confinement,
16.0% of mental health diagnoses occurred
within 10 days before or after the date of
solitary confinement, including 69.3% of
mental health diagnoses given more than
7 days after jail entry (Table 1). Proportionally
more male, age 21 years or younger, and
non-White patients received mental health diagnoses 7 days or more after admission than
received diagnoses within 7 days of admission.
They were also more likely to go to solitary
confinement, be injured, and stay longer in jail.

250

Frequency

200

150

100

Patients in this group were less likely to be
diagnosed with SMI and depression or anxiety,
but more likely to be diagnosed with mood,
adjustment, or antisocial personality disorders
(Table 1). In addition, among those with
a late mental health diagnosis, only 8.8% of
Whites ever went into solitary confinement,
compared with 38.8% of Blacks and 25.6%
of Hispanics. Overall, non-White patients and
those aged 21 years or younger were more
likely to receive diagnosis of mood, adjustment,
or antisocial personality disorder and less likely
to receive depression or anxiety diagnoses
(P < .001 for all comparisons; data not shown).
The first 2 logistic regression models demonstrated that entry into mental health services
and late entry into mental health services were
significantly associated with being in solitary
confinement, female gender, older age, longer
stay, and non-Hispanic White (compared with
Hispanic and non-Hispanic Black; Table 2)
race/ethnicity. Patients who were female, older
than 21 years, non-Hispanic White (compared
with Hispanic and non-Hispanic Black), in
solitary confinement, and who stayed in jail
longer were more likely to receive mental
health services (Table 2). On the other hand,
patients who were male, Hispanic (compared
with non-Hispanic White), aged 21 years or
younger, in solitary confinement, and who
stayed longer in jail were more likely to enter
mental health services 7 or more days after jail
admission (Table 2). The third logistic regression model showed that solitary confinement
was strongly associated with the same independent variables. Patients who were male,
non-White, aged 21 years or younger, and
stayed longer in jail were more likely to be
sentenced to solitary confinement.

DISCUSSION

50

0
-1000

-500

0

500

1000

Days After First Solitary Confinement
Note. 0 = service entry on the first day of solitary confinement. Mean = –43.82 days; SD = 168.822 days. The sample size was
n = 876.

FIGURE 2—Timing of mental health service entry with respect to the first solitary
confinement episode (n = 876): New York City jail, 2011–2013.

1914 | Research and Practice | Peer Reviewed | Kaba et al.

These data reveal concerns that some
groups in the jail system are more likely to elicit
treatment responses whereas others are more
likely to meet with a punishment response.
Both non-White and young patients in the New
York City jail system appear to be less likely to
enter the jail mental health system and more
likely to enter solitary confinement than their
White and older counterparts. One startling
observation is that non-Hispanic Black and
Hispanic patients are 2.52 and 1.65 times

American Journal of Public Health | September 2015, Vol 105, No. 9

RESEARCH AND PRACTICE

TABLE 2—Multivariate Analysis Results for Predictors of Receiving Mental Health Services,
Timing of the Entry Into Mental Health Services, and Entry Into Solitary Confinement:
New York City Jail, 2011–2013
Variables

OR (95% CI)

Receipt of mental health services
Ever in solitary confinement during this incarceration

2.44 (2.16, 2.76)

Female vs male

3.36 (3.14, 3.60)

Non-Hispanic Black vs non-Hispanic White
Hispanic vs non-Hispanic White

0.57 (0.52, 0.63)
0.49 (0.44, 0.53)

Age category 16–21 y vs ‡ 22 y

0.86 (0.80, 0.93)

Length of stay (6-mo increments)

2.59 (2.48, 2.71)

Timing of entry into mental health services (‡ 7 d after admission)
Ever in solitary confinement during this incarceration

2.64 (2.20, 3.16)

Female vs male

0.73 (0.63, 0.84)

Hispanic vs non-Hispanic White

1.26 (1.04, 1.53)

Age category 16–21 y vs ‡ 22 y
Length of stay (6-mo increments)

1.44 (1.25, 1.66)
1.89 (1.76, 2.03)

Solitary confinement
Female vs male

0.77 (0.62, 0.92)

Non-Hispanic Black vs non-Hispanic White

2.52 (1.88, 3.83)

Hispanic vs non-Hispanic White

1.65 (1.23, 2.22)

Age category 16–21 y vs ‡ 22 y

4.99 (4.43, 5.61)

Length of stay (6-mo increments)

4.99 (4.72, 5.28)

Notes. CI = confidence interval; OR = odds ratio.

more likely to enter solitary confinement than
White patients. In addition, to the extent that
patients in these age- and race-based risk
groups enter into the mental health system, this
entry appears much more likely to coincide
with being punished with solitary confinement
than for White and older patients.
We have several hypotheses about the
sources of these patterns. Some of the disparities in diagnosis by race/ethnicity likely reflect
differences in rates of diagnosis and engagement in care in the community, such as outpatient mental health treatment.12 The higher
rates of early diagnosis among White and adult
incarcerated patients mirror reports from
community settings. There, Whites have higher
rates of mental health visits than other racial/
ethnic groups, a finding that appears not to
have narrowed over time.15 Although some or
part of this disparity in diagnosis is linked to
access, provider-level bias may also contribute.
There is a well-documented social tendency to
view non-White persons as criminal or untruthful, which in our mental health setting

could lead staff to not detect mental illness or to
give a more pejorative diagnostic label when
patients exhibit stress from solitary confinement.16,17 The report by the Institute of Medicine on the topic of racial disparities in health
care identified provider bias and patient mistrust as important features of addressing the
uneven terrain that affects encounters between
patients and their providers.18
We also hypothesized that new disparities
may occur in the jail setting in adults, reflecting
race or age-related bias in the health system or
the security system’s punishment apparatus.
There is evidence to suggest that inmate race/
ethnicity is associated with whether someone
with a mental health diagnosis and behavioral
problems elicits a treatment or a punishment
(e.g., solitary confinement) response. Among
those with a late mental health diagnosis, only
8.8% of Whites ever went into solitary confinement, compared with 38.8% of Blacks and
25.6% of Hispanics. Both security and health
staff may be predisposed to view behavioral
problems by White inmates as a manifestation

September 2015, Vol 105, No. 9 | American Journal of Public Health

of mental illness that merits treatment, as
opposed to non-White inmates whom they may
view as requiring punishment. These tendencies have been noted in community settings
when perceptions of police officers have been
assessed. Also, recent observations that mass
incarceration is viewed more favorably when
portrayed as disproportionately including
non-Whites supports the link between nonWhites and a perceived need for punishment.19
Late entries into mental health services are
closely associated with solitary confinement
and self-harm by patients to avoid or get
released from solitary confinement. Our clinical
experience is that some patients will go to
extreme lengths to avoid or get released from
solitary confinement, including lighting fires in
a closed cell, banging one’s head on the wall,
and forms of potentially fatal self-harm. The
histogram (Figure 2) showing a normal distribution of timing of entry into the mental health
service around the time that patients enter
solitary confinement is strikingly similar to that
of solitary confinement and self-harm that we
previously published, suggesting a temporal
link between solitary confinement, self-harm,
and entry into the mental health service.12
Patients who receive a psychiatric diagnosis
because of self-harm may represent a cohort
with mental health problems that went unnoticed during the initial jail admission process.
Conversely, these patients may be adaptively
responding to extreme environmental conditions in hopes of escaping the setting, as those
who receive a mental health diagnosis while in
solitary confinement may be removed from the
setting by the medical team. The concept of
pathologizing normal adaptive behavior along
racial lines has historical precedent in the term
drapetomania, a contrived diagnosis given to
slaves who fled plantations in the 1800s.20
On the basis of these findings, we have
begun the process of training staff on how to
deliver culturally appropriate care, starting
with a grant-funded program to promote culturally appropriate care to Latino patients in
jail.21 A core component of such training is to
start with an acknowledgment of existing disparities in the delivery of care. We will expand
these efforts with a focus on how both security
and health staff respond to patients in jail with
behavioral problems, confronting staff’s personal biases that can lead to inappropriate and

Kaba et al. | Peer Reviewed | Research and Practice | 1915

RESEARCH AND PRACTICE

differential treatment response. Related to this,
the infraction process that security staff uses to
adjudicate violations of jail rules will benefit
from similar scrutiny and training. Given
the lack of inmate representation or outside
scrutiny in most jail infraction processes, it
would be equally useful to conduct assessments of jail infractions with an eye toward
potential race- or age-related biases.

Limitations
In this analysis, we focused on demographic
and clinical information present in the EHRs.
Criminal charges and jail infraction information
were not available. As a consequence, some of
the differences may reflect disparities at play in
the arrest, arraignment, and bail processes. An
important area for future study is to examine
the criminal charges of these groups to assess
the relation between length of stay and entry
into the mental health service.
In addition, our focus on first jail incarceration
reduced our sample size from approximately
225 557 jail admissions during the time period
of analysis to 45 189. Our analysis did not
account for incarcerations outside the New York
City jail system, and thus may have missed the
impact that these events could have on our
variables of interest. Finally, the diagnostic
groupings used were prompted by input from
clinical staff but may not reflect differences
reported or used in community settings.

Conclusions
These data from persons in the New York
City jail system for their first incarceration
reveal age and race-based disparities in when
and how patients enter the mental health
system in the New York City jail system. Individuals who are aged 21 years and younger
and who are non-White are more likely to get
a mental illness diagnosis late in their stay,
spend time in solitary confinement, have their
mental health diagnosis associated with solitary
confinement, and receive a diagnosis of mood,
adjustment, or antisocial disorder. They are less
likely to get a diagnosis of anxiety or depression.
Even compared with others who have a late
mental health diagnosis, they are much more
likely to spend time in solitary confinement and
more likely to get a diagnosis of mood, adjustment, or antisocial personality disorder. We hypothesize that these findings reflect a combination

of factors, including community disparities in
mental health engagement, as well as differences
in clinical versus punishment responses that occur
inside jail. More investigation of these findings is
warranted. We have begun efforts to train our
mental health providers on culturally appropriate
methods of promoting engagement in care. j

About the Authors
Fatos Kaba, Angela Solimo, Jasmine Graves, Sarah GlowaKollisch, Allison Vise, Ross MacDonald, Anthony Waters,
Zachary Rosner, Nathaniel Dickey, and Homer Venters are
with the Bureau of Correctional Health Services, New York
City Department of Health and Mental Hygiene, Queens,
NY. Sonia Angell is with the Division of Prevention and
Primary Care, New York City Department of Health and
Mental Hygiene.
Correspondence should be sent to Homer Venters, MD,
MS, Bureau of Correctional Health Services, New York City
Department of Health and Mental Hygiene. 42-09 28th St,
WS 10-84, Queens, NY 11101 (e-mail: hventer1@health.
nyc.gov). Reprints can be ordered at http://www.ajph.org by
clicking the “Reprints” link.
This article was accepted March 28, 2015.

Contributors

6. Baillargeon J, Penn J, Thomas C, Temple J,
Baillargeon G, Murray O. Psychiatric disorders and
suicide in the nation’s largest state prison system. J Am
Acad Psychiatry Law. 2009;37(2):188---193.
7. Karnik NS, Jones P, Campanero A, Haapanen R,
Steiner H. Ethnic variation of self-reported psychopathology among incarcerated youth. Community Ment
Health J. 2006;42(5):477---486.
8. Karnik NS, Soller M, Redlich A, et al. Prevalence
differences of psychiatric disorders among youth after nine
months or more of incarceration by race/ethnicity and age.
J Health Care Poor Underserved. 2010;21(1):237---250.
9. Teplin LA. The prevalence of severe mental disorder among male urban jail detainees: comparison with
the epidemiologic catchment area program. Am J Public
Health. 1990;80(6):663---669.
10. Teplin LA, Abram K, McClelland G, Dulcan M,
Mericle A. Psychiatric disorders in youth in juvenile detention. Arch Gen Psychiatry. 2002;59(12):1133---1143.
11. Office of the Surgeon General, Center for Mental Health
Services, National Institute of Mental Health. Mental Health:
Culture, Race and Ethnicity, a Supplement to Mental Health:
A Report of the Surgeon General. Rockville, MD: Substance
Abuse and Mental Health Services Administration; 2001.
12. Kaba F, Lewis A, Glowa-Kollisch S, et al. Solitary
confinement and risk of self-harm among jail inmates. Am
J Public Health. 2014;104(3):442---447.

F. Kaba conducted statistical analyses, and conceptualized, drafted, and revised the article. A. Solimo facilitated
the statistical analyses, contributed to interpretation of
results, and revised the article. J. Graves, S. GlowaKollisch, A. Vise, R. MacDonald, A. Waters, Z. Rosner,
and N. Dickey drafted and revised the article with critical
content. S. Angell revised the article with critical content.
H. Venters was responsible for study conceptualization,
design, and oversight; he also drafted and revised the
article with critical content.

13. New York Office of Mental Health. Criteria for serious
and persistent mental illness. Available at: http://www.
omh.ny.gov/omhweb/guidance/serious_persistent_
mental_illness.html. Accessed September 18, 2014.

Acknowledgments

16. Hurwitz J, Peffley M. Public perceptions of race and
crime: the role of racial stereotypes. Am J Pol Sci.
1997;41(2):375---401.

The authors would like to acknowledge the contributions of
Mary Bassett, MD, MPH, and James Hadler, MD, MPH, of the
New York City Department of Health and Mental Hygiene.

Human Participant Protection
Institutional review board approval was not needed for
this study as it represents routine public health surveillance by the Bureau of Correctional Health Services.

References
1. US Department of Justice, Office of Justice Programs,
Bureau of Justice Statistics. Jail inmates at midyear 2011 (NCJ
237961). 2012. Available at: http://www.bjs.gov/content/
pub/pdf/jim11st.pdf. Accessed September 18, 2014.
2. Bonney LE, Clarke J, Simmons E, Rose J, Rich J.
Racial/ethnic sexual health disparities among incarcerated women. J Natl Med Assoc. 2008;100(5):553---558.
3. Harzke AJ, Baillargeon J, Kelley M, Diamond P,
Goodman K, Paar D. HCV-related mortality among male
prison inmates in Texas. Ann Epidemiol. 2009;19
(8):582---589.
4. Stein MS, Spaulding A, Cunningham M, et al. HIVpositive and in jail: race, risk factors, and prior access to
care. AIDS Behav. 2013;17(suppl 2):S108---S117.
5. Wolff N, Shi J, Blitz C. Racial and ethnic disparities in
types and sources of victimization inside prison. Prison J.
2008;88(4):451---472.

1916 | Research and Practice | Peer Reviewed | Kaba et al.

14. Diagnostic and Statistical Manual of Mental Disorders, Fifth Edition. Washington, DC: American Psychiatric
Association; 2013.
15. Manseau M, Case B. Racial-ethnic disparities in
outpatient mental health visits to U.S. physicians, 1993--2008. Psychiatr Serv. 2014;65(1):59---67.

17. Ghandnoosh N. Race and punishment: racial perceptions of crime and support for punitive policies,
The Sentencing Project. 2014. Available at: http://
sentencingproject.org/doc/publications/rd_Race_and_
Punishment.pdf. Accessed September 18, 2014.
18. Brian D, Smedley B, Stith A, Nelson A. Unequal
Treatment Confronting Racial and Ethnic Disparities in
Health Care; Institute of Medicine (US) Committee on
Understanding and Eliminating Racial and Ethnic Disparities in Health Care. Washington, DC: National Academies Press; 2003.
19. Hetey RC, Eberhardt J. Racial disparities in incarceration increase acceptance of punitive policies.
Psychol Sci. 2014;Epub ahead of print.
20. Cartwright S. Diseases and peculiarities of the Negro
race. 1851. Available at: http://www.pbs.org/wgbh/aia/
part4/4h3106t.html. Accessed April 2, 2015.
21. Special Programs of National Significance: culturally
appropriate interventions of outreach, access and retention
among Latino(a) populations (SPNS Latino Initiative).
H97HA27431-01-00 for Special Projects of National
Significance to New York, City of (the), Long Island City,
New York is provided by the Health Resources and Services
Administration. 2014. Available at: http://hab.hrsa.gov/
abouthab/special/latino.html#3. Accessed April 2, 2015.

American Journal of Public Health | September 2015, Vol 105, No. 9