Ethnic density and prevalence of psychiatric morbidity among patients with hiv infection in Sokoto, Nigeria—A control study

doi:10.4236/ojpsych.2012.24041

Paper Menu >>

Journal Menu >>

Open Journal of Psychiatry, 2012, 2, 292-300 OJPsych

http://dx.doi.org/10.4236/ojpsych.2012.24041 Published Online October 2012 (http://www.SciRP.org/journal/ojpsych/)

Ethnic density and prevalence of psychiatric morbidity

among patients with hiv infection in Sokoto, Nigeria—A

control study

Mufutau A. Yunusa*, Ayodele Obembe

Department of Psychiatry, Usmanu Danfodiyo University, Sokoto, Nigeria

Email: *[email protected]

Received 4 September 2012; revised 2 October 2012; accepted 10 October 2012

ABSTRACT

Background: Previous studies among people living

with HIV infection suggested that prevalence of psy-

chiatric morbidity was high. In addition, among non-

HIV infected patients, ethnic density influence the

prevalence. The present study was aimed to deter-

mine the prevalence and effects of ethnic density on

psychiatric morbidity among these patients in Sokoto,

Nigeria. Methods: This prospective cross-sectional

study was conducted among patients who had been

diagnosed with HIV infection in a teaching hospital in

Sokoto. Questionnaire relating to sociodemographic

variables and psychiatric morbidity were adminis-

tered to the patients. Data obtained were analyzed

using SPSS version 16.0 while test for significance

was set at P < 0.05. Result: The mean age of the pa-

tient was 32 ± 9 years (range = 12 - 63), male being

older than the female. Of the patients, 71% were

married while and about two third were of Islamic

religion. Twenty seven percent had no formal educa-

tion and were mainly Hausa/Fulani ethnicity. Seven

percent of the patients had definite depression while

8% had definite anxiety. When the subjects were di-

chotomized to Hausa/Fulani and others, they were

similar with regard to age and gender (χ2 = 4.43; P =

0.49 and χ2 = 0.22; P = 0.64 respectively). Across the

ethnicity (Hausa/Fulani and others), the subjects dif-

fer significantly with regard to religion (χ2 = 0.68; P =

0.00), marital status (χ2 = 15.05; P = 0.00), education

(χ2 = 30.56; P = 0.00) and employment status (χ2 =

9.81; P = 0.01). The Hausa/Fulani ethnic group had

less psychiatric morbidity. In addition, marital status

had significant pathoplastic effect on depression

across ethnicity (χ2 = 0.42; P = 0.02). Conclusion:

Ethnic density was associated with decrease preva-

lence of common mental disorder among patients

with HIV infection. Environmental manipulation may

play a role in the management of this patient.

Keywords: Ethnicity; HIV; Morbidity; Prevalence;

Psychiatric

1. INTRODUCTION

The prevalence of anxiety and depression among HIV

patients is high, however varied [1-3]. In one report,

nearly half of the patients with HIV infection were re-

ported to have psychiatric morbidity [4]. However in

another study a smaller percentage was reported [5]. A

prevalence of 22% to 32% [6,7] which was 2 to 3 times

higher than the prevalence of psychiatric disorders in

general community population has also been reported.

However in a longitudinal study of Maj et al. [5], lower

prevalence of 9% of major depression and 2% of anxiety

disorder were reported after 6-months follow up [8]. In

south west Nigeria, prevalence of depression among pa-

tients with HIV infection was 59.1% [9].

The effects of psychiatric morbidity on HIV infection

underscored the need to study psychiatric morbidity c l osel y

among the patients and identify the predisposing factors.

Depression and anxiety disorder were reported to speed

progression of the disease [10,11]. In addition, depres-

sion has negative effect on course and outcome of HIV

infection [12] and substantially impact on quality of life

of patients while anxiety has negative consequence on

social role and mental functioning [13].

Ethnic density is one factor that had been reported to

influence distribution of psychiatric morbidity and in

particular beneficial pathoplastic effects on psychiatric

morbidity. It is defined as the relative size of a given

ethnic group in a multi ethnic neighbourhood [14]. In

one report Rabkin [14] reported on the hazards of ethnic

minority status on psychiatric hospitalization. They

showed that the ethnic density had protective association

on suicide and self harm as well as on psychosis [15]. In

a large community study in England and Wales [16],

5167 ethnic minority and 2867 white were studied.

The protective effects of ethnic density on psychiatric

*Corresponding a uthor.

OPEN ACCESS

M. A. Yunusa, A. Obembe / Open Journal of Psychiatry 2 (2012) 292-300 293

morbidity were also observed.

T his st udy wa s aimed at determin ing the influen ce of eth-

nic density on prevalence of anxiety and depression among

Hausa/Fulani ethnic group with HIV infection in Sokoto.

2. METHODS

2.1. Study Design and Location

This was part of a large study. Detail on methodology

was reported in earlier report [17]. This cross sectional

study was carried out among patients who were dia-

gnosed of HIV infection at the VCT [voluntary coun-

seling and testing] centre of Usmanu Danfodiyo Univer-

sity Teaching Hospital, Sokoto, North Western Nigeria.

The study included 167 consecutive adult patients who

were attending their routine clinic. Both symptomatic and

non symptomatic patients were included.

2.2. Data Collection

Variables relating to socio demographic profile and substance

use were obtained throu gh the use of questionnaire designed

by the authors while psychiatric morbidity was assessed using

Hospital Anxiety and Depression Scale (HADS) [18].

2.3. Sociodemographic Questionnaire

Sociodemographic questionnaire was designed by the

authors to enquire about basic epidemiological variables

including age, sex, occupation and religion.

2.4. Hospital Anxiety and Depression Scale

This 14-item questionnaire was developed by Zigmond

and Snaith [18] to determine the presence of anxiety

and depression among patients with medical conditions.

Using Likert scoring scale, score range is 0 - 21 for

each of the condition. While patients with score of 0 - 7

are considered as non cases, those that scored 8 - 10 and

11 and above were considered as borderline and definite

cases for anxiety or depression respectively. It has been

validated and used in previous studies in Nigeria.

Abiodun [19] reported from a Nigerian community that

the sensitivity for the anxiety subscale ranged from

85.0% in the medical and surgical wards to 92.9% in

the ante-natal clinic, while sensitivity for the depression

sub-scale ranged from 89.5% in the community sample

to 92.1% in the gynaecology clinic. The specificity for

the anxiety sub-scale ranged from 86.5% in the gynae-

colog y clinic to 90.6% in the community sample, while

specificity for the depression sub-scale ranged from

86.6% in the medical and surgical wards to 91.1% in

the ante-natal clinic and community sample. Misclassi-

fication rates ranged from 9.9% in the community sam-

ple to 13.2% in the medical and surgical wards. Rela-

tive operating characteristics (ROC) analyses showed

the HADS and the GHQ 12 to be quite similar in ability

to discriminate between cases and non cases. Fatoye et

al. [20] used HADS in the study of prevalence of anxi-

ety and depression in patients with epilepsy in a Nige-

rian community. A study had shown that depression

subscale is useful to determine the presence of clinical

depression than beck depression inventory (Jose, et al.)

[21].

2.5. Analysis

For the purpose of analysis anxiety and depressive symp-

toms was made for any patients that cross the threshold

of 7 on HADS in the scoring thereby comprising of bor-

derline and definite anxiety and depression, while those

with definite anxiety and depression were treated sepa-

rately in other analysis. In addition age of onset of illness

was calculated hypothetically by subtracting age at time of

the study from the period since the illness was diagnosed.

Data was analyzed descriptively using SPSS for win-

dows version 16.0. Cases with missing data for the

HADS were excluded.

3. RESULT

A total of one hundred and sixty seven consecutive adult

patients were recruited for the study. Of these patients, 8

(4.8%) did not fill HADS questionnaire completely to be

incorporated into the analysis giving response rate of

95.2%. Eighty six (55.8%) of them were Hausa/Fulani

ethnic group while 68 (44.2%) others included Yoruba,

Igbo among others (Figure 1). The mean age of the pa-

tients was 34.52 ± 8.93. One hundred and fourteen

(71 .7 %) w er e mar r i ed , 25 (15.7%) were widowed, 8 (5%)

were divorced and 11 (8.9%) were never married. Also,

ninety seven (61%) were Muslims and 60 (37.7%) were

Christians. About a quarter of the patients had no formal

education while about 30% had post secondary educa-

tion. Of the subjects, fifteen (9.5%) were found to have

borderline depression while 12 (7.6%) had definite de-

pression. In addition, 10 (6.3%) were found to have

anxiety while 14 (8.8%) had definite anxiety (Tables 1

and 2). Mean score for the patients on HADS—anxiety,

subscale was 3.62 ± 4.03 and HADS (depression) was

4.33 ± 3.81. The mean HADS score for anxiety and de-

pression among patients who had definite anxiety and

depression were 13.00 ± 2.63 and 13.17 ± 2.76 respec-

tively. Table 3 showed the sociodemographic of the

Hausa/Fulani ethnic group against the other ethnic group.

With regard to age and gender, the two groups were

similar (χ2 = 4.43; P = 0.49) and (χ2 = 0.22; P = 0.64).

The groups differed significantly across religion (χ2 =

0.68; P = 0.00) and marital status with more of the

Hausa/Fulani ethnic group being widow (χ2 = 15.05; P =

0.00). In addition more of the Hausa ethnic group had no

M. A. Yunusa, A. Obembe / Open Journal of Psychiatry 2 (2012) 292-300

294

tribe

Figure 1. Ethnicity.

Table 1. Sociodemographic characteristics and prevalence of

psychiatric morbidity. Table 2. Sociodemographic characteristics and prevalence of

psychiatric morbidity (cont’d).

Characteristics Number %

AGE

<20 2 1.3

20 - 29 47 29.9

30 - 39 66 42.0

40 - 49 33 21.0

50 - 59 8 5.1

60 - 60+ 1 0.6

Total 157 100.0

Gender

Male 48 30.2

Female 111 69.8

Total 159 100.0

Religion

Islam 97 61.8

Christianity 60 38.2

Total 157 100.0

Marital status

Never married 11 6.9

Married 114 71.7

Separated 1 0.6

Divorced 8 5.0

Widow 25 15.7

Total 159 100.0

Education

No formal education 44 27.8

Primary 19 12.0

Secondary 47 29.7

Post secondary 48 30.4

Total 158 99.9

Number %

Tribe

Hausa / Fulani 86 55.8

Others 68 44.2

Total 154 100.0

Depression

Normal 130 82.3

Borderline 15 9.5

Definite 12 7.6

Total 158 99.4

Anxiety

Normal 134 84.3

Borderline 10 6.3

Definite 14 8.8

Total 158 99.4

formal education compared to the other ethnic group (χ2 =

30.56; P = 0.00) and similarly, more of the Hausa ethnic

group were unemployed (χ2 = 9.81; P = 0.01). As shown

in Table 4, prevalence of definite depression and anxiety

disorder were higher than that of the Hausa/Fulani ethnic

group.

In Table 5, sociodemographic characteristics of the

subjects were cross tabulated against psychiatric morbid-

dity. Subjects who were of age group 20 - 29 years were

mor e as s oci a t ed with borderline psychiatric morbidity and

those who were divorced. In addition, sociodemo-graphic

characteristics of each of the 2 groups (Hausa/Fulani and

others) were examined for the distribution of psychiatric

morbidity (Tables 6 and 7). Across both groups, being

OPEN ACCESS

M. A. Yunusa, A. Obembe / Open Journal of Psychiatry 2 (2012) 292-300 295

Table 3. Sociodemographic characteristics across ethnicity of patients.

Characteristics Hausa/Fulani No. (%) Others No. (%) χ2 P-value

Age

<20 1 (1.2) 1 (1.5) 4.43 0.49

20 - 29 22 (25.9) 24 (35.8)

30 - 39 36 (42.4) 28 (41.8)

40 - 49 21 (24.7) 11 ( 1 6.4)

50 - 59 5 (5.9) 2 (3.0)

60 - 60+ 0 (0.0) 1 (1.5)

Total 85 (100) 67 (100)

Gender

Male 27 (31.4) 19 (27.1) 0.22 0.64

Female 59 (68.6) 49 (72.1)

Total 86 (100.0) 68 (100.0)

Religion

Islam 77 (91.7) 17 (25.0) 0.68 0.00

Christianity 7 (8.3) 51 (75.0)

Total 84 (100.0) 68 (100.0)

Marital status

Never married 2 (2.3) 9 (13.2) 15.05 0.00

Married 57 (66.3) 52 (76.5)

Separated 1 (1.2) 0 (0.0)

Divorced 7 (8.1) 1 (1.5)

Widow 19 (22.1) 6 (8.8)

Total 86 (100.0) 68 (100.0)

Education

No formal education 39 (45.9) 4 (5.9) 30.56 0.00

Primary 9 (10.6) 10 (14.7)

Secondary 17 (20.0) 28 (41.2)

Tertiary 20 (23.5) 26 (38.3)

Total 85 (100.0) 68 (100.0)

Employment status

Employed 31 (36.9) 40 (62.5) 9.81 0.01

Unemploy e d 49 (58.3) 23 (35.9)

Table 4. Distribution of psychiatric morbidity and ethnicity.

CHARACTERISTICS HAUSA/FULANI No. (%)OTHERS NO. (%) χ2 P-Value

Depression

Normal 71 (83.5) 56 (82.4) 1.50 0.68

Borderline 9 (10.6) 6 (8.8)

Definite 5 (5.9) 5 (7.4)

TOTAL 85 (100.0) 68 (100.0)

Anxiety

Normal 74 (86.0) 56 (82.4) 1.89 0.59

Borderline 6 (7.0) 4 (5.9)

Definite 6 (7.0) 7 (10.3)

TOTAL 86 (100.0) 67 (99.6)

M. A. Yunusa, A. Obembe / Open Journal of Psychiatry 2 (2012) 292-300

296

Table 5. Sociodemographic charac teristics and distribution of psychiatric morbidity among the patients.

Depression Anxiety

Normal Borderline Definiteχ2 P-valueNormal Borderline Definite χ2 P-value

Age class (years)

<20 2 (100.0) 0 (0.0) 0 (0.0) 8.25 0.91 0 (0. 0) 2 (100.0) 0 (0.0) 0.37

20 - 29 35 (74.5) 7 (14.9) 4 (8.5)

35 (74.5)4 (8.5) 7 (14.9)

30 - 39 56 (86.2) 3 (4.6) 6 (9.2)

56 (84.8)5 (7.6) 5 (7.6)

40 - 49 28 (84.8) 4 (12.1) 1 (3.0)

31(93.9) 1 (3.0) 1 (3.0)

50 - 59 6 (75.0) 1 (12. 5 ) 1 (12.5)

7 (87.5) 0 (0.0) 1 (12.5)

60 - 60+ 1 (100.0) 0 (0.0) 1 (0.0)

1 (100.0)0 (0.0) 0 (0.0)

Marital status

Never married 7 (63.6) 3 (27.3) 1 (9.6) 18.090.11 7 (63.6) 4 (36.4) 0 ( 0.0) 19.580.08

Married 96 (85.0) 7 (6.2) 9 (8.0)

97 (85.1)5 (4.4) 11 (9.6)

Separated 0 (0.0) 1 (100) 0 (0.0)

0 (0.0) 1 (10 0.0) 0 (0.0)

Divorced 7 (87.5) 0 (-) 1 (12.5)

7 (87.5) 0 (0.0) 1 (12.5)

Widow 20 (80.0) 4 (16.0) 1 (4.0)

22 (88.0)1 (4.0) 2 (8.0)

Tribe

Hausa/ Fulani 7 1 (83.5) 9 (10.6) 5 (5.9) 1.50 0.68

74 (86.0)6 (7.0) 6 (7.0) 1.89 0.59

Others 56 (82.4) 6 (8.8) 5 (7.4)

56 (82.4)4 (5.9) 7 (10.3)

Table 6. Characteristics, prevalence of definite depression among the patients.

Hausa/Fulani ethnic group Other ethnic group

Definite depression χ2 P-value

Age

<20 0 (0.0)

0.29 0.49 0 (0.0) 0.41 0.55

20 - 29 0 (0.0)

4 (16.7)

30 - 39 4 (11.4)

1 (3.6)

40 - 49 0 (0.0)

0 (0.0)

50 - 59 1 (2 0 .0)

0 (0.0)

60 - 60+

Total

Gender

Male 1 (3.7)

0.11 0.60 0 (0.0) 0.19 0.46

Female 4 (6.9)

5 (10.2)

Total

Religion

Islam 5 (6.6)

0.08 0.8 2 ( 11.8) 0.13 0.76

Christianity 0 (0.0)

3 (5.9)

Total

Marital status

Never married 1 (50.0) 0.42 0.02 0 (0.0) 0.36 0.32

Married 3 (5.4)

4 (7.7)

Separated 0 (0.0)

0 (0.0)

Divorced 1 (14.3)

0 (0.0)

Widow 0 (0.0)

1 (16.7)

Total

Education

No formal education 1 (2.6) 0.33 0.26 1 (25.0) 0.31 0.84

Primary 2 (22.2)

1 (10.0)

Secondary 2 (11.8)

1 (3.6)

Tertiary 0 (0.0)

2 (10.0)

Total

M. A. Yunusa, A. Obembe / Open Journal of Psychiatry 2 (2012) 292-300

297

OPEN ACCESS

Table 7. Characteristics, prevalence of anxiety among the patients.

Hausa/Fulani P-value χ2 Others P-value χ2

Age

<20 0 (0.0)

0.30 0.39

0 (0.0) 0.35 0.87

20 - 29 3 (13.6)

4 (16.7)

30 - 39 1 (2.8)

3 (10.7)

40 - 49 1 (4.8)

0 (0.0)

50 - 59 1 (20.0)

0 (0.0)

60 - 60+

Total

Gender

Male 2 (7.4)

0.87 0.72

1 (5.3) 0.17 0.57

Female 4 (6.8)

6 (12.2)

Total

Religion

Islam 5 (6.5)

2 (11.8) 0.12 0.53

Christianity 1 (14.3)

5 (9.8) 0.16 0.61

Total

Marital status

Never married 0 (0.0) 0.28 0.52

0 (0.0) 0.43 0.08

Married 4 (7.0)

6 (11.5)

Separated 0 (0.0)

0 (0.0)

Divorced 1 (14.3)

0 (0.0)

Widow 1 (5.3)

1 (16.7)

Total

Education

No formal education 1 (2.6)

1 (25.0)

Primary 1 (11.1)

2 (20.0)

Secondary 1 (5.9)

1 (3.6)

Tertiary 2 (10.0)

3 (11.5)

Total

Employment status

Employed 2 (6.5)

0.18 0.56

5 (12.5) 0.18 0.90

Unemployed 4 (8.2)

2 (8.7)

married and having higher education were associated

with lower prevalence of psychiatric morbidity.

4. DISCUSSION

This study set out to determine the prevalence of psy-

chiatric morbidity among patients with HIV infection

who attended outpatient clinic of a tertiary hospital in

Sokoto, Nigeria. In addition, to determine the impact of

ethnic density on prevalence of psychiatric morbidity

among the patients.

The subjects were mainly young and sexually active

age group with about one third being married. More than

two third of the patients were not gainfully employed,

over half of them were married while another one third

were widowed. In this culture, women often remarried

soon after bereavement or divorce. This could be of in-

terest in the study of HIV disease transmission.

Anxiety and depressive symptoms were present in

17.1% and 15.1% of the patients respectively while defi-

nite anxiety and depression were present in 8.8% and

7.5% respectively. We observed that the following were

significantly associated with high prevalence of anxiety

and depression namely: Young age group (<20 years),

female gender, tertiary education, being employed and

M. A. Yunusa, A. Obembe / Open Journal of Psychiatry 2 (2012) 292-300

298

being with the illness for greater than 3 years. Also, de-

pressive symptom was more frequently associated with

age group <20 years, female gender, and being with the

illness for duration more than 5 years. Definite depres-

sion was found to be common among those who were of

young age, female gender, with no formal education.

The prevalence of mood disorder in present study was

consistent with previous studies among HIV infected

patients. Grant et al. [22] reported prevalence of mood

disorders in US population to be 9.21% while that of

anxiety disorder was 11.08%. This was also consistent

with findings in a Kenya [5] and Tanzania [23] study.

However other studies reported higher prevalence. Chan-

dra et al. [24] reported prevalence of 40% of depression

and 36% of anxiety among patients who attended tertiary

centre in India using HADS. In Ethiopia, using Kassler

[25 ] scale prevalence of common mental disorders among

patients with HIV infection was 46.7% which was higher

than findings in our study. The diff er e n ce s may b e a s so c i-

ated to sample size, socioculture and duration of illness.

For instance in their study patients were recruited within

4 - 6 weeks of revelation of HIV status unlike our study

with varied duration of illness from 2 weeks to 9 years. A

previous study in Nigeria reported prevalence of 59.1%

[9]. This difference may be associated with differences

in socioculture and instrument used to assess for psy-

chiatric morbidity. The subjects reported in that study

were mainly of Yoruba ethnic group south west Nigeria

which socioculturally differed from the Northwest Ni-

gerians where the present study took place. In addition

the instrument used had the advantage in discriminating

against physical symptoms associated with chronic phy-

sical illness such as fatigue, which DSM IV they used

could not.

The subjects were predominantly Hausa/Fulani ethnic

group while the remaining subjects comprised of more

than 10 different ethnic groups. We found variations in

sociodemographic characteristics when the Hausa/Fulani

ethnic group was compared with the other groups. The

Hausa/Fulani group was similar to the other ethnic group

with regard to age and gender. However more of the

Hausa/Fulani were less educated and less likely to be

married o r employed .

Also subjects who were ethnic minor ity were found to

have higher psychiatric morbidity than the Hausa/Fulani

ethnic. In addition, age and marital status appeared to

have effects on the prevalence across the ethnicity. This

finding was consistent with previous study on ethnic

density hypothesis which proposed that persons who live

in neighbourhood with a greater proportion of residents

of their own race or ethnicity have better mental health

outcomes and lower levels of depression symptoms than

persons who live in neighbourhood members with few

people of their own race/ethnicity [16]. A review by

Shaw et al. [15] showed consistent finding of the protect-

tion of ethnic density on depression and anxiety. This

protection was also extended to suicide and self harm.

This finding has been supported by other previous stu-

dies. In one study, the smaller the ethnic group, the

higher its hospitalization rate in comparison to both the

rate of other residents in the same area and that of mem-

bers of the same ethnic group living in areas where they

constituted a numerical majority [14]. An extensive study

which analyzed two cross sectional nationally represen-

tative surveys showed that nominally similar measures of

ethnic density perform differently across health outcomes

and measures of experienced ra cis m in the two cou ntr ie s.

In the US, increased Caribbean ethnic density was as-

sociated with improved health including mental health

[26]. Other study which supported our finding was

conducted among millennium group cohort which was a

large prospective study of 18,819 infants and their

18,533 families born in 2000-2002 in the United King-

dom [27]. They found protective effect of ethnic density

for limiting long term illness among Bangladeshi moth-

ers at 5% - 30% density and Pakistani mothers at all

higher densities. However it was unrelated to infant

outcomes.

The Hausa/Fulani ethnic group who w ere of ag e group

30 - 39 years had more definite anxiety than other age

group among the ethnic group. However the other group

who were of age group 30 - 39 years had more definite

anxiety disorder than other age group among same eth-

nicity and among same age group of other ethnic group.

However across gender, female patients reported anxiety

disorder than the male subjects. Marriage appeared to

have significant pathoplastic effects among the Hausa/

Fulani ethnic group.

The mechanism for this protection of ethnic density on

mental health has been related to shared culture, social

networks and social capital [27]. In addition, majority of

the patient being Muslim have attribution hypothesis

which states that everything has been preordained which

may result in attenuation of emotion associated with

chronic illness. Other hypothesis to support reasons why

ethnic minority who were not presently living in own

ethnic group include selective migration, genetic, neuro-

developmental, substance use and psycho social factors

[28]. Migration: Odegaard [29] reported that individuals

who were likely to migrate were due to selective migra-

tion and associated this with poor migration in Norway.

However this was not supported by the findings of Selten

et al. [30] which showed that Surinamese migrants were

more likely than the Dutch had it been all the Surinamese

were brought to Neitherlands. In addition, the in itial neg-

ative symptoms which proceeded schizophrenia would

reduce the likelihood for migration. Genetic: The study

among the black Carribeans suggested that genetic play ed

M. A. Yunusa, A. Obembe / Open Journal of Psychiatry 2 (2012) 292-300 299

little role in the prevalence of psychiatric morbidity and

associated the differences more to environment. Psycho-

social factors such as unfamiliar culture and beliefs, dif-

ferent climate and environment, challenging interactions

with government institutions and new language.

It is imperative to emphasize that the findings in this

study should be interpreted with caution because of some

limitation. For instance, being hospital based it is diffi-

cult to generalize. Also, sample size would appear to be

small. In spite of these limitations, this study supported

the protection role of ethnic density on psychiatric mor-

bidity among patients with HIV infection suggesting that

environmental manipulation could be of benefit in the

management of the patient. Future study which these au-

thors would be eager to carry out, involving larger sam-

ple size from the community is encouraged .

5. ACKNOWLEDGEMENTS

We acknowledge Drs. Gana, G.J., Ango, J.T., and Abdullahi, Z. of the

department community medicine for assisting in the administration of

the questionnaire.

REFERENCES

[1] Bing, E.G., et al. (2001) Psychiatric disorders and drug

use among human immunodeficiency virus-infected adults

in the United States. Archives of General Psychiatry, 58,

721-728. doi:10.1001/archpsyc.58.8.721

[2] Collins, P.Y., Holman, A.R., Freeman, M. and Patel, V.

(2006) What is the relevance of mental health to HIV/

AIDS care and treatment programs in developing coun-

tries? A systematic review. AIDS, 20, 1571-1582.

doi:10.1097/01.aids.0000238402.70379.d4

[3] Ciesla, J.A. and Roberts, J.E. (2001) Meta analysis of the

relationship between HIV infection and risk for depres-

sive disorders. American Journal of Psychiatry, 158, 725-

730. doi:10.1176/appi.ajp.158.5.725

[4] Bing, E.G., Burnam, M.A., Longshore, D., Fleishman,

J.A., Sherbourne, C.D., London, A.S., Turner, B.J., Eg-

gan Ferd, M.A., Beckma n, R., Vitiello, B., Morton Sally,

C., Maria, O., Bozzette, S.A., Ortiz-Barron, L. and Sha-

piro, M. (2001) Psychiatric disorders and drug use among

human immunodeficiency virus-infected adults in the

United States. Archives of General Psychiatry, 58, 721-

728. doi:10.1001/archpsyc.58.8.721

[5] Maj, M., et al. (1994) WHO neurop sychiatric AIDS study,

cross-sectional phase I. Study design and psychiatric find-

ings. Archives of General Psychiatry, 51, 39-49.

doi:10.1001/archpsyc.1994.03950010039006

[6] Evans, S., Ferrando, S., Sewell, M., Goggin, K., Fishman,

B. and Rabkin, J. (1998) Pain and depression in HIV ill-

ness. Psychosomatics, 39, 528-535.

doi:10.1016/S0033-3182(98)71285-X

[7] Rabkin, J.G., Goetz, R.R., Remien, R.H., Williams, J.B.,

Todak, G. and Gorman, J.M. (1997) Stability of mood

despite HIV illness progression in a group of homosexual

men. American Journal of Psychiatry, 154, 1632-1633.

[8] Perkins, D.O., Stern, R.A., Golden, R.N., Murphy, C.,

Naftolowitz, D. and Evans, D.L. (1994) Mood disorders

in HIV infection: Prevalence and risk factors in a none-

picenter of the AIDS Epidemic. American Journal of Psy-

chiatry, 151, 233.

[9] Adewuya, A.O., Afola bi, M.O., Ola, B.A., Ogundele, O. A.,

Ajibare, A.O. and Oladipo, B.F. (2007) Psychiatric dis-

orders among the HIV-positive population in Nigeria: A

control study. Journal of Psychosomatic Research, 63,

203-206. doi:10.1016/j.jpsychores.2007.03.006

[10] Farinpour, R., et al. (2003) Psychosocial risk factors of

HIV morbidity and mortality: Findings from the Multi-

center AIDS Cohort Study (MACS). Journal of Clinical

and Experimental Neuropsychology, 25, 654-670.

doi:10.1076/jcen.25.5.654.14577

[11] Carrico, A.W., et al. (2011) Psychiatric risk factors for

hiv disease progression: The role of inconsistent patterns

of antiretroviral therapy utilization. Journal of Acquired

Immune Deficiency Syndromes, 56, 146-150.

doi:10.1097/QAI.0b013e318201df63

[12] Leserman, J., et al. (1995) Progression to AIDS: The ef-

fects of stress, depressive symptoms, and social support.

Psychosomatic Medicine, 61, 397-406.

[13] Ironson, G., et al. (2005) Psychosocial factors predict

CD4 and viral load change in men and women with hu-

man immunodeficiency virus in the era of highly active

antiretroviral treatment. Psychosomatic Medicine, 67, 1013-

1021. doi:10.1097/01.psy.0000188569.58998.c8

[14] Rabkin, J.G. (1979) Ethnic density and psychiatric hospi-

talization: Hazards of minority status. American Journal

of Geriatric Psychiatry, 136, 1562-1566.

[15] Shaw, R., et al. A review of the impact of ethnic density

on adult mental disorders. British Journal of Psychiatry,

in Press.

[16] Halpern, D. and Nazroo, J. (2000) The ethnic density ef-

fect: Results from a national community survey of Eng-

land and Wales. International Journal of Social Psy-

chiatry, 46, 34-46. doi:10.1177/002076400004600105

[17] Yunusa, M.A., Obembe, A., Ibrahim, M.T.O. and Njoku,

C.H. (2011) Prevalence and specific psychosocial factors

associated with substance use and psychiatric morbidity

among patients with HIV infection at Usmanu Danfodiyo

University Teaching Hospital, Sokoto State, Nigeria. Af-

rican Journals of Drugs and Alcohol Studies, 10, 11-16.

[18] Zigmond, A.S. and Snaith, R.P. (1983) The hospital an-

xiety and depression scale. Acta Psychiatrica Scandina-

vica, 67, 361-370.

[19] Abiodun, O.A. (1994) A validity study of the hospital

anxiety and depression scale in general hospital units and

a community sample in Nigeria. The British Journal of

Psychiatry, 165, 669-672. doi:10.1192/bjp.165.5.669

[20] Fatoye, F.A. , Mosaku, K.S., Komolafe, M. and Adewuya,

A.O. (2006) Interictal anxiety and depression symptoms

in Nigerians with epilepsy: A controlled study. Epilepsy &

Behavior, 9, 312-316.

[21] Savard, J., Laberge, B., Gauthier, J.G. and Bergeron, M.G.

(1999) Screening clinical depression in HIV-seropositive

M. A. Yunusa, A. Obembe / Open Journal of Psychiatry 2 (2012) 292-300

300

OPEN ACCESS

patients using the hospital anxiety and depression scale.

AIDS and Behavior, 3, 167-175.

doi:10.1023/A:1025444225120

[22] Grant, B.F., Stinson, F.S., Dawson, D.A., Chou, S.P., Du-

four, M.C., Compton, W., Pickering, R.P. and Kaplan,

K.B.S. (2004) Prevalence and co-occurrence of substance

use disorders and independent mood and anxiety disor-

ders: Results from the national epidemiologic survey on

alcohol and related conditions. Archives of General Psy-

chiatry, 61, 807-816. doi:10.1001/archpsyc.61.8.807

[23] Katherine, F.M.M. and Sylvia, F.K. (2010) Prevalence of

depression and anxiety disorders in HIV-positive outpa-

tients in rural Tanzania. AIDS Care, 22, 415-419.

doi:10.1080/09540120903253981

[24] Chandra, P.S., Ravi, V., Desai, A. and Subbakrishna, D.K.

(1998) Anxiety and depression among hiv-infected het-

erosexuals—A report from India. Journal of Psychoso-

matic Research, 45, 401-409.

doi:10.1016/S0022-3999(98)00028-2

[25] Kessler, R.C., Andrews, G., Colpe, L.J., Hiripi, E., Mroc-

zek, D.K., Normand, S.L., Walters, E.E. and Zaslavsky,

A.M. (2002) Short screening scales to monitor population

prevalences and trends in non-specific psychological dis-

tress. Psychological Medicine, 32, 959-976.

doi:10.1017/S0033291702006074

[26] Bécares, L., Nazroo, J., Jackson, J. and Heuvelman, H.,

(2012) Ethnic density effects on health and experienced

racism among Caribbean people in the US and England:

A cross-national comparison. Social Science & Medicine,

30, 1-9.

[27] Pickett, K., Shaw, R., Atkin, K., Kiernan, K. and Wilkin-

son, R. (2009) Ethnic density effects on maternal and in-

fant health in the Millennium Cohort Study. Social Sci-

ence & Medicine, 69, 1476-1483.

doi:10.1016/j.socscimed.2009.08.031

[28] Morgan, C., Charalambides, M., Hutchinson, G. and Mur-

ray, R.M. (2010) Migration, ethnicity, and psychosis: To-

ward a sociodevelopmental model. Schizophrenia Bulle-

tin, 36, 655-664. doi:10.1093/schbul/sbq051

[29] Ødegaard, Ø. (1932) Emigration and insanity. Acta Psy-

chiatrica et Neurologica Scandinavica. Supplementum, 4,

1-206.

[30] Selten, J.P., Slaets, J.P. and Kahn, R.S. (1997) Schizo-

phrenia in Surinamese and Dutch Antillean immigrants to

the Netherlands: Evidence of an increased incidence. Psy-

chological Medicine, 27, 807-811.

doi:10.1017/S0033291797005199