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  • Research article
  • Open Access
  • Open Peer Review

Depression, suicidality, and alcohol use disorder among people living with HIV/AIDS in Nigeria

  • 1Email author,
  • 2,
  • 2,
  • 3,
  • 4 and
  • 4
BMC Public HealthBMC series – open, inclusive and trusted201717:542

https://doi.org/10.1186/s12889-017-4467-5

©  The Author(s). 2017

  • Received: 20 December 2016
  • Accepted: 25 May 2017
  • Published:
Open Peer Review reports

Abstract

Background

People Living with HIV/AIDS (PLHIV) face various day-to-day and long-term personal, interpersonal, social, physical and psychological challenges as a result of, and in addition to the health conditions they are susceptible to due to their HIV status. There is a dearth of large-scale research to provide robust prevalence estimates of mental health problems among PLHIV, especially in Nigeria. This study aimed to ascertain the prevalence and factors associated with major depressive episodes, suicidality, and alcohol use disorder among people living with HIV/AIDS in Nigeria.

Methods

A survey of 1187 participants aged 18 years and above was conducted within three HIV treatment centres in Abuja, Nigeria. Depression, suicidality, and alcohol use disorder modules of the WHO World Mental Health Composite International Diagnostic Interview questionnaire were used for this study. A socio-demographic questionnaire was also used to collect other health and demographic data. Descriptive statistics (frequency distribution, percentage, mean, median, mode, and standard deviation) and regression analyses were conducted to explore associations between mental health problems and demographic and other health-related factors.

Results

Twelve-month prevalence rates were 28.2% for major depressive episodes, 2.9% for suicidal ideation, 2.3% for suicide attempts, 7.8% for harmful alcohol use, 7.0% for alcohol abuse, and 2.2% for alcohol dependence. Major depressive episodes were significantly associated with having planned suicide and marital status. Suicidal ideation was significantly associated with major depressive episodes, marital status, and religion. Females were less likely to be diagnosed with alcohol disorders.

Conclusions

Some people living with HIV/AIDS also tend to suffer from depression, suicidality, and alcohol use disorders. These findings highlight the need for the integration of mental health services into HIV/AIDS care in Nigeria.

Keywords

  • HIV/AIDS
  • Depression
  • Alcohol use disorder
  • Suicidality
  • Nigeria

Background

Sub-Saharan Africa accounts for about 70% of the global HIV burden with a 4.4% prevalence as of 2015 [1]. Nigeria is the most populous nation in Africa with an estimated population of over 170 million people [2]. HIV prevalence in Nigeria as of 2015 was 3.2% (amounting to about 3.5 million people living with HIV in the country) [3]. The emergence of the HIV/AIDS pandemic brought with it many burdens on the society, health system, families, and the people who are infected with HIV [4]. At the onset of the pandemic, initial interventions focused mainly on how to reduce infection rates and the death rates of those already infected with the virus [4]. Globally, attention is now being increasingly drawn towards improving the quality of life of people living with HIV/AIDS (PLHIV) [5]. This trend is important especially with the positive strides already gained in the fight against AIDS over the years regarding improved anti-retroviral drugs (ARVs), leading to increased life expectancy of people infected with the virus, as well as, reduced rates of new infection [5].

The reason for the shift in the focus of the care for PLHIV is due to the co-morbidity of HIV infection with many other diseases (apart from the established opportunistic infections) which tend to reduce the quality of life of PLHIV. For example, it has been found in various studies within and outside Nigeria that many PLHIV also suffer from depression and other mental disorders [6–16]. Common mental disorders (CMDs) are also more common among PLHIV than in the general population [17, 18]. CMDs have been known to increase disease progression among PLHIV and are the leading cause of disability among PLHIV [17]. Some of the reasons proffered for the higher prevalence of CMDs among PLHIV include decreased adherence to antiretroviral therapy [19], emotional stress associated with the knowledge of one’s HIV-positive status [20], externalized and internalized AIDS-related stigma [21] and a compromised immune system [21].

A systematic review on depression among PLHIV on anti-retroviral therapy (ART) in sub-Saharan Africa reported a pooled estimate of 31.2% (95% CI 25.5–38.2%) prevalence of depressive symptoms among this population [9]. This systematic review included 30 studies from 10 countries in sub-Saharan Africa (three studies were from Nigeria) with a pooled sample size of over 10,000 participants [9]. In a study carried out in Lagos, Nigeria, about 29% of PLHIV were diagnosed with depression using the Hamilton Depression Scale Rating, [15] though this study had a small sample size (n = 87). Depression is linked with a poorer health-related quality of life and poor adherence to drug regimen among PLHIV [6, 22]. In a study carried out in Kano State, Nigeria, with 162 PLHIV aged 15 to 25 years using the Hospital Anxiety and Depression Scale, the prevalence of depression was found to be about 40% [12]. Another study involving 310 PLHIV in the city of Zaria in Kaduna State, using the Centre for Epidemiological Studies Depression Scale (CES-D), found 21% of PLHIV had significant depressive symptoms [22]. The fairly wide variation in the results from studies investigating the prevalence of depression among PLHIV in Nigeria may be partly linked to the sample sizes which are relatively small and the differences in the geographical location where these studies were carried out.

Suicidality, which includes suicidal ideation, self-harm, suicide attempt and completion of suicide [23], is another mental health concern for PLHIV [23–25]. Poor quality of life is a determinant of suicidal ideation among PLHIV [24]. Early identification and treatment of PLHIV with suicidal ideation will help to improve their mental health, adherence to treatment and overall quality of life [26]. In their study of PLHIV in the United States, Carrico et al., and Kalichman et al., found 19% and 26% of their participants reporting suicidal ideation respectively [24, 25]. A study by Chikezie et al. among PLHIV in Benin City, Nigeria, using item 9 of the Beck Depression Inventory version 2 (BDI-II) [27], found that 34.7% (n = 150) of the study participants experienced suicidal ideation in the month prior to the study while 9.3% had attempted suicide 6 months prior to the study [27].

Alcohol use among PLHIV is also an issue of concern to health care and public health professionals because it tends to interfere with the treatment pathway of HIV/AIDS and the infection pathway of the virus [28, 29]. Research has found the misuse of alcohol to be associated with the risk of HIV infection [30] and with risky sexual behaviour among PLHIV [9, 31]. Alcohol use can interfere with the efficacy of ARVs as well as drug adherence, thus reducing the treatment outcome associated with the use of such drugs [32]. Risky sexual behaviours like engaging in unprotected sex and having multiple sexual partners especially by PLHIV are the major drivers of the HIV infection [33]. When carried out with other PLHIV, such risky behaviour can lead to the transmission of drug resistant strains of the virus thus leading to HIV treatment failure [34, 35]. The development of drug-resistant strains of HIV would, in turn, creates the need for more research to develop new drugs which will likely be more expensive [35]. There is limited information on the prevalence of alcohol use disorder among PLHIV in Nigeria. One study involving 399 PLHIV conducted in Abuja, Nigeria using the Alcohol Use Disorders Identification Test (AUDIT) found a 12% prevalence of hazardous alcohol use among this subpopulation [30].

Our study aimed to build on previous studies on the prevalence of depression, suicidality and alcohol use disorder among PLHIV in Nigeria and Sub-Saharan Africa, by providing more robust estimates of the prevalence of these mental disorders using a larger sample size and the use of multiple HIV treatment sites. This study was conducted to provide stronger evidence to inform the provision of mental health care for PLHIV in Nigeria and other similar settings. Studies have shown psychiatric co-morbidity exists both in the general population and among PLHIV in other settings [36–38] hence our investigating the co-morbidity of depression, suicidality and alcohol use disorder in this study. We also investigated demographic and other health-related factors associated with depression, suicidality, and alcohol use disorder among PLHIV in Abuja, Nigeria.

Methods

Study design and setting

This study employed a cross-sectional quantitative survey research design using a structured, interviewer-administered clinical assessment tool, the World Health Organization (WHO) World Mental Health Composite International Diagnostic Interview (WMH-CIDI) questionnaire. The study was conducted in Abuja, Federal Capital Territory (FCT), Nigeria. Nigeria is made up of 36 states and the FCT, Abuja which are further grouped into six geopolitical zones (GPZs). Three GPZs are located in northern Nigeria i.e. North-east, North-central, and North-west GPZs, while southern Nigeria comprises the South-west, South-east and South-south GPZs. Abuja is part of the North-central GPZ. This study was conducted in three HIV treatment centres in Abuja. HIV treatment centres are health centres dedicated to provide anti-retroviral therapy (ART) to PLHIV. These centres are run by government and non-governmental organisations in Nigeria.

Study population

The study was carried out among the PLHIV who were receiving services at HIV treatment centres located in the FCT, Abuja as at January 2015. Based on available records from the National Agency for the Control of AIDS (NACA) in Nigeria, there was an estimated population of 787,282 PLHIV who were either in-care or on ART at 38 dedicated treatment centres in Abuja (excluding HIV treatment sites which cater for the prevention of mother-to-child transmission of HIV).

Study sample

The study sample was drawn from three conveniently-sampled HIV treatment centres located in the FCT. These treatment sites were selected based mainly on the availability of well-kept patient’s records which facilitated the randomization of the study participants and the ability to retrieve contact details of potential study participants. The individual inclusion criteria for participating in this study were: being HIV+, being 18 years and above, and seeking or receiving treatment in one of the three HIV treatment centres involved in this study. The exclusion criteria were: being HIV+ and pregnant, being under the age of 18, and not being able to communicate in English or Hausa languages.

The software Epi-info [39] was used to arrive at a sample size of 1081 for the study using a population size of 787,282 PLHIV in the study area (based on available records from NACA) and with a 99.9% confidence level. Previous prevalence of 31.2% for depression among PLHIV in sub-Saharan Africa [9] was used in the power calculation since depression has the highest prevalence among the three mental disorders this study covers. However, to cater for attrition, 1200 participants were targeted for recruitment in the study.

For each of the study sites, participants were recruited in five sample cohorts. This categorization was done to ensure the recruitment of all categories of PLHIV in order to obtain a representative sample. The five cohorts include patients who:
  1. a)

    Are not on drugs but fall under the “care and monitoring” classification

     
  2. b)

    Have been on ART for less than 1 month

     
  3. c)

    Have been on ART for between one and 6 months

     
  4. d)

    Have been on ART for more than 6 months and

     
  5. e)

    Patients on second-line drugs

     

Sampling procedure

A stratified random sampling design with proportional allocation of the sample [40] was used to ascertain the sample size for each cohort and for each of the study sites. This procedure involved an initial proportional calculation of the sample size for each of the sampled study sites (Table 1) using a target total sample of 1200. This calculation was followed by a proportional calculation of the sample size per cohort per site (Table 1). The five cohorts served as the categories into which participants were stratified. Data of PLHIV registered in each of the study sites were obtained from the Institute of Human Virology, Nigeria (IHVN).
Table 1

Distribution of population of PLHIV and sample size by study site by cohort

Treatment site

Site 1

Site 2

Site 3

Total

Cohort

(Pop.; Sample)

(Pop.; Sample)

(Pop.; Sample)

(Pop.; Sample)

In care

357 (29)

59 (5)

542 (44)

958 (78)

On art for <1 month

40 (3)

30 (2)

980 (79)

1050 (84)

On art for 1 month > × < 6 months

144 (12)

145 (12)

3455 (278)

3744 (302)

On art for >6 months

4653 (375)

1374 (111)

1444 (116)

7471 (602)

On second-line drugs

379 (30)

137 (11)

1152 (93)

1668 (134)

Total (Population; Sample)

5573 (449)

1745 (141)

7573 (610)

14,891 (1200)

Calculation of sample size by study site by cohort

The proportionate sample size for each treatment site was calculated using the formula:

Sample x = Population X/14,891 (total number of PLHIV in the 3 study sites)*1200 (where ‘x’ is the calculated sample size for the study site, and ‘X’ = the total number of clients at that study site).

Systematic sampling technique was then used to select potential participants for the study in each cohort and for each site using the clients’ list provided by the IHVN. Systematic sampling involves the use of a list of the population of potential participants and choosing, in a systematic way, participants who will form the sample of a study [41]. This sampling technique has the advantage of creating a sample that is comprehensive and representative of the population and includes randomization which gives every potential participant equal chance to be selected [41]. Sampled participants were contacted by phone or on their clinic days to join the study at a date and time convenient to them. Also, efforts were made to locate participants whose telephone numbers were unreachable during their scheduled clinic days. Supplementary lists of potential participants were created for each cohort and for each study site. These supplementary lists were used to call up potential participants when the names on the main study lists were exhausted. A total of 1187 participants were interviewed for this study (i.e. 98.9% recruitment rate).

Instruments for data collection

The research instrument used for this study was the interviewer-administered paper and pencil instrument (PAPI, version 7.1) of the WMH-CIDI questionnaire. Specific modules of this instrument relevant for this study were the depression, suicidality, and the alcohol use disorder questionnaires (https://www.hcp.med.harvard.edu/wmhcidi/download-the-who-wmh-cidi-instruments/). The screening section of the WMH-CIDI was merged with a socio-demographic questionnaire created by the research team. Additions made to this section of the CIDI instrument include questions on: participants’ state of origin, number of persons in household, date of first diagnosis of HIV, religion, number of children, highest level of education attained, employment status, estimated monthly household income. A team of researchers from Gede Foundation headed by Cynthia Ticao were trained on how to administer the WMH-CIDI by certified trainers at the University of Ibadan, Nigeria. Members of this team then trained all interviewers who conducted the fieldwork for this study.

The WHO WMH-CIDI has been validated and used for conducting research in many countries [42–44]. A critical review of validity and reliability studies of the CIDI carried out by Wittchen [42] showed that this instrument has been extensively used in clinical and other related research with good-to-excellent kappa coefficients for most of its diagnostic sections as determined by test-retest and inter-rater reliability studies [45, 46]. Wittchen also reported that the CIDI has been judged to be an acceptable instrument for use in various kinds of settings and countries [42]. The WHO WMH-CIDI has also been used in the Nigerian context with acceptable reliability and validity [44]. The Hausa language version of the CIDI used in this study was sourced from Dr. Abdulaziz Muhammad of the Kaduna Psychiatric Hospital, Nigeria who had used it in a previous study [47]. The Hausa version has been previously validated following the World Health Organisation’s protocol for translation and adaptation of research instruments [48] and used for the World Mental Health survey in Nigeria [49, 50].

Data collection procedure

Data collection occurred from June to October, 2015 (18 weeks). Interviewers possessed Bachelor’s degrees in any health-related field/discipline or psychology and at least one-year work experience with a recognized research institution/project. Thirteen interviewers were recruited (10 English speaking and 3 Hausa speaking). After undergoing a five-day training workshop on how to use the CIDI tool and their role as interviewers, interviewers practiced using the instrument for 2 weeks with PLHIV who were not clients receiving treatment from any of the selected treatment sites where the study took place.

Recruiting study participants

The recruitment of study participants was carried out by Site Trackers (STs) who were known by all patients at the treatment sites. STs were staff of the HIV treatment centres recruited to assist in the study by providing logistic support. Six STs were involved in this study. STs were responsible for recruiting participants following a pre-determined procedure contained in the research protocol as follows: STs contacted potential participants telephonically or in person during the patients’ regular clinic appointment with their doctor; STs ascertained potential participant’s eligibility and availability using a Recruitment Form. The form contained the exclusion questions (i.e., age and pregnancy status), appointment dates, and preferred language for the interview during the telephone call or on-site recruitment. STs obtained interim consent from potential participants at this stage after briefing them of what the study is about and their rights to anonymity, confidentiality, and ability to withdraw at any stage of the research.

Data were simultaneously collected in all three study sites within the study area. Three Hausa interviewers conducted interviews for participants who preferred to be interviewed in Hausa language. A total of 3, 2, and 5 interviewers were assigned to sites 1, 2, and 3, respectively according to their relative sample sizes. In addition, one Hausa interviewer was present in each of the three study sites. For quality assurance, weekly site visits were made to all study sites by members of the research team during the period of the fieldwork. One of the interviewers served as on-field Project Coordinator to oversee logistics, recruitment, and to write weekly field reports. A debriefing session was held with interviewers on Fridays of each working week during the period of the fieldwork to ensure quality control throughout the fieldwork exercise. These sessions were used to collect feedback and address any pressing issues faced by interviewers on the field.

Interviewers conducted an average of 91 interviews each (maximum = 118; minimum = 22 interviews) during the entire period of the study. Participants who did not screen positive for depression, suicidality and alcohol use disorder exited the interview earlier and did not proceed to the core modules in accordance with the ‘skip question’ pattern of the CIDI.

Data analysis

Before the analysis, data collected were coded and entered into Microsoft Excel programme. The Excel datasheet was then converted to and cleaned in the Statistical Package for the Social Sciences (SPSS) version 21 [51]. Descriptive statistics (frequency distribution, percentage, mean, median, mode and standard deviation) were first used to explore the data and to present results of prevalence and socio-demographic data. Logistic regression analyses were carried out to ascertain the associations between depression, suicidality, alcohol use disorder, and demographic and health related factors. An alpha level of 0.05 was used for all analyses.

Relationship between depression, suicidality, alcohol use disorder and other key variables

Demographic and health-related variables of interest (Table 4) were initially investigated using Chi Square test and linear regression (for the variable ‘age’ only) to determine which variables had significant relationship with the five dependent variables of interest: major depressive episode, lifetime suicidal ideation, ever planned suicide, alcohol dependence and harmful alcohol abuse. Only variables having significant relationship (at p < .05) with the dependent variables of interest were included in the respective logistic regression models. Direct logistic regression analyses were carried out to explore the strength of the associations between these variables (Table 5).

Results

Demographic details of respondents

Participants in the study came from all six GPZs which is typical of the capital city of Nigeria. A total of 1059 (89.2%) and 128 (10.8%) participants were interviewed in English and Hausa languages, respectively. The sample comprised 66.5% female (n = 789) and 33.5% (n = 398) males. The mean age of participants was 39.3 years (SD = 9.1) with the youngest participant being 18 years, while the oldest was 79 years. The modal age was 35 years (7.8%; n = 93). Number of participants on ART was 1146 (96.5%) while those not on ART were 41 (3.5%). On average, participants reported having five persons per household (SD = 3.27). Twenty-two participants (1.9%) did not know when they were diagnosed of HIV while one participant (0.1%) was diagnosed 25 years ago.

Participants’ state of origin

Participants originated from all the states in Nigeria except two (Lagos and Yobe States). There was also one participant from Togo. The state with the highest number of participants was Benue (n = 198; 16.7%), while the lowest was Sokoto (n = 1; 0.1%). Almost 50% of the participants came from five states: Benue (n = 198; 16.7%); Kaduna (n = 142; 12.0%); Kogi (n = 122; 10.3%); Nasarawa (n = 94; 7.9%) and Enugu (n = 62; 5.2%) States.

Marriage-like relationship

These were participants (usually two adults; male and female) co-habiting and in a relationship which has not been officially solemnized by any form of formal marriage. A total of 16.4% (n = 195) of the participants indicated being in a marriage-like relationship. Other demographic characteristics of the study participants are presented in Table 2.
Table 2

Distribution of socio-demographic and health-related variables

 

Male

Female

Total

Categories

Frequency

Percent

Frequency

Percent

Frequency

Percenta

Age (N = 1174):

 18–25 years

6

.5

34

2.9

40

3.4

 26–35 years

68

5.8

346

29.5

414

35.3

 36–45 years

169

14.4

299

25.5

468

39.9

 46–55 years

111

9.5

78

6.6

189

16.1

 56–65 years

33

2.8

17

1.4

50

4.2

 66–75 years

10

.9

2

.2

12

1.1

  > 75 < 80

1

.1

0

0.0

1

.1

Marital status (N = 1185):

 Married

335

28.3

412

34.8

747

63.1

 Separated

8

.7

62

5.2

70

5.9

 Divorced

4

.3

27

2.3

31

2.6

 Widowed

12

1.0

167

14.1

179

15.1

 Never married

39

3.3

119

10.0

158

13.3

Geopolitical zone of origin (N = 1186):

 North-central

186

15.7

377

31.8

563

47.5

 North-east

22

1.9

40

3.4

62

5.3

 North-west

56

4.7

111

9.4

167

14.1

 South-east

78

6.6

140

11.8

218

18.4

 South-south

39

3.3

90

7.6

129

10.9

 South-west

17

1.4

30

2.5

47

4.0

Religion (N = 1187):

 Christian

321

27.0

659

55.5

980

82.6

 Muslim

75

6.3

128

10.8

203

17.1

 Traditional religion

0

0.0

1

.1

1

.1

 None

1

.1

0

0.0

1

.1

 Others

1

.1

1

.1

2

.2

Highest level of education (N = 1186):

 No education

20

1.7

64

5.4

84

7.1

 Primary education

80

6.7

142

12.0

222

18.7

 Secondary education

142

12.0

299

25.2

441

37.2

 Tertiary education (HND, NCE, OND, BSc, BEd, BA)

133

11.2

265

22.3

398

33.5

 Postgraduate education (MA/MSc/Ph.D.)

23

1.9

18

1.5

41

3.5

Employment status (N = 1186):

 Private sector

66

5.6

98

8.3

164

13.8

 Public sector

124

10.5

159

13.4

283

23.9

 Self-employed

156

13.2

358

30.2

514

43.3

 Unemployed

35

3.0

151

12.7

186

15.7

 Student

3

.3

12

1.0

15

1.3

 Retired

14

1.2

8

.7

22

1.9

 Unable to work

0

0.0

2

.2

2

.2

Estimated monthly household income (N = 1167):

 N19,999 and below

65

5.6

248

21.3

313

26.8

 N20,000 –N49,999

140

12.0

210

18.0

350

30.0

 N50,000 – N79,999

80

6.9

131

11.2

211

18.1

 N80,000 – N119,999

42

3.6

61

5.2

103

8.8

 N120,000 – N499,999

43

3.7

52

4.5

95

8.1

 N500,000 – N999,000

6

.5

2

.2

8

.7

 N1 million and above

2

.2

1

.1

3

.3

 None

15

1.3

69

5.9

84

7.2

Research category (N = 1187):

 Care and monitoring

11

.9

34

2.9

45

3.8

 Started ART on or before Jan. 2015

6

.5

10

.8

16

1.3

 Between August – December 2014

12

1.0

22

1.9

34

2.9

 On or before July 2014

321

27.0

621

52.3

942

79.4

 On second-line drugs

48

4.0

102

8.6

150

12.6

Smoking status (N = 1186):

 Smoker

21

1.8

4

.3

25

2.1

 Ex-smoker

123

10.4

27

2.3

150

12.6

 Never smoker

254

21.4

757

63.8

1011

85.2

Number of years living with HIV (N = 1187):

 20–25 years

4

.3

3

.3

7

.6

 15–19 years

17

1.4

18

1.5

35

3.0

 10–14 years

86

7.2

141

11.9

227

19.5

 5–9 years

149

12.6

365

30.7

514

44.1

 1–4 years

130

11.0

244

20.6

374

32.1

  < 1 year

4

.3

4

.3

8

.7

Don’t know

8

.7

14

1.2

22

1.9

aOnly valid percent reported

Prevalence of depression, suicidality, and alcohol use disorder

Using the Diagnostic and Statistical Manual of Mental Disorders (DSM)-IV diagnostic criteria for 12-month prevalence of major depressive episode, 28.2% (n = 335) of the study participants screened positive for major depressive episode. The prevalence of lifetime suicidal ideation was found to be 14.3% (n = 170), while 12-month suicidal ideation was 2.9% (n = 35). Prevalence of lifetime suicide attempt was 2.9% (n = 34). At least 2.3% of the population (n = 27) have attempted suicide at least once (Table 3). Only one suicide attempt was life-threatening leading to hospitalization (Table 4).
Table 3

Gender distribution of some mental disorders among PLHIV

 

Male

Female

Total

Mental health problem

Frequency

Percent

Frequency

Percent

Frequency

Percent

Major depressive episode

 Yes

81

6.8

254

21.4

335

28.2

 No

317

26.7

535

45.1

852

71.8

 Total

398

33.5

789

66.5

1187

100.0

Lifetime suicidal ideation

 Yes

45

3.8

125

10.5

170

14.3

 No

353

29.7

664

55.9

1017

85.7

 Total

398

33.5

789

66.5

1187

100.0

12-month suicidal ideation

 Yes

8

.7

27

2.2

35

2.9

 No

390

32.8

762

64.3

1152

97.1

 Total

398

33.5

789

66.5

1187

100.0

Ever planned suicide

 Yes

15

1.3

47

4.0

62

5.3

 No

383

32.2

742

62.5

1125

94.7

 Total

398

33.5

789

66.5

1187

100.0

Alcohol dependence (DSM IV)a

 Yes

17

1.4

9

.8

26

2.2

 No

381

32.8

780

65.7

1161

97.8

 Total

398

33.5

789

66.5

1187

100.0

Harmful Alcohol Abuse (ICD-10)a

 Yes

70

5.9

13

1.1

83

7.0

 No

328

27.6

776

65.4

1104

93.0

 Total

398

33.5

789

66.5

1187

100.0

aPrevalence of all alcohol disorders are for a 12-month period

Table 4

Suicidality among PLHIV

Variable (n)

Categories

Frequency (%)a

Lifetime suicidal ideation (1187)

Yes

170 (14.3)

No

1017 (85.7)

Age at first suicidal ideation (170)

Mean age

29.6 years

Age range

10–66 years

12-month suicidal ideation (169)

Yes

35 (20.7)

No

134 (79.3)

Age at last suicidal ideation (138)

Mean age

29.3 years

Age range

11–53 years

Lifetime planned suicide (170)

Yes

62 (36.5)

No

108 (63.5)

Age at first suicidal planning (64)

Mean age

28.2 years

Age range

11–51 years

12-month planned suicide (65)

Yes

8 (12.3)

No

57 (87.7)

Age at most recent suicidal planning (57)

Mean age

28.2 years

Age range

11–51 years

Lifetime suicide attempt (170)

Yes

34 (20.0)

No

136 (80.0)

Number of suicide attempts (34)

Modal times

Once (n = 27; 79.4%)

Range

1–8 times

Age first suicide attempt (7)

Mean age

30.6 years

Age range

23–43 years

Describe suicide attempt (8)

Made a serious attempt to commit suicide

6 (75.0)

Suicide attempt was a cry for help

2 (25.0)

12-month suicide attempts (33)

Yes

4 (12.1)

No

29 (87.9)

Age last suicide attempt (29)

Mean age

17–43 years

Age range

27.7 years

Lethality (1)

Yes

1

Describe suicide attempt (32)

Made a serious attempt to commit suicide but was lucky it was unsuccessful

22 (66.7)

 

Attempted suicide but knew that the method was not fool proof

3 (9.1)

 

Suicide attempt was a cry for help, did not intend to die

7 (21.2)

Suicide method (5)

Used sharp instruments

1

poisoning e.g. Carbon monoxide (CO), rat poison

2

other

1

Overdose of other drugs (e.g. alcohol, heroin, crack)

1

aOnly valid percent reported

The 12-month prevalence of alcohol abuse (for both DSM-IV and the International Classification of Diseases (ICD)-10 criteria) was 7% (n = 83), while twenty-six (2.2%) of the participants met the DSM-IV criteria for alcohol dependence within the last 12 months. The12-month prevalence of harmful alcohol abuse (ICD-10 criteria) was 7% (n = 83) (Table 3).

Gender distribution of depression, suicidality, and alcohol use disorder

Females living with HIV were found to have a higher prevalence of major depressive episode and suicidality (suicidal ideation and suicide plan) than their male counterpart. However, for 12-month alcohol disorders (alcohol dependence and harmful alcohol abuse), the prevalence was found to be higher among males living with HIV than among females. Table 3 presents the distribution of mental health problems among PLHIV by gender.

Factors associated with depression, suicidality, and alcohol use disorder

Depression

Major depressive episode

The model to explore the association between major depressive episode and age, gender, marital status, marriage-like relationship, monthly income, lifetime suicidal ideation and ever planned suicide was statistically significant, X 2 (12, N = 167) = 21.15, p < .05. Major depressive episode was significantly associated with ever planned suicide (OR = 2.46, 95% CI [1.23, 4.95]), being in a marriage-like relationship (OR = .33, 95% CI [.11, .96]), and never married (OR = 2.81, 95% CI [1.11, 7.15]). Participants who reported ever planning suicide were about 2 times more likely to be diagnosed with major depressive episode than those who have never planned suicide (Table 5). Also, participants who reported being in a marriage-like relationship were 3 times less likely to have major depressive episode than those not in a marriage-like relationship, while those who were never married were almost 3 times more likely to have major depressive episode than those who were married.
Table 5

Correlates of depressive episode, suicidal ideation, ever planned suicide, alcohol dependence and harmful alcohol abuse

Dependent variables

Major Depressive Episode

Lifetime suicidal ideation

Ever planned suicide

Alcohol dependence

Harmful Alcohol Abuse

Independent variables

OR [95% CI]*

OR [95% CI]*

OR [95% CI]*

OR [95% CI]*

OR [95% CI]*

Gender

   

Female (.32 [.13, .76])

Female (.10 [.05, .19])+

Religion

 

Christian (2.41 [1.36, 4.26])

  

Christian (3.44 [1.43, 8.27])

Being in a marriage-like relationship

.33 [.11, .96]

    

Marital status

Never married (2.81 [1.11, 7.15])

Separated (3.05 [1.67, 5.57])+

   

Divorced (2.66 [1.07, 6.63])

Never married (1.94 [1.22, 3.09])

Overall physical health

 

.49 [.29, .84]

   

Major depressive episode

 

1.84 [1.29, 2.62]

2.37 [1.25, 4.51]

  

Ever planned suicide

2.46 [1.23, 4.95]+

    

* p < 0.05; +best predictor in the mode

Suicidality

Lifetime suicidal ideation

The model to explore the strength of the relationship between lifetime suicidal ideation and age, gender, marital status, religion, overall physical health and major depressive episode was statistically significant, X 2 (9, N = 1168) = 59.36, p < .001. Lifetime suicidal ideation was significantly associated with marital status: being separated (OR = 3.05, 95% CI [1.67, 5.57]), never married (OR = 1.94, 95% CI [1.22, 3.09]), and divorced (OR = 2.66, 95% CI [1.07, 6.63]), as well as, being Christian (OR = 2.41, 95% CI [1.36, 4.26]), major depressive episode (OR = 1.84, 95% CI [1.29, 2.62]), and overall physical health (OR = .49, 95% CI [.29, .84]). Participants who have separated from their partners were 3 times more likely to report ever having suicidal ideation than those married. Also, participants who were divorced were about 2 times more likely to report having suicidal ideation than those married while participants who were never married were 94% of the times more likely to report having suicidal ideation than those married (Table 5).

Ever planned suicide

The model to explore the strength of the association between ever planned suicide and major depressive episode was statistically significant, X 2 (1, N = 170) = 7.07, p < .008. The model had only one variable (major depressive episode) which was found to be associated with ever planned suicide. Major depressive episode is significantly associated with ever planned suicide with an unadjusted OR of 2.37 (95% CI [1.25–4.51]). Participants who were diagnosed with major depressive episode were 2 times more likely to report ever planning a suicide (Table 5).

Alcohol use disorder

Alcohol dependence

The model to explore the association between alcohol dependence, age, and gender was statistically significant, X 2 (2, N = 1174) = 12.23, p = .002. Of the two variables in the model, only gender was significantly associated with alcohol dependence (OR = .32, 95% CI [.13, .76]). Female participants were about 3 times less likely to be alcohol dependent based on the DSM-IV diagnostic criteria (Table 5).

Harmful alcohol abuse

The model to explore the association between harmful alcohol abuse and age, gender, marital status, religion, and educational qualification was statistically significant, X 2 (8, N = 1167) = 116.42, p < .001. Harmful alcohol abuse was significantly associated with gender (being female) (OR = .10, 95% CI [.05, .19]) and religion (Christian) OR = 3.44, 95% CI (1.43, 8.27). Female participants were 10 times less likely to be diagnosed with harmful alcohol abuse, while participants who reported being Christians were 3 times more likely to be diagnosed with harmful alcohol abuse (Table 5).

Discussion

In the largest study to date of people living with HIV in Nigeria, we found that nearly one out of three PLHIV suffered from depression during the past year. This burden was greatest among women living with HIV, with one out of three female PLHIV experiencing depression compared to one out of five male PLHIV. Ferrari et al., reported a 5.5% average prevalence of depression in Sub-Saharan Africa [52], while Abas et al., reported 8.8% for the same region [53]. Our findings show a prevalence rate four times greater than general population rates for depression in Sub-Saharan Africa. In our study, major depressive episode was associated with not being in a marriage-like relationship, never been married, and prior suicide plan. A previous study in France found a similar prevalence (28.1%) of major depressive episode among PLHIV [54]. Consistent with the findings in our study, a cross national study involving 10 countries in North America, Asia, Europe and Latin America found that major depressive episode was more common among women than men and among the unmarried than the married [55]. A study conducted in Canada also found a positive association between women and unmarried persons with depression [56] as with this study. The implication of this finding for the population of PLHIV is that depression has been associated with poor adherence to ART and disease progression among PLHIV [57]. The high prevalence of depression among PLHIV found in this study compared to the regional prevelence speaks to the need for mental health screening and treatment services to be integrated in the treatment package offered to PLHIV which will ultimately lead to better clinical outcomes for PLHIV [58]. Targeted and gender-specific interventions to prevent major depressive episode will also be a useful addition to HIV treatment guidelines.

This study found a prevalence of 14.3% for suicidal ideation among PLHIV. This result is slightly lower than the 15.5% found in a similar population in Ibadan, Nigeria using the CIDI instrument [26]. Lifetime suicide attempt in our study was 2.9% which is lower than the 3.9% found in a similar study in Uganda [59]. Suicidal ideation among PLHIV has been linked to poor social support and unemployment [26, 60]. In our study, 20% of those who had suicidal ideation had attempted suicide. Suicidal ideation was significantly associated with being Christian, being separated, divorced, never been married, poorer overall physical health, and major depressive episode. Suicide attempt is an indicator of extreme emotional distress and a predictor of completed suicide [26]. Previous studies have found associations between depression and suicidality [26, 59], as well as with living alone and suicidal thoughts [60]. Suicidal ideation and suicide attempts are sometimes made by PLHIV as means to cope or escape from the psychological stress they face due to their HIV status [60] and suicidality has been linked to poor quality of life for PLHIV [59]. Regular assessment leading to early identification of PLHIV with increased risks of suicidality has been recommended in order to quicken their referral for psychological treatments [23–25, 27].

The prevalence of alcohol abuse found in this study was 7% while about 8% of the participants screened positive for harmful alcohol abuse. Being male was significantly associated with both alcohol dependence and harmful alcohol abuse, while being Christian was associated with harmful alcohol abuse. A similar study among PLHIV in Ethiopia using the AUDIT tool found a prevalence of 2.8% and 5.1% of harmful drinking and alcohol dependence, respectively [61]. This Ethiopian study also found an association between being male and being Christian with alcohol use disorder [61]. Galvan et al. found a rate of 8% in their study of drinking problems among PLHIV [62]which is consistent with findings from our study.

Among PLHIV, alcohol abuse has been associated with depression [63], non-adherence and reduced response to ART [9, 29], as well as, increased risk of engaging in risky behaviour [64, 65]. Any intervention to reduce the prevalence of alcohol disorder among this population will be beneficial to the overall treatment outcome including reducing HIV infection rates and improving the quality of life of PLHIV. Such interventions can be tailored according to gender since males are more likely be diagnosed with alcohol use disorder [61].

This study provides more evidence for the call to prioritize mental health care services for PLHIV [18]. Such services should begin with the screening for mental disorders at HIV treatment centres. One common problem associated with the provision of comprehensive mental health care services for PLHIV, especially in low-resource settings, is the shortage of specialist mental health care service providers [57]. Chibanda et al. suggest the training of lay health workers to provide basic mental health screening and treatment services in health settings to make up for the scarcity of specialist mental health care service providers in this setting [66]. In support of the study by Chibanda et al., a systematic review of lay counsellors’ role in providing care in primary health care settings, found that lay counsellors have the potential to effectively provide some basic health services for CMDs such as brief counselling [57]. Screening and treatment services for mental disorders can be provided as ancillary services in HIV treatment centres and by trained lay counsellors [57]. However, in general, best practice guidelines stress the importance of using culturally adapted and validated instruments to ensure accurate diagnosis [67].

In the same vein, more qualitative research is needed to explore the causes of mental health problems among PLHIV given the fact that the rates of mental health problems in this subpopulation have been found to be higher than the general population in diverse settings [18, 54]. Such research will be helpful to inform tailored interventions to prevent mental health problems among PLHIV.

The Mental Health Gap Action Programme (mhGAP) was developed by the WHO with the objective of scaling up care for mental, neurological and substance use disorders (MNS) disorders in low and middle-income countries (LMIC) [68]. One identified approach to achieving success with mhGAP is increasing the commitment of all stakeholders towards achieving higher coverage of care for MNS in LMIC [69]. In line with the objectives of mhGAP, we make the following suggestions to improve mental health care for PLHIV.

  • Mental health services should be incorporated into HIV treatment guidelines. Such services should include screening for mental disorders like depression, suicidality, and alcohol use disorder with the use of culturally adapted tools.

  • Rehabilitation services and facilities to treat alcohol abuse should be provided for PLHIV suffering from alcohol use disorder.

  • Support groups for PLHIV should pay attention to the mental health needs of their members so as to prevent and/or identify the onset of mental health problems before they progress to more severe disorders.

Limitations

Not all potential participants who were initially systematically sampled for this study could be contacted due to out-of-date contact details in clinic records. Some participants were therefore contacted during their clinic days. Also, there was a disparity between the actual study category into which participants fell and what the list obtained from the study sites indicated. The category reported by the participants was used for the data analysis. Gender was not considered during the sampling exercise because the client information obtained from the IHVN did not include their gender. It was, therefore, not feasible to know which participant was of a specific gender during the sampling exercise. The data collected in this study did not lend themselves to the determination of other forms of clinical depression i.e. major depressive disorder and minor depressive disorder. Our data are based on self-report which can introduce social desirability bias. However, as noted in the declaration section (ethics approval and consent to participate), measures were taken to mitigate this potential type of bias.

Conclusion

Our study found a higher prevalence of depression among PLHIV in Nigeria than the regional prevalence of depression reported for Sub Saharan Africa in 2013 [52]. Women were more likely to report depression and suicidality than men, while men were more likely to meet the criteria for alcohol use disorders than women. In addition to ARTs being offered to PLHIV, it is critical that screening services for early detection of mental disorders be integrated into HIV testing and treatment guidelines. Psychosocial and medical help should be given to those who screen positive for mental disorders. HIV treatment services need to move towards the provision of more holistic care for PLHIV as a necessary next step to improve the quality of life of this sub-population.

Abbreviations

ART: 

Anti-Retroviral therapy

ARVs: 

Anti-Retroviral drugs (ARVs)

AUDIT: 

Alcohol Use Disorders Identification Test

BDI-II: 

Beck Depression Inventory version 2 (BDI-II)

CES-D: 

Centre for Epidemiological Studies Depression Scale

CMDs: 

Common Mental Disorders

DSM: 

Diagnostic and Statistical Manual of Mental Disorders

FCT: 

Federal Capital Territory

GPZs: 

Geopolitical Zones

HIV/AIDS: 

Human Immunodeficiency Virus/Acquired Immune-Deficiency Syndrome

ICD: 

International Classification of Diseases

IHVN: 

Institute of Human Virology Nigeria

LMIC: 

Low and middle-income countries

mhGAP: 

Mental Health Gap Action Programme

MNS: 

Mental, neurological and substance use disorders

NACA: 

National Agency for the Control of AIDS

PAPI: 

Paper and pencil instrument

PLHIV: 

People living with HIV/AIDS

SPSS: 

Statistical Package for the Social Sciences

STs: 

Site trackers

WHO: 

World Health Organization

WMH-CIDI: 

World Mental Health Composite International Diagnostic Interview

Declarations

Acknowledgements

The authors are grateful to Drs. Nadra Lisha and Kwaku Oppong Asante who provided guidance at various stages of data analysis. Dr. Anne Berit Petersen is also appreciated for her feedback on an initial draft of this paper. We also acknowledge the interviewers and staff of the HIV treatment centres where this study was conducted.

Funding

This study was funded by Gede Foundation Nigeria, a non-governmental organization working with the underserved population suffering from stigmatized health burdens in Nigeria including people living with HIV/AIDS and mental disorders.

Availability of data and materials

The datasets used and/or analyzed during the current study are available from Gede Foundation Nigeria on reasonable request and subject to the Foundation’s policies on data sharing.

Authors’ contributions

COE prepared the research protocol with contributions from CJT and JGM and wrote the first draft of this paper. CJT, JGM, PSD and EE were involved in data collection and provided useful feedback on the first draft. BAK provided useful feedback on the first and subsequent drafts. All authors read and approved the final draft.

Competing interests

JGM and CJT work for Gede Foundation Nigeria. The authors declare that they have no other competing interests.

Consent for publication

Not applicable.

Ethics approval and consent to participate

Ethical approval to conduct this study was obtained from the Institute of Human Virology Nigeria (IHVN) Health Research Ethics Committee on June 10, 2015. Copies of the Ethics approval and the approved research protocol were provided to each project site through their Medical Director.

After obtaining initial consent from eligible participants during the recruitment exercise, a formalization of this consent was required of each participant by their respective interviewers. Prior to the formal interview, interviewers handed the study information sheet to each participant and verbally informed them about the content of the sheet. Interviewers again emphasized to each of the participants the purpose of the study, their rights to confidentiality, anonymity, and withdrawal from the study at any stage if they decide to participate. They were again assured that their care would not be affected by their answers. Each participant was then asked to sign the consent form (or affix a thumb mark) as an attestation to their willingness to participate in the study. Each participant was assigned a code name as means of identification to ensure anonymity, and this code name was written by the interviewer on the answer booklet. Each participant was given snacks and the sum of N1,000 as compensation for transportation.

To ensure the participants’ privacy was maintained, interviews were conducted in private rooms within the study sites. Interviewers were trained to keep all interview content confidential. Two participants experienced distress during the interview and were referred to the hospital psychiatrist for immediate care as per protocol.

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Authors’ Affiliations

(1)
Center for Tobacco Control Research and Education, University of California San Francisco, 530 Parnassus Avenue, Suite 366, San Francisco, CA 94143, USA
(2)
Institute of Human Virology, Nigeria, 252 Herbert Macaulay Way, Central Business District, Abuja, Nigeria
(3)
Duke Global Health Institute & Department of Psychiatry, Duke University, Box 90519, Durham, NC 27708, USA
(4)
Gede Foundation Nigeria, 13 Danube Street, Abuja, Nigeria

References

  1. Global Health Observatory (GHO) data - HIV/AIDS [http://www.who.int/gho/hiv/en/.]
  2. Nigeria: WHO statistical profile [http://www.who.int/gho/countries/nga.pdf?ua=1.]
  3. HIV and AIDS in Nigeria [ http://www.avert.org/professionals/hiv-around-world/sub-saharan-africa/nigeria.]
  4. Whiteside A. HIV/AIDS: a very short introduction. Oxford: Oxford University Press; 2008.View ArticleGoogle Scholar
  5. Oguntibeju OO: Quality of life of people living with HIV and AIDS and antiretroviral therapy. HIV/Aids (Auckland, NZ) 2012, 4:117.Google Scholar
  6. Adewuya AO, Afolabi MO, Ola BA, Ogundele OA, Ajibare AO, Oladipo BF, et al. Relationship between depression and quality of life in persons with HIV infection in Nigeria. Int J Psychiatry Med. 2008;38(1):43–51.View ArticlePubMedGoogle Scholar
  7. Gonzalez JS, Batchelder AW, Psaros C, Safren SA. Depression and HIV/AIDS treatment nonadherence: a review and meta-analysis. J Acquir Immune Defic Syndr. 2011;58(2):181–7.View ArticlePubMedGoogle Scholar
  8. Gupta R, Dandu M, Packel L, Rutherford G, Leiter K, Phaladze N, et al. Depression and HIV in Botswana: a population-based study on gender-specific socioeconomic and behavioral correlates. PLoS One. 2010;5(12):e14252.View ArticlePubMedPubMed CentralGoogle Scholar
  9. Nakimuli-Mpungu E, Bass JK, Alexandre P, Mills EJ, Musisi S, Ram M, et al. Depression, alcohol use and adherence to antiretroviral therapy in sub-Saharan Africa: a systematic review. AIDS Behav. 2012;16(8):2101–18.View ArticlePubMedGoogle Scholar
  10. Ndu A, Arinze-Onyia S, Aguwa E, Obi I. Prevalence of depression and role of support groups in its management: a study of adult HIV/AIDS patients attending HIV/AIDS clinic in a tertiary health facility in South-eastern Nigeria. J Public Health Epidemiol. 2011;3(4):182–6.Google Scholar
  11. Olley B, Seedat S, Nei D, Stein D. Predictors of major depression in recently diagnosed patients with HIV/AIDS in South Africa. AIDS Patient Care STDs. 2004;18(8):481–7.View ArticlePubMedGoogle Scholar
  12. Sale S, Gadanya M. Prevalence and factors associated with depression in HIV/AIDS patients aged 15–25 years at Aminu Kano teaching hospital, Nigeria. J Child and Adolesc Mental Health. 2008;20(2):95–9.View ArticleGoogle Scholar
  13. Savard J, Laberge B, Gauthier JG, Bergeron MG. Screening clinical depression in HIV-seropositive patients using the hospital anxiety and depression scale. AIDS Behav. 1999;3(2):167–75.View ArticleGoogle Scholar
  14. Sherr L, Clucas C, Harding R, Sibley E, Catalan J. HIV and depression–a systematic review of interventions. Psychol Health Med. 2011;16(5):493–527.View ArticlePubMedGoogle Scholar
  15. Igie I, Udoh M: Prevalence of depression in HIV/AIDS patients, Lagos state university hospital (LUTH), Lagos, Nigeria. International AIDS society. In: 6th IAS conference on HIV Pathogenesis, Treatment and Prevention: Rome, Italy: July 17–20, 2011.Google Scholar
  16. Adewuya AO, Afolabi MO, Ola BA, Ogundele OA, Ajibare AO, Oladipo BF. Psychiatric disorders among the HIV-positive population in Nigeria: a control study. J Psychosom res. 2007;63(2):203–6.View ArticlePubMedGoogle Scholar
  17. Chibanda D, Cowan F, Gibson L, Weiss HA, Lund C. Prevalence and correlates of probable common mental disorders in a population with high prevalence of HIV in Zimbabwe. BMC Psychiatry. 2016;16(1):55.View ArticlePubMedPubMed CentralGoogle Scholar
  18. Brandt R. The mental health of people living with HIV/AIDS in Africa: a systematic review. Afr J AIDS Res. 2009;8(2):123–33.View ArticlePubMedGoogle Scholar
  19. Primeau MM, Avellaneda V, Musselman D, St Jean G, Illa L. Treatment of depression in individuals living with HIV/AIDS. Psychosomatics. 2013;54(4):336–44.View ArticlePubMedGoogle Scholar
  20. Kidia K, Machando D, Bere T, Macpherson K, Nyamayaro P, Potter L, et al. ‘I <?show [?A3B2 twb=.27w?]?><?show [?A3B2 tlsb=-.09pt?]?>was thinking too much’: experiences of HIV-positive adults with common mental disorders and poor adherence to antiretroviral therapy in Zimbabwe. Tropical med Int Health. 2015;20(7):903–13.View ArticleGoogle Scholar
  21. Yi S, Chhoun P, Suong S, Thin K, Brody C, Tuot S. AIDS-related stigma and mental disorders among people living with HIV: a cross-sectional study in Cambodia. PLoS One. 2015;10(3):e0121461.View ArticlePubMedPubMed CentralGoogle Scholar
  22. Olisah V, Baiyewu O, Sheikh T. Adherence to highly active antiretroviral therapy in depressed patients with HIV/AIDS attending a Nigerian university teaching hospital clinic: original article. Afr J Psychiatry. 2010;13(4):275–9.View ArticleGoogle Scholar
  23. Catalan J, Harding R, Sibley E, Clucas C, Croome N, Sherr L. HIV infection and mental health: suicidal behaviour–systematic review. Psychol Health Med. 2011;16(5):588–611.View ArticlePubMedGoogle Scholar
  24. Carrico AW, Johnson MO, Morin SF, Remien RH, Charlebois ED, Steward WT, et al. Correlates of suicidal ideation among HIV-positive persons. Aids. 2007;21(9):1199–203.View ArticlePubMedGoogle Scholar
  25. Kalichman SC, Heckman T, Kochman A, Sikkema K, Bergholte J. Depression and thoughts of suicide among middle-aged and older persons living with HIV-AIDS. Psychiatr Serv. 2000;51(7):903–7.View ArticlePubMedGoogle Scholar
  26. Oladeji BD, Taiwo B, Mosuro O, Fayemiwo SA, Abiona T, Fought AJ, Robertson K, Ogunniyi A, Adewole IF: Suicidal Behavior and Associations with Quality of Life among HIV/AIDS-Infected Patients in Ibadan, Nigeria. Journal of the International Association of Providers of AIDS Care. 2015.Google Scholar
  27. Chikezie U, Otakpor A, Kuteyi O, James B. Suicidality among individuals with HIV/AIDS in Benin City, Nigeria: a case-control study. AIDS Care. 2012;24(7):843–5.View ArticlePubMedGoogle Scholar
  28. Neuman MG, Schneider M, Nanau RM, Parry C. Alcohol consumption, progression of disease and other comorbidities, and responses to antiretroviral medication in people living with HIV. AIDS Res Treat. 2012;2012:751827.PubMedPubMed CentralGoogle Scholar
  29. Hahn JA, Woolf-King SE, Muyindike W. Adding fuel to the fire: Alcohol’s effect on the HIV epidemic in sub-Saharan Africa. Current HIV/AIDS Reports. 2011;8(3):172.View ArticlePubMedGoogle Scholar
  30. Farley J, Miller E, Zamani A, Tepper V, Morris C, Oyegunle M, et al. Screening for hazardous alcohol use and depressive symptomatology among HIV-infected patients in Nigeria: prevalence, predictors, and association with adherence. J Int Assoc Physicians in AIDS Care (JIAPAC). 2010;9(4):218–26.View ArticleGoogle Scholar
  31. Stein M, Herman DS, Trisvan E, Pirraglia P, Engler P, Anderson BJ. Alcohol use and sexual risk behavior among human immunodeficiency virus–positive persons. Alcohol Clin exp res. 2005;29(5):837–43.View ArticlePubMedGoogle Scholar
  32. Lucas GM, Gebo KA, Chaisson RE, Moore RD. Longitudinal assessment of the effects of drug and alcohol abuse on HIV-1 treatment outcomes in an urban clinic. Aids. 2002;16(5):767–74.View ArticlePubMedGoogle Scholar
  33. Morris CN, Levine B, Goodridge G, Luo N, Ashley J. Three-country assessment of alcohol-HIV related policy and programmatic responses in Africa. Afr J Drug Alcohol Stud. 2006;5(2):169–84.Google Scholar
  34. Yerly S, Kaiser L, Race E, Bru JP, Clavel F, Perrin L. Transmission of antiretroviral-drug-resistant HIV-1 variants. Lancet. 1999;354(9180):729–33.View ArticlePubMedGoogle Scholar
  35. Deeks SG. Treatment of antiretroviral-drug-resistant HIV-1 infection. Lancet. 2003;362(9400):2002–11.View ArticlePubMedGoogle Scholar
  36. Dowling NA, Cowlishaw S, Jackson AC, Merkouris SS, Francis KL, Christensen DR. Prevalence of psychiatric co-morbidity in treatment-seeking problem gamblers: a systematic review and meta-analysis. Aust N Z J Psychiatry. 2015;49(6):519–39.View ArticlePubMedPubMed CentralGoogle Scholar
  37. Kessler R, Adler L, Berglund P, Green JG, McLaughlin K, Fayyad J, et al. The effects of temporally secondary co-morbid mental disorders on the associations of DSM-IV ADHD with adverse outcomes in the US National Comorbidity Survey Replication Adolescent Supplement (NCS-A). Psychol med. 2014;44(08):1779–92.View ArticlePubMedGoogle Scholar
  38. Israelski DM, Prentiss DE, Lubega S, Balmas G, Garcia P, Muhammad M, et al. Psychiatric co-morbidity in vulnerable populations receiving primary care for HIV/AIDS. AIDS Care. 2007;19(2):220–5.View ArticlePubMedGoogle Scholar
  39. Dean A, Arner T, Sunki G, Friedman R, Lantinga M, Sangam S, Zubieta J, Sullivan K, Brendel K, Gao Z: Epi Info™, A database and statistics program for public health professionals. Centers for Disease Control and Prevention. Atlanta, Georgia, USA. 2007.Google Scholar
  40. Salkind NJ, editor. Encyclopedia of research design. Vol. 1. California: Sage; 2010.Google Scholar
  41. Singh YK. Fundamental of research methodology and statistics. New Delhi: New Age International; 2006.Google Scholar
  42. Wittchen H-U. Reliability and validity studies of the WHO-composite international diagnostic interview (CIDI): a critical review. J Psychiatr res. 1994;28(1):57–84.View ArticlePubMedGoogle Scholar
  43. Gelaye B, Williams MA, Lemma S, Deyessa N, Bahretibeb Y, Shibre T, et al. Diagnostic validity of the composite international diagnostic interview (CIDI) depression module in an east African population. Int J Psychiatry Med. 2013;46(4):387–405.View ArticlePubMedPubMed CentralGoogle Scholar
  44. Gureje O, Von Korff M, Kola L, Demyttenaere K, He Y, Posada-Villa J, et al. The relation between multiple pains and mental disorders: results from the world mental health surveys. Pain. 2008;135(1):82–91.View ArticlePubMedGoogle Scholar
  45. Haro JM, Arbabzadeh-Bouchez S, Brugha TS, De Girolamo G, Guyer ME, Jin R, et al. Concordance of the composite international diagnostic interview version 3.0 (CIDI 3.0) with standardized clinical assessments in the WHO world mental health surveys. Int J Methods Psychiatr res. 2006;15(4):167–80.View ArticlePubMedGoogle Scholar
  46. Üstün T, Ayuso-Mateos JL, Chatterji S, Mathers C, Murray CJ. Global burden of depressive disorders in the year 2000. Br J Psychiatry. 2004;184(5):386–92.View ArticlePubMedGoogle Scholar
  47. Mohammed A, Said JM, Wakil MA, Rabbebe IB, Sheikh T, Agunbiade S. Unrecognized psychiatric disorders among adult patients admitted into a general hospital in Maiduguri, Northeastern Nigeria. Pan Afr Med J. 2014;19:197.View ArticlePubMedPubMed CentralGoogle Scholar
  48. Process of translation and adaptation of instruments [http://www.who.int/substance_abuse/research_tools/translation/en/].
  49. Wakawa IA, Said JM, Abba WM, Shehu S, Rabbebe IB, Beida O. The impact of comorbid clinical depression on the health-related quality of life of adults on highly active antiretroviral therapy in Maiduguri, northeastern Nigeria. Indian J Psychol Med. 2014;36(4):408.View ArticlePubMedPubMed CentralGoogle Scholar
  50. Lee S, Tsang A, Breslau J, Aguilar-Gaxiola S, Angermeyer M, Borges G, et al. Mental disorders and termination of education in high-income and low- and middle-income countries: epidemiological study. Br J Psychiatry. 2009;194(5):411–7.View ArticlePubMedPubMed CentralGoogle Scholar
  51. IBM. IBM SPSS statistics version 21. Boston: Mass: International Business Machines Corp; 2012.Google Scholar
  52. Ferrari AJ, Charlson FJ, Norman RE, Patten SB, Freedman G, Murray CJ, et al. Burden of depressive disorders by country, sex, age, and year: findings from the global burden of disease study 2010. PLoS med. 2013;10(11):e1001547.View ArticlePubMedPubMed CentralGoogle Scholar
  53. Abas M, Ali GC, Nakimuli-Mpungu E, Chibanda D. Depression in people living with HIV in sub-Saharan Africa: time to act. Tropical med Int Health. 2014;19(12):1392–6.View ArticleGoogle Scholar
  54. Feuillet P, Lert F, Tron L, Aubriere C, Spire B, Dray-Spira R. Prevalence of and factors associated with depression among people living with HIV in France. HIV Medicine. 2016;Google Scholar
  55. Andrade L, Caraveo-anduaga JJ, Berglund P, Bijl RV, Graaf RD, Vollebergh W, et al. The epidemiology of major depressive episodes: results from the international consortium of psychiatric epidemiology (ICPE) surveys. Int J Methods Psychiatr res. 2003;12(1):3–21.View ArticlePubMedGoogle Scholar
  56. Akhtar-Danesh N, Landeen J. Relation between depression and sociodemographic factors. Int J Ment Heal Syst. 2007;1:1.View ArticleGoogle Scholar
  57. Petersen I, Fairall L, Egbe CO, Bhana A. Optimizing lay counsellor services for chronic care in South Africa: a qualitative systematic review. Patient Educ Couns. 2014;95(2):201–10.View ArticlePubMedGoogle Scholar
  58. Gaynes BN, O’Donnell J, Nelson E, Heine A, Zinski A, Edwards M, et al. Psychiatric comorbidity in depressed HIV-infected individuals: common and clinically consequential. Gen Hosp Psychiatry. 2015;37(4):277–82.View ArticlePubMedPubMed CentralGoogle Scholar
  59. Kinyanda E, Hoskins S, Nakku J, Nawaz S, Patel V. The prevalence and characteristics of suicidality in HIV/AIDS as seen in an African population in Entebbe district, Uganda. BMC Psychiatry. 2012;12(1):63.View ArticlePubMedPubMed CentralGoogle Scholar
  60. Dabaghzadeh F, Jabbari F, Khalili H, Abbasian L. Associated factors of suicidal thoughts in HIV-positive individuals. Iran J Psychiatry. 2015;10(3):185–91.PubMedPubMed CentralGoogle Scholar
  61. Soboka M, Tesfaye M, Feyissa GT, Hanlon C. Alcohol use disorders and associated factors among people living with HIV who are attending services in south west Ethiopia. BMC Res Notes. 2014;7(1):828.View ArticlePubMedPubMed CentralGoogle Scholar
  62. Galvan FH, Bing EG, Fleishman JA, London AS, Caetano R, Burnam MA, et al. The prevalence of alcohol consumption and heavy drinking among people with HIV in the United States: results from the HIV cost and services utilization study. J Stud Alcohol. 2002;63(2):179–86.View ArticlePubMedGoogle Scholar
  63. Williams EC, Bradley KA, Balderson BH, McClure JB, Grothaus L, McCoy K, et al. Alcohol and associated characteristics among older persons living with human immunodeficiency virus on antiretroviral therapy. Subst Abus. 2014;35(3):245–53.View ArticlePubMedPubMed CentralGoogle Scholar
  64. Molina PE, Bagby GJ, Nelson S. Biomedical consequences of alcohol use disorders in the HIV-infected host. Curr HIV res. 2014;12(4):265–75.View ArticlePubMedPubMed CentralGoogle Scholar
  65. Fisher JC, Bang H, Kapiga SH. The association between HIV infection and alcohol use: a systematic review and meta-analysis of African studies. Sex Transm Dis. 2007;34(11):856–63.View ArticlePubMedGoogle Scholar
  66. Chibanda D, Cowan F, Verhey R, Machando D, Abas M, Lund C. Lay health Workers’ experience of delivering a problem solving therapy intervention for common mental disorders among people living with HIV: a qualitative study from Zimbabwe. Community Ment Health J. 2016;53(2):143–53.View ArticlePubMedGoogle Scholar
  67. Tsai AC: Reliability and validity of depression assessment among persons with HIV in sub-Saharan Africa: systematic review and meta-analysis. J Acquir Immune Defic Syndr (1999) 2014, 66(5):503-511.Google Scholar
  68. World Health Organization: mhGAP intervention guide for mental, neurological and substance use disorders in non-specialized health settings: mental health gap Action Programme (mhGAP) – version 2.0. In. Geneva, Switzerland: World Health Organization, 2016.Google Scholar
  69. World Health Organization. Mental health gap Action Programme: scaling up care for mental, neurological, and substance use disorders. Geneva: WHO Press; 2008.Google Scholar

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