Open Access

Risky HIV sexual behaviour and depression among University of Nairobi students

  • Caleb J Othieno1Email author,
  • Roselyne Okoth1,
  • Karl Peltzer2, 3, 4,
  • Supa Pengpid2, 4 and
  • Lucas O Malla5
Annals of General Psychiatry201514:16

https://doi.org/10.1186/s12991-015-0054-2

Received: 17 April 2014

Accepted: 24 March 2015

Published: 11 April 2015

Abstract

Background

Prevalence rates of human immunodeficiency virus (HIV) infection among the youth are disproportionately high compared to that of other age groups in Kenya. Poor mental health has been linked to risky HIV behaviour, yet few local studies have explored these aspects. This study sought to determine associations between HIV risky sexual behaviour and depression among undergraduate students at the University of Nairobi.

Method

A random sample of 923 (525 males and 365 females) undergraduate students was interviewed using a questionnaire to record sociodemographic variables and risky sexual behaviour including having multiple sexual partners, inconsistent condom use and engaging in sex after drinking. Depressive symptoms were measured using the Centre for Epidemiological Studies Short Depression Scale (CES-D 10).

Results

The students’ mean age was 23 years (s.d.4.0). Overall, 41.33% of the students scored above the cut-off point of 10 on the CES-D 10 scale, with 35.71% having moderate symptoms and 5.62% having severe depressive symptoms. The percentage of those who had ever been diagnosed with sexually transmitted infections (STIs) was 9.71% (males 8.65%; females 11.01%); and for HIV 3.04% (males 2.02%; females 4.05%). Nearly 30% reported having had multiple partners in the previous 12 months, 27.4% of the students did not use condoms with sexual partners and 21% had engaged in sex after drinking within the previous 3 months. In multivariable-bivariate logistic regression, being older, having depressive symptoms, alcohol use/binge drinking, tobacco use, sex after drinking, previous diagnosis of STI, physical abuse, sexual coercion and history of sexual abuse as a child were significantly associated with having multiple partners. Further, younger age, being female, tobacco use and previous diagnosis of STI were significantly associated with inconsistent condom use.

Conclusion

The prevalence of HIV rate infection is low compared to the national average but risky sexual behaviour is common among the students and is positively linked to depressive symptoms among other factors. Programmes aimed at HIV prevention should be integrated with mental health interventions.

Keywords

StudentsDepressionRisky sexual behaviourHIV

Background

Despite reductions in human immunodeficiency virus (HIV) inflection prevalence rates and increased coverage of those who need ARV drugs in sub-Saharan Africa, the numbers of those infected are still quite high in Kenya and recent studies show a need to reduce the prevalence rate further particularly among the youth [1]. Overall, the national HIV prevalence rate is dropping but wide regional variations continue to be seen. For example, Oluoch and his co-workers [2] reported a national average of 5.6% ranging from 1.2% in North Eastern Province to 16.1% in Nyanza Province. Using data from several sources, recent reports give a national prevalence rate of 6% (5.6% for males and 7.6% for females). The range varied from 0.2% in Wajir in the northern parts to 25.7% in Homa Bay County around Lake Victoria. Although the HIV prevalence among the youth is 2.7% for females and 1.7% for males, the report estimated that young women in the age group 15–24 years account for 21% of all the new HIV infections in Kenya [3].

The high rates of HIV infection in the youth could be linked to risky sexual behaviour since most of the HIV infections are through heterosexual transmission. For example, inconsistent condom use and unprotected sex with multiple partners, both of which are risk factors for HIV, have been reported among university students [4-7]. A study involving 24 countries in sub-Saharan Africa reported that multiple sexual partnerships were more common among urban males and females with higher education [8]. Among university students, the changes in living arrangements and access to information further increase these risks. [5,9]. Since the university population is a vulnerable group with respect to HIV, it is important to determine factors related to the risky behaviours [5,10,11] and to monitor the trends [8].

Depressive symptomatology in youth has been associated with high-risk sexual behaviour such as early sexual debut, higher number of sexual partners and having sex while under influence of alcohol and drugs [12]. Similar findings have been demonstrated in studies done in sub-Saharan Africa where HIV is endemic in several countries. Youths in Uganda who had high scores on depression were more likely to report having high numbers of sexual partners [13]. In South Africa, there is evidence that depression is linked to risky sexual behaviour. Young men and women were more likely to have experienced intimate partner violence and to have engaged in unprotected sex or to report incorrect condom use [14]. The same study also found that depression could be a marker of increased HIV risk [14]. The same trends have been observed among university students in Ivory Coast where poor mental health including alcohol use and partner violence was found to be associated with HIV risk behaviour [15]. Although studies from other parts of the world have linked poor mental health to risky sexual behaviour, relatively few studies have been done in Kenya on adolescents and youth mental health. This study, therefore, aims to provide more data on the links between depression and HIV risky behaviour.

Objective

The objectives of this study were to describe the HIV risky sexual behaviours in relation to depressive symptoms and other sociodemographic variables among undergraduate students at the University of Nairobi in Kenya.

Methods

Study population

We obtained permission from the Kenyatta National Hospital and the University of Nairobi Ethics and Research Committee. University of Nairobi is the largest of the seven public universities in Kenya. It has six colleges; College of Architecture and Engineering (Main Campus), College of Humanities and Social Sciences (Main Campus), College of Health Sciences (Kenyatta National Hospital), College of Education and External Studies (Kikuyu Campus and Kenya Science Campus), College of Agriculture and Veterinary Sciences (Upper Kabete Campus) and the College of Biological and Physical Sciences (Chiromo Campus). The research targeted the University of Nairobi students. The total student population in the University of Nairobi is 36,991 (22,734 males and 14,257 females) [16].

Sampling design

From the total registered students in the University of Nairobi, each of the six colleges participated in the study in order to achieve representativeness and to increase statistical power. Proportional stratified sampling was used to ensure that the colleges forming different student subpopulations were represented in the sample in same proportions as the population. The sampling process proceeded in two steps. In the first stage, the number of participants to be obtained from each college was determined using calculations based on probability proportional to size. Next, a sampling frame containing a list of all students was compiled from each college. In the second step, a simple random sample was selected within each college using computer-generated random numbers and the available sampling frame.

Measurement of study variables

We administered a purpose-designed questionnaire to record sociodemographic data including age, sex year of study, socioeconomic status and performance in studies.

Questions on risky sexual behaviour enquired on having multiple sexual partners, inconsistent condom in past 3 months, sex after drinking alcohol, age at first pregnancy/made someone pregnant and past history of sexually transmitted infection.

Depression

The Centre for Epidemiological Studies Short Depression Scale (CES-D 10) consists of ten questions. It has been used in other parts of sub-Saharan Africa. We used a cut-off point of ≥10. Those who had a score of 0–9 were classified as having a mild level of depressive symptoms, 10–14 as moderate depressive symptoms and ≥15 representing severe depressive symptoms. [17-19]. Binge drinking was defined as having more than four or five drinks at a sitting.

HIV risk behaviour

In terms of HIV risk behaviour, university students were asked, “During the past 12 months how many sexual partners did you have?” “During the past 3 months did you use a condom with your primary partner?” (Response options ranged from 1 = never to 5 = every time; inconsistent condom use was defined as not having used a condom every time in the past 3 months). Further, students were asked if they had had sex after drinking alcohol in the past 3 months, with the response option, “yes” or “no”.

STIs and HIV status: STIs status was assessed with the question, “Have you ever been diagnosed with a sexually transmitted infection?” and HIV status, “Have you ever been diagnosed HIV positive?

Handling of survey non response and missing data

The response rate was about 70%. To achieve this, extensive awareness of the research was done and this included visits of lecture halls, by research assistants, to educate students on the benefits of the study and also the use of study introductory letter on every questionnaire. Research assistants traced the selected students through the chairmen of their departments where they obtained their contacts. Thereafter, they rung the students to introduce the study and arrange a meeting. Those who were unreachable on phone were traced through their colleagues and their lecture halls. All the respondents filled in a pencil-paper-based questionnaire. All missing data were assumed to be at random.

Statistical analysis

Results of sociodemographic factors were presented using frequencies and proportions, with their distributions examined separately for males and females. Also, the prevalence of depressive symptoms was presented using proportions, and association between depressive symptoms and potential predictors was investigated using chi-square test. On the other hand, a bivariate logistic regression was fitted to determine the associations between risky sexual behaviour, defined by inconsistent condom use and multiple sexual partners, and potential mental health covariates. Variable selection proceeded as follows; first, unadjusted bivariate model was fitted for each covariate. All covariates that were statistically significant (P value <0.05) were then included in a multivariable-bivariate model. In the study design, sampling was clustered within colleges and college membership included as a fixed effect in the final bivariate model. Twelve respondents, who were married and did not use condoms with partners, were excluded in bivariate analyses.

Software

Exploratory analyses, calculation of frequencies and proportions were done using IBM SPSS (version 22.0) and bivariate logistic regression fitted using the Zelig package in R version 3.0.2.

Results

The sociodemographic characteristics of the study sample are shown in Table 1. We obtained data from 923 students (525 males and 365 females). The mean age was 23 years (s.d.4.0). Two-thirds resided within the campus. Ninety percent were single. More females (15%) were married compared to the males (approximately 7%). Nearly half (48%) of the students rated themselves as coming from families that were either not well off or were poor. Less than 1% of the students recorded their academic performance as not satisfactory. The percentage of those who had ever been diagnosed with sexually transmitted disease was 9.71% (males 8.65%; females 11.01%); and for HIV 3.04% (males 2.02%; females 4.05%).
Table 1

Sociodemographic characteristics

 

Overall

Male

Female

 

N

%

N

%

N

%

All

923

 

525

 

365

 

Age

      

<20

200

23.39

122

24.11

78

22.35

20–24

515

60.23

311

61.46

204

58.45

25–29

84

9.82

49

9.68

35

10.03

30 and above

56

6.54

24

4.74

32

9.17

Year of study

      

First

185

21.17

128

25.40

56

15.60

Second

256

29.29

143

28.37

111

30.92

Third

195

22.31

107

21.23

85

23.68

Fourth, fifth and sixth

238

27.22

126

25.00

107

29.81

College

      

CAVS

66

7.17

41

7.69

25

6.70

CAE

149

16.18

101

18.95

45

12.06

CBPS

150

16.28

93

17.45

57

15.28

CEES

193

20.95

109

20.45

81

21.72

CHS

30

3.25

12

2.25

18

4.83

CHSS

333

36.16

177

33.21

147

39.41

Marital status

      

Married

90

9.96

35

6.67

54

14.79

Single

813

90.03

490

93.33

311

85.21

Religion

      

Christian

752

82.28

439

82.67

303

82.34

Muslim

61

6.67

34

6.40

24

6.52

Other

101

11.05

58

10.92

41

11.14

Residence

      

On campus

616

67.99

387

73.71

219

60

Off campus (on your own or with parents/guardians)

290

32.01

138

26.28

146

40.11

Family background

      

Wealthy/Quite well off

469

52.00

251

47.68

207

56.87

Not very well off/Quite poor

433

48.0

271

51.91

157

43.13

Academic performance

      

Excellent/Very good

449

57.93

260

57.14

182

58.30

Good/Satisfactory

320

41.29

191

41.97

125

40.46

Not satisfactory

6

0.77

4

0.88

2

0.65

Depression

The prevalence of depression among the students is shown in Table 2. Overall, 41.33% of the students scored above the cut-off point of 10 on the CES-D 10 scale, with 35.71 having moderate symptoms and 5.62% having severe depressive symptoms. Proportionately, more females had depressive symptoms compared to males but the difference was not statistically significant. Similarly, no statistically significant difference was noted among the different age groups although approximately half of those in the age group of 30 years and above were reported to have mild–moderate symptoms of depression. The rates of depressive symptoms among those who reported binge drinking were high (though not statistically significant) compared to that of those who did not report binge drinking. However, tobacco use was significantly associated with depressive symptoms.
Table 2

Prevalence of depressive symptoms

 

Moderate (%)

Severe (%)

Chi-square ( P value)

All

35.71 (30.03–36.20)

5.62 (3.90–6.89)

 

Social demographic

   

Age

   

<20

30.65 (24.22–37.89)

6.45 (3.53–11.26)

0.0933

20–24

37.01 (32.71–41.51)

5.82 (3.97–8.40)

 

25–29

27.50 (18.39–38.80)

6.25 (2.32–14.61)

 

30 and above

50.94 (37.00–64.75)

1.89 (0.00–11.38)

 

Gender

   

Male

33.54 (29.39–37.96)

5.35 (3.59–7.84)

0.2598

Female

39.03 (33.94–44.37)

5.13 (3.16–8.13)

 

Year of study

   

First

36.26 (29.15–43.98)

7.60 (4.28–12.92)

0.2598

Second

35.74 (29.69–42.27)

4.26 (2.18–7.92)

 

Third

38.33 (31.28–45.89)

5.56 (2.85–10.26)

 

Fourth, fifth and sixth

33.63 (27.54–40.29)

4.48 (2.29–8.33)

 

College

   

CAVS

35.00 (23.44–48.48)

6.67 (2.16–17.00)

0.0745

CAE

38.24 (30.15–46.99)

6.62 (3.26–12.55)

 

CBPS

34.33 (26.48–43.09)

5.22 (2.31–10.87)

 

CEES

42.62 (35.42–50.14)

2.73 (1.01–6.60)

 

CHS

14.81 (4.86–34.61)

0.00

 

CHSS

33.33 (28.18–38.90)

7.37 (4.83–11.00)

 

Marital status

   

Married

37.21 (27.22–48.35)

4.65 (1.50–12.13)

0.9073

Single

35.56 (32.14–39.13)

5.61 (4.12–7.58)

 

Religion

   

Christian

36.55 (32.98–40.26)

5.04 (3.58–7.00)

0.3581

Muslim

29.09 (18.02–43.09)

7.27 (2.36–18.43)

 

Other

33.68 (24.51–44.20)

9.47 (4.69–17.67)

 

Residence

   

On campus

35.27 (31.37–39.38)

6.70 (2.36–18.43)

0.0833

Off campus (on your own or with parents and guardians)

35.93 (30.26–42.00)

2.96 (1.38–5.98)

 

Family background

   

Wealthy/Quite well off

33.72 (29.30–38.43)

2.56 (1.35–4.67)

<0.0001

Not very well off/Quite poor

37.44 (32.75–42.37)

8.87 (6.37–12.17)

 

Academic performance

   

Excellent/Very good

37.23 (32.62–42.08)

5.97 (3.98–8.79)

0.1754

Good/Satisfactory

30.17 (25.06–35.81)

5.76 (3.50–9.24)

 

Not satisfactory

50.0 (18.76–81.23)

16.67 (0.87–63.52)

 

Alcohol usage

   

Alcohol use

38.9 (33.78–44.28)

5.76 (3.65–8.90)

0.2473

No Alcohol use

33.53 (29.46–37.85)

5.52 (3.78–7.98)

 

Binge drinking

   

Binge drinking

41.11 (33.92–48.69)

6.11 (3.24–10.95)

0.3160

Non-binge drinking

35.90 (27.39–45.35)

3.42 (1.10–9.04)

 

Tobacco usage

   

Tobacco use

37.63 (27.97–48.33)

13.98 (7.94–23.08)

0.0004

Non-tobacco use

33.83 (30.08–37.80)

4.50 (3.04–6.56)

 

Sexual behaviour

   

Number of partners for past 12 months

   

None or 1

34.15 (30.29–38.24)

4.40 (2.93–6.52)

0.0195

≥2

38.81 (33.18–44.75)

8.04 (5.28–11.98)

 

Consistent use of condom with partner

32.78 (28.37–37.51)

6.84 (4.71–9.79)

0.0967

Non–consistent use

38.60 (34.01–43.41)

4.42 (2.76–6.94)

 

Sex after drinking past 3 months

46.75 (39.09–54.55)

5.33 (2.22–9.43)

0.0066

No sex after drinking past 3 months

33.50 (29.76–37.46)

4.73 (3.73–7.52)

 

Ever diagnosed with STI

50.65 (39.10–62.13)

6.49 (2.42–15.15)

0.0101

Never diagnosed with STI

34.26 (30.82–37.87)

5.13 (3.69–7.07)

 

Ever diagnosed with HIV

57.69 (37.19–76.03)

19.23 (7.31–39.98)

<0.0001

Never diagnosed with HIV

34.58 (31.25–38.05)

4.88 (3.52–6.71)

 

Ever been hit by a sexual partner

56.67 (43.30–69.18)

11.67 (5.21–23.18)

<0.0001

Never been hit by sexual partner

34.05 (30.67–37.59)

4.67 (3.34–6.53)

 

Ever been forced to have sex

65.12 (54.00–74.87)

9.30 (4.39–18.00)

<0.0001

Never been forced to have sex

32.28 (30.11–37.10)

4.83 (3.43–6.72)

 

Physically abused as a child

43.24 (31.94–55.24)

13.51 (7.02–23.91)

0.0007

Never physically abused as a child

34.83 (31.41–38.40)

4.63 (3.27–6.47)

 

Sexually abused as a child

53.06 (38.42–67.22)

8.16 (2.65–20.48)

0.0122

Never sexually abused as a child

34.56 (31.20–38.09)

5.15 (3.73–7.01)

 

Other factors associated with high levels of depressive symptoms included having a positive history of HIV or STI infection. Those who reported traumatic events such as having been hit by a sexual partner, having been forced to have sex and having been physically abused as a child also reported significantly higher levels of depressive symptoms compared to those who did not report such events.

Association with risky sexual behaviour

The two factors defining risky sexual behaviour were having more than two sexual partners within the past 12 months and inconsistent condom use. The former was reported by 30% of the students. Inconsistent condom use was reported by 27.48% of the students (males 26.74 and females 28.75). One-fifth of the students reported engaging in sex after drinking. In multivariable-bivariate logistic regression, being older, having depressive symptoms, alcohol use/binge drinking, tobacco use, sex after drinking, previous diagnosis of STI and sexually abused as a child were significantly associated with having multiple partners. Further, younger age, being female, tobacco use and previous diagnosis of STI were significantly associated with inconsistent condom use (Table 3).
Table 3

Associations between risky sexual behaviour (multiple sexual partners, inconsistent condom use) and mental health covariates

 

Multiple sexual partners

Inconsistent condom use

 

Unadjusted odds Ratio (95% C.I)

Adjusted odds ratio (95% C.I)

Unadjusted odds ratio (95% C.I)

Adjusted odds ratio (95% C.I)

Social demographic

    

Age

0.95 (0.92–0.99)**

1.12 (1.00–1.28)*

0.85 (0.80–0.89)***

0.90 (0.83–0.97)***

Gender

    

Femalea

    

Male

1.74(1.30–2.33)***

4.10 (1.72–10.43)

0.87 (0.66–0.92)*

0.99 (0.67–1.47)***

Year of study

    

First a

    

Second

1.36 (0.92–2.03)

3.20 (0.93–11.69)

0.89 (0.61–1.31)

-

Third

1.26 (0.82–1.93)

2.18 (0.58–8.56)

0.74 (0.49–1.12)

-

Fourth, fifth and sixth

1.76 (1.17–2.67)**

3.05 (0.84–11.61)

0.80 (0.54–1.19)

-

College

    

CAVSa

    

CAE

0.87 (0.43–1.67)

0.29 (0.04–2.06)

0.61 (0.33–1.11)

1.22 (0.52–2.86)

CBPS

0.54 (0.27–1.03)

0.99 (0.12–7.37)

0.40 (0.22–0.73)**

0.55 (0.23–1.31)

CEES

0.36 (0.19–0.67)**

0.52 (0.34–0.62)*

0.24 (0.13–0.43)***

0.46 (0.18–1.13)

CHS

0.76 (0.29–2.05)

0.31 (0.03–2.55)

1.28 (0.51–3.36)

2.71 (0.76–10.46)

CHSS

0.73 (0.39–1.33)

0.67 (0.05–10.70)

0.63 (0.36–1.08)

0.76 (0.34–1.66)

Marital status

    

Marrieda

    

Single

1.08 (0.66–1.75)

-

1.56 (0.98–1.92)

-

Religion

    

Christiana

    

Muslim

1.53 (0.85–2.90)

-

0.66 (0.38–1.14)

-

Other

1.16 (0.75–1.85)

-

0.60 (0.39–1.12)

-

Residence

    

On campusa

    

Off campus (on your own or with parents and guardians)

1.18 (0.87–1.60)

-

0.47 (0.35–1.42)

-

Family background

    

Wealthy/Quite well offa

    

Not very well off/Quite poor

1.10 (0.83–1.45)

-

1.05 (0.80–1.37)

-

Academic performance

    

Excellent/Very gooda

    

Good/Satisfactory

0.94 (0.70–1.28)

-

1.49 (0.07–1.99)

-

Not satisfactory

1.03 (0.20–7.50)

-

0.56 (0.08–2.90)

-

Depression

    

No depressiona

    

Moderate

1.78 (1.57–2.05)

2.76 (1.83–3.11)**

1.80 (1.60–2.06)*

0.92 (0.61–1.39)

Severe

1.51 (1.27–1.95)*

2.01 (1.50–3.22)**

1.38 (0.75–2.59)

1.18 (0.47–2.97)

Alcohol use (reference = No)

2.07 (1.57–2.75)***

3.68 (2.64–4.13)***

1.55 (1.18–2.02)**

1.98 (0.64–2.52)

Binge drinking (reference = No)

1.82 (1.14–2.89)*

2.12 (1.85–2.46)**

1.18 (0.74–1.89)

-

Tobacco use (reference = No)

3.36 (2.18–5.22)***

2.26 (2.02–2.39)***

1.97 (1.27–3.14)**

1.78 (1.44–2.87)**

Sexual behaviour

    

Sex after drinking past 3 months (reference = No)

5.10 (3.58–7.33)***

3.94 (1.62–10.17)*

3.81 (2.59–5.72)***

3.77 (0.22–7.04)

Ever diagnosed with STI (reference = No)

3.70 (2.32–5.99)***

6.48 (1.36–20.33)*

3.60 (2.12–6.44)***

2.99 (1.21–4.50)*

Ever diagnosed with HIV (reference = No)

2.25 (0.97–5.25)

 

2.53 (1.04–7.09)

-

Ever been hit by a sexual partner (reference = No)

2.33 (1.32–3.77)**

2.35 (0.44–3.77)

2.39 (0.33–4.36)

2.13 (0.11–6.23)

Ever been forced to have sex (reference = No)

1.74 (1.11–2.73)*

3.56 (0.92–4.61)

1.68 (1.07–2.69)*

5.29 (0.43–17.50)

Physically abused as a child (reference = No)

1.04 (0.63–1.67)

-

1.01 (0.64–1.61)

-

Sexually abused as a child (reference = No)

1.78 (0.98–3.20)

1.87 (1.52–2.11)**

2.20 (1.19–4.30)*

1.81 (0.92–3.21)

Based on bivariate logistic regression estimates.

*P < .05; **P < .01; ***P < .001.

aReference level.

C.I = confidence level.

Discussion

The overall prevalence rate of HIV in this sample was 3.04% (males 2.02% and females 4.05%). This is lower than the Kenyan national average for a comparable age group. However, the study shows that a considerable number of students engage in risky sexual behaviour. Approximately 30% reported having had multiple sexual partners, and one-fifth of the students had engaged in sex after drinking. More than one quarter of both males and females reported non-use of condoms with sexual partners, yet 36% of the males and 21% of the females had more than two sex partners in the proceeding 12 months. These findings are comparable to other studies among university students in the region. A local study among Maseno University students in Western Kenya reported that 25.6% of the students engaged in sex while intoxicated with alcohol [20]. Similar findings have been also been reported from Ugandan university students where risky sexual behaviour was linked to drinking and high STI levels [21].

HIV transmission in Kenya is mainly through heterosexual sex, and efforts to decrease the HIV transmission rates in Kenya have concentrated mainly on reproductive health with an emphasis on safe sexual practices such as condom use, voluntary counselling and testing and more recently voluntary medical male circumcision [22]. While these interventions have had some effect and there has been a general decline in HIV prevalence rates among the age group 15–49 from 1990s to 2008, there are concerns that the prevalence rate has since stabilised and that infection rates among the youth account for 21% of all new infections [3]. To sustain the gains made, a rate of zero infections should be the aim. It is therefore essential to explore all the correlates of risky sexual behaviour and formulate appropriate interventions.

Risky sexual behaviour is positively linked to depression as has been shown in studies from other student groups [13,14]. Similarly in this study, having depressive symptoms was associated with having multiple partners. It could be that depressive feelings lead to risky sexual behaviour. Alternatively, risky sexual behaviour, being forced to have sex and being hit by a sexual partner, factors which are high in this sample, are the causes of high depressive symptoms. Sexual coercion was also found to be common among Ugandan university students, having affected nearly one-third of those sampled and was associated with subsequent risky sexual behaviour [23]. Further studies are needed to confirm these links particularly in areas with high HIV prevalence rates.

Given the low number of mental health workers in Kenya, it is possible that many of those with moderate to severe depressive symptoms that would need some intervention may go untreated. It is therefore important that workers in reproductive health or general health facilities be made aware of the links between STI risky HIV behaviour and poor mental health. Students who present to the student health services with STIs, history of alcohol use and physical abuse should be screened for depressive illnesses. Programmes that address issues of HIV, for example awareness campaigns, should also include discussions on identification of depression.

Limitations

Since this was a cross-sectional study dependent and was dependent upon self report of symptoms, there could have been errors related to inaccurate reporting. The university population sampled in this study also differs from the youth population in education and exposure to different cultures and social pressures. These factors could limit the generalisability of the results. However, this is a national university that admits students from all over Kenya and so the findings may be applicable to students from other developing countries in the region.

Conclusions

HIV rates are lower in the students’ population compared to the national average, but the prevalence of risky sexual behaviour is high and positively linked to depression. Interventions aimed at HIV prevention should be integrated with mental health assessment and treatment.

Declarations

Acknowledgements

We thank the students who participated in the study, the administration of the University of Nairobi, especially Registrar Academics for facilitating the study; Cherryl Ojjerro, Rachel Maina, Eston Nyakiya, Julius Oduor and Amelia Awoko who assisted with the data collection.

Authors’ Affiliations

(1)
Department of Psychiatry, University of Nairobi
(2)
ASEAN Institute for Health Development, Mahidol University
(3)
Human Sciences Research Council
(4)
University of Limpopo
(5)
Kenya Medical Research Institute, Wellcome Trust

References

  1. Kimanga DO, Ogola S, Umuro M, Nganga A, Kimondo L, Mureithi P, et al. Prevalence and incidence of HIV infection, trends, and risk factors among persons aged 15–64 years in Kenya: results from a nationally representative study. J Acquired Immune Deficiency Syndrome. 2014.Google Scholar
  2. Oluoch T, Mohammed I, Bunnell R, Kaiser R, Kim AA, Gichangi A, et al. Correlates of HIV infection among sexually active adults in Kenya: a national population-based survey. Open AIDS J. 2011;5:125–34.View ArticlePubMed CentralPubMedGoogle Scholar
  3. National AIDS and STI Control Programme. Kenya HIV estimates. Nairobi: Government of Kenya; 2014.Google Scholar
  4. Heere GA, Mandeya A, Jemmott JB, Chiruka RT, Marange CS, Batidzirai JM, et al. Multiple partners and condom use among students at a South African university. J Evid Based Soc Work. 2014;11:437–44.View ArticleGoogle Scholar
  5. Liu Z, Wei P, Huang M, Liu YB, Li L, Gong X, et al. Determinants of consistent condom use among college students in China: application of the information-motivation-behavior skills (IMB). Plos One. 2014;9(9):e108976.View ArticlePubMed CentralPubMedGoogle Scholar
  6. Ngatu NR, Hirota R, Eitoku M, Muzembo BA, Nishimori M, Kuramochi M, et al. Perception of the risk of sexual transmission of HIV among Congolese and Japanese university students. Environ Health Prev Med. 2012;12(2):139–46.View ArticleGoogle Scholar
  7. Rahamefy OH, Rivard M, Ravaoarinoro M, Ranaivoharisoa L, Rasamindrakotroka AJ, Morisset R. Sexual behaviour and condom use among university students in Madagascar. SAHARA J. 2008;5(1):28–35.View ArticlePubMedGoogle Scholar
  8. Doyle AM, Mavedzenge SN, Plummer ML, Ross DA. The sexual behaviour of adolescents in sub-Saharan Africa: patterns and trends from national surveys. Trop Med Int Health. 2012;17(7):796–807.View ArticlePubMedGoogle Scholar
  9. Onipede W. Mass media and sexual health behaviour of college students in Nigeria: a study of Lagos State University. East Afr J Public Health. 2009;6(3):303–8.PubMedGoogle Scholar
  10. Mmari K, Blum RW. Risk and protective factors that affect adolescent reproductive health in developing countries: a structured literature review. Glob Public Health. 2009;4:350–66.View ArticlePubMedGoogle Scholar
  11. Okonkwo PI, Fatusi AO, Ilika AL. Perception of peers’ behaviour regarding sexual health decision making among female undergraduates in Anambra State, Nigeria. Afr Health Sci. 2005;5(2):107–13.PubMed CentralPubMedGoogle Scholar
  12. Rubin AG, Gold MA, Primack BA. Associations between depressive symptoms and sexual risk behaviour in a diverse sample of female adolescents. J Paediatr Adolesc Gynaecol. 2009;22:306–12.View ArticleGoogle Scholar
  13. Argadh A, Cantor-Graae E, Ostergren PO. Youth, sexual risk-taking behavior, and mental health: a study of university students in Uganda. Int J Behav Med. 2012;19(2):208–16.View ArticleGoogle Scholar
  14. Nduna M, Jewkes RK, Dunkle KL, Shai N, Colman I. Associations between depressive symptoms, sexual behaviour and relationship characteristics: a prospective cohort study of young women and men in Eastern Cape, South Africa. J Int AIDS Soc. 2010;13:44.View ArticlePubMed CentralPubMedGoogle Scholar
  15. Peltzer K, Pengpid S, Tiembre I. Mental health, childhood abuse and HIV sexual risk behaviour among university students in Ivory Coast. Ann Gen Psychiatr. 2013;12:18.View ArticleGoogle Scholar
  16. University of Nairobi. University population. 2013.Google Scholar
  17. Andreasen EM, Malmgren JA, Carter WB, Patrick DL. Screening for depression in well adults: evaluation of a short form of the CES-D (Center for Epidemiological Studies Depression Scale). Am J Prev Med. 1994;10(2):77–84.Google Scholar
  18. Mulrow CD, Williams JWJ, Gerety MB, Ramirez G, Montiel OM, Kerber C. Case-finding instruments for depression in primary care setting. Ann Intern Med. 1995;122(12):913–21.View ArticlePubMedGoogle Scholar
  19. Kilbourne A, Justice A, Rollman B, McGinnis K, Weissman S. Clinical importance of HIV and depressive symptoms among veterans with HIV infection. J Gen Intern Med. 2002;17(7):512–20.View ArticlePubMed CentralPubMedGoogle Scholar
  20. Munyaka BS. Perceived benefits and barriers toward testing for sexually transmitted infections among undergraduate students at Maseno University Kisumu, Kenya. Nairobi: Jomo Kenyatta University of Agriculture and Technology; 2011.Google Scholar
  21. Choudhry V, Agardh A, Stafstrom M, Ostergren P-O. Patterns of alcohol consumption and risky sexual behaviour: a cross-sectional study among Ugandan university students. BMC Public Health. 2014;14:128.View ArticlePubMed CentralGoogle Scholar
  22. Centres for Disease Control and Prevention. Voluntary medical male circumcision—southern and eastern Africa, 2010–2012. MMWR Morb Mortal Wkly Rep. 2013;62(47):953–7.Google Scholar
  23. Agardh A, Odberg-Pettersson K, Ostergren P-O. Experience of sexual coercion and risky sexual behaviour among university students. BMC Public Health. 2011;11:527.View ArticlePubMed CentralPubMedGoogle Scholar

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© Othieno et al.; licensee BioMed Central. 2015

This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly credited. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated.

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