Consistent Condom Use Among Men Who Have Sex With Men in Lomé and Kara,Togo

Abstract

High transmission probability of HIV during condomless anal sex puts men who have sex with men (MSM), transgender, and nonbinary individuals at increased risk of infection. This analysis aims to examine the socioeconomic, biological, and behavioral factors that are associated with consistent condom use (CCU) during insertive/receptive anal sex among MSM in the last month in the cities of Lomé and Kara, Togo. A total of 683 MSM ≥18 years of age were surveyed using respondent-driven sampling (RDS) for a cross-sectional survey in Lomé (n = 354; 51.8%) and Kara (n = 329; 48.2%). Participants completed a structured questionnaire and were tested for HIV and syphilis. Statistical analyses included RDS-weighted proportions, bootstrapped confidence intervals (CIs), and logistic regression models. When compared with Lomé, MSM in Kara had lower odds of CCU [adjusted odds ratio (aOR) = 0.29, 95% CI = 0.19–0.44]. Other factors associated with lower CCU were having an income of 2,000 Communaute Financiere Africaine (CFA)–12,000 CFA (aOR = 0.53, 95% CI = 0.36–0.77) or above 12,000 CFA (aOR = 0.34, 95% CI = 0.20–0.57), transgender women (aOR = 0.47, 95% CI = 0.25–0.92), and intersex gender (aOR = 0.42, 95% CI = 0.24–0.73), and ever being forced to have sex (aOR = 0.42, 95% CI = 0.21–0.82). Factors associated with CCU were identified in this study including older age (aOR = 1.49, 95% CI = 1.04–2.14) and having easy access to condoms (aOR = 2.70, 95% CI = 1.23–5.94) and very easy access to condoms (aOR = 2.73, 95% CI = 1.20–6.16). Reported condom use in this study was low, and several factors associated with CCU were identified including older age and access to condoms. This study highlights multiple barriers to preventive services experienced by MSM in Togo and therefore leveraging strategies to address these barriers may improve prevention of HIV and syphilis.

Introduction

There is an HIV pandemic among men who have sex with men (MSM) represented by a consistently higher burden of HIV compared with other male adults of reproductive age.^1
–3 This disproportionate burden is observed across high, middle, and lower income settings.^1
–3 Even across concentrated and generalized HIV epidemics in West African countries, ∼2 in 10 MSM in Burkina Faso, 1 in 10 MSM in The Gambia, and 1 in 4 MSM in Benin and Senegal are living with HIV.^4

–8 In the more generalized HIV epidemics in the same region, where HIV consistently exceeds 1% among pregnant women,⁹ the relative increase in the burden of HIV among MSM compared with other populations is more pronounced, such is the case of Cote d'Ivoire, which has reported up to 16 times higher HIV prevalence among MSM compared with the broader population.^2,10

–14

MSM have been defined as MSM, regardless of whether or not they also have sex with woman or have a personal or social gay or bisexual identity.¹⁵ Being cisgender refers to a person who by nature or choice conforms to gender/sex assigned at birth-based expectations of society.¹⁶ In contrast, those whose psychological gender differs from the social expectations for the physical sex they were assigned at birth are defined as transgender.¹⁶ MSM are at increased biological risk for HIV infection partly because of the transmission efficiency of the virus; specifically, the high transmission probability during condomless anal intercourse (CAI) with a serodiscordant and viremic partner.¹⁷ Consistent condom use (CCU) is associated with lower HIV and sexually transmitted infection (STI) risks and diagnoses among MSM.^18
–20 Despite the risks associated with CAI with serodiscordant or HIV-status unknown partners, reported condom use during the most recent anal intercourse remains low among MSM across low and middle-income countries.²¹ In West Africa, the percentage of men reporting condom use the last time they had anal sex with a male partner had a high variability, from 19.5% in Liberia to 91.5% reported in Benin.²²

Social and structural determinants, such as condom negotiation, access to water-based lubricants, social cohesion, stigma, and cost of condoms have been documented as influencing condom use among MSM across sub-Saharan Africa.^23

–26 Condom use may vary for individuals, as different partners may present diverse challenges in successful condom use based on condom acceptance and the frequency of use. In Swaziland, condom negotiation was reported to be difficult for individuals both with partners who did not want to use condoms and partners with whom they did not use condoms consistently.²⁴ Social cohesion is also an influential factor in successful condom use, as high levels of social cohesion increase odds of condom use among MSM in sub-Saharan Africa.²⁴ Separately, perceived, anticipated, and enacted health care-related stigmas attributable to being MSM, including fear of seeking, avoidance, and denial of health care services, and also mistreatment in the health care setting, were associated with increased CAI among MSM in Lesotho.²⁶ In settings where same-sex practices are criminalized, condom use has been shown to be negatively associated with fear of seeking health services and with discrimination because of same sex sexual behavior.²⁴ In addition, a recent systematic review suggested that the cost of condoms may be a structural barrier for condom use among MSM, as condoms provided at reduced or no cost increased condom utilization.²³ Finally, not knowing one's HIV-positive status and limited exposure to HIV prevention services were associated with lower CCU among MSM in Cameroon.²⁵

Togo is a low-income country in West Africa with a population of 6.8 million people, 22% of whom live in the capital city of Lomé.²⁷ Togo has a generalized HIV epidemic with an estimated HIV prevalence of 2.3% (1.4%–4.1%) among adults aged 15–49 years, with most cases reported in urban settings.²⁸ In contrast, the prevalence of HIV among MSM in Togo has been estimated to be as high as 20%.^4,29 Same-sex practices in Togo are currently criminalized, with sentences of up to 3 years of imprisonment and up to 500,000 Communaute Financiere Africaine (CFA) francs (800 USD approx.) as fine.³⁰ Identifying and understanding the characteristics of MSM who engage in CCU can support the development of interventions specifically addressing determinants of condom use. Thus, these analyses aim to examine the socioeconomic, biological, and behavioral factors that are associated with CCU among MSM in the cities of Lomé and Kara, Togo.

Materials and Methods

Study population

This was a cross-sectional study conducted between December 2012 and June 2013 in the cities of Lomé and Kara, Togo. Lomé is the capital of Togo and Kara is a major city in the north of the country, with HIV prevalence estimates among MSM of 17% and 10%, respectively.¹⁴ The study was implemented by the local nongovernmental organizations (NGO) Espoir Vie Togo (EVT) in collaboration with Arc-en-Ciel and Force en Action pour la Mieux être de la Mère et de l'Enfant (FAMME). Eligibility was assessed by applying an eligibility screener included in the questionnaire that had five questions. Eligible participants reported to be assigned the male sex at birth, ≥18 years of age, reported having anal sex with a male partner in the past 12 months (MSM definition for the study), had lived in Togo for at least the past 3 months, have a valid study coupon, and provide informed consent for a questionnaire and for syphilis and HIV testing.

Respondent-driven sampling (RDS), a peer-recruitment sampling method designed to sample hard-to-reach populations was used to recruit MSM.³¹ These methods have been well described, but briefly, initial community engagement was conducted with MSM groups to inform recruitment and study implementation. Four heterogeneous seeds were provided guidance about the study and its aim. A maximum of three RDS coupons to recruit other MSM in their network were given to each seed, thus, limiting the number of MSM that could be recruited by one participant and beginning a series of referral sampling chains. Characteristics of those who were offered but did not accept a coupon were tracked using a postrecruitment questionnaire. Participants were reimbursed based on the cost of return transport and the equivalent of a meal, free condoms, condom-compatible lubricants, and HIV information materials. Participants were further reimbursed for each eligible MSM they recruited to cover transportation and phone credit needed to make contact and distribute the coupon. During the study, no recruitment challenges were reported.

For secondary data analyses, the combined total sample size of 683 was sufficient to detect the reported prevalence (54.8%) of condom use at last anal sex. The minimum required sample size to detect the observed prevalence assuming design effect of 2, was 550 participants.³²

The study received ethical approval from the Johns Hopkins Bloomberg School of Public Health Institutional Review Board and the National Ethics Committee of Togo.

Data collection

After providing oral informed consent, participants completed an interviewer-administered questionnaire in a private room in one of the two languages spoken (French and Ewe). The questionnaire was designed to explore the multiple dimensions of HIV risk outlined in the Modified Socio-Ecological Model.³³ Participants were first asked sociodemographics questions followed by a series of questions related to human rights violations, including indicators focused on community, social, and health system-related stigma and discrimination; sexual behavior risk factors (Table 2), history of STI symptoms, and testing in the past 12 months, and for those who knew that they were living with HIV, antiretroviral therapy status. Survey questions were pilot tested with members of the MSM community in both languages to ensure they were understood and reflected the original intent of the English and French questionnaires developed by the study team.

Table 2.

Condom Use, Sexual Behavior, Stigma, and Discrimination Characteristics of Men Who Have Sex With Men Living in Lomé (n = 354) and Kara (n = 329)

Characteristic	Lomé		Kara		Pooled
Characteristic	n/N (%)	RDS-weighted % (95% CI)	n/N (%)	RDS-weighted % (95% CI)	n/N (%)	p
Total	354/354 (100)		329/329 (100)		683/683 (100)
Condom used always in the last month when having anal sex with another male partner	224/354 (63.3)	56.2 (47.9–64.5)	150/329 (45.6)	44.0 (37.7–50.3)	374/683 (54.8)	<.01
Was a condom used last time you had sex with…
Male	280/354 (79.1)	76.4 (69.6–83.2)	244/329 (74.2)	70.3 (64.1–76.6)	524/683 (76.7)	.13
Main male partner	212/286 (74.1)	68.9 (59.3–78.6)	231/321 (72.0)	69.5 (63.1–76.0)	443/607 (73.0)	.55
Casual male partner	217/246 (88.2)	87.2 (79.7–94.7)	213/247 (86.2)	83.7 (77.0–90.6)	430/493 (87.2)	.51
Female (anal/vaginal)	120/179 (67.0)	58.6 (38.7–78.5)	72/115 (62.6)	NA	192/294 (65.3)	<.01
Main female partner	79/124 (63.7)	76.7 (58.4–95.1)	55/77 (71.4)	82.1 (68.7–95.4)	134/201 (66.7)	.26
Casual female partner	64/83 (80.1)	82.1 (60.7–100)	57/68 (83.8)	83.9 (69.3–98.6)	121/151 (80.1)	.30
Condom access when needed						<.01
Very difficult	7/354 (2.0)	1.6 (−0.0 to 3.1)	28/329 (8.5)	10.0 (5.9–14.1)	35/683 (5.1)
Sometimes	101/354 (28.5)	26.7 (19.3–34.1)	224/329 (68.1)	66.5 (60.0–73.1)	325/683 (47.6)
Very easy	242/354 (68.4)	70.6 (63.1–78.2)	71/329 (21.6)	22.3 (16.5–28.0)	313/683 (45.8)
Refused to answer/do not know	4/354 (1.1)	1.1 (−0.0 to 2.3)	6/329 (1.8)	1.2 (0.0–2.4)	10/683 (1.5)
In the last 12 months…, mean (IQR)
No. of men you have had anal sex with	3.7 (1–25)	NA	4.0 (1–28)	NA	3.9 (1–40)	.59
No. of men you have had insertive anal sex with	1.1 (0–20)	NA	1.2 (0–8)	NA	1.2 (0–20)	.95
No. of men you have had receptive anal sex with	1.4 (0–30)	NA	0.9 (0–9)	NA	1.0 (0–20)	.42
No. of main partners you have had anal sex^a	1.1 (0–5)	NA	1.5 (0–7)	NA	1.3 (0–9)	<.01
No. of casual partners you have had anal sex^a	2.9 (0–19)	NA	2.3 (0–13)	NA	2.6 (0–25)	.17
No. of partners anal sex with last month^a	3.4 (0–15)	NA	3.4 (0–18)	NA	3.4 (0–20)	.96
Ever felt that family members have made discriminatory remarks^b	54/354 (15.3)	10.3 (6.2–14.4)	64/329 (19.5)	16.8 (12.0–21.7)	118/683 (17.3)	.15
Ever had difficulties accessing health services^b	60/354 (17.0)	22.2 (15.4–29.0)	24/329 (7.3)	78.0 (3.5–12.5)	84/683 (12.3)	<.01
Ever avoided health services^b	25/354 (7.1)	7.6 (3.7–11.6)	30/329 (9.1)	13.0 (7.8–18.3)	55/683 (8.1)	.32
Ever been verbally harassed^b	67/354 (18.9)	12.9 (8.3–17.6)	60/329 (18.2)	15.1 (10.8–19.3)	127/683 (18.6)	.82
Ever been blackmailed^b	57/354 (16.1)	11.2 (7.0–15.3)	72/329 (21.9)	19.3 (14.4–24.3)	129/683 (19.0)	.05
Ever been forced to have sex	25/354 (7.1)	6.7 (2.8–10.6)	27/329 (8.2)	8.8 (5.1–12.5)	52/683 (7.6)	.57

Significant p-values are noted in bold.

Insertive or receptive anal sex.

Because of having sex with other men.

Laboratory testing

Trained technicians collected blood samples and administered all biological testing. HIV and syphilis testing were conducted according to Togolese National guidelines.³⁴ HIV testing included voluntary counseling, HIV screening, and confirmatory testing using rapid kits. The HIV testing algorithm was sequential, with the first test being Determine HIV 1/2 Ag/Ab Combo Rapid Test (Watham, MA). All positive tests were confirmed using First Response HIV test 1–20 cards (PMC Medical, Nani Damam, India). Western blot was used for discrepant results. Syphilis testing was conducted using treponema pallidum hemagglutination assay (TPHA) and Venereal Disease Research Laboratory (VDRL) test. Participants who tested positive for syphilis were provided with free treatment onsite, and those who tested positive for HIV were referred to a health care center that was known to be capable of addressing the particular needs of MSM.

Statistical analyses

Indicators for each city were analyzed and reported as crude numbers and proportions, and RDS-adjusted (RDSa) estimates. Crude estimates represent the numbers and proportions reported from the study sample, and RDSa proportions are estimates of the broader MSM population of each city, with each variable's proportion based on the number of participants who answered each question. RDSa proportion estimates were calculated from these weights, which attempt to address homophily, the tendency of participants to recruit others like them, and for the variation in network size, two potential biases of RDS.³¹ Volz-Heckathorn was used as an estimator to account for differences in social network sizes of participants. The variable “In the last month, how often were condoms used when you had anal sex with male partners” was utilized to generate individual weights for bivariate analysis. All seeds were included in the analysis. Network size was assessed by asking: “How many people do you know personally who are men who have sex with men?” RDSa proportions and 95% confidence intervals (CIs) were estimated using a bootstrap method with 1,000 repetitions for all variables explored.³⁵ Gender identity was determined based on a two-step gender assessment, asking first to the participant if their sex at birth was male, followed by the question about gender with the options of man, woman, or intersex. Transgender woman was defined as someone with a female gender identity and a male sex assigned at birth³⁶ and intersex was defined as someone assigned male sex at birth and identifying as intersex gender.

Logistic regression models were used to estimate the association between condom use during insertive/receptive anal sex in the last month with any male partner (CCU) (outcome) and variables selected based on our knowledge and published literature.²⁹ Multivariable logistic regression models were built to estimate the adjusted odds ratio (aOR). Pooled, crude estimates were used in the multivariable logistic regression model. For regression analysis, quantitative variables such as age (18–24/>24 years) and income [≤2,000 CFA (∼4 USD), 2,001–12,000 CFA (∼4–24 USD), >12,000 CFA (∼24 USD)] were categorized. The final model included age income, gender (male, female, and intersex), and condom access (very difficult, somewhat difficult/easy, and very easy). It also included dichotomous variables with yes/no responses: ever been forced to have sex, HIV status, health service access, and history of being blackmailed (Table 4). Pearson's chi square and Fisher's exact tests were used to explore associations of binary variables, and statistical significance was set at p < .05.^37,38 Akaike information criteria (AIC) and Bayesian information criteria (BIC) were used to identify more parsimonious models and to determine the final model.^37,39 Crude, instead of RDSa estimates were used for the final multivariable model given that the data for Kara and Lomé are not linked, and as a standard for the use of RDSa estimates in these models is not yet established.³⁷ Therefore, pooled estimates from both cities were provided without weights for consistency with the logistic regression models. All data were analyzed using Stata 12.1 (Stata/IC, College Station, TX).

Results

In Lomé, a total of 439 coupons were distributed, and 354 (80%) were returned to the site. All the 354 MSM with coupons were eligible for the survey. Seed one generated 97 (27.4%) recruits, seed two 71 (20.6%) recruits, seed three 135 (38.1%) recruits, and seed four 51 (14.4%) recruits. Eight RDS recruitment waves were sufficient to enroll the a priori determined sample size. Homophily for HIV status was −0.49 among HIV-negative MSM and 0.2 for those living with HIV. In Kara, 468 coupons were distributed, and 329 (70.3%) were returned to the site. All the participants who returned the coupon were eligible. Seed 1 generated 101 (30.7%) recruits, seed 2 generated 226 (68.7%) recruits, and seeds 3 and 4 generated 1 recruit each (0.3, respectively). Eight recruitment waves were needed to reach the predetermined sample size.

Table 1 presents the demographic and biological characteristics for each study site, and also pooled data from both cities. A total of 683 MSM were surveyed, 354 (51.8%) in the capital city of Lomé and 329 (48.2%) in the northern city of Kara. Overall, 62.8% (429/623) of the participants were between 18 and 24 years of age, with a median age of 23.9 years, almost 70% (476/683) had secondary school or more, and >90% (640/683) were single or had never been married. Median income was 5,000 CFA/week (∼8.1 USD/week). Over 2/3 of the sample self-identified as gay/homosexual and >80% (556/683) self-identified as being male.

Table 1.

Sociodemographic and Biological Characteristics of Men Who Have Sex With Men Living in Lomé (n = 354) and Kara (n = 329)

Characteristic	Lomé		Kara		Pooled
Characteristic	n (%)	RDS-weighted, % (95% CI)	n (%)	RDS-weighted, % (95% CI)	n (%)	p
Total	354 (100)		329 (100)		683 (100)
Age, median (IQR) (years)	23.2 (18–40)		24.7 (18–35)		23.9 (18–45)	<.01
18–24	253 (71.5)	79.1 (73.6–84.7)	176 (53.5)	55.5 (49.0–62.0)	429 (62.8)	<.01
25 and older	101 (28.5)	20.9 (15.4–26.5)	153 (46.5)	44.5 (38.0–51.1)	254 (37.2)
Gender						<.01
Male	255 (72.0)	67.9 (59.8–76.1)	301 (91.5)	91.2 (87.4–95.1)	556 (81.4)
Transgender woman	43 (12.2)	18.1 (10.1–26.2)	6 (1.8)	1.3 (0.0–2.7)	49 (7.2)
Intersex	56 (15.8)	13.9 (8.7–19.2)	22 (6.7)	7.4 (3.8–11.0)	78 (11.4)
Marital status to a woman						<.01
Single/never married	322 (91.0)	91.7 (88.0–95.5)	318 (96.7)	95.4 (92.3–98.6)	640 (93.7)
Married	9 (2.5)	1.6 (0.3–3.0)	3 (0.9)	1.3 (−0.0 to 3.0)	12 (1.8)
Other	21 (5.9)	6.6 (3.0–10.3)	7 (2.1)	3.3 (0.1–5.9)	31 (4.8)
Education						<.01
Secondary or less	141 (39.8)	40.6 (32.7–48.5)	66 (20.1)	19.9 (14.7–25.1)	207 (30.3)
More than secondary	213 (60.2)	59.4 (51.5–67.3)	263 (79.9)	80.1 (74.9–85.3)	476 (69.7)
Employment/occupation						.03
Student	129 (36.4)	38.2 (30.4–46.1)	113 (34.4)	37.0 (30.2–43.4)	242 (35.4)
Employed or self-employed	197 (55.7)	55.9 (47.8–63.9)	169 (51.4)	49.0 (42.3–55.6)	366 (53.6)
Unemployed	28 (7.9)	5.9 (2.5–9.3)	47 (14.3)	14.0 (9.5–18.6)	75 (11.0)
Weekly income (CFA^a), median (IQR) (years)		5,250 (2,000–12,000)		3,000 (1,500–7,000)	5,000 (2,000–10,000)	<.01
≤2,000 CFA	93 (26.3)	23.0 (17.0–29.0)	135 (41.0)	41.3 (34.9–47.7)	228 (33.4)	<.01
2,001–12,000 CFA	171 (48.3)	46.5 (38.8–54.2)	158 (48.0)	48.7 (42.2–55.2)	329 (48.2)
More than 12,000 CFA	90 (25.4)	31.0 (22.6–38.5)	36 (10.9)	10.0 (6.4–13.6)	126 (18.5)
Sexual orientation						<.01
Gay/homosexual	216 (61.0)	61.2 (53.2–69.2)	226 (68.7)	62.6 (56.2–69.1)	442 (64.7)
Bisexual	124 (35.0)	34.4 (26.9–41.9)	103 (31.1)	37.4 (30.9–43.8)	227 (33.2)
Heterosexual	3 (0.9)	1.13 (−0.01 to 0.0)	0 (0.0)	0 (0.0)	3 (0.4)
Transgender	11 (3.1)	0.03 (0.0–0.01)	0 (0.0)	0 (0.0)	11 (1.6)
No. of MSM^b who you personally know, median (IQR)	44.1 (2–500)		10.3 (2–65)		27.8 (27.8)	<.01
Ever tested for HIV	247 (69.8)	66.7 (59.4–74.1)	236 (71.7)	71.5 (22.6–34.5)	483 (70.7)	.57
Living with HIV	61 (17.5)	10.4 (6.6–14.3)	1 (0.3)	0.2 (−0.2 to 1.0)	62 (9.2)	<.01
Tested positive for syphilis	5 (1.4)	1.3 (97.6–2.5)	2 (1.6)	0.9 (−0.3 to 2.2)	7 (1.0)	.29

Significant p-values are noted in bold.

CFA exchange rate December 2013; 1 USD = 476.2 CFA.

CFA, Communaute Financiere Africaine; IQR, interquartile range; MSM, men who have sex with men.

MSM living in Lomé were younger (p < .01), had a higher income (p < .01), were less frequently single/never married (p < .01), less educated (p < .01), and employment was more prevalent (p = .03) compared with MSM surveyed in Kara. In total, 9.2% (62/683) of the participants were living with HIV, 17.5% (61/354) in Lomé and 0.3% (1/329) in Kara (p < .01). No individuals were found to be coinfected with syphilis and HIV. In addition, ever feeling discriminatory remarks from family members was reported by 17.3% (118/683), difficulties accessing health services by 12.3% (84/683), ever being verbally harassed by 18.6% (127/683), or blackmailed by 19.0% (129/683) of the participants (Table 1).

Table 2 presents the crude and RDSa estimates of condom use and sexual behavior, and crude estimates for the pooled data. Overall, more than half [54.8% (374/683)] of MSM sampled reported always using condoms for anal sex with a male partner during the last month. In addition, in the past 12 months, participants reported having, on average, insertive anal sex with 1.2 male partners and receptive anal sex with 1 male partner (Table 2).

MSM living in Kara had decreased odds of reporting CCU in the last month during anal sex with another male partner compared with those living in Lomé (OR = 0.49, 95% CI = 0.36–0.66). In addition, men who had an income between 2,001 and 12,000 CFA had lower odds of CCU with a male partner during the last month compared with the lowest income group (OR = 0.58, 95% CI = 0.41–0.82). When compared with men, MSM self-identifying their gender as intersex (OR = 0.45, 95% CI = 0.28–0.74), and those who had ever been forced to have sex (OR = 0.31, 95% CI = 0.17–0.57) had lower odds of CCU (Table 3).

Table 3.

Factors Associated with Always Using a Condom During Anal Sex in the Last Month Among Men Who Have Sex With Men Living in Lomé and Kara, Togo

	Always used condom anal sex last month, n (%)	OR (95% CI)	p	aOR (95% CI)	p
City
Lomé	224/354 (63.3)	1.0		1.0
Kara	150/329 (45.6)	0.49 (0.36–0.66)	<.01	0.29 (0.19–0.44)	<.01
Age (years)
18–24	234/429 (54.6)	1.0		1.0
25 and older	140/254 (55.1)	1.02 (0.75–1.40)	.88	1.49 (1.04–2.14)	.03
Income (CFA)
≤2,000	146/228 (64.0)	1.0		1.0
2,001–12,000	167/329 (50.8)	0.58 (0.41–0.82)	<.01	0.53 (0.36–0.77)	<.01
More than 12,000	61/126 (48.4)	0.53 (0.34–0.82)	<.01	0.34 (0.20–0.57)	<.01
Gender
Male	322/556 (57.9)	1.0		1.0
Transgender woman	22/49 (44.9)	0.59 (0.33–1.07)	.80	0.47 (0.25–0.92)	<.03
Intersex	30/78 (38.5)	0.45 (0.28–0.74)	<.01	0.42 (0.24–0.73)	<.01
Condom access
Very difficult	11/35 (31.4)	1.0		1.0
Somewhat difficult/easy	171/325 (52.6)	2.4 (1.15–5.11)	.02	2.70 (1.23–5.94)	.01
Very easy	1,192/313 (61.3)	3.46 (1.64–7.32)	<.01	2.73 (1.20–6.16)	.02
Ever been forced to have sex	15/52 (28.9)	0.31 (0.17–0.57)	<.01	0.42 (0.21–0.82)	.01
Living with HIV	31/62 (50)	0.81 (0.48–1.37)	.44	0.69 (0.38–1.26)	.23

Significant p-values are noted in bold.

aOR, adjusted odds ratio; OR, odds ratio.

After adjusting for potential confounders, MSM living in Kara (aOR = 0.29, 95% CI = 0.19–0.44), and men reporting a higher income [2,001 and 12,000 CFA aOR = 0.53, 95% CI = 0.36–0.77 and >12,000 CFA (∼24 USD) aOR = 0.34, 95% CI = 0.20–0.57] had lower odds of CCU. In addition, transgender woman (aOR = 0.47, 95% CI = 0.25–0.92) and intersex (aOR = 0.42, 95% CI = 0.24–0.73) had lower odds of CCU. Lifetime history of forced sex was also associated with inconsistent condom use (aOR = 0.42, 95% CI = 0.21–0.82). Older MSM (aOR = 1.49, 95% CI = 1.04–2.14) and those with more access to condoms (aOR = 2.73, 95% CI = 1.20–6.16) had increased odds of CCU (Table 3).

Discussion

These analyses described the socioeconomic, demographic, and biological determinants that influence the use of condoms for anal sex among MSM living in Togo. Our sample was composed mainly of young, medium income, educated, and cis-MSM. Approximately 1 of every 10 reported some form of stigma and/or discrimination. The average size of an individual's network was four times larger in Lomé than in Kara. Overall, MSM in Lomé reported using condom more consistently during anal sex with another male partner in the past month. CCU was highest in Lomé when having anal sex with a casual male partner. The prevalence of CCU by MSM in Togo was comparable with reports of limited condom use in other West African countries.^22,25,40,41 Finally, the adjusted models show that the odds of CCU were higher among older MSM, and among those who had easier access to condoms. Taken together, these results highlight the importance of understanding the social, cultural, educational, and behavioral characteristics that might be conditioning condom use among MSM in these settings, information that would be fundamental toward the development of effective interventions.

Although we report on the positive association between CCU and older age among MSM, regional results on this factor have been inconsistent. Studies from Nigeria, Swaziland, and Cameroon found no association between age and CAI among MSM.^24,25,40 In contrast, Lane et al. reported that MSM 25 years of age and older were more likely to have CAI.⁴² CCU among older MSM could be explained by greater negotiating skills and/or increased access to counseling services that educate and promote the importance of CCU as a preventive tool against HIV infection. Results support the development of behavioral interventions that address the needs and risk behaviors of young MSM in Togo. In addition, studies from high-income countries have reported links between both having casual partners and alcohol/drug consumption with decreased CCU among young MSM.^43,44 Based on our findings, young MSM should be further engaged in future HIV/STI services that provide access to condoms in Togo. It is important for programs to consider structural factors that can hamper program success, such as stigma, discrimination, culture, and government policy toward same sex behavior. Young MSM represent a population that is very difficult to reach and, when underage, are not likely to be characterized in behavioral and biological surveys. The latter should be taken into account to improve and/or develop better and more effective preventive services.

The role that personal income has on condom use among MSM in low-income countries is complex and understudied. This association can be mediated by other socioeconomic factors, such as education, marital status, and biological determinants, such as HIV status.^45,46 In Lomé and Kara, MSM with higher income were less likely to report CCU contrasting with findings reported among MSM in South Africa, China, and the United States, where no association has been observed between economic status and CCU.^47
–49 In contrast with our results, Bakai et al. reported, using data from a cross-sectional survey that recruited MSM using snowball sampling, that MSM in Togo with a higher educational level and who had participated in HIV and STI prevention activities were more likely to have used a condom during the last anal intercourse.⁵⁰ In our study, there was no association between educational level and CCU among MSM living in Lomé and Kara during the last month. Independent of their educational level, the underlying reasons for condom use may be far more complex, starting with HIV serostatus knowledge, having access to condoms when needed, and stigma. In addition, network dynamics may also shape access to services and decision-making among MSM regardless of their educational level. Finally, limited research and contrasting results on the relationship between income and CCU among MSM make interpretation of these data challenging and highlight the need for additional research.^25,41,51,52

The relationship between gender identity and sexual behavior is poorly understood in much of sub-Saharan Africa.⁵³ In this study, after adjusting for potential confounders, transgender women were shown to have decreased odds of CCU. Research in multiple high and middle-income countries suggest that transgender women are at higher risk of stigma, discrimination, marginalization, and HIV infection by differing levels of risk^33,54,55 even when compared with other key populations. However, data on CCU for transgender women are limited. Studies have highlighted that cis-MSM living with HIV are more likely to use condoms during anal sex, aiming to reduce the risk of transmitting the infection to others.^56,57 Transgender women have been reported to be less likely to use condoms and to have difficulties negotiating condom use with their primary sexual partner and other sexual partners.^58,59 The association found in Togo may be partially explained by the high access to HIV preventive services regardless of gender identity. These findings provide important information to guide prevention programs to specify messages based on an individuals' gender identity aiming to enhance CCU.

There is limited information on MSM's population size, social isolation, conservative attitudes, and restricted access to health services and how these factors guide behavior related to condom use.^60
–62 In these analyses, a higher proportion of MSM in the urban city of Lomé, compared with those living in Kara, reported CCU. This finding is inconsistent with results from a study conducted in Nigeria, reporting that MSM living in urban areas are less likely to report CCU.⁴⁰ Other factors explored in these analyses might explain the reported differences. First, sexual behaviors within MSM networks, social norms, and conventions might differ between Lomé and Kara, allowing MSM to have more access to preventive services or other types of social support such as friends or families.^33,63 Second, in Kara, behaviors associated with stigma and discrimination, such as difficulties accessing health services and being blackmailed were significantly higher compared with Lomé. These factors may partially explain the lower prevalence of CCU in the city of Kara. Finally, the number of NGOs providing services and their capacity to reach MSM can also impact CCU and linkage to the continuum of HIV care.^12,64 Collectively, our findings suggest that successful interventions might differ in relation to the characteristics of the city, and should be taken into consideration as they are developed, aiming to increase CCU among MSM. In addition, social capital was higher for MSM living in Kara. When information on social capital is available and reliable, it should be considered as programs are developed and implemented, given its inherent potential for understanding the population, resulting in improved access to HIV treatment, care, and preventive services. Finally, given the high variability that exists when reporting implementation studies, it would be useful for NGOs and other agencies, to report their findings using guidelines specifically developed to capture the diversity that is inherent to the context and the population of an intervention.⁶⁵

Results should be viewed in light of a few limitations. The cross-sectional design of the study limits causal inference. The generalizability of these findings should be made with caution given the significant variability regarding different behavioral, social, and biological factors that affect CCU that has been reported in different countries across sub-Saharan Africa.^{12,21,25,40,63} In addition, social desirability bias could be present when self-reporting sensitive sexual behavior including condom use during anal sex. RDS was used to account for the limited access to the population; however, the results may not represent the individuals less connected to larger networks. In addition, a high number of participants reported being “intersex,” which was defined as people who did not have sexual/reproductive anatomy conforming to biological norms. The high prevalence could be a result of participants misunderstanding being intersex as falling within the transfeminine spectrum. Finally, adjusted analyses of RDS could not be conducted for the bivariate and multivariate analysis for Kara and Lomé combined given that the networks in the two cities were unrelated. Consequently, multivariate analysis was conducted with unadjusted pooled data and estimation may not be generalizable to the population.

CCU is an important and effective strategy to prevent HIV acquisition and transmission during anal sex among MSM.^66,67 Several factors associated with CCU were identified in this study including older age and access to condoms. Considering the low condom use reported, and multiple barriers to preventive services experienced by this population, alternative prevention strategies should be considered as options for individual MSM such as preexposure prophylaxis, lubricants, and condoms that aim to increase usage (e.g., flavors, size, shape, color, and lubricants). Structural level barriers such as decriminalization and protective legislation of same sex behavior in Togo should also be targeted to improve training of health care providers and law enforcement agencies using stigma mitigating intervention and rights-based approach.^68,69 CCU remains essential toward HIV/STI prevention in this group. These data provide insight into determinants that can be leveraged to increase condom use among MSM in these settings.

Footnotes

Acknowledgments

The authors thank the men who participated in the study for their engagement and making this analysis possible. The authors concurrently thank the Togo Ministry of Health for approving and collaborating on this study and Erin Papworth and Ping-An Chen for their support in implementing the study. The authors also acknowledge the team at United States Agency for International Development (USAID) and USAID West Africa, for their continued dedication and important role in the success of this study and similar studies across the region. The study was implemented by USAID | Project SEARCH, Task Order No. 2, which is funded by the U.S. Agency for International Development under Contract No. GHH-I-00-07-00032-00, beginning September 30, 2008, and supported by the President's Emergency Plan for AIDS Relief. S.B.'s efforts for this publication were supported by National Institutes of Mental Health and Office of AIDS Research of the National Institutes of Health under award number R01MH110358. Finally, this publication was made possible with help from the Johns Hopkins University Center for AIDS Research, an National Institutes for Health (NIH)-funded program (P30AI094189), which is supported by the following NIH co-funding and participating Institutes and Centers: National Institute of Allergy and Infectious Diseases (NIAID), National Cancer Institute (NCI), National Institute of Child Health and Human Development (NICHD), National Heart, Lung, and Blood Institute (NHLBI), National Institute on Drug Abuse (NIDA), National Institute of Mental Health (NIMH), National Institute on Aging (NIA), Fogarty International Center (FIC), National Institute of General Medical Sciences (NIGMS), National Institute of Diabetes and Digestive and Kidney Diseases (NIDDK), and the Office of AIDS Research (OAR). The content is solely the responsibility of the authors and does not necessarily represent the official views of the NIH. The funding sources had no role in the study design; in the collection, analysis, and interpretation of data; in the writing of the articles; or in the decision to submit the article for publication.

Author Disclosure Statement

No competing financial interests exist.

References

Beyrer

, Baral

, van Griensven

, et al.: Global epidemiology of HIV infection in men who have sex with men. Lancet, 2012; 380:367–377.

Baral

, Sifakis

, Cleghorn

, Beyrer

: Elevated risk for HIV infection among men who have sex with men in low-and middle-income countries 2000–2006: A systematic review. PLoS Med, 2007; 4:e339.

van Griensven

, van Wijngaarden

JWdL

, Baral

, Grulich

: The global epidemic of HIV infection among men who have sex with men. Curr Opin HIV AIDS, 2009; 4:300–307.

Fitzergerald

:: The Changing Face of HIV Prevention Programs in Burkina Faso and Togo: Opportunities and Challenges of Providing HIV Prevention Programs and Services for Most-at-Risk Population in Burkina Faso and Togo. USAID, Arlington, VA, 2013.

Mason

, Ketende

, Peitzmeier

, et al.: A cross-sectional analysis of population demographics, HIV knowledge and risk behaviors, and prevalence and associations of HIV among men who have sex with men in the Gambia. AIDS Res Hum Retroviruses, 2013; 29:1547–1552.

MSM, HIV, and the Road to Universal Access: How Far Have We Come?. amfAR, The Foundation for AIDS Research, Washington, DC, 2008.

Report of the Modes of Transmission HIV Study. Benin, 2009.

Lyons

, Ketende

, Diouf

, et al.: Potential impact of integrated stigma mitigation interventions in improving HIV/AIDS Service Delivery and Uptake for Key Populations in Senegal. J Acquir Immune Def Syndr, 2017; 74 Suppl 1:S52–s59.

World Health Organization: Definitions of Key Terms. 2013. Available at www.who.int/hiv/pub/guidelines/arv2013/intro/keyterms/en (2013), accessed 2018.

10.

Wade

, Larmarange

, Diop

, et al.: Reduction in risk-taking behaviors among MSM in Senegal between 2004 and 2007 and prevalence of HIV and other STIs. ELIHoS Project, ANRS 12139. AIDS Care, 2010; 22:409–414.

11.

Merrigan

, Azeez

, Afolabi

, et al.: HIV prevalence and risk behaviours among men having sex with men in Nigeria. Sex Transm Infect, 2011; 87:65–70.

12.

Park

, Papworth

, Kassegne

, et al.: HIV prevalence and factors associated with HIV infection among men who have sex with men in Cameroon. J Int AIDS Soc, 2013; 16 Suppl 3:18752.

13.

Vuylsteke

, Semde

, Sika

, et al.: High prevalence of HIV and sexually transmitted infections among male sex workers in Abidjan, Cote d'Ivoire: Need for services tailored to their needs. Sex Transm Infect, 2012; 88:288–293.

14.

Papworth

, Grosso

, Ketende

, et al.: Examining Risk Factors for HIV and Access to Services Among Female Sex Workers (FSW) and Men who have Sex with Men (MSM) in Burkina Faso, Togo and Cameroon. USAID Project Search: Research to Prevention, Baltimore, 2014.

15.

Joint United Nations Programme on HIV/AIDS: UNAIDS Terminology Guidelines . 2015. Joint United Nations Programme on HIV/AIDS, Geneva, Switzerland, 2015.

16.

Centers for Educational Justince and Community Engagement UC Berkley: Gender Equity Resource Center: Definitions of terms. Available at http://ejce.berkeley.edu/geneq/resources/lgbtq-resources/definition-terms (2017), accessed January, 2017.

17.

Baggaley

, White

, Boily

: HIV transmission risk through anal intercourse: Systematic review, meta-analysis and implications for HIV prevention. Int J Epidemiol, 2010; 39:1048–1063.

18.

Yang

, Huang

, Dong

, et al.: Risk factors for HIV diagnosis among men who have sex with men: Results of a case-control study in one sample of Eastern China. AIDS Res Hum Retroviruses, 2016; 32:1163–1168.

19.

Tohme

, Egan

, Stall

, Wagner

, Mokhbat

: HIV prevalence and demographic determinants of unprotected anal sex and HIV testing among male refugees who have sex with men in Beirut, Lebanon. AIDS Behav, 2016; 20:408–416.

20.

Stahlman

, Liestman

, Ketende

, et al.: Characterizing the HIV risks and potential pathways to HIV infection among transgender women in Cote d'Ivoire, Togo and Burkina Faso. J Int AIDS Soc, 2016; 19(3 Suppl 2):20774.

21.

Adam

, de Wit

, Toskin

, et al.: Estimating levels of HIV testing, HIV prevention coverage, HIV knowledge, and condom use among men who have sex with men (MSM) in low-income and middle-income countries. J Acquir Immune Def Syndr, 2009; 52:S143–S151.

22.

United Nations Joint Program on HIV and AIDS: Condom use among men who have sex with men. Available at http://aidsinfo.unaids.org (2016), accessed 2016.

23.

Ubrihien

, Davies

, Driscoll

: Is cost a structural barrier preventing men who have sex with men accessing condoms? A systematic review. AIDS Care, 2016; 28:1473–1480.

24.

Brown

, Grosso

, Adams

, et al.: Characterizing the individual, social, and structural determinants of condom use among men who have sex with men in Swaziland. AIDS Res Hum Retroviruses, 2016; 32:539–546.

25.

Henry

, Marcellin

, Yomb

, et al.: Factors associated with unprotected anal intercourse among men who have sex with men in Douala, Cameroon. Sex Transm Infect, 2010; 86:136–140.

26.

Wendi

, Stahlman

, Grosso

, et al.: Depressive symptoms and substance use as mediators of stigma affecting men who have sex with men in Lesotho: A structural equation modeling approach. Ann Epidemiol, 2016; 26:551–556.

27.

The World Bank: Togo. Available at http://data.worldbank.org/country/togo (2016), accessed March 11, 2016 .

28.

UNAIDS: Report of the response to HIV/AIDS in Togo. Togo, 2014.

29.

Baral

, Grosso

, Holland

, Papworth

: The epidemiology of HIV among men who have sex with men in countries with generalized HIV epidemics. Curr Opin HIV AIDS, 2014; 9:156–167.

30.

2011 Country Reports on Human Rights Practices: Togo, Bureau of Democracy, Human Rights and Labor. U.S. Department of State, 2011.

31.

Heckathorn

: Respondent-driven sampling: A new approach to the study of hidden populations. Social Prob, 1997; 44:174–199.

32.

Salganik

: Variance estimation, design effects, and sample size calculations for respondent-driven sampling. J Urban Health, 2006; 83(6 Suppl):i98–i112.

33.

Baral

, Logie

, Grosso

, Wirtz

, Beyrer

: Modified social ecological model: A tool to guide the assessment of the risks and risk contexts of HIV epidemics. BMC Public Health, 2013; 13:482.

34.

Conseil National de Lutte Contre le SIDA et les Infections Sexuallement Transmissibles (CNLS-IST): National policy against HIV/AIDS in Togo: Vision 2020. Available at https://hivhealthclearinghouse.unesco.org/sites/default/files/resources/politique_nationale_de_lutte_contre_le_sida_au_togo_vision_2020.pdf (2012), accessed July 2018 .

35.

Schonlau

, Liebau

: Respondent-driven sampling. Stata J, 2012; 12:72–93.

36.

University of San Francisco Center of Excellence for Transgender Health: Terminology and definitions. Available at http://transhealth.ucsf.edu/tcoe?page=guidelines-terminology (2017), accessed August 2017 .

37.

Akaike

: Information theory and an extension of the maximum likelihood principle. Paper presented at: 2nd International Symposium on Information Theory. Budapest, Akademiai Kiado, 1973.

38.

Schwarz

: Estimating the dimension of a model. Ann Stat, 1978; 6:461–464.

39.

Konishi

, Kitagawa

: Bayesian information criteria. Inf Criteria Stat Model, 2008:211–237.

40.

, Andrinopoulos

, Tun

, Adebajo

: High levels of unprotected anal intercourse and never testing for HIV among men who have sex with men in Nigeria: Evidence from a cross-sectional survey for the need for innovative approaches to HIV prevention. Sex Transm Infect, 2013; 89:659–665.

41.

Larmarange

, Wade

, Diop

, et al.: Men who have sex with men (MSM) and factors associated with not using a condom at last sexual intercourse with a man and with a woman in Senegal. PLoS One, 2010; 5:e13189.

42.

Lane

, Shade

, McIntyre

, Morin

: Alcohol and sexual risk behavior among men who have sex with men in South African township communities. AIDS Behav, 2008; 12:78–85.

43.

Weinhardt

, Carey

: Does alcohol lead to sexual risk behavior? Findings from event-level research. Ann Rev Sex Res, 2000; 11:125–157.

44.

Knight

, Shade

, Purcell

, et al.: Sexual transmission risk behavior reported among behaviorally bisexual HIV-positive injection drug-using men. J Acquir Immune Def Syndr, 2007; 46:S80–S87.

45.

Poundstone

, Strathdee

, Celentano

: The social epidemiology of human immunodeficiency virus/acquired immunodeficiency syndrome. Epidemiol Rev, 2004; 26:22–35.

46.

Arnold

, Fisher

, McFarland

: Socioeconomic position and HIV risk-relevant behavior among lower-income heterosexuals in San Francisco. AIDS Behav, 2011; 15:499–506.

47.

Mhlongo

, Dietrich

, Otwombe

, Robertson

, Coates

, Gray

: Factors associated with not testing for HIV and consistent condom use among men in Soweto, South Africa. PLoS One, 2013; 8:e62637.

48.

, Li

, Wang

, Lau

: Prevalence and associated factors of unprotected anal intercourse with regular male sex partners among HIV negative men who have sex with men in China: A cross-sectional survey. PLoS One, 2015; 10:e0119977.

49.

Pines

, Gorbach

, Weiss

, et al.: Individual-level, partnership-level, and sexual event-level predictors of condom use during receptive anal intercourse among HIV-negative men who have sex with men in Los Angeles. AIDS Behav, 2016; 20:1315–1326.

50.

Bakai

, Ekouevi

, Tchounga

, et al.: Condom use and associated factors among men who have sex with men in Togo, West Africa. Pan Afr Med J, 2016; 23:118.

51.

Julio

, Friedman

, Cunha

, et al.: Unprotected sexual practices among men who have sex with women and men who have sex with men living with HIV/AIDS in Rio de Janeiro. Arch Sex Behav, 2015; 44:357–365.

52.

Holtz

, Pattanasin

, Chonwattana

, et al.: Longitudinal analysis of key HIV-risk behavior patterns and predictors in men who have sex with men, Bangkok, Thailand. Arch Sex Behav, 2015; 44:341–348.

53.

Malebranche

, Gvetadze

, Millett

, Sutton

: The relationship between gender role conflict and condom use among Black MSM. AIDS Behav, 2012; 16:2051–2061.

54.

De Santis

: HIV infection risk factors among male-to-female transgender persons: A review of the literature. J Assoc Nurs AIDS Care, 2009; 20:362–372.

55.

Sausa

, Keatley

, Operario

: Perceived risks and benefits of sex work among transgender women of color in San Francisco. Arch Sex Behav, 2007; 36:768–777.

56.

Crepaz

, Marks

, Liau

, et al.: Prevalence of unprotected anal intercourse among HIV-diagnosed MSM in the United States: A meta-analysis. Aids, 2009; 23:1617–1629.

57.

Van Kesteren

, Hospers

, Kok

: Sexual risk behavior among HIV-positive men who have sex with men: A literature review. Patient Educ Counsel, 2007; 65:5–20.

58.

Clements-Nolle

, Marx

, Guzman

, Katz

: HIV prevalence, risk behaviors, health care use, and mental health status of transgender persons: Implications for public health intervention. Am J Public Health, 2001; 91:915.

59.

Nemoto

, Operario

, Keatley

, Han

, Soma

: HIV risk behaviors among male-to-female transgender persons of color in San Francisco. Am J Public Health, 2004; 94:1193–1199.

60.

D'Augelli

: Coming out in community psychology: Personal narrative and disciplinary change. Am J Commun Psychol, 2003; 31:343–354.

61.

D'Augelli

, Hart

: Gay women, men, and families in rural settings: Toward the development of helping communities. Am J Commun Psychol, 1987; 15:79–93.

62.

Oswald

, Culton

: Under the rainbow: Rural gay life and its relevance for family providers. Fam Relat, 2003; 52:72–81.

63.

Ostergren

, Rosser

, Horvath

: Reasons for non-use of condoms among men who have sex with men: A comparison of receptive and insertive role in sex and online and offline meeting venue. Cult Health Sexual, 2011; 13:123–140.

64.

Holland

, Papworth

, Billong

, et al.: Antiretroviral treatment coverage for men who have sex with men and female sex workers living with HIV in Cameroon. J Acquir Immune Def Syndr, 2015; 68:S232–S240.

65.

Pinnock

, Epiphaniou

, Sheikh

, et al.: Developing standards for reporting implementation studies of complex interventions (StaRI): A systematic review and e-Delphi. Implement Sci: IS, 2015; 10:42.

66.

Johnson

, Diaz

, Flanders

, et al.: Behavioral interventions to reduce risk for sexual transmission of HIV among men who have sex with men. Cochrane Database Syst Rev, 2008;(3):CD001230.

67.

Nodin

, Carballo-Dieguez

, Ventuneac

, Balan

, Remien

: Knowledge and acceptability of alternative HIV prevention bio-medical products among MSM who bareback. AIDS Care, 2008; 20:106–115.

68.

Duvall

, Irani

, Compaoré

, et al.: Assessment of policy and access to HIV prevention, care, and treatment services for men who have sex with men and for sex workers in Burkina Faso and Togo. JAIDS J Acquir Immune Def Syndr, 2015; 68:S189–S197.

69.

Delany-Moretlwe

, Cowan

, Busza

, Bolton-Moore

, Kelley

, Fairlie

: Providing comprehensive health services for young key populations: Needs, barriers and gaps. J Int AIDS Soc, 2015; 18(2 Suppl 1):19833.