Most (87.4%) reported having ever had sexual intercourse, and 72.3% reported sexual intercourse in the past 12 months. Among these, 11.5% reported 2 or more partners in the past 12 months. Eighty-five percent of participants reported no to low self-perceived risk of HIV infection. Anal sex was reported by 1.9%. Receiving money, gifts, and favors in exchange for sex was reported by 3.8%. In total, 17.8% of men reported ever giving money, gifts, or favors in exchange for sex. Symptoms of STI in the past 12 months, including genital sores and/or vaginal (women only), penile (men only), or anal discharge were reported by 5.8% (2.7% of men and 8.7% of women). Among women, 78.8% had ever been pregnant, and 6.2% were currently pregnant at the time of the survey. Ninety-one percent of men were circumcised, and 70.1% of women reported that their current male partner was circumcised.
HIV Prevalence and Incidence
HIV prevalence was 5.6% (95% CI: 4.9 to 6.3), and HIV incidence was 0.5% (95% CI: 0.2 to 0.9), corresponding to an annual HIV transmission rate of 8.9 per 100 HIV-infected persons. Regional differences in HIV prevalence were observed with the highest HIV prevalence noted in Nyanza region (15.1%, 95% CI: 11.4 to 18.8) and lowest in Eastern North region (2.1%, 95% CI: 1.0 to 3.2) (Table 2). Women had significantly higher HIV prevalence than men (6.9% vs. 4.4%; P < 0.0001). HIV prevalence increased with age, peaking at age 35–39 years among women (12.3%, 95% CI: 9.4 to 15.2) and age 45–54 years among men (7.2%, 95% CI: 4.9 to 9.6) (data not shown). HIV prevalence was highest among persons who had been widowed (20.0%, 95% CI: 16.2 to 23.7), separated or divorced (10.9%, 95% CI: 8.4 to 13.4), or were married or cohabiting in a polygamous relationship (9.7%, 95% CI: 6.4 to 13.1).
Trends in HIV Prevalence, 2007–2012
HIV prevalence declined significantly from 7.2% (excluding North Eastern region) in 2007 to 5.6% in 2012 (P = 0.002; Fig. 1). Significant declines were observed for both men (5.5% in 2007 to 4.4% in 2012; P = 0.0310) and women (8.5% in 2007; 6.9% in 2012; P = 0.006) (data not shown). We observed differential changes in HIV prevalence across age groups. In 2007, HIV prevalence peaked among persons aged 30–34 years (11.9%; 95% CI: 10.0 to 13.5), while in 2012, HIV prevalence peaked among persons aged 45–49 years (9.8%, 95% CI: 7.1 to 12.5). HIV prevalence declined significantly for persons who were aged 15–34 years in 2007 and 2012 (P ≤ 0.010) but remained unchanged among persons aged 35 years and older in the same time period.
In Table 3, we describe trends in HIV prevalence between 2007 and 2012 for select age groups by sex, geographic location, and residence. Among persons aged 15–24 years, we observed significant declines in HIV prevalence for women (5.6% in 2007 to 3.0% in 2012; P < 0.001) but not for men (1.0% in 2007 to 1.1% in 2012; P = 0.864). For women aged 15–24 years, significant declines in HIV prevalence were observed among those residing in Nairobi (5.8% in 2007 to 1.8% in 2012; P = 0.038), Coast (5.7% in 2007 to 2.0% in 2012; P = 0.026), and Eastern (4.3%, in 2007 to 0.6% in 2012; P = 0.001) regions and those residing in rural areas (5.7% in 2007 to 2.8% in 2012; P < 0.001). Among men aged 15–24 years, significant declines in HIV prevalence were observed among those residing in Coast region (4.5% to 0.5%; P = 0.041) and rural areas (1.4% to 0.4%; P = 0.012).
Among persons aged 25–34 years, we observed declining HIV prevalence among men (8.1% in 2007 to 5.4% in 2012; P = 0.013) and women (12.0% in 2007 to 7.3% in 2012; P < 0.001). Among women aged 25–34 years, significant declines were observed among those residing in Nairobi (14.0% to 6.6%; P = 0.002), Coast (11.6% to 4.1%; P = 0.005), and Rift Valley (11.2% to 4.0%; P = 0.003) regions and those residing in both rural (11.4% to 6.3%; P < 0.001) and urban (13.5% to 8.7%; P = 0.036) areas in 2007 and 2012, respectively. Among men aged 25–34 years, significant declines were observed in Coast region (7.1% in 2007 to 0.6% in 2012; P = 0.002) and among persons residing in rural areas (8.0% in 2007 to 4.9% in 2012; P = 0.033). Among persons aged 35 years and older, no changes in HIV prevalence were observed across sex and urban/rural residences between 2007 and 2012. HIV prevalence, however, increased significantly among women residing in Central region, from 3.1% in 2007 to 8.4% 2012 (P = 0.001).
Factors Associated With Undiagnosed HIV Infection
Of the 10,097 persons who had ever had sex, 6.3% (95% CI: 5.3 to 7.1) were HIV infected (Table 2); 52.2% (95% CI: 46.5 to 57.8) of these had undiagnosed HIV infection (data not shown). We compared individuals with undiagnosed HIV infection with those who were HIV uninfected to assess factors associated with undiagnosed HIV infection. Among men, factors that were independently associated with increased odds of undiagnosed HIV infection were widowhood (AOR: 8.1, 95% CI: 1.9 to 34.6, P = 0.005) and using a condom with the last sexual partner in the past year (AOR: 3.3, 95% CI: 1.8 to 6.2, P < 0.001) (Table 4). In contrast, men who were circumcised had significantly lower odds of undiagnosed HIV infection (AOR: 0.3, 95% CI: 0.1 to 0.5, P < 0.001). Among women, higher odds of undiagnosed HIV infection were associated with being aged 34–39 years (AOR: 4.5, 95% CI: 1.1 to 18.3, P = 0.037), separated or divorced (AOR: 2.3, 95% CI: 1.1 to 5.0, P = 0.033), residence in Nyanza region (AOR: 2.9, 95% CI: 1.4 to 6.0, P = 0.004), living in urban areas (AOR: 1.8, 95% CI: 1.1 to 2.7, P = 0.012), having a moderate self-perceived risk of HIV infection (AOR: 2.1, 95% CI: 1.3 to 3.5, P = 0.002), using a condom with the last sexual partner in the past year (AOR: 2.3, 95% CI: 1.2 to 4.2, P < 0.009), and reporting ≥ 4 lifetime number of sexual partners (AOR: 1.9, 95% CI: 1.1 to 3.4, P = 0.026).
This population-based survey provides an update on the status of the HIV epidemic in Kenya. HIV prevalence was 5.6% and HIV incidence was 0.5% among persons aged 15–64 years. This represents approximately 1,192,000 million (95% CI: 1,037,000 to 1,347,000) adults and adolescents living with HIV in 2012, 106,000 (95% CI 32,000 to 180,000) of whom had recently acquired their HIV infection within the preceding year. These results broadly corroborate the 2012 estimates published by the Joint United Nations Programme on HIV/AIDS in 2013, which reported that the number of Kenyan adults and adolescents aged ≥15 years living with HIV/AIDS in 2012 was 1,400,000 (lower estimate: 1,400,000; upper estimate: 1,500,000), and the number of new infections was 85,000 (lower estimate: 80,000; upper estimate: 96,000).1 Based on our results, the annual HIV transmission rate was 8.9 per 100 persons living with HIV in 2012. In other words, 9% of all persons living with HIV in 2012 were transmitting to HIV-negative persons. In comparison, the annual transmission rate in the United States, where 16% of the HIV-infected population remains undiagnosed, was 4.1 per 100 HIV-infected persons in 2010.10
Our data confirm a significant decline in HIV prevalence from 7.2% (excluding North Eastern region) in 2007 to 5.6% in 2012, with similar declines noted across male and female sex. Based on mathematically modeled HIV incidence in 2007, our results also suggest that HIV incidence may have declined from 0.7% in 2007 to 0.5% in 2012, coinciding with similar declines in new HIV infections reported by at least 26 countries in Africa, Asia, and the Caribbean between 2001 and 2012.1,11 Declining incidence is also supported by the observation that HIV prevalence reduced significantly among younger persons aged 15-34 years between 2007 and 2012 but remained unchanged among older persons aged 35 years and above.
Among persons aged 15-34 years, we observed differential trends in HIV prevalence across geographic regions and sex, providing important epidemiologic evidence on sub-populations where substantial reductions in HIV infection may be occurring. Among women, declining prevalence was observed for women aged 15–34 years in Nairobi and Coast regions, women aged 15–24 years in Eastern region, and women aged 25–34 years in Rift Valley region. Among men, declining prevalence was observed among men aged 15–34 years in Coast region. Of concern, we found a significant increase in HIV prevalence among middle-aged and older women (aged ≥35 years) residing in Central region.
Reductions in HIV prevalence on a population level is possible if there are marked declines in new HIV infections or high rates of HIV-related death in a population. If substantial, both scenarios on their own could result in a diminished pool of infected people in the population. Over the past 5 years, Kenya has experienced substantial progress in linking HIV-infected persons into HIV care and placing those that require ART on treatment.12 Increased coverage of ART and high levels of viral suppression on ART have led to significant reductions in HIV mortality and HIV transmission risk, likely contributing to a possible decline in HIV incidence over the past 5 years.1,12 Still, over half of HIV-infected persons in the country remained undiagnosed by the year-end (2012), representing a major barrier to achieving even greater reductions in HIV transmission to eventually halt the spread of infection.13 A critical component to reversing this trend will be to accelerate ART coverage in the country by prioritizing HIV testing in settings that will yield greater numbers of HIV-infected persons, facilitating their immediate linkages into HIV care services, and treating them promptly.
Our findings provide important insight on groups with increased risk of transmitting HIV to sexual partners, highlighting opportunities for targeted HIV prevention. Markers of high-risk sexual behaviors, including multiple sexual partners and perceived risk of HIV infection were associated with higher odds of undiagnosed HIV infection. Surprisingly, we found that persons who used a condom with their last sexual partner in the past 12 months had higher odds of undiagnosed HIV infection. This positive association may be a reflection of reluctance or denial in admitting to unprotected sex. Alternatively, it could suggest that persons who choose to use condoms with their sexual partners may already know that they are at high risk of HIV infection despite lack of awareness of their HIV infection. The use of condoms in this group is an encouraging finding for HIV-positive prevention strategies but raises the question as to whether current condom use campaigns are effective in reaching the general population with messages on the important benefits of correct and consistent condom use for HIV prevention.
Widowhood has been previously described as a factor associated with HIV infection in Kenya and other countries in sub-Saharan Africa although the factors that place widowed men at higher risk of HIV infection are not clear-cut.14–18 Widowers whose spouses died of HIV disease may have been exposed to high viral load from their partners, which can occur during late-stage disease,17 but it is also possible that widowed men were sources of infection for their spouses who died from the disease. Studies have also demonstrated that widowers are more likely to engage in high-risk sexual behavior after the death of their spouse and contribute to new HIV infections in the population.15
In addition to widowhood, the link between HIV infection and divorce or separation in women sheds additional light on the vulnerability of women in the Kenyan HIV epidemic. Previous studies in sub-Saharan Africa have reported that the dissolution of marriage, through divorce or separation, is often the result of a female's HIV status within the couple relationship. HIV-infected women in serodiscordant relationships are more likely to be separated or divorced than HIV-infected men in serodiscordant relationships, reinforcing the gender disparities that exist around sexual norms in the African context.18 Further exploration of the impact of serodiscordancy on marital outcomes and implications for the spread of HIV may help to understand how to appropriately strategize prevention, care, and treatment services for couples and formerly married individuals.
Male circumcision has been widely cited as a key pillar of HIV prevention that can significantly reduce new HIV infections in a population.19–21 Because of an aggressive national strategy on male circumcision, which was implemented in 2008, Kenya has observed substantial increases in male circumcision over the past 5 years, increasing from 85.0% in 2007 to 91.2% in 2012.11 Greatest increases were noted in the 4 priority regions for the national voluntary male medical circumcision program: Nairobi, Nyanza, Rift Valley, and Western regions.11 However, coverage in traditionally noncircumcising communities, where regional HIV prevalence is highest, still remains far below the national target of 80% of adult men.22 We found lower odds of HIV infection among circumcised men highlighting that the prevention benefits of this intervention will continue to play an important role in addressing the HIV epidemic in Kenya. Further scale-up of HIV prevention should aim for universal male circumcision accompanied with sexual risk reduction strategies for greater impact in the longer term.
Our results provided important information on geographic areas which require specialized attention for HIV prevention. Continued momentum is needed to address persistently high levels of HIV infection in Nyanza region. Moreover, the observed increases in HIV prevalence among middle-aged and older women in Central region, as well as elevated risk of HIV infection among women in urban residences, are areas which require more focused strategies.
Our study had several limitations. Because this study was cross-sectional in design, we were unable to infer directionality of associations, such as the associations between HIV infection and condom use with last sexual partner, widowhood among men, and divorce or separation among women. Behaviors, circumcision status, and symptoms of STI were self-reported, and associations observed may have been impacted by social desirability bias. Selection bias may have been introduced by decisions to exclude North Eastern region from the sampling frame because of security concerns. The North Eastern region, however, is relatively sparsely populated and had an HIV prevalence of only 0.8% in KAIS 2007,5 and we feel it is unlikely that excluding this region affected our results substantially. Differences in HIV prevalence between KAIS 2007 and KAIS 2012 could also reflect changes in composition of the sample between the two surveys. Compared with KAIS 2007, the sample in KAIS 2012 had significantly higher proportions of persons who were aged 25–34 years, never married or never cohabited, reported secondary education or higher and were from urban residences.7 The demographic, behavioral, and biological differences observed among KAIS 2012 participants in the interview and serologic sample may have also contributed to either an underestimation or overestimation of HIV prevalence in 2012, limiting our ability to accurately interpret trends in HIV prevalence.
Despite these limitations, KAIS 2012 was a large representative study whose primary findings were based on biological samples obtained during the survey. We believe that evidence of decreasing HIV prevalence to be encouraging yet underscores the need to establish routine and standardized surveillance methods to monitor trends in recently acquired HIV infections and HIV-related mortality for a clearer interpretation of the epidemiology of HIV in the country. Our data support that substantial interventions are needed to improve identification of HIV-infected persons to effectively reach those in need of ART for improved survival and continued reductions in transmission risks. Continued monitoring of the burden of HIV disease through enhanced surveillance and seeking to assess and respond to factors associated with undiagnosed HIV infection are central to an effective response to the HIV epidemic in Kenya.
The authors thank the fieldworkers and supervisors for their excellent work during KAIS data collection and all the individuals who participated in this national survey. The authors also thank Timothy Kellogg for his statistical input; George Rutherford and Joy Mirjahangir for discussing and reviewing the article; Anthony Gichangi, John Bore, James Ng'ang'a, Ray Shiraishi, Eddas Bennett, and Paul Stupp for their input in weighting of the data set; and the KAIS Study Group for their contribution to the design of the survey and collection of the data set: Willis Akhwale, Sehin Birhanu, John Bore, Angela Broad, Robert Buluma, Thomas Gachuki, Jennifer Galbraith, Anthony Gichangi, Beth Gikonyo, Margaret Gitau, Joshua Gitonga, Mike Grasso, Malayah Harper, Andrew Imbwaga, Muthoni Junghae, William Maina, Nicolas Muraguri, Mutua Kakinyi, Samuel Mwangi Kamiru, Nicholas Owenje Kandege, Lucy Kanyara, Yasuyo Kawamura, Timothy Kellogg, George Kichamu, Andrea Kim, Lucy Kimondo, Davies Kimanga, Elija Kinyanjui, Stephen Kipkerich, Danson Kimutai Koske, Boniface O. K'Oyugi, Veronica Lee, Serenita Lewis, William Maina, Ernest Makokha, Agneta Mbithi, Joy Mirjahangir, Ibrahim Mohamed, Rex Mpazanje, Silas Mulwa, Nicolas Muraguri, Patrick Murithi, Lilly Muthoni, James Muttunga, Jane Mwangi, Mary Mwangi, Sophie Mwanyumba, Francis Ndichu, Anne Ng'ang'a, James Ng'ang'a, John Gitahi Ng'ang'a, Lucy Ng'ang'a, Carol Ngare, Bernadette Ng'eno, Inviolata Njeri, David Njogu, Bernard Obasi, Macdonald Obudho, Edwin Ochieng, Linus Odawo, Jacob Odhiambo, Caleb Ogada, Samuel Ogola, David Ojakaa, James Kwach Ojwang, George Okumu, Patricia Oluoch, Tom Oluoch, Kenneth Ochieng Omondi, Osborn Otieno, Yakubu Owolabi, Bharat Parekh, George Rutherford, Sandra Schwarcz, Shahnaaz Sharrif, Victor Ssempijja, Lydia Tabuke, Yuko Takenaka, Mamo Umuro, Brian Eugene Wakhutu, Wanjiru Waruiru, Celia Wandera, John Wanyungu, Anthony Waruru, Paul Waweru, Larry Westerman, and Kelly Winter.
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Keywords:© 2014 by Lippincott Williams & Wilkins
HIV; prevalence; incidence; surveillance; Kenya