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In this study we generated multi\u2010factor profiles of HIV acquisition\/transmission risk for men in Durban, South Africa, to help inform targeted programming and service delivery.<\/jats:p><\/jats:sec><jats:sec><jats:title>Methods<\/jats:title><jats:p>Data come from surveys with 947 men ages 20 to 40 conducted in two informal settlements from May to September 2017. Using latent class analysis (LCA), which detects a small set of underlying groups based on multiple dimensions, we identified classes based on nine HIV risk factors and socio\u2010demographic characteristics. We then compared HIV service use between the classes.<\/jats:p><\/jats:sec><jats:sec><jats:title>Results<\/jats:title><jats:p>We identified four latent classes, with good model fit statistics. The<jats:bold>older high\u2010risk class<\/jats:bold>(20% of the sample; mean age 36) were more likely married\/cohabiting and employed, with multiple sexual partners, substantial age\u2010disparity with partners (eight years younger on\u2010average), transactional relationships (including more resource\u2010intensive forms like paying for partner\u2019s rent), and hazardous drinking. The<jats:bold>younger high\u2010risk class<\/jats:bold>(24%; mean age 27) were likely unmarried and employed, with the highest probability of multiple partners in the last year (including 42% with 5+ partners), transactional relationships (less resource\u2010intensive, e.g., clothes\/transportation), hazardous drinking, and inequitable gender views. The<jats:bold>younger moderate\u2010risk class<\/jats:bold>(36%; mean age 23) were most likely unmarried, unemployed technical college\/university students\/graduates. They had a relatively high probability of multiple partners and transactional relationships (less resource\u2010intensive), and moderate hazardous drinking. Finally, the<jats:bold>older low\u2010risk class<\/jats:bold>(20%; mean age 29) were more likely married\/cohabiting, employed, and highly gender\u2010equitable, with few partners and limited transactional relationships. Circumcision (status) was higher among the younger moderate\u2010risk class than either high\u2010risk class (<jats:italic>p<\/jats:italic>\u00a0&lt;\u00a00.001). HIV testing and treatment literacy score were suboptimal and did not differ across classes.<\/jats:p><\/jats:sec><jats:sec><jats:title>Conclusions<\/jats:title><jats:p>Distinct HIV risk profiles among men were identified. Interventions should focus on reaching the highest\u2010risk profiles who, despite their elevated risk, were less or no more likely than the lower\u2010risk to use HIV services. By enabling a more synergistic understanding of subgroups, LCA has potential to enable more strategic, data\u2010driven programming and evaluation.<\/jats:p><\/jats:sec>","DOI":"10.1002\/jia2.25518","type":"journal-article","created":{"date-parts":[[2020,6,27]],"date-time":"2020-06-27T09:14:34Z","timestamp":1593249274000},"update-policy":"https:\/\/doi.org\/10.1002\/crossmark_policy","source":"Crossref","is-referenced-by-count":26,"title":["Creating HIV risk profiles for men in South Africa: a latent class approach using cross\u2010sectional survey data"],"prefix":"10.1002","volume":"23","author":[{"ORCID":"https:\/\/orcid.org\/0000-0001-6422-9478","authenticated-orcid":false,"given":"Ann","family":"Gottert","sequence":"first","affiliation":[{"name":"Population Council Washington DC USA"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-5177-1508","authenticated-orcid":false,"given":"Julie","family":"Pulerwitz","sequence":"additional","affiliation":[{"name":"Population Council Washington DC USA"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-8138-6640","authenticated-orcid":false,"given":"Craig J","family":"Heck","sequence":"additional","affiliation":[{"name":"Population Council New York NY USA"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-5031-2518","authenticated-orcid":false,"given":"Cherie","family":"Cawood","sequence":"additional","affiliation":[{"name":"Epicentre Health Research Pietermaritzburg South Africa"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-1645-6734","authenticated-orcid":false,"given":"Sanyukta","family":"Mathur","sequence":"additional","affiliation":[{"name":"Population Council Washington DC USA"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"311","published-online":{"date-parts":[[2020,6,26]]},"reference":[{"key":"e_1_2_9_2_1","doi-asserted-by":"publisher","DOI":"10.1111\/j.1365-3156.2011.02767.x"},{"key":"e_1_2_9_3_1","volume-title":"Blind spot: reaching out to men and boys","author":"UNAIDS","year":"2017"},{"key":"e_1_2_9_4_1","doi-asserted-by":"publisher","DOI":"10.1097\/COH.0b013e32832c7d10"},{"key":"e_1_2_9_5_1","doi-asserted-by":"publisher","DOI":"10.7448\/IAS.18.2.19408"},{"key":"e_1_2_9_6_1","doi-asserted-by":"publisher","DOI":"10.1016\/S2352-3018(18)30104-8"},{"key":"e_1_2_9_7_1","volume-title":"Get on the fast track: the life\u2010cycle approach to HIV","author":"UNAIDS","year":"2016"},{"key":"e_1_2_9_8_1","unstructured":"SimbayiL ZumaK ZunguN MoyoS MarindaE JoosteS et al. 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