{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,7,30]],"date-time":"2026-07-30T23:07:58Z","timestamp":1785452878351,"version":"3.56.0"},"reference-count":59,"publisher":"F1000 Research Ltd","license":[{"start":{"date-parts":[[2018,12,2]],"date-time":"2018-12-02T00:00:00Z","timestamp":1543708800000},"content-version":"unspecified","delay-in-days":0,"URL":"http:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"content-domain":{"domain":["f1000research.com"],"crossmark-restriction":false},"short-container-title":["F1000Res"],"abstract":"<ns4:p>\n                    <ns4:bold>Background:<\/ns4:bold>\n                    It is unclear why HIV prevalence varies by nearly two orders of magnitude between regions within countries in sub-Saharan Africa. In this ecological study, we assess if HIV prevalence by region is associated with any of four markers of higher risk sexual behavior: lifetime number of partners, multiple partners in past year, higher risk sex (defined as sex with non-cohabiting, non-marital partners) and age at debut.\n                  <\/ns4:p>\n                  <ns4:p>\n                    <ns4:bold>Methods:<\/ns4:bold>\n                    We performed Pearson\u2019s correlation between the 4 behavioral risk factors and HIV prevalence by region in 47 nationally representative surveys from 27 sub-Saharan African countries, separately by gender. In addition, principal components analysis was used to reduce the eight risk factors (four for each gender) to two principal components (PCs). Mixed effects linear regression was used to assess the relationship between the resulting two PCs and HIV prevalence after controlling for the prevalence of male circumcision.\n                  <\/ns4:p>\n                  <ns4:p>\n                    <ns4:bold>Results:<\/ns4:bold>\n                    HIV prevalence varied by a median 3.7 fold (IQR 2.9-7.9) between regions within countries. HIV prevalence was strongly associated with higher risk sex and, to a lesser extent, the other risk factors evaluated. Both PCs were strongly associated with HIV prevalence when assessed via linear regression.\n                  <\/ns4:p>\n                  <ns4:p>\n                    <ns4:bold>Conclusions:<\/ns4:bold>\n                    Differences in sexual behavior may underpin the large differences in HIV-prevalence between subpopulation within sub-Saharan African countries.\n                  <\/ns4:p>","DOI":"10.12688\/f1000research.17108.1","type":"journal-article","created":{"date-parts":[[2018,12,2]],"date-time":"2018-12-02T06:15:06Z","timestamp":1543731306000},"page":"1879","update-policy":"https:\/\/doi.org\/10.12688\/f1000research.crossmark-policy","source":"Crossref","is-referenced-by-count":9,"title":["Strong association between higher-risk sex and HIV prevalence at the regional level: an ecological study of 27 sub-Saharan African countries"],"prefix":"10.12688","volume":"7","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-2557-8998","authenticated-orcid":false,"given":"Chris R.","family":"Kenyon","sequence":"first","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Jozefien","family":"Buyze","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Ilan S.","family":"Schwartz","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"2560","published-online":{"date-parts":[[2018,12,2]]},"reference":[{"key":"ref-1","doi-asserted-by":"publisher","first-page":"122","DOI":"10.1186\/s12916-014-0122-5","article-title":"Findings from the SASA! 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