@article {Marstoni64, author = {M Marston and E Slaymaker and I Cremin and S Floyd and N McGrath and I Kasamba and T Lutalo and M Nyirenda and A Ndyanabo and Z Mupambireyi and B {\.Z}aba}, title = {Trends in marriage and time spent single in sub-Saharan Africa: a comparative analysis of six population-based cohort studies and nine Demographic and Health Surveys}, volume = {85}, number = {Suppl 1}, pages = {i64--i71}, year = {2009}, doi = {10.1136/sti.2008.034249}, publisher = {The Medical Society for the Study of Venereal Disease}, abstract = {Objectives: To describe trends in age at first sex (AFS), age at first marriage (AFM) and time spent single between events and to compare age-specific trends in marital status in six cohort studies.Methods: Cohort data from Uganda, Tanzania, South Africa, Zimbabwe and Malawi and Demographic and Health Survey (DHS) data from Uganda, Tanzania and Zimbabwe were analysed. Life table methods were used to calculate median AFS, AFM and time spent single. In each study, two surveys were chosen to compare marital status by age and identify changes over time.Results: Median AFM was much higher in South Africa than in the other sites. Between the other populations there were considerable differences in median AFS and AFM (AFS 17{\textendash}19 years for men and 16{\textendash}19 years for women, AFM 21{\textendash}24 years and 18{\textendash}19 years, respectively, for the 1970{\textendash}9 birth cohort). In all surveys, men reported a longer time spent single than women (median 4{\textendash}7 years for men and 0{\textendash}2 years for women). Median years spent single for women has increased, apart from in Manicaland. For men in Rakai it has decreased slightly over time but increased in Kisesa and Masaka. The DHS data showed similar trends to those in the cohort data. The age-specific proportion of married individuals has changed little over time.Conclusions: Median AFS, AFM and time spent single vary considerably among these populations. These three measures are underlying determinants of sexual risk and HIV infection, and they may partially explain the variation in HIV prevalence levels between these populations.}, issn = {1368-4973}, URL = {https://sti.bmj.com/content/85/Suppl_1/i64}, eprint = {https://sti.bmj.com/content/85/Suppl_1/i64.full.pdf}, journal = {Sexually Transmitted Infections} }