Background Women who start using contraception ("adopters") are a key population for family planning goals, but little is known about characteristics that predict the adoption of contraception as opposed to current use. We used prospective data from women and facilities for five countries, (Democratic Republic of Congo, India, Kenya, Nigeria, and Burkina Faso) and identified baseline characteristics that predicted adoption of modern contraception in the short term. Methods We used data from the Performance Monitoring for Action (PMA) Agile Project. PMA Agile administered service delivery point (SDP) client exit interview (CEI) surveys in urban sites of these five countries. Female clients responding to the CEI were asked for phone numbers that were used for a phone follow-up survey approximately four months later. For our analysis, we used data from the SDP and CEI baseline surveys, and the phone follow up to compare women who start using contraception during this period with those who remain nonusers. We used characteristics of the facility and the woman at baseline to predict her contraception adoption in the future. Results Discussing FP with a partner at baseline was associated with greater odds of adoption in DRC (OR 2.34; 95% CI 0.97-5.66), India (OR 2.27; 95% CI 1.05-4.93), and Kenya (OR 1.65; 95% CI 1.16-2.35). Women who discussed family planning with any staff member at the health facility had 1.72 greater odds (95% CI 1.13-2.67) of becoming an adopter in Nigeria. The odds of adoption were lower in Nigerian facilities that had a stockout (OR 0.66 95% CI 0.44-1.00) at baseline. Other characteristics associated with contraception adoption across settings were education, age, wealth, parity, and marital status. Conclusions Characteristics of both the woman and the health facility were associated with adoption of modern contraception in the future. Some characteristics, like discussing family planning with a spouse, education, and parity, were associated with contraceptive adoption across settings. Other characteristics that predict contraceptive use, such as health facility measures, varied across countries.
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