P277 How do we measure unmet need within sexual and reproductive health? A systematic review

Abstract

<h3>Background</h3> Addressing health inequality with sexual and reproductive health requires an understanding of unmet need within a range of populations. This review examined the methods and definitions that have been used to measure unmet need, and the populations most frequently assessed. <h3>Methods</h3> Five databases (PubMed, Web of Science, Scopus, CINAHL and HMIC) were searched for studies that described quantitative measurement of unmet need within sexual and/or reproductive health between 2010 to 2020. A narrative synthesis was then undertaken to ascertain themes within the literature. <h3>Results</h3> The database search yielded 18539 papers; 145 papers were included after screening. 128 studies assessed unmet reproductive health need, of which 94 were analyses of trends among women living in low/lower-middle income countries; 121 used cross-sectional data, with only seven analyses being longitudinal. Twelve studies analysed unmet sexual health need, of which nine focused on high and upper-middle income populations. All twelve used cross-sectional analyses. The remaining five studies examined unmet need for a combination of sexual and reproductive health services, all among populations from upper-middle or high income countries and all being cross-sectional analyses. 138 of the papers were analyses of questionnaire data, five used reviews of medical records, one compared demand before and after an intervention, and one used modelling techniques. 113 studies used the DHS definition of unmet need; no other standardised definition was used among the remaining papers. <h3>Discussion</h3> There is a significant focus on unmet need for contraception among women in low income countries within the published literature, leaving considerable evidence gaps in relation to unmet need within sexual health generally and among men in particular, and unmet reproductive health need in high income settings. Additionally, using an increased range of data collection methods, analyses and definitions of unmet need would enable better understanding of health inequality in this area.