P-445 Prevalence of medically assisted reproduction use and its social and demographic determinants - findings from a German representative survey

Abstract

Abstract Study question What percentage of people use types medically assisted reproduction (MAR) in Germany? Is MAR use unequally distributed by social categories and stage of treatment? Summary answer The lifetime prevalence of MAR use in Germany is 11.4%. Treatment use varies by social categories and stage of treatment. What is known already Increasing postponement of births to higher ages in most European countries contributes to higher risk of infertility and seeking assisted reproductive technologies (ART) or broader MAR. Studies indicate several non-medical factors associated with MAR use. Demographic and socio-economic factors, reproductive history, and attitudes are associated with MAR use. Country context is crucial for understanding MAR use patterns because access and reimbursement schemes differ widely among nations. Retrospective and longitudinal studies suggest the benefit of conceptualizing MAR use as a sequential process. The social and demographic determinants of MAR use differ across treatment stages. Study design, size, duration This study uses pre-release data from the first wave of the newly established FReDA panel survey (Family Research and Demographic Analysis), a large-scale representative survey of German residents 18 to 49 years. Information on infertility and MAR use was included in sub-wave W1A, therefore most of the data come from wave W1A, and other sub-waves as needed. We will present results from the official data release at the conference. Participants/materials, setting, methods For the lifetime indicator of MAR use participants were categorized into the highest category that they indicated: (0) no treatment, (1) see a doctor, (2) receiving medication only, (3) MAR services (insemination, operations, In-Vitro-Fertilisation, Intracytoplasmatic Sperm Injection). A Brant test shows that the parallel regression assumption for ordinal regression is not met. The less restrictive partial proportional odds model is estimated, allowing coefficients for gender, age, parity, and ever infertile to vary across stages. Main results and the role of chance The sample consists of 15,263 persons. The lifetime-prevalence of any MAR use is 11.4%. 3% saw a doctor, 3.1% had medication only and 5.2% used further MAR services. Women are more likely than men to use MAR at all stages. Those 30-34 years have the highest odds when comparing no treatment to seeing a doctor or higher treatment categories, and when it comes to being in the treatment category of receiving medication or higher. The odds for being in the highest treatment category increase from youngest ( < =29 years) to oldest (45+ years) age group. Having children increases the odds of seeing a doctor or higher treatment category, but not the odds for being in any higher treatment category. Having ever experienced infertility is a strong predictor of MAR use at all stages. Coefficients of the following variables are the same across treatment categories. Having ever been married increases MAR use considerably. The odds of help-seeking are lower in suburban areas compared to cities. Those who evaluate their economic situation as good are more likely to use MAR. Positive child orientation of both partners increases MAR use. Migration background, religion, education, and subjective health are not linked to MAR use. Limitations, reasons for caution Characteristics of individuals are based on self-reports that cannot be validated externally. Use of a lifetime-indicator of MAR use could imply that temporal order of explanatory variables and the outcome are inconclusive No further information on duration of infertility, diagnosis, and the timing of help-seeking was available. Wider implications of the findings Seeking MAR is a multifaceted process influenced by many social and demographic factors. The use of lower levels of services prior to the use of more invasive services such as ART is common. More studies should focus on MAR, not just ART, to understand inequities in use. Trial registration number not applicable