Dec 8 2017
New research from Lancaster University has identified the 'invisible infertile', a group of marginalized people missing from survey data sources because they do not fit neatly into popular notions of who is at risk of infertility.
Around the world, the 'invisible infertile' includes racial and ethnic minorities, those with limited economic resources, those who do not have access to affordable healthcare, the LGBTQ community, persons with disabilities, and more often men than women.
While it is estimated 15% of couples worldwide are infertile, researchers say this figure, hinges critically on the quality, inclusiveness and availability of data sources used to track infertility.
The article, 'Reimagining Infertility: A critical examination of fertility norms, geopolitics and survey bias' was published in the journal, 'Health Policy and Planning'.
The article states current infertility data and statistics fail to account for the infertility experiences of some social groups. Because these data and statistics are used for policymaking and decisions about reproductive health services, omission of these groups contributes to uneven access to state resources and health services.
Authors Dr Jasmine Fledderjohann at Lancaster's Department of Sociology and Dr Liberty Walther Barnes at the University of Oregon in the US, refer to the omission of these groups, whether intentional or unintentional, as the process of 'invisibilization'. It has previously been identified that many cultural factors complicate efforts to track infertility across populations including infertility regarded as a taboo subject in some cultures.
Dr Fledderjohann and Dr Barnes outline how reproductive health (RH) survey datasets include or exclude different social groups within and across populations.
The study identifies two processes through which invisibility is produced in survey data:
- Sampling, with focus on how it is decided who will be selected to participate in the survey
- Questionnaire design, with focus on who is asked particular questions and how those questions are worded
Examples of these processes are drawn from the Integrated Fertility Survey Series and the Demographic and Health Surveys. Dr Fledderjohann and Dr Barnes argue that research is not designed in an objective vacuum. Surveys and sampling techniques are shaped and influenced by the sociocultural norms and geopolitical context of the time and place in which they are created and conducted, reflecting broader social beliefs about family building and reproduction.
Relatedly, population policy aimed at curbing overpopulation in some places contributes to the problem of 'invisibilization' by effectively rendering the infertility of some groups as unfathomable. In this light many marginalized groups are missing from the reproductive health statistics.
"The omission of entire groups from the scientific discourse casts doubt on the quality of the research questions, validity of the analytical tools and the accuracy of scientific findings," says the article.
This can lead to misguided evidence-based reproductive health and family planning policies and deter equitable access to reproductive healthcare for some social groups.
"The common perception that infertility is disproportionately a white, Western, middle-class woman's issue is really inaccurate and problematic," says Dr Fledderjohann.
"The highest rates of infertility in the world are in the Global South, but the population level data on infertility in many countries in the Global South are severely limited. This just compounds the problem - we collect much richer infertility data on Western women, which increases their visibility and further contributes to the misperceptions around who is -- and is not -- at risk of infertility."
The research suggests positive routes forward including calls for:
- An examination of existing data to consider who is missing and what the implications are
- Revision of survey wording and design to reduce bias
- Engagement of policymakers, medics, and researchers in an open dialogue about the invisible infertile
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