Reimagining infertility: a critical examination of fertility norms, geopolitics and survey bias
Reimagining infertility: a critical examination of fertility norms, geopolitics and survey bias
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DOI：
10.1093/heapol/czx148
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发表时间：
2018-01-01
影响因子：
3.2
通讯作者：
Barnes, Liberty Walther
中科院分区：
文献类型：
--
作者：
Fledderjohann, Jasmine;Barnes, Liberty Walther
据估计，全世界有15%的夫妇不育，但这一数字主要取决于不孕数据来源的质量、包容性和可用性。目前的不孕症数据和统计数据未能说明一些社会群体的不孕症经历。我们将这些人确定为看不见的不孕不育，并将他们从不孕不育数据和统计数据中遗漏--无论是有意还是无意--称为隐形的过程。我们确定了在调查数据中产生隐形化的两个过程：抽样，重点是对高危人口的排他性定义，以及调查工具设计，重点是跳跃模式和问题措辞。这些过程的例证摘自综合生育率调查系列和人口与健康调查。实证研究不是在客观真空中设计的。相反，调查工具和抽样技术受到创建和进行调查的时间和地点的社会文化规范和地缘政治背景的塑造和影响，反映了关于家庭建设和生殖的更广泛的社会信仰。此外，旨在遏制世界高生育率地区人口过剩的人口政策限制了所收集的生殖数据的类型，实际上使一些群体的不孕不育在流行病学上难以捉摸。鉴于这些社会文化和地缘政治力量，生殖健康(RH)统计数据中缺少许多边缘化群体。整个群体从科学话语中被省略，使人对研究问题的质量、分析工具的有效性和科学发现的准确性产生怀疑。隐蔽性还可能误导以证据为基础的生殖健康和计划生育政策，阻碍一些社会群体公平地获得生殖保健，使社会不平等永久化。
While it is estimated that 15% of couples worldwide are infertile, this figure hinges critically on the quality, inclusiveness and availability of infertility data sources. Current infertility data and statistics fail to account for the infertility experiences of some social groups. We identify these people as the invisible infertile, and refer to their omission from infertility data and statistics-whether intentional or unintentional-as the process of invisibilization. We identify two processes through which invisibilization in survey data is produced: sampling, with focus on exclusionary definitions of the population at-risk, and survey instrument design, with focus on skip patterns and question wording. Illustrative examples of these processes are drawn from the Integrated Fertility Survey Series and the Demographic and Health Surveys. Empirical research is not designed in an objective vacuum. Rather, survey instruments 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. Furthermore, population policy singularly aimed at curbing overpopulation in high fertility parts of the world limits the type of reproduction data collected, effectively rendering the infertility of some groups epidemiologically unfathomable. In light of these sociocultural and geopolitical forces, many marginalized groups are missing from reproductive health (RH) statistics. The omission of entire groups from the scientific discourse casts doubt on the quality of research questions, validity of the analytic tools, and accuracy of scientific findings. Invisibility may also misguide evidence-based RH and family planning policies and deter equitable access to reproductive healthcare for some social groups, perpetuating social inequalities.