Thomas W. Hilgers, M.D., testifying to the Australian Royal Commission on Human Relationships in 1975, alleged that liberal abortions laws in the U.S. caused more deaths among women of childbearing age than they prevented. This inference was subsequently challenged because his analysis used a misleading extrapolation of linear regression, applied information from 2 incomparable data sets, and selected unreasonable item intervals for comparisons. On October 14, 1981, Hilgers testified before the U.S. Senate Subcommittee on the Constitution. He stated that America's legal abortion policy has had no measurable beneficial effect on maternal deaths and also implied that "natural pregnancy" was safer than induced abortion. These inferences were based on his recent analysis of abortion mortality with the use of national data from 1940 to 1978. Exception is still taken with Hilgers' inferences for the following reasons: neglect of risk associated with the last half of pregnancy; use of provisional 1978 data; selection of inappropriate states and time intervals; absence of the most appropriate references; use of relative frequency rather than absolute numbers; and aggregation of abortion mortality with maternal mortality. Contrary to the statements by Hilgers, the availability of legal abortion has had a measurable impact on deaths among American women of reproductive age. In 1965, even before the availability of legal abortion, deaths of women from all types of abortion (legal, illegal, and spontaneous) began to decline more rapidly than deaths from other pregnancy related causes. In 1970 the decline of abortion mortality rapidly accelerated and generally continued through 1976. In sum, legalized abortion has had a definite impact on the health of American women of childbearing age who are faced with unwanted pregnancies.
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PMID 7072785 7072785 DOI 10.1016/0002-9378(82)90773-6 10.1016/0002-9378(82)90773-6 Cates Jr et al. 1982, Cates Jr 1982
Cite this article
Cates, W., Jr. (1982). "Abortion myths and realities": who is misleading whom? American Journal of Obstetrics and Gynecology, 142(8), 954-956. https://doi.org/10.1016/0002-9378(82)90773-6
Cates W Jr. "Abortion myths and realities": who is misleading whom? Am J Obstet Gynecol. 1982;142(8):954-956. doi:10.1016/0002-9378(82)90773-6
Cates, W., Jr. ""Abortion myths and realities": who is misleading whom?" American Journal of Obstetrics and Gynecology, vol. 142, no. 8, 1982, pp. 954-956.
Teede HJ et al., 2026·Lancet (London, England)·
Open Access
Polyendocrine metabolic ovarian syndrome (PMOS), previously named polycystic ovary syndrome (PCOS), affects one in eight women. However, the term PCOS is inaccurate, implying pathological ovarian cysts, obscuring diverse endocrine and metabolic features, and contributing to delayed diagnosis, fragmented care, and stigma, while curtailing research and policy framing. Building on an international mandate for change, we outline an unprecedented, rigorous, multistep global consensus process for the name change. Funding and governance were established with engagement of 56 leading academic, clinical, and patient organisations. Using iterative global surveys (with responses from 14 360 people with PCOS and multidisciplinary health professionals from all world regions), modified Delphi methods, nominal group technique workshops, and marketing and implementation analyses, we identified principles prioritising scientific accuracy, clarity, stigma avoidance, cultural appropriateness, and implementation feasibility. An accurate new name was prioritised over retaining the PCOS acronym or a generic name. Implementation approaches prioritised evolution rather than transformation. Preferred terms were polyendocrine, metabolic, and ovarian, reflecting the condition's multisystem pathophysiology, and polyendocrine metabolic ovarian syndrome was the consensus new name. Accuracy was improved by omitting cysts and by capturing endocrine, metabolic, and ovarian dysfunction. A co-designed global implementation strategy, including a transition period, education, and alignment with health systems and disease classification, is under way.
Advocacy and Public Understanding · Public Awareness
Parnell TA et al., 2026·Journal of Restorative Reproductive Medicine
This study examined public attitudes toward restorative reproductive medicine (RRM) and in vitro fertilization (IVF) using secondary analysis and comparative reporting of two independent surveys conducted in the United States. It also explored preferences among individuals with fertility issues and the general population’s views on treatment options. A secondary analysis was conducted using data from two nationally representative online surveys, designed and administered by organizations independent of the researchers, whose samples demographically reflected the U.S. adult population. The surveys—conducted by J.L. Partners (N=1002) and McLaughlin & Associates (N=1000)—assessed familiarity, acceptance, and attitudes toward IVF and RRM. The J.L. Partners survey focused on IVF, including medical risks, creation and use of embryos, preimplantation genetic testing, arguments for government oversight of IVF, and overall attitudes toward IVF. The McLaughlin survey focused on comparative descriptions of IVF and RRM. Pearson’s Chi-Square tests of independence were used to assess differences in response distributions across demographic subgroups and between survey items of interest. Findings: Overall, there was strong consistency of responses to items that were similar in the two surveys. Approximately 80% supported IVF initially, although both surveys found respondents to have limited knowledge about IVF procedures. In contrast, 33% supported RRM initially, with 43% having never heard of RRM. After learning more about the characteristics of RRM and IVF approaches, as presented within the surveys, preference shifted toward approaches consistent with RRM (e.g., 69% preference for an approach for natural fertilization in a woman’s body vs. 17% for fertilization in a lab). Respondents prioritized baby health (74%) over cost (13%) and time to conceive (6%). Many IVF patients were concerned about undiagnosed health issues and being rushed into IVF. Overall, 70% wanted treatments that addressed underlying causes; nearly half were unaware of any medical risks of IVF. Stated support for IVF declined by 10% overall after presentation of medical risks, questions about the creation and use of embryos and genetic testing, and arguments to support government oversight of IVF. Both surveys showed strong support for patient access to full information about treatments and treatment processes. While IVF is widely accepted, these national survey data suggest preferences for fertility treatments that prioritize diagnosis and restoration of natural reproductive health, which is the focus of restorative reproductive medicine. Comprehensive assessment, restoration of healthy function, transparency regarding treatment processes, and sensitivity to ethical concerns in patient care reflect important public values. Greater awareness and public education, improved consent, more research, and ongoing surveys are needed to inform public health strategies and meet patient needs in fertility care.
Endometriosis is a debilitating, chronic disease that is estimated to affect 11% of reproductive-age women. Diagnosis of endometriosis is difficult with diagnostic delays of up to 12 years reported. These delays can negatively impact health and quality of life. Vague, nonspecific symptoms, like pain, with multiple differential diagnoses contribute to the difficulty of diagnosis. By investigating previously imprecise symptoms of pain, we sought to clarify distinct pain symptoms indicative of endometriosis, using an artificial intelligence-based approach. We used data from 473 women undergoing laparoscopy or laparotomy for a variety of surgical indications. Multiple anatomical pain locations were clustered based on the associations across samples to increase the power in the probability calculations. A Bayesian network was developed using pain-related features, subfertility, and diagnoses. Univariable and multivariable analyses were performed by querying the network for the relative risk of a postoperative diagnosis, given the presence of different symptoms. Performance and sensitivity analyses demonstrated the advantages of Bayesian network analysis over traditional statistical techniques. Clustering grouped the 155 anatomical sites of pain into 15 pain locations. After pruning, the final Bayesian network included 18 nodes. The presence of any pain-related feature increased the relative risk of endometriosis (p-value < 0.001). The constellation of chronic pelvic pain, subfertility, and dyspareunia resulted in the greatest increase in the relative risk of endometriosis. The performance and sensitivity analyses demonstrated that the Bayesian network could identify and analyze more significant associations with endometriosis than traditional statistical techniques. Pelvic pain, frequently associated with endometriosis, is a common and vague symptom. Our Bayesian network for the study of pain-related features of endometriosis revealed specific pain locations and pain types that potentially forecast the diagnosis of endometriosis.