The concept of “causal crypticity” was introduced by Richardson (2021) to describe the DOHaD field’s high tolerance for both causes and effects that are challenging to observe in nature, show small effect sizes, and are unstable across study populations and contexts. Causal crypticity can be understood in three ways: as an epistemic norm; as a boundary-delimiting signature of field culture or epistemic style; and as a promissory mode. Increasingly, causal crypticity characterizes many fields of the big data-rich, postgenomic life sciences, making DOHaD science a useful index case for scholars of the history, philosophy, and social studies of science interested in the epistemic terrain and social implications of postgenomic sciences. The chapter concludes with a discussion of ethical and accountable claimsmaking in DOHaD science under conditions of causal crypticity. Contact srichard@fas.harvard.edu for advance copy.

"The Women’s Health movement has aimed, since the 1970s, to put knowledge in the hands of women and to build collective power within communities around needs identified by women. The Sprint for Women’s Health sharply diverges from this vision. Appropriating the mission of women’s health equity and a potentially transformative infusion of government support, it diverts public resources into private profit-driven businesses."

Understanding sex-related variation in health and illness requires rigorous and precise approaches to revealing underlying mechanisms. A first step is to recognize that sex is not in and of itself a causal mechanism; rather, it is a classification system comprising a set of categories, usually assigned according to a range of varying traits. Moving beyond sex as a system of classification to working with concrete and measurable sex-related variables is necessary for precision. Whether and how these sex-related variables matter—and what patterns of difference they contribute to—will vary in context-specific ways. Second, when researchers incorporate these sex-related variables into research designs, rigorous analytical methods are needed to allow strongly supported conclusions. Third, the interpretation and reporting of sex-related variation require care to ensure that basic and preclinical research advance health equity for all.

In this State of the Field essay, we introduce the central methods, concepts, and key terms in the field of sociogenomics and related genetic sciences. We then review high profile claims from this field that posit genetic theories of gender and sexuality, or that analyze gender and sexuality as variables in the characterization of brain, psychiatric, and medical conditions. Lastly, we characterize the conceptual, methodological, social, and ethical questions opened by this new frontier for an interdisciplinary audience, emphasizing the gap between the sociogenomic imaginary and what the data can and do currently show. Our goal is to build on existing critical perspectives by translating and contextualizing highly technical developments in the new era of genetics research, and to invite scholars to engage with the issues it raises. The article is co-first authored by Alex Borsa and Mia Miyagi. 

Pharmacovigilance databases contain larger numbers of adverse drug events (ADEs)
that occurred in women compared to men. The cause of this disparity is frequently
attributed to sex-linked biological factors. We offer an alternative Gender Hypothesis,
positing that gendered social factors are central to the production of aggregate sex
disparities in ADE reports. We describe four pathways through which gender may
influence observed sex disparities in pharmacovigilance databases: healthcare
utilization; bias and discrimination in the clinic; experience of a drug event as adverse;
and pre-existing social and structural determinants of health. We then use data from
the U.S. FDA Adverse Event Reporting System (FAERS) to explore how the Gender
Hypothesis might generate novel predictions and explanations of sex disparities in
ADEs in existing widely referenced datasets. Analyzing more than 33 million records of
ADEs between 2014 and 2022, we find that patient-reported ADEs show a larger
female skew than healthcare provider-reported ADEs and that the sex disparity is
markedly smaller for outcomes involving death or hospitalization. We also find that the
sex disparity varies greatly across types of ADEs, for example, cosmetically salient
ADEs are skewed heavily female and sexual dysfunction ADEs are skewed male.
Together, we interpret these findings as providing evidence of the promise of the
Gender Hypothesis for identifying intervenable mechanisms and pathways contributing
to sex disparities in ADEs. Rigorous application of the Gender Hypothesis to additional
datasets and in future research studies could yield new insights into the causes of sex
disparities in ADEs. (Open Access: https://doi.org/10.1016/j.socscimed.2023.116385)

Data from pharmacovigilance databases like the U.S. FDA Adverse Event Reporting System (FAERS) are widely cited as evidence for claims that women experience adverse drug events (ADEs) at as high as twice the rate of men. Biological factors are typically hypothesized to explain these sex differences. However, many factors could influence the distribution of ADE reports by sex, including well-known disparities in the rates at which men and women use prescribed drugs. This study examined ADEs reported by sex in the FAERS database after adjusting for drug use by men and women, finding that adjusting pharmacovigilance data from FAERS with nationally representative data on sex disparities in usage of drugs greatly attenuates the apparent sex disparity in ADE reports, reducing the gap in the median number of ADEs for women compared to men from 45.1% to 15.0%. The commonly cited claim that women experience 1.5 to 2 times the number of ADEs as men was demonstrated to be highly unlikely, with a probability of less than 5% after accounting for drug usage. After accounting for underlying drug use, reported numbers of ADE were similar between men and women when looking across drugs, suggesting that gender/sex disparities in drug use may largely explain observed gender/sex disparities in ADEs. Rushovich, Gompers, and Lockhart are co-first authors of this publication, and the article is available Open Access.

Across the globe, health care is increasingly in the hands of corporate entities. Women's health is a vivid example of this trend. Private equity firms, start-ups, and other private-sector companies are streaming into women's health, appealing to its historical aims of equity, empowerment, and social justice, while also expecting big profits. As this industry expands, tensions between profitability, innovation, quality, and equity are already surfacing within the USA, signalling what other nations may soon encounter.

The U.S. Food and Drug Administration’s (FDA) 2013 decision to lower recommended Ambien dosing for women has been widely cited as a hallmark example of the importance of sex differences in biomedicine. Using regulatory documents, scientific publications, and media coverage, this article analyzes the making of this highly influential and mobile ‘sex-difference fact’. As we show, the FDA’s decision was a contingent outcome of the drug approval process. Attending to how a contested sex-difference fact came to anchor elite women’s health advocacy, this article excavates the role of regulatory processes, advocacy groups, and the media in producing perceptions of scientific agreement while foreclosing ongoing debate, ultimately enabling the stabilization of a binary, biological sex-difference fact and the distancing of this fact from its conditions of construction. 

"Within the sciences, there are increasing calls for incorporating intersectionality as a theoretical framework in the development of research questions and in methodological approaches. When we consider our recent research experiences, the primary question that arises is not whether quantitative fields can effectively incorporate intersectionality methodologically. Rather, it is whether these disciplines are prepared to expand their definitions of ways of knowing so as to create space for intersectional analysis in the STEM fields." 

En este artículo se desarrolla el marco conceptual del “contextualismo sexual” para el estudio de las variables relacionadas con el sexo en la investigación biomédica. El contextualismo sexual ofrece una alternativa a los enfoques sexuales binarios y esencialistas del estudio del sexo como variable biológica. Específicamente, el contextualismo sexual reconoce el pluralismo y la especificidad contextual que tienen las operacionalizaciones de “sexo” a través de la investigación experimental de laboratorio. A la luz de recientes normativas para la consideración del sexo como variable biológica, el contextualismo sexual ofrece una guía constructiva a los/as investigadores/as biomédicos/as para abordar la variación biológica relacionada con el sexo. En tanto alternativa y crítica al esencialismo binario del sexo biológico, el contextualismo sexual contribuye a los debates actuales en filosofía de la biología, estudios feministas de la ciencia y ontología social en torno a la construcción de categorías de la diferencia sexual/genérica en la investigación científica.

Overall, men have died from COVID-19 at slightly higher rates than women. But cumulative estimates of mortality by sex may be misleading. We analyze New York State COVID-19 mortality by sex between March 2020 and August 2021, demonstrating that 72.7% of the total difference in the number of COVID-19 deaths between women and men was accrued in the first seven weeks of the pandemic. Thus, while the initial surge in COVID-19 mortality was characterized by stark sex disparities, this article shows that disparities were greatly attenuated in subsequent phases of the pandemic. Investigating changes over time could help illuminate how contextual factors contributed to the development of apparent sex disparities in COVID-19 outcomes. [Open Access]

The interplay between legal and bioscientific understandings of sex is prolific and complex. Biological evidence and reasoning circulate in lawmaking and policy-making across an array of politically contested issues, including health care, education, and LGBTQI+ rights and protections. There is often a substantial disjoint, however, between how scientists define and operationalize sex differences in their research and how lawmakers and policy-makers make sense of these definitions and concepts as they strategically seek to bolster or challenge legal governance. Medical and life scientists who routinely incorporate sex-related variables in their research cannot eliminate superficial or malicious misuse of research by lawmakers and policy-makers, but awareness of the legal and policy landscape can clarify the possible downstream consequences of researchers’ choices about how to operationalize sex-related variables in their studies.

Policies that require male-female sex comparisons in all areas of biomedical research conflict with the goal of improving health outcomes through context-sensitive individualization of medical care. Sex, like race, requires a rigorous, contextual approach in precision medicine. A “sex contextualist” approach to gender-inclusive medicine better aligns with this aim.

This paper presents the first longitudinal study of sex disparities in COVID-19 cases and mortalities across U.S. states, derived from the unique 13-month dataset of the U.S. Gender/Sex COVID-19 Data Tracker. To analyze sex disparities, weekly case and mortality rates by sex and mortality rate ratios and rate differences were computed for each U.S. state, and a multilevel crossed-effects conditional logistic binomial regression model was fitted to estimate the variation of the sex disparity in mortality over time and across states. Results demonstrate considerable variation in the sex disparity in COVID-19 cases and mortalities over time and between states. These data suggest that the sex disparity, when present, is modest, and likely varies in relation to context-sensitive variables, which may include health behaviors, preexisting health status, occupation, race/ethnicity, and other markers of social experience.

This paper develops the conceptual framework of “sex contextualism” for the study of sex-related variables in biomedical research. Sex contextualism offers an alternative to binary sex essentialist approaches to the study of sex as a biological variable. Specifically, sex contextualism recognizes the pluralism and context-specificity of operationalizations of ‘sex’ across experimental laboratory research. In light of recent policy mandates to consider sex as a biological variable, sex contextualism offers constructive guidance to biomedical researchers for attending to sex-related biological variation. As an alternative to and critique of biological binary sex essentialism, sex contextualism contributes to current debates in philosophy of biology, feminist science studies, and social ontology on the construction of categories of gender/sex differences in scientific research.

Gender/sex comparisons of COVID-19 case fatality rates are subject to systematic bias owing to differential testing rates. Nonrandom COVID-19 testing in the population means that there is considerable uncertainty around CFR estimates in men and women. Specifically, widespread lower testing among men compared with women likely artificially inflates the CFR among men, as demonstrated by a predictive, inverse relationship between testing skew and CFR ratio. The more disparate testing becomes between men and women, the greater the observed sex disparity in CFR; when testing becomes more similar, observed CFRs become more similar. The case study of COVID-19 offers an important teachable and generalizable example for women's health scholars of the caution that is needed in interpreting sex disparities in CFRs.

A collaboration between scholars in history and social studies of science and leading DOHaD scientists, this article argues that in a world of extreme inequalities, we need a science of DOHaD that attends to how factors that influence the development of health and disease are socially patterned, shifting the focus from individual-level characteristics of the mother–child dyad in early development (independent of fathers, partners and other caregivers), to complex social processes that stratify society over the life-course.  

We explain and contextualize our new study out in Human Fertility in this essay for Slate.

The sex disparity in COVID-19 mortality varies widely and is of uncertain origin. In their recent Nature paper “Sex differences in immune responses that underlie COVID-19 disease outcomes,” Takahashi et al. assess immune phenotype in a sample of COVID-19 patients and conclude that the “immune landscape in COVID-19 patients is considerably different between the sexes,” warranting different vaccine and therapeutic regimes for men and women -- a claim widely disseminated following the publication. Here, we argue that these inferences are not supported by their findings: this study does not demonstrate that biological sex explains COVID-19 outcomes among patients. This study is diagnostic of an ongoing pattern in sex difference research of overstatement of findings and superficial treatment of factors beyond innate sex in analyzing the causes of gender/sex disparities in health outcomes.

The past 50 years have seen heated debate in the reproductive sciences about global trends in human sperm count. In 2017, Levine and colleagues published the most methodologically rigorous and largest meta-regression analysis to date and reported that average total sperm concentration among men from “Western” countries has decreased by 59.3% since 1973, with no sign of halting. These results reverberated in the scientific community and in public discussions about men and masculinity in the modern world, in part because of scientists’ public-facing claims about the societal implications of the decline of male fertility. We find that existing research follows a set of implicit and explicit assumptions about how to measure and interpret sperm counts, which collectively form what we term the Sperm Count Decline hypothesis (SCD). Using the study by Levine and colleagues, we identify weaknesses and inconsistencies in the SCD, and propose an alternative framework to guide research on sperm count trends, the Sperm Count Biovariability hypothesis (SCB). SCB asserts that sperm count varies within a wide range, much of which can be considered non-pathological and species-typical. Knowledge about the relationship between individual and population sperm count and life-historical and ecological factors is critical to interpreting trends in average sperm counts and their relationships to health and fertility.