Sex contextualism in laboratory research: Enhancing rigor and precision in the study of sex-related variables.

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.

A Gender Hypothesis of sex disparities in adverse drug events.

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 3 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.

Adverse Drug Events by Sex After Adjusting for Baseline Rates of Drug Use.

This cross-sectional study examines adverse drug events reported by sex in the US Food and Drug Administration (FDA) database after adjusting for drug use by males and females.

Making a 'sex-difference fact': Ambien dosing at the interface of policy, regulation, women's health, and biology.

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.

Equality as a work in progressThe Patriarchs Angela Saini Beacon Press, 2023. 256 pp.

History shows that neither patriarchy nor parity is inevitable.

How Cumulative Statistics Can Mislead: The Temporal Dynamism of Sex Disparities in COVID-19 Mortality in New York State.

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.

Why "sex as a biological variable" conflicts with precision medicine initiatives.

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.

Law, policy, biology, and sex: Critical issues for researchers.

Researchers should be aware of how sex-difference science is (mis)applied in legal and policy contexts.

Sex disparities in COVID-19 outcomes in the United States: Quantifying and contextualizing variation.

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 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.

Developmental Origins of Health and Disease, resilience and social justice in the COVID era.

The COVID-19 pandemic has shone a spotlight on how health outcomes are unequally distributed among different population groups, with disadvantaged communities and individuals being disproportionality affected in terms of infection, morbidity and mortality, as well as vaccine access. Recently, there has been considerable debate about how social disadvantage and inequality intersect with developmental processes to result in a heightened susceptibility to environmental stressors, economic shocks and large-scale health emergencies. We argue that DOHaD Society members can make important contributions to addressing issues of inequality and improving community resilience in response to COVID-19. In order to do so, it is beneficial to engage with and adopt a social justice framework. We detail how DOHaD can align its research and policy recommendations with a social justice perspective to ensure that we contribute to improving the health of present and future generations in an equitable and socially just way.

Sex Disparities in COVID-19 Mortality Vary Across US Racial Groups.

BACKGROUND: Inequities in COVID-19 outcomes in the USA have been clearly documented for sex and race: men are dying at higher rates than women, and Black individuals are dying at higher rates than white individuals. Unexplored, however, is how sex and race interact in COVID-19 outcomes. OBJECTIVE: Use available data to characterize COVID-19 mortality rates within and between race and sex strata in two US states, with the aim of understanding how apparent sex disparities in COVID-19 deaths vary across race. DESIGN AND PARTICIPANTS: This observational study uses COVID-19 mortality data through September 21, 2020, from Georgia (GA) and Michigan (MI). MAIN MEASURES: We calculate age-specific rates for each sex-race-age stratum, and age-standardized rates for each race-sex stratum. We investigate the sex disparity within race groups and the race disparity within sex groups using age-standardized rate ratios, and rate differences. KEY RESULTS: Within race groups, men have a higher COVID-19 mortality rate than women. Black men have the highest rate of all race-sex groups (in MI: 254.6, deaths per 100,000, 95% CI: 241.1-268.2, in GA:128.5, 95% CI: 121.0-135.9). In MI, the COVID-19 mortality rate for Black women (147.1, 95% CI: 138.7-155.4) is higher than the rate for white men (39.1, 95% CI: 37.3-40.9), white women (29.7, 95% CI: 28.3-31.0), and Asian/Pacific Islander men and women. COVID-19 mortality rates in GA followed the same pattern. In MI, the male:female mortality rate ratio among Black individuals is 1.7 (1.5-2.0) while the rate ratio among White individuals is only 1.3 (1.2-1.5). CONCLUSION: While overall, men have higher COVID-19 mortality rates than women, our findings show that this sex disparity does not hold across racial groups. This demonstrates the limitations of unidimensional reporting and analyses and highlights the ways that race and gender intersect to shape COVID-19 outcomes.

It's the mother!: How assumptions about the causal primacy of maternal effects influence research on the developmental origins of health and disease.

Research on the developmental origins of health and disease (DOHaD) has traditionally focused on how maternal exposures around the time of pregnancy might influence offspring health and risk of disease. We acknowledge that for some exposures this is likely to be correct, but argue that the focus on maternal pregnancy effects also reflects implicit and deeply-held assumptions that 1) causal early life exposures are primarily transmitted via maternal traits or exposures, 2) maternal exposures around the time of pregnancy and early infancy are particularly important, and 3) other factors, such as paternal factors and postnatal exposures in later life, have relatively little impact in comparison. These implicit assumptions about the "causal primacy" of maternal pregnancy effects set the agenda for DOHaD research and, through a looping effect, are reinforced rather than tested. We propose practical strategies to redress this imbalance through maintaining a critical perspective about these assumptions.