BME 3.0: Engineering Education and Training in Sexism, Racism, and Social Determinants of Health

Introduction:: Biomedical engineering is the application of engineering principles to create understanding, approaches, and technologies that improve health and healthcare. The current paradigm for training engineers who can innovate to improve health and healthcare typically requires expertise in three domains: engineering fundamentals, biology and/or physiology, and hypothesis- or discovery driven research. Despite the emerging knowledge that health depends on social factors such as economic stability, social and community context, neighborhood and environment, access to health care, and education (social determinants of health; SDOH), that sex-, gender-, and race/ethnicity-based biases affect health care delivery, and that healthcare access depends on national policies, which themselves can be sex-, gender-, and race/ethnicity-based biased, traditional education and training of biomedical engineers does not include instruction or even exposure to these principles.


Materials and Methods:: One example of the critical need for biomedical engineers with these broader perspectives is in cardiovascular disease (CVD), which is the leading cause of death globally and kills more than 17.9 million people each year [1]. In the U.S., CVD kills more women than all forms of cancer combined, with profound race-based disparities such that Black women, Latinas, and other women of color have disproportionately high CVD rates and low survival levels. Moreover, members of the lesbian, gay, bisexual, trans, queer, and questioning (LGBTQ+) community who are Black have higher CVD risk factors than those who are not [2]. This heavier burden and earlier onset of poor health outcomes observed in Black Americans are not fully explained by other sociodemographic factors (e.g., age, education) [3]. Recent public health research has shown that structural racism, such as disadvantages in political participation, employment, and judicial treatment, is associated with increased risk of myocardial infarction in Black Americans but not White Americans [4]. Stereotype threat can lead to emotional stress and impaired decision making, which in turn contribute to hypertension and weight gain [5]. Individuals accepting negative stereotypes as true are associated with higher levels of alcohol consumption and obesity [6]. Even living in a racist environment is positively associated with heart disease mortality as well as the delivery of low birthweight newborns, which has lifelong consequences for cardiovascular health [7].


Results, Conclusions, and Discussions:: Biomedical engineers who lack this knowledge and expertise can exacerbate these health disparities in four important ways. First, medical devices can introduce race-based errors. For instance, when devices use optical methods without accounting for skin melanin content, such as many existing light-based pulse oximeters [8] and other wearable systems [9], the fundamental measurement itself contains an artifact and can be in error. Second, bias in the software or in the data sets used to develop devices can introduce racial bias [10]. Third, when clinicians apply unequal, race-based standards to the readouts from medical devices, errors in interpretation can occur, such as with respirometers [11]. And lastly, use considerations such as affordability and access are not embedded into the technology development process. Therefore, training engineers to create understanding, approaches, and technologies that improve health and healthcare for all, requires multidisciplinary training, including, critically, psychological scientists (race and gender as societal constructs; identity and perception), public health experts (medical system designers and community-facing professionals), and social ecologists (experts in the impacts of discrimination and racism).


We propose transforming the undergraduate and graduate biomedical engineering education and training to equip the next generation of biomedical engineers to address health and healthcare inequities and create understanding, approaches, and technologies that are effective for all Americans. Specifically, we recommend providing education and training on (1) the ways in which identity and ancestry affect health and healthcare, (2) social determinants of health and healthcare access, and (3) research strategies to investigate sex and ancestry as biological variables and gender and race as societal variables with biological consequences.


Acknowledgements (Optional): : NCC is supported by the UCI Chancellor’s Inclusive Excellence Professorship and the Edwards Lifesciences Foundation.

References (Optional): :

1. WHO. Cardiovascular diseases. Available from: https://www.who.int/health-topics/cardiovascular-diseases#tab=tab_1.


2. Caceres et al. “A Systematic Review of Cardiovascular Disease in Sexual Minorities,” Am J Public Health, 2017, PMID: 28207331


3. Tang et al. “Incidence of AD in African-Americans, Caribbean Hispanics, and Caucasians in northern Manhattan,” Neurology, 2001, PMID: 11148235


4. Lukachko et al. “Structural racism and myocardial infarction in the United States,” Soc Sci Med, 2014, PMID: 24507909


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6. Williams et al. “Discrimination and Racial Disparities in Health: Evidence and Needed Research,” J Behav Med, 2009, PMID: 19030981


7. Leitner et al. “Blacks' Death Rate Due to Circulatory Diseases Is Positively Related to Whites' Explicit Racial Bias,” Psychol Sci, 2016, PMID: 27557618; Chae et al. “Area racism and birth outcomes among Blacks in the United States,” Soc Sci Med, 2018, PMID: 28454665


8. Sjoding et al. “Racial Bias in Pulse Oximetry Measurement,” N Engl J Med 2020 DOI: 10.1056/NEJMc2029240


9. Shcherbina et al. “Accuracy in wrist-worn, sensor-based measurements of heart rate and energy expenditure in a diverse cohort,” J Pers Med. 2017, PMID: 28538708; Fallow et al. “Influence of skin type and wavelength on light wave reflectance,” J Clin Monit Comput. 2013, PMID: 23397431


10. Obermeyer, Z., Powers, B., Vogeli, C. & Mullainathan, S. Science 336, 447–453 (2019)


11. Sjoding MW, Ansari S, Valley TS. Origins of Racial and Ethnic Bias in Pulmonary Technologies. Annu Rev Med. 2023 Jan 27;74:401-412. doi: 10.1146/annurev-med-043021-024004. Epub 2022 Jul 28. PMID: 35901314; PMCID: PMC9883596.