Race & Spirometry (Part III)

In case you’ve missed the first two articles, it may be helpful to go read those first. The first article details the broader history of race in American medicine. The second article details predictive equations in spirometry, and race as a factor of prediction. This article will tie those two by detailing the history of race in spirometry. Much of this article goes into details chronicled by Dr. Lundy Braun in her book, Breathing Race into the Machine. If this series interests you, I would encourage you to read her book, available in paperback in January and currently available in hardback.

History of Race in Spirometry: Founding Fathers

Roots of race in spirometry were established when Thomas Jefferson noted differences in lung function between White and Black individuals, possibly as a way of further justifying slavery.¹ ² Spirometry was imagined in many capacities, but modern spirometry began to take shape in Europe in the 1840s through the work, study, apparatus and nomenclature created by John Hutchinson.¹ He promoted height as a potential predictive factor of lung function later adding in occupation.

However by the time spirometry made it to the United States, Jefferson’s mentality around racial differences in biological capacities was cultivated by the pseudo-science of eugenics and nurtured by skull sizing, craniology and racial differences as famously chronicled by Samuel Morton.³ In the 1850s, Samuel Cartwright a prominent physician and plantation owner who forced individuals into enslaved labor began using his educational background to justify racial differences to build a device in order to justify that the Black individuals “consume less oxygen than white people”⁴ and accounted for a 20% difference numerically.

1850 on: Civil War

The notion of racial differences helped fuel ideas of enslaved labor and environmental tolerance that made one race better suited for labor than another. By the time the Civil War broke out, the United States commissioned a Sanitary Commission in order to understand the hygiene and physical burdens of the war on the Union Army’s success.¹ Originally race was not a factor in this study.

The focus changed when Benjamin Apthrop Gould led the helm, a prominent astronomer and data analyst (also one of the original founders of the National Academy of Sciences),⁵ fueled by funding from the life insurance industry.¹ The original mission advanced to compare White soldiers to Black soldiers recently authorized to join the fight. His efforts ended in Investigations in the Military and Anthropological Statistics of American Soldiers, in which the hefty volume details various anthropomorphic differences from baldness, facial angle, and number of teeth lost to the use of spirometry organized by race and “nativity” over occupation for the first time.⁶

Bias and A Lack of Reliable Data

Field reporters who helped with the survey were told to assess race visually and estimate level of non-white race compared to a White standard soldier.¹ He noted “marked inferiority of the values observed in the black race” in lung capacity and used “inferior” to describe “Indian” and “Mulatto” groups throughout the volume.⁶ While Gould looked at differences between some occupational factors like job or rank, for White individuals, these were ignored for other races.

Lastly in a push to publish, data was lost or misclassified, leaving numbers that are likely untrue.¹ The study was published and accepted despite a pretty similar study conducted by Jedidah Baxter, the chief medical officer for the Bureau of the War Department, that found no differences.¹ ⁷ Additionally prominent Black physicians, scientists, and intellectuals like W.E.B. DuBois, Kelly Miller, and M.V. Ball protested, nevertheless, the idea that “non-white” individuals had weaker lungs persisted and prevailed.

Early 1900s: Life & Medicine

Frederick Hoffman, chief statistician for Prudential Life Insurance Co. used the data from Gould’s study from the Civil War as justification for eliminating industrial life insurance policies for Black individuals.¹ This was premised on his argument that Black individuals will die at faster rates due to the insufficient capacities of handling emancipation, and inferior lung health and capacity.¹ ⁸ ⁹

Medical Handbook

Hoffman’s conclusion that White individuals fundamentally had higher lung capacity than other racial groups took root. These racial differences (and differences based on sex) were then incorporated in a clinical handbook by JA Myers in 1925,¹⁰ setting the stage for an official standard worldwide and solidifying race as a predictive variable. Research in 1960 emphasized these racial differences further and brought it to the international forefront. One study compared lung function in mills and ginneries cross-borders between Uganda and Kenya with England and concluded smaller lung capacity without confounding or additional factors.¹¹

Scaled Factors and Pushing Out Other Factors

Differences led to a scaled factor first presented (to my knowledge) from Tulane University in 1974. This 13% difference can still be seen in modern equations including within the NHANES formulas. This New Orleans-based study entirely dismissed social and economic factors. In the discussion section, the authors cite that because their results reflect other studies, “these factors may be unimportant.”¹² Additionally they recommend that the results “be taken representative of the ethnic differences throughout the U.S.A.” despite solely comparing Black and White asbestos cement workers in the south.

Around the same time, a book was published on predictive values and only looked at the function of age and height over time in its regression formulas.¹⁴ This book did not claim race as a factor, but race as a factor in spirometry persisted.

Centering of White Men

Predictive values accepted by spirometers today date back to the 1960s. Early values like those produced by Berglund and colleagues originate in European countries with a White population forming a norm to compare other individuals.¹⁵Additional previous acceptable measures of predicted values include Knudson, 1976 and Knudson, Lebowitz, Holberg, and Burrows 1982. The latter looked at “white non-Mexican-American” participants in Arizona.¹⁴

White men become the standard that is left unweighted and untouched while individuals outside of that identity are adapted via “corrective” values or formulas, and often crippled in the process in terms of weighted variables within a predictive equation.

The 1990s brings us to the NHANES formulas focused in the USA and comparisons in accessible datasets across White, African-American, and Mexican American populations.⁶

Back to GLI

Last article, we focused a lot on the Global Lung Function Initiative predictive equations, largely acceptable, with over 74,000 participants within the study and an intent to reach and incorporate more age groups and ethnic groups.

The GLI equations are often globally acceptable and to their credit wide reaching. Yet they are still really limited in the various ethnic identities they can predict. They don’t account for movement across regions or racial/ethnic identity within a country; they don’t account for generational or immigration status. The authors even mentioned that certain variation may be a result of advanced lung function based on altitude of a city or region, for example. There has been research on pretty substantial differences based on altitude,¹⁶ ¹⁷ ¹⁸ but these factors are not accounted for in the analyses.¹⁹

The issue with these predictive formulas is that race, as shown through historic timelines, is not a good proxy for things like proximity to pollution, whether you were raised at altitude, if you have impactful biological factors that may impact your age, sex, height, and ultimately your lung capacity.

With their national acceptance and integration into spirometers using baseline information in order to even access the device, these algorithms are hard to move away from. The study has large study sample sizes in various centers across the world, making the study highly impactful, while still squandering ethnic identity into four categories. This can be dangerous in the realm of science, where we rely on doctors and scientists to interpret results meaningfully, and we trust the integrity of that science based on their expertise, the peer-review process, and the quality of journals and statistical methodology. We want professionals to focus on impact over intent, and to recognize ethical implications of interpretability.

The issue with intent though, is it doesn’t factor in societal assumptions, the implicit biases that individuals foster based on those assumptions, and our country’s storied history. All of these funnel into impacting an individual’s health.

Steps towards Centering of the Individual

At VitalFlo we’re seeking to predict an individual’s lung capacity from their own baseline based on vital capacity, environmental air quality, time in the year, and other variables that influence how well you breathe as an individual.

We’re attempting to break potentially harmful cycles that are determined by social norms of gender and ethnic or racial identities, while recognizing that these are important aspects to an individuals identity and a possible social determinant. While we will continue to offer access to these national and international standards, we want to ensure that our audiences recognize the detailed history and possible impact that these predictions are empowered with.

‍The American Medical Association just this week publicly recognized racism as a threat to public health,²⁰ which is a huge step towards tackling historical precedence and focusing on impactful health outcomes. We hope as a healthcare startup that AMA will continue to hone in on the impacts of racism and its part in medicine, and we plan on continuing that fight.

Stay Tuned

In the next article we’ll talk about the impact of these predictive equations.

References

1. Braun L. Breathing Race into the Machine: The Surprising Career of the Spirometer from Plantation to Genetics. U of Minnesota Press; 2014.
2. Thomas Jefferson, “Notes on the State of Virginia,” in Race and the Enlightenment: A Reader, ed. Emmanuel Eze (Malden, Mass., and London: Blackwell Publishing, 1997), 98. Enlightenment thinking about race played out differently in India. See Mark Harrison, Climates and Constitutions: Health, Race, Environment and British Imperialism in India, 1600–1850 (Oxford: Oxford University Press, 1999).
3. Fabian A. The Skull Collectors: Race, Science, and America’s Unburied Dead. University of Chicago Press; 2010.
4. Gould BA, Elliott EN, Schomburg Center for Research in Black Culture, Adam Matthew Digital. Slavery in the Light of Ethnology. In: Cotton Is King, and pro-Slavery Arguments Comprising the Writings of Hammond, Harper, Christy, Stringfellow, Hodge, Bledsoe, and Cartwright, on This Important Subject / [Edited] by E.N. Elliott ; with an Essay on Slavery in the Light of International Law / by the Editor. Slavery, abolition & social justice. Pritchard, Abbott & Loomis; 1860:701. Accessed November 3, 2020. http://www.slavery.amdigital.co.uk/Contents/DocumentDetails.aspx?documentid=136902
5. National Academy of Sciences. History: Incorporators of the NAS. National Academy of Sciences. Accessed November 3, 2020. http://www.nasonline.org/about-nas/history/archives/nas-incorporators.html
6. Gould BA. Investigations in the Military and Anthropological Statistics of American Soldiers. U.S. sanitary commission; 1869.
7. Jedediah H. Baxter, Statistics, Medical and Anthropological of the Provost-Marshal-General’s Bureau Derived from Records of the Examination for Military Service in the Armies of the United States during the Late War of the Rebellion of over a Million Recruits, Drafted Men, Substitutes, and Enrolled, 2 vols. (Washington, D.C.: U.S. Government Printing Office, 1875).
8. Frederick L. Hoffman, History of the Prudential Insurance Company of
   America (Industrial Insurance), 1875–1900 (Newark: Prudential Press, 1900); “The Colored Race in Life Assurance,” Lancet 2 (1898), 902; Haller, “Race, Mortality, and Life Insurance.”
9. Hoffman FL. Race Traits and Tendencies of the American Negro. American Economic Association; 1896.
10. J.A. Myers, Vital Capacity of the Lungs: A Handbook for Clinicians and
    Others Interested in the Examination of the Heart and Lungs Both in Health and Disease (Baltimore: Williams & Wilkins Company, 1925).
11. J.C. Gilson, H. Stott, B.E.C. Hopwood, S.A. Roach, C. B. McKerrow,
    and R.S. F. Schilling, “Byssinosis: The Acute Effect of Ventilatory Capacity of Dusts in Cotton Ginneries, Cotton, Sisal, and Jute Mills,” British Journal of Industrial Medicine 18 (1962).
12. Rossiter CE, Weill H. Ethnic Differences in Lung Function: evidence for proportional differences. Int J Epidemiol. 1974;3(1):55–61. doi:10.1093/ije/3.1.55
13. Edge JR. The Aging Lung: Normal Function. Ardent Media; 1974.
14. Knudson RJ, Lebowitz MD, Holberg CJ, Burrows B. Changes in the Normal Maximal Expiratory Flow-Volume Curve with Growth and Aging. Am Rev Respir Dis. 1983;127(6):725–734. doi:10.1164/arrd.1983.127.6.725
15. Berglund E, Birath G, Bjure J, et al. Spirometric Studies in Normal Subjects I. Acta Medica Scandinavica. 1963;173(2):185–192. doi:10.1111/j.0954–6820.1963.tb16520.x
16. Gilbert-Kawai, E.T., Milledge, J.S., Grocott, M.P. and Martin, D.S., 2014. King of the mountains: Tibetan and Sherpa physiological adaptations for life at high altitude. Physiology, 29(6), pp.388–402.
17. Wood, S., Norboo, T., Lilly, M., Yoneda, K. and Eldridge, M., 2003. Cardiopulmonary function in high altitude residents of Ladakh. High altitude medicine & biology, 4(4), pp.445–454.
18. Roh, H. and Lee, D., 2014. Respiratory function of university students living at high altitude. Journal of physical therapy science, 26(9), pp.1489–1492.
19. Quanjer, P.H., Stanojevic, S., Cole, T.J., Baur, X., Hall, G.L., Culver, B.H., Enright, P.L., Hankinson, J.L., Ip, M.S., Zheng, J. and Stocks, J., 2012. Multi-ethnic reference values for spirometry for the 3–95-yr age range: the global lung function 2012 equations. doi: 10.1183/09031936.00080312
20. O’Reily, K. B. (2020, November 16). AMA: Racism is a threat to public health. Retrieved November 18, 2020, from https://www.ama-assn.org/delivering-care/health-equity/ama-racism-threat-public-health