A More Intentional Analysis of Race and Racism in Research

Earlier this year, the Journal of Hospital Medicine updated its author guidelines to include recommendations on addressing race and racism.¹ These recommendations include explicitly naming racism (rather than race) as a determinant of health. Operationalizing these recommendations into manuscripts represents a fundamental shift in how we ask research questions, structure analyses, and interpret results.

In this issue, Maxwell et al² illustrate how to disseminate research through this lens in their retrospective cohort study of children with type 1 diabetes hospitalized with diabetic ketoacidosis (DKA). Using 6 years of data from a major academic pediatric medical center, the authors examine the association between risk for DKA admission and three factors: neighborhood poverty level, race, and type of insurance (public or private). Secondary outcomes include DKA severity and length of stay. In their unadjusted model, poverty, race, and insurance were all associated with increased hospitalizations. However, following adjustment, the association between race and hospitalizations disappeared.In line with the journal’s new guidelines, the authors point out that the statistically significant associations of poverty and insurance type with clinical outcomes suggest that racism, rather than race, is a social factor at work in their population. The authors provide further context regarding structural racism in the United States and the history of redlining, which has helped shape a society in which Black individuals are more likely to live in areas of concentrated poverty and be publicly insured.

Two other findings related to the impact of racism are notable. First, in both their univariate and multivariate models, the authors found significant A1c differences between Black and White children—higher than those of previous reports.³ These findings suggest the existence of structural factors at work in the health of their patients. Second, Black patients had longer lengths of stay when compared to White patients with the same severity of DKA. Neither poverty level nor insurance status were significantly associated with length of stay. While the analysis was limited to detecting this difference, rather than identifying its causes, the authors suggest factors at both individual and structural levels that may be impacting outcomes. Specifically, care team bias may impact discharge decisions, and factors such as less flexible times to complete diabetes education, transportation barriers, and childcare challenges could also impact discharge timing.

This work provides a template for how to address the impact of racism on health with intentionality. Moreover, individuals’ lived environments should be considered through alternative economic measurements and neighborhood definitions. The proportion of people within a census tract living below the federal poverty line is just one measure of the complex dynamics that contribute to an individual’s socioeconomic status. An alternative measure is the area deprivation index, which incorporates 17 indicators at the more granular census block group level to describe an individual’s environment⁴ and could be useful in this area of research.

Perhaps most relevant is the use of public insurance as a marker of socioeconomic status. Medicaid, although not without its flaws, provides fairly comprehensive coverage. However, many Americans have incomes too high to qualify for public insurance but too low to afford adequate insurance coverage. Theoretically, these individuals qualify for subsidies through the Affordable Care Act, yet underinsurance remains a significant issue.⁵ Future analyses to further understand and describe clinical outcomes could include this population of underinsured children as a distinct at-risk group. Maxwell et al² provide an excellent example of how we should address race and racism in disseminated literature. Although initially challenging, writing with intentionality regarding this fundamental determinant of health can provide rich and actionable information for practitioners and policy-makers.

Earlier this year, the Journal of Hospital Medicine updated its author guidelines to include recommendations on addressing race and racism.¹ These recommendations include explicitly naming racism (rather than race) as a determinant of health. Operationalizing these recommendations into manuscripts represents a fundamental shift in how we ask research questions, structure analyses, and interpret results.

In this issue, Maxwell et al² illustrate how to disseminate research through this lens in their retrospective cohort study of children with type 1 diabetes hospitalized with diabetic ketoacidosis (DKA). Using 6 years of data from a major academic pediatric medical center, the authors examine the association between risk for DKA admission and three factors: neighborhood poverty level, race, and type of insurance (public or private). Secondary outcomes include DKA severity and length of stay. In their unadjusted model, poverty, race, and insurance were all associated with increased hospitalizations. However, following adjustment, the association between race and hospitalizations disappeared.In line with the journal’s new guidelines, the authors point out that the statistically significant associations of poverty and insurance type with clinical outcomes suggest that racism, rather than race, is a social factor at work in their population. The authors provide further context regarding structural racism in the United States and the history of redlining, which has helped shape a society in which Black individuals are more likely to live in areas of concentrated poverty and be publicly insured.

Two other findings related to the impact of racism are notable. First, in both their univariate and multivariate models, the authors found significant A1c differences between Black and White children—higher than those of previous reports.³ These findings suggest the existence of structural factors at work in the health of their patients. Second, Black patients had longer lengths of stay when compared to White patients with the same severity of DKA. Neither poverty level nor insurance status were significantly associated with length of stay. While the analysis was limited to detecting this difference, rather than identifying its causes, the authors suggest factors at both individual and structural levels that may be impacting outcomes. Specifically, care team bias may impact discharge decisions, and factors such as less flexible times to complete diabetes education, transportation barriers, and childcare challenges could also impact discharge timing.

This work provides a template for how to address the impact of racism on health with intentionality. Moreover, individuals’ lived environments should be considered through alternative economic measurements and neighborhood definitions. The proportion of people within a census tract living below the federal poverty line is just one measure of the complex dynamics that contribute to an individual’s socioeconomic status. An alternative measure is the area deprivation index, which incorporates 17 indicators at the more granular census block group level to describe an individual’s environment⁴ and could be useful in this area of research.

Perhaps most relevant is the use of public insurance as a marker of socioeconomic status. Medicaid, although not without its flaws, provides fairly comprehensive coverage. However, many Americans have incomes too high to qualify for public insurance but too low to afford adequate insurance coverage. Theoretically, these individuals qualify for subsidies through the Affordable Care Act, yet underinsurance remains a significant issue.⁵ Future analyses to further understand and describe clinical outcomes could include this population of underinsured children as a distinct at-risk group. Maxwell et al² provide an excellent example of how we should address race and racism in disseminated literature. Although initially challenging, writing with intentionality regarding this fundamental determinant of health can provide rich and actionable information for practitioners and policy-makers.

Earlier this year, the Journal of Hospital Medicine updated its author guidelines to include recommendations on addressing race and racism.¹ These recommendations include explicitly naming racism (rather than race) as a determinant of health. Operationalizing these recommendations into manuscripts represents a fundamental shift in how we ask research questions, structure analyses, and interpret results.

In this issue, Maxwell et al² illustrate how to disseminate research through this lens in their retrospective cohort study of children with type 1 diabetes hospitalized with diabetic ketoacidosis (DKA). Using 6 years of data from a major academic pediatric medical center, the authors examine the association between risk for DKA admission and three factors: neighborhood poverty level, race, and type of insurance (public or private). Secondary outcomes include DKA severity and length of stay. In their unadjusted model, poverty, race, and insurance were all associated with increased hospitalizations. However, following adjustment, the association between race and hospitalizations disappeared.In line with the journal’s new guidelines, the authors point out that the statistically significant associations of poverty and insurance type with clinical outcomes suggest that racism, rather than race, is a social factor at work in their population. The authors provide further context regarding structural racism in the United States and the history of redlining, which has helped shape a society in which Black individuals are more likely to live in areas of concentrated poverty and be publicly insured.

Two other findings related to the impact of racism are notable. First, in both their univariate and multivariate models, the authors found significant A1c differences between Black and White children—higher than those of previous reports.³ These findings suggest the existence of structural factors at work in the health of their patients. Second, Black patients had longer lengths of stay when compared to White patients with the same severity of DKA. Neither poverty level nor insurance status were significantly associated with length of stay. While the analysis was limited to detecting this difference, rather than identifying its causes, the authors suggest factors at both individual and structural levels that may be impacting outcomes. Specifically, care team bias may impact discharge decisions, and factors such as less flexible times to complete diabetes education, transportation barriers, and childcare challenges could also impact discharge timing.

This work provides a template for how to address the impact of racism on health with intentionality. Moreover, individuals’ lived environments should be considered through alternative economic measurements and neighborhood definitions. The proportion of people within a census tract living below the federal poverty line is just one measure of the complex dynamics that contribute to an individual’s socioeconomic status. An alternative measure is the area deprivation index, which incorporates 17 indicators at the more granular census block group level to describe an individual’s environment⁴ and could be useful in this area of research.

Perhaps most relevant is the use of public insurance as a marker of socioeconomic status. Medicaid, although not without its flaws, provides fairly comprehensive coverage. However, many Americans have incomes too high to qualify for public insurance but too low to afford adequate insurance coverage. Theoretically, these individuals qualify for subsidies through the Affordable Care Act, yet underinsurance remains a significant issue.⁵ Future analyses to further understand and describe clinical outcomes could include this population of underinsured children as a distinct at-risk group. Maxwell et al² provide an excellent example of how we should address race and racism in disseminated literature. Although initially challenging, writing with intentionality regarding this fundamental determinant of health can provide rich and actionable information for practitioners and policy-makers.