• Let’s Retire Myths About Individual Behavior and Health

    Carmen Mitchell is currently a fourth-year health policy doctoral student in the Department of Health Management and Systems Sciences at the University of Louisville School of Public Health and Information Sciences (SPHIS). She is currently affiliated with The Afya Project, an interdisciplinary research initiative seeking to increase PrEP availability and use among African Americans in Louisville, Kentucky. She completed her Master’s in public health in 2016 at the University of Louisville. She tweets at @carmenrmitchell.

    In Christmas Eve tweets, the entrepreneur and presidential candidate Andrew Yang expressed the following:

    Yang’s tweets were widely interpreted to mean if more people ate healthier and exercised more, healthcare expenses would be lower and population health outcomes better. Though intuitive to many, healthcare is not this simple.

    Let’s start with the relationship between health-related behaviors (like diet and exercise) and spending. Unfortunately, as Dr. Aaron Carroll notes in the New York Times, the research on different types of preventative care — including interventions centered on health behavior —consistently fails to find savings.

    Of course, just because there isn’t an immediate payoff from healthy behaviors doesn’t mean that we shouldn’t encourage them. But, in doing so, we should be honest about the benefits: eating well and exercising regularly are good for health and wellbeing.

    Even so, they won’t address some of America’s major health problems. Granted, heart disease — which is associated with diet and exercise — remains the top cause of death in the United States.

    But suicide and drug overdose — which are not associated with diet and exercise — remain top killers for adults in the U.S. between the ages of 15 and 64. As recently as 2017, homicide was ranked 4th for causes of death among Black men (and #1 overall among Black men under 45), while HIV and complications related to pregnancy are among the top 10 causes of death for Black women between ages 20 and 44. Neither gym memberships nor healthy eating habits would fix any of this.

    Furthermore, using financial incentives to promote diet and exercise (as Yang is suggesting) misses the underlying structural factors driving health behaviors. For example, food intake behaviors are influenced by many community and structural factors, including prices, accessibility, social and cultural norms, and habits developed during formative years. Those can’t be fixed by sending people to nutritionists. The same goes for exercise and buying gym memberships.

    Calling for better diets and more exercise as solutions, even if they worked, has classist and racist undertones. People who have low-incomes will not have the resources to purchase the food a nutritionist would recommend, and they may not have the time to go to the gym if they are balancing multiple jobs and families. People of color disproportionately face these structural barriers.

    This isn’t a fine point. Yang’s suggestions miss a lot of people and a lot of deep problems. A recent report estimated that nearly 44% of the US workforce — 53 million people — work in “low wage” jobs. Most of these workers lack college degrees and are women and/or people of color.

    As has been written about extensively, Black Americans are more likely to experience chronic financial instability as a result of racist policies, and the corresponding community problems that arise from it. They are more likely to live in environmentally polluted neighborhoods (think Flint, MI, although this is a phenomenon everywhere), experience incarceration, and have fractured relationships with healthcare services because of completely justifiable medical mistrust, as well as suffer from constant stress of racism and racism-based encounters.

    All of these are major drivers of health that cannot be fixed with diet and exercise. They are longstanding American problems that today’s candidates and elected officials, including Yang, rarely address head on.

    To those of us who work in health services research, I likely haven’t mentioned anything you don’t know; we are very aware that tackling continuously rising spending and working to address health outcomes will require a significant amount of structural reform outside the health system and beyond the individual.

    Despite this, the language of individualism and personal responsibility pervades talking points among public officials. They’re correct that to improve health for all Americans we need to look beyond the health system. But they’re wrong to think we don’t need to look within other complex social, cultural, economic, and political systems.

    For example, in the halls of the state capitol in my home state of Kentucky, one of the states hit hardest by the opioid crisis, it is still quite common to hear public officials point to individuals’ moral failings as the problem’s source and their personal responsibility as the solution. In truth, failure in government oversight and economic distress have both played large roles in the problem. We won’t be able to meaningfully tackle it without addressing those systematic factors, along with promoting evidence-based medical treatment in lieu of shame and punishment.

    Individual-centered messaging would be less of a problem if it was just coming from Yang and a small group of like-minded policymakers. Unfortunately, we hear similar messages from many facets of society, including “health and wellness” media and advertising (both for-profit and non-profit), workplaces, doctors and other healthcare professionals, public health institutions and health-focused academic disciplines.

    This partially reflects a failure of the health services research disciplines to effectively communicate the truths we’ve learned. What else can we do?

    As I have argued previously, incorporating more systems-focused curriculum in graduate training would be a great way to help future health researchers and practitioners move away from individual centered-thinking. We might also promote more opportunities to build translation and communication skills among health professionals; there are currently several AcademyHealth initiatives for this purpose, though we might consider how we can create more accessible learning on campus. (As an example, this week Cornell announced a new undergraduate minor in science communication.)

    We could also seek more ways to partner with organizations focused on improving community health in a systematic way. Drivers of Health, a Robert Wood Johnson funded project examining meaningful empirical research on social determinants, is a great example of this.

    If we — policymakers and health services researchers alike — are all committed to improving population health, it is imperative that we shift the conversation to the true underlying causes. We have a lot of work to do. Flint Michigan still doesn’t have clean water. Nearly 3 in 10 Americans skip filling a prescription because of costs. So, let’s focus less on gym memberships and more on what really matters.

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  • Healthcare Triage Podcast: CAR T-Cell Therapy and the Future of Cancer Treatment

    Aaron Carroll talks to Dr. Sherif Farag of Indiana University about his work harnessing the power of patients’ own immune systems to treat blood cancers like multiple myeloma.


    The Healthcare Triage podcast is sponsored by Indiana University School of Medicine whose mission is to advance health in the state of Indiana and beyond by promoting innovation and excellence in education, research and patient care.

    IU School of Medicine is leading Indiana University’s first grand challenge, the Precision Health Initiative, with bold goals to cure multiple myeloma, triple negative breast cancer and childhood sarcoma and prevent type 2 diabetes and Alzheimer’s disease.

    Available wherever you get your podcasts! Including iTunes


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  • Childhood Obesity Is a Major Problem. Research Isn’t Helping.

    The following originally appeared on The Upshot (copyright 2020, The New York Times Company)


    Childhood obesity is a major public health problem, and has been for some time. Almost 20 percent of American children are affected by obesity, as well as about 40 percent of adults. Over all, this costs the United States around $150 billion in health care spending each year.

    Pediatricians like me, and many other health professionals, know it’s a problem, and yet we’ve been relatively unsuccessful in tackling it. About six years ago, some reports seemed to show that rates had stabilized in children and even decreased in those ages 2 to 5. Later studies showed this trend to be an illusion. If anything, things have gotten worse.

    Efforts to help can backfire. People on diets often gain weight. Although individual studies have pointed to potential interventions and solutions, these have not yet translated into actual improvements. Part of the problem may be flawed research.

    recent paper in Pediatric Obesity provided a guide on how to do better. Its suggestions fall into five general themes.


    1. When things look better, it’s critical to ask “compared to what?”

    In short, you need a control group. Over time, changes in behaviors or measurements often follow a pattern known as regression toward the meanOutliers (in this case those who are more overweight) tend to move toward the average. Thus, interventions might look as if they’re working when they’re not. Control groups — participants who don’t receive the intervention — can help ensure that we’re seeing real effectiveness.

    Even then, things can get tricky. In a randomized controlled trial, it’s important to keep the comparisons directly between the intervention and control groups. A common mistake is comparing each group after the intervention with the same group before the intervention. In other words, people could compare a dieting group to itself, before and after, and compare the control group to itself, before and after, to see if the dieting group achieved a significant decrease.

    This is known as a “differences in nominal significance” error. Doing this can make an intervention look as if it achieved a significant change against a baseline measurement when it probably did not against the control group.

    Creating and studying large obesity interventions is hard and expensive. It’s only natural that researchers want them to work. But if your well-designed study doesn’t result in significant improvements in an intervention group over a control group, you can’t then fall back on claims that those who received the intervention still lost weight. Control groups are there for a reason. You can’t dismiss them after the fact.

    2. Don’t change the analysis plan.

    Before a study begins, its expected primary outcome should be clearly defined. For most obesity studies, that’s going to be a decrease in body mass index. You can’t later add in other outcomes that might show results even if the main outcome does not.

    Sometimes, to get statistically significant results, researchers will adjust analyses in ways that achieve them. This is called p-hacking. Changing outcomes can result in different numbers of patients “qualifying” through inclusion and exclusion criteria in such a way as to change the actual groups being studied.

    3. Be careful when designing studies and picking outcomes.

    Too often, when trying to prove that subjects changed their diet or exercise habits, we simply ask them if they did. This risks getting results influenced by self-report bias. If a study’s focus is an educational intervention that tells students they should walk more and watch less TV, we shouldn’t be surprised that they say they did, even when there’s no change in body fat percentage.

    Because interventions tend to be delivered in groups (randomly assigning by classes or schools), it’s important that we analyze results only by groups. There are only as many “participants” as there are groups. Too often, researchers conduct statistics on the individuals, and when they see improvements, it’s because of the differences between groups, not the interventions.

    4. Not significant is not significant.

    Negative results — those that do not back up the hypothesis of the researcher — should not be spun as positive. Researchers are often tempted to argue that these results are clinically significant, or that they have “promise.”

    Sometimes, researchers want to test one intervention against an already proven one. If they find that there’s no difference, they conclude that the two are equally effective. This can be a mistake.

    5. Don’t assume that an intervention is better than nothing.

    Most studies conduct a two-sided analysis. This means they look at whether an intervention is better or worse, then consider the results significant if the p-value is less than 0.05. In some studies, though, researchers assume that interventions can only help people lose weight, not gain it. They therefore conduct a one-sided test, which effectively doubles the allowable p-value. Results that would not have been significant become so.


    Some of these rules are technical. Others involve not overreaching on the results. And some acknowledge that researchers are human beings who are predisposed to want to get positive results. These are certainly true with respect to obesity, but they’re true for almost all health research.

    To be effective, interventions and policies need to be built upon solid data. There are no assurances that interventions can only do good. It’s possible that interventions — almost all of which are done on a small scale — may not be the solution. Michelle Obama’s “Let’s Move” initiative — which was done on a large scale — was often credited in helping to slow or reverse childhood obesity, but there’s no evidence that’s true.

    Processed food, and the advertising and marketing of it, is one driver of the problem. So is a lack of effort and resources put toward maintaining a healthy lifestyle. (If there are no sidewalks, you may be unlikely to walk to the store or to school, for example.)

    Major problems like poverty can’t be overcome with a couple of workshops in a school or a doctor’s visit. Obesity is a major societal problem that probably requires a major societal response. We can’t allow our desire to make things better lead us to accept lower-quality research that might convince us otherwise.




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  • The effects of sense of belonging on student mental health outcomes

    Nambi Ndugga is a Policy Analyst with Boston University’s School of Public Health. She tweets at @joerianatalie

    Content warning: mentions of sexual assault and suicide

    Feelings of depression, suicidal ideation, and attempted suicide among college students have dramatically increased in recent years. Researchers have found that 20 percent of college students have experienced suicidal ideation and 9 percent have attempted suicide. The numbers are even more striking for students who identify as sexual minorities; for example, over 50 percent of bisexual students experience suicidal ideation and self-harm and over 25 percent have attempted suicide.

    Numerous studies support these findings, showcasing that mental health conditions are common among college students, especially among students who do not identify as heterosexual. Further, these studies show that students who struggle with mental health conditions, including depression, also experience diminished energy levels and difficulty concentrating. This adversely affects their sense of wellbeing, academic performance, and the probability of college completion.

    New Research

    An international group of researchers recently studied the effects of varying levels of sense of belonging and the experience of sexual assault on predicting suicidality and depression among LGBQ and heterosexual college students. The team included Insa Backhaus, Sarah K. Lipson, Lauren B. Fisher, Ichiro Kawachi, and Paola Pedrelli – from Sapienza University of Rome, Harvard T.H. Chan School of Public Health, Department of Health, Law, Policy & Management at Boston University School of Public Health, Massachusetts General Hospital, and Harvard Medical School.

    The researchers used a subset of data from the 2017-2018 Healthy Mind Study (HMS) – an annual, web-based survey that examines mental health, service utilization, and other related factors among over 60,000 graduate and undergraduate students from 60 US campuses. Most of the participants included were white (61.2 percent) and female (61.5 percent). LGBQ students made up 21 percent of the sample, with 5 percent identifying as gay or lesbian, 7 percent as bisexual, and 7 percent as queer or questioning.

    Backhaus et al. assessed the relationships among sexual orientation, sexual assault, sense of belonging, and depression and suicidal ideation. They hypothesized that a high sense of belonging would be associated with overall lower depressive symptoms and suicidal ideation and that it would play a protective role in the presence of sexual assault.

    Key Measures

    The researchers defined key concepts and variables in the following ways:

    Sexual orientation: The sex of the person whom an individual is sexually and emotionally attracted to, including, lesbian, gay, bisexual, queer, and questioning individuals.

    Sexual assault: Any unwanted, unconsented sexual contact, regardless of where it happened.

    Sense of belonging: An individual’s experience of feeling valued, needed, and accepted by a social system (college campus). This was based on how much students’ agreed or disagreed with the following statements: (a) I see myself as part of the campus community, (b) I fit in well at my school, (c) I feel isolated from campus life, (d) Other people understand more than I do about campus life.

    Depression and suicidal ideation: Depressive symptoms were identified and measured using the Patient Health Questionnaire (PHQ-9) – a multipurpose instrument for screening, diagnosing, monitoring, and measuring the severity of depression. They used item #9 of the questionnaire to measure self-harm and suicidal ideation.


    Significantly more LGBQ students reported depressive symptoms, suicidal ideation, and experiences of sexual assault within a twelve-month period than heterosexual students. Depression and suicidal ideation had a significantly strong positive correlation to each other among both groups of students, while sexual assault and depression had a smaller positive correlation.

    Sexual orientation, sexual assault, and sense of belonging were significant predictors of depressive symptoms. Sexual orientation and sexual assault were significant predictors of suicidal ideation for students with a low sense of belonging, but not for those with a high sense of belonging. Sense of belonging provided a protective effect against depression and suicidal ideation in the presence of sexual assault in both LGBQ and heterosexual students but the effect was much greater among LGBQ students.


    The work of Backhaus et al. identifies pathways that can be used to improve mental health outcomes and reduce the mental health disparities between LGBQ and heterosexual students within the college context. In particular, the results emphasize the need for a greater focus on students’ sense of belonging within the college context by adequately addressing the prevalence of sexual assault on college campuses and increasing the availability of mental health resources for students.

    Though more could be done, in recent years numerous schools have implemented mental health information sessions during orientation week to reduce the stigma surrounding mental illness and introduce students to the available services. Some, such as UCLA, have implemented comprehensive programs that offer screening, tracking, and treatment of anxiety, depression, and suicidality to all students.

    With the understanding that LGBQ students are more likely to experience adverse mental health outcomes, most college campuses have versions of a LGBTQ alliance (including transgender students as well) which have been shown to reduce the severity of adverse mental health outcomes among LGBTQ students. Further, schools are using data from HMS, Columbia’s Sexual Health Initiative to Foster Transformation, and other comprehensive datasets to inform sexual assault prevention strategies and increase feelings of safety and belonging on campus.

    These steps help students in multiple ways. Improved mental health outcomes and sense of belonging clearly foster wellbeing. They are also strongly associated with increased student retention and student academic and personal success.

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  • Brief summary of *White Fragility*

    My mom sent me her brief summary of White Fragility, by Robin DiAngelo.

    In countless ways, white people in American society are the standard and people of color the exception. White dominance is a product of racism, but also a protection from its traumas. Whites live in “a cocoon of racial comfort, centrality, superiority, entitlement, racial apathy, and obliviousness, all rooted in an identity of being good people free of racism.” As a result, whites become defensive and emotional if confronted with the racism embedded in their status, a reaction that the author — a trainer in racial and social justice — labels “white fragility.” DiAngelo makes this point repeatedly and with many examples, and she offers advice for a lifelong effort to rid oneself of white fragility and the racism that feeds it. A succinct version can be found in DiAngelo’s article “White Fragility,” International Journal of Critical Pedagogy, Vol 3 (3) (2011) pp 54-70.


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  • Recent publications from Boston University’s Department of Health Law, Policy and Management: January 2020 Edition

    Below are recent publications from me and my colleagues from Boston University’s Department of Health Law, Policy and Management. You can find all posts in this series here.

    January 2020 Edition

    Addo-Tabiri NO, Chudasama R, Vasudeva R, Leiva O, Garcia B, Ravid JD, Bunze T, Rosen L, Belghasem M, Francis J, Brophy M, Johnson B, Ferguson R, Weinberg J, Chitalia VC. Black Patients Experience Highest Rates of Cancer-associated Venous Thromboembolism. Am J Clin Oncol. 2019 Dec 04. PMID: 31809329.

    Ananthakrishnan R, Green S, Li D, LaValley M. 2D (2 Dimensional) TEQR design for Determining the optimal Dose for safety and efficacy. Contemp Clin Trials Commun. 2019 Dec; 16:100461. PMID: 31799471.

    Banack HR, Bea JW, Stokes A, Kroenke CH, Stefanick ML, Beresford SA, Bird CE, Garcia L, Wallace R, Wild RA, Caan B, Wactawski-Wende J. It’s Absolutely Relative: The Effect of Age on the BMI-Mortality Relationship in Postmenopausal Women. Obesity (Silver Spring). 2020 Jan; 28(1):171-177. PMID: 31799808.

    Bernard B, Burnett C, Sweeney CJ, Rider JR, Sridhar SS. Impact of age at diagnosis of de novo metastatic prostate cancer on survival. Cancer. 2019 Nov 26. PMID: 31769876.

    Bertrand KA, Bethea TN, Rosenberg L, Bandera EV, Khoury T, Troester MA, Ambrosone CB, Palmer JR. Risk factors for estrogen receptor positive ductal carcinoma in situ of the breast in African American women. Breast. 2019 Nov 06; 49:108-114. PMID: 31786415.

    Blevins CE, Grimone KR, Caviness CM, Stein MD, Abrantes AM. Categorizing Cannabis and Alcohol Use Patterns of Emerging Adults in Psychiatric Partial Hospitalization Treatment. J Psychiatr Pract. 2019 Nov; 25(6):491-498. PMID: 31821229.

    Bonawitz R, McGlasson KL, Kaiser JL, Ngoma T, Fong RM, Biemba G, Bwalya M, Hamer DH, Scott NA. Quality and utilization patterns of maternity waiting homes at referral facilities in rural Zambia: A mixed-methods multiple case analysis of intervention and standard of care sites. PLoS One. 2019; 14(11):e0225523. PMID: 31774838.

    Bor J, Thirumurthy H. Bridging the Efficacy-Effectiveness Gap in HIV Programs: Lessons From Economics. J Acquir Immune Defic Syndr. 2019 Dec; 82 Suppl 3:S183-S191. PMID: 31764253.

    Brennan AT, Maskew M, Ive P, Shearer K, Long L, Sanne I, Fox MP. Increases in regimen durability associated with the introduction of tenofovir at a large public-sector clinic in Johannesburg, South Africa. J Int AIDS Soc. 2013; 16:18794. PMID: 24256692.

    Brennan AT, Shearer K, Maskew M, Long L, Sanne I, Fox MP. Impact of choice of NRTI in first-line antiretroviral therapy: a cohort analysis of stavudine vs. tenofovir. Trop Med Int Health. 2014 May; 19(5):490-8. PMID: 24589363.

    Broder-Fingert S, Kuhn J, Sheldrick RC, Chu A, Fortuna L, Jordan M, Rubin D, Feinberg E. Using the Multiphase Optimization Strategy (MOST) framework to test intervention delivery strategies: a study protocol. Trials. 2019 Dec 16; 20(1):728. PMID: 31842963.

    Cabral KE, Rozanski EA, Cabral HJ, Buckley GJ. Does do not resuscitate (DNR) always mean DNR? Exploring DNR orders in small animal veterinary medicine. Can Vet J. 2019 Dec; 60(12):1331-1341. PMID: 31814641.

    Cerda Diez M, E Cortés D, Trevino-Talbot M, Bangham C, Winter MR, Cabral H, Norkunas Cunningham T, M Toledo D, J Bowen D, K Paasche-Orlow M, Bickmore T, Wang C. Designing and Evaluating a Digital Family Health History Tool for Spanish Speakers. Int J Environ Res Public Health. 2019 Dec 07; 16(24). PMID: 31817849.

    Connor BA, Dawood R, Riddle MS, Hamer DH. Cholera in travellers: a systematic review. J Travel Med. 2019 Dec 23; 26(8). PMID: 31804684.

    Cozier YC, Heaton B, Bethea TN, Freudenheim JL, Garcia RI, Rosenberg L. Predictors of self-reported oral health in the Black Women’s Health Study. J Public Health Dent. 2019 Dec 16. PMID: 31840825.

    Dennis EL, Disner SG, Fani N, Salminen LE, Logue M, Clarke EK, Haswell CC, Averill CL, Baugh LA, Bomyea J, Bruce SE, Cha J, Choi K, Davenport ND, Densmore M, du Plessis S, Forster GL, Frijling JL, Gonenc A, Gruber S, Grupe DW, Guenette JP, Hayes J, Hofmann D, Ipser J, Jovanovic T, Kelly S, Kennis M, Kinzel P, Koch SBJ, Koerte I, Koopowitz S, Korgaonkar M, Krystal J, Lebois LAM, Li G, Magnotta VA, Manthey A, May GJ, Menefee DS, Nawijn L, Nelson SM, Neufeld RWJ, Nitschke JB, O’Doherty D, Peverill M, Ressler KJ, Roos A, Sheridan MA, Sierk A, Simmons A, Simons RM, Simons JS, Stevens J, Suarez-Jimenez B, Sullivan DR, Théberge J, Tran JK, van den Heuvel L, van der Werff SJA, van Rooij SJH, van Zuiden M, Velez C, Verfaellie M, Vermeiren RRJM, Wade BSC, Wager T, Walter H, Winternitz S, Wolff J, York G, Zhu Y, Zhu X, Abdallah CG, Bryant R, Daniels JK, Davidson RJ, Fercho KA, Franz C, Geuze E, Gordon EM, Kaufman ML, Kremen WS, Lagopoulos J, Lanius RA, Lyons MJ, McCauley SR, McGlinchey R, McLaughlin KA, Milberg W, Neria Y, Olff M, Seedat S, Shenton M, Sponheim SR, Stein DJ, Stein MB, Straube T, Tate DF, van der Wee NJA, Veltman DJ, Wang L, Wilde EA, Thompson PM, Kochunov P, Jahanshad N, Morey RA. Altered white matter microstructural organization in posttraumatic stress disorder across 3047 adults: results from the PGC-ENIGMA PTSD consortium. Mol Psychiatry. 2019 Dec 19. PMID: 31857689.

    Dignard C, Leibler JH. Recent Research on Occupational Animal Exposures and Health Risks: A Narrative Review. Curr Environ Health Rep. 2019 Dec; 6(4):236-246. PMID: 31823248.

    Drainoni ML, Childs E, Biello KB, Biancarelli DL, Edeza A, Salhaney P, Mimiaga MJ, Bazzi AR. “We don’t get much of a voice about anything”: perspectives on photovoice among people who inject drugs. Harm Reduct J. 2019 Nov 27; 16(1):61. PMID: 31775757.

    Emrani S, Lamar M, Price CC, Wasserman V, Matusz E, Au R, Swenson R, Nagele R, Heilman KM, Libon DJ. Alzheimer’s/Vascular Spectrum Dementia: Classification in Addition to Diagnosis. J Alzheimers Dis. 73 (2020) 63–71. PMID: 31815693. Epub Dec 2, 2019.

    Epstein RL, Wang J, Hagan L, Mayer KH, Puro J, Linas BP, Assoumou SA. Hepatitis C Virus Antibody Testing Among 13- to 21-Year-Olds in a Large Sample of US Federally Qualified Health Centers. JAMA. 2019 12 10; 322(22):2245-2248. PMID: 31821424.

    Evans D, Berhanu R, Moyo F, Nguweneza A, Long L, Fox MP. Can Short-Term Use of Electronic Patient Adherence Monitoring Devices Improve Adherence in Patients Failing Second-Line Antiretroviral Therapy? Evidence from a Pilot Study in Johannesburg, South Africa. AIDS Behav. 2016 Nov; 20(11):2717-2728. PMID: 27146828.

    Evans L, Charns MP, Cabral HJ, Fabian MP. Change in geographic access to community health centers after Health Center Program expansion. Health Serv Res. 2019 Aug; 54(4):860-869. PMID: 30937888.

    Farooqui AA, Srivastava PN. Isolation, characterization and the role of rabbit testicular arylsulphatase A in fertilization. Biochem J. 1979 Aug 01; 181(2):331-7. PMID: 40545.

    Fonda JR, Gradus JL, Brogly SB, McGlinchey RE, Milberg WP, Fredman L. Traumatic Brain Injury and Opioid Overdose Among Post-9/11 Veterans With Long-Term Opioid Treatment of Chronic Pain. J Head Trauma Rehabil. 2019 Nov 08. PMID: 31834063.

    Fox MP, Ive P, Long L, Maskew M, Sanne I. High rates of survival, immune reconstitution, and virologic suppression on second-line antiretroviral therapy in South Africa. J Acquir Immune Defic Syndr. 2010 Apr 1; 53(4):500-6. PMID: 19838128.

    Frakt AB. Making Health Care More Productive. JAMA. 2019 Nov 7; 322(23):2274-2275. PMID: 31846006.

    Galea S. The Basic Criterion of Public Health. Milbank Q. 2019 Nov 25. PMID: 31763710.

    Gardiner P, Luo M, D’Amico S, Gergen-Barnett K, White LF, Saper R, Mitchell S, Liebschutz JM. Effectiveness of integrative medicine group visits in chronic pain and depressive symptoms: A randomized controlled trial. PLoS One. 2019 Dec 18; 14(12):e0225540. PMID: 31851666.

    Ghany MG, Marks KM, Morgan TR, Wyles DL, Aronsohn AI, Bhattacharya D, Broder T, Falade-Nwulia OO, Feld JJ, Gordon SC, Heller T, Jhaveri RR, Jonas MM, Kiser JJ, Linas BP, Lo Re V, Peters MG, Reddy KR, Reynolds A, Scott JD, Searson G, Spradling P, Terrault NA, Trooskin SB, Verna EC, Wong JB, Woolley AE, Workowski KA. Hepatitis C Guidance 2019 Update: AASLD-IDSA Recommendations for Testing, Managing, and Treating Hepatitis C Virus Infection. Hepatology. 2019 Dec 09. PMID: 31816111.

    Girdwood S, Govender K, Long L, Miot J, Meyer-Rath G. Primary healthcare delivery models for uninsured low-income earners during the transition to National Health Insurance: Perspectives of private South African providers. S Afr Med J. 2019 Sep 30; 109(10):771-783. PMID: 31635576.

    Gordon AR, Meyer IH. Gender nonconformity as a target of prejudice, discrimination, and violence against LGBT individuals. J LGBT Health Res. 2007; 3(3):55-71. PMID: 19042905.

    Gradus JL, Horváth-Puhó E, Jiang T, Rosellini AJ, Lash TL, Sørensen HT. Rates Of Suicide And Non-Fatal Suicide Attempts Among Persons Undergoing Organ Transplantation In Denmark From 1995 Through 2015. Clin Epidemiol. 2019; 11:1011-1013. PMID: 31819654.

    Gupta A, Feldman S, Perkins RB, Stokes A, Sankar V, Villa A. Predictors of dental care use, unmet dental care need, and barriers to unmet need among women: results from NHANES, 2011 to 2016. J Public Health Dent. 2019 12; 79(4):324-333. PMID: 31407356.

    Halaris AE, Belendiuk KT, Freedman DX. Antidepressant drugs affect dopamine uptake. Biochem Pharmacol. 1975 Oct 15; 24(20):1896-7. PMID: 19.

    Heiger-Bernays WJ, Tomsho KS, Basra K, Petropoulos ZE, Crawford K, Martinez A, Hornbuckle KC, Scammell MK. Human health risks due to airborne polychlorinated biphenyls are highest in New Bedford Harbor communities living closest to the harbor. Sci Total Environ. 2019 Nov 18; 135576. PMID: 31785914.

    Heinke D, Nestoridi E, Hernandez-Diaz S, Williams PL, Rich-Edwards JW, Lin AE, Van Bennekom CM, Mitchell AA, Nembhard WN, Fretts RC, Roberts DJ, Duke CW, Carmichael SL, Yazdy MM. Risk of Stillbirth for Fetuses With Specific Birth Defects. Obstet Gynecol. 2020 Jan; 135(1):133-140. PMID: 31809437.

    Hendrickson C, Moolla A, Maskew M, Long L, Fox MP, Sanne I, Majuba P, Pascoe S. “Even if you’re HIV-positive there’s life after if you take your medication”: experiences of people on long-term ART in South Africa: a short report. AIDS Care. 2019 Aug; 31(8):973-978. PMID: 30913899.

    Jamieson L, Evans D, Berhanu R, Ismail N, Aucock S, Wallengren K, Long L. Data quality of drug-resistant tuberculosis and antiretroviral therapy electronic registers in South Africa. BMC Public Health. 2019 Dec 05; 19(1):1638. PMID: 31805982.

    Jasuja GK, Ameli O, Reisman JI, Rose AJ, Miller DR, Berlowitz DR, Bhasin S. Health Outcomes Among Long-term Opioid Users With Testosterone Prescription in the Veterans Health Administration. JAMA Netw Open. 2019 Dec 02; 2(12):e1917141. PMID: 31825502.

    Kaiser JL, Fong RM, Ngoma T, McGlasson KL, Biemba G, Hamer DH, Bwalya M, Chasaya M, Scott NA. The effects of maternity waiting homes on the health workforce and maternal health service delivery in rural Zambia: a qualitative analysis. Hum Resour Health. 2019 Dec 04; 17(1):93. PMID: 31801578.

    Kim B, Bolton RE, Hyde J, Fincke BG, Drainoni ML, Petrakis BA, Simmons MM, McInnes DK. Coordinating across correctional, community, and VA systems: applying the Collaborative Chronic Care Model to post-incarceration healthcare and reentry support for veterans with mental health and substance use disorders. Health Justice. 2019 Dec 12; 7(1):18. PMID: 31832790.

    Kressin NR, Wormwood JB, Battaglia TA, Gunn CM. Differences in Breast Density Awareness, Knowledge, and Plans Based on State Legislation Status and Sociodemographic Characteristics. J Gen Intern Med. 2019 Dec 16. PMID: 31845108.

    Kuhn J, Sheldrick RC, Broder-Fingert S, Chu A, Fortuna L, Jordan M, Rubin D, Feinberg E. Simulation and minimization: technical advances for factorial experiments designed to optimize clinical interventions. BMC Med Res Methodol. 2019 Dec 16; 19(1):239. PMID: 31842765.

    Lapham G, Boudreau DM, Johnson EA, Bobb JF, Matthews AG, McCormack J, Liu D, Samet JH, Saxon AJ, Campbell CI, Glass JE, Rossom RC, Murphy MT, Binswanger IA, Yarborough BJH, Bradley KA. Prevalence and treatment of opioid use disorders among primary care patients in six health systems. Drug Alcohol Depend. 2019 Nov 15; 207:107732. PMID: 31835068.

    Lee SY, Cabral HJ, Aschengrau A, Pearce EN. Associations between Maternal Thyroid Function in Pregnancy and Obstetric and Perinatal Outcomes. J Clin Endocrinol Metab, dgz275. 2019 Dec 15. PMID: 31838502.

    Obisesan OH, Mirbolouk M, Osei AD, Orimoloye OA, Uddin SMI, Dzaye O, El Shahawy O, Al Rifai M, Bhatnagar A, Stokes A, Benjamin EJ, DeFilippis AP, Blaha MJ. Association Between E-Cigarette Use and Depression in the Behavioral Risk Factor Surveillance System, 2016-2017. JAMA Netw Open. 2019 Dec 02; 2(12):e1916800. PMID: 31800073.

    Pase MP, Himali JJ, Beiser AS, DeCarli C, McGrath ER, Satizabal CL, Aparicio HJ, Adams HHH, Reiner AP, Longstreth WT, Fornage M, Tracy RP, Lopez O, Psaty BM, Levy D, Seshadri S, Bis JC. Association of CD14 with incident dementia and markers of brain aging and injury. Neurology. 2019 Dec 09. pii: 10.1212/WNL.0000000000008682. PMID: 31818907.

    Smit RAJ, Trompet S, Leong A, Goodarzi MO, Postmus I, Warren H, Theusch E, Barnes MR, Arsenault BJ, Li X, Feng Q, Chasman DI, Cupples LA, Hitman GA, Krauss RM, Psaty BM, Rotter JI, Cessie SL, Stein CM, Jukema JW. Statin-induced LDL cholesterol response and type 2 diabetes: a bidirectional two-sample Mendelian randomization study. Pharmacogenomics J. 2019 Dec 05. PMID: 31801993.

    Volgman AS, Bairey Merz CN, Benjamin EJ, Curtis AB, Fang MC, Lindley KJ, Pepine CJ, Vaseghi M, Waldo AL, Wenger NK, Russo AM. Sex and Race/Ethnicity Differences in Atrial Fibrillation. J Am Coll Cardiol. 2019 Dec 03; 74(22):2812-2815. PMID: 31779796.

    Ulrich MR. Revisionist History? Responding to Gun Violence Under Historical Limitations. American Journal of Law & Medicine. 2019 Nov. 13; 188-201. PMID: 31722627.

    Ulrich MR. A Public Health Approach to Gun Violence, Legally Speaking. Journal of Law, Medicine, & Ethics. 2019 July 12, 112-15. PMID: 31298120.

    Walkey AJ, Bor J, Cordella NJ. Novel tools for a learning health system: a combined difference-in-difference/regression discontinuity approach to evaluate effectiveness of a readmission reduction initiative. BMJ Qual Saf. 2019 Dec 16. PMID: 31843880.

    Wang B, Lunetta K, Dupuis J, Lubitz SA, Trinquart L, Yao L, Ellinor PT, Benjamin EJ, Lin H. Integrative Omics Approach to Identifying Genes Associated with Atrial Fibrillation. Circ Res. 2019 Dec 05. PMID: 31801406.

    Weinstein G, Davis-Plourde KL, Beiser AS, Seshadri S. Author response: Non-alcoholic fatty liver disease, liver fibrosis score and cognitive function in middle-aged adults: The Framingham study. Liver Int. 2019 Dec 18. PMID: 31850659.

    Yih WK, Kulldorff M, Leibler JH, Friedman DJ, Brooks DR. Comment on Sarathkumara et al.: Exposure to Hantavirus is a Risk Factor Associated with Kidney Diseases in Sri Lanka: A Cross Sectional Study. Viruses. 2019 Dec 11; 11(12). PMID: 31835714.


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  • Race and Medicine: The Harm That Comes From Mistrust

    The following originally appeared on The Upshot (copyright 2020, The New York Times Company). It also appeared on page B5 of the print edition on January 14, 2020.

    Racial discrimination has shaped so many American institutions that perhaps it should be no surprise that health care is among them. Put simply, people of color receive less care — and often worse care — than white Americans.

    Reasons includes lower rates of health coverage; communication barriers; and racial stereotyping based on false beliefs.

    Predictably, their health outcomes are worse than those of whites.

    African-American patients tend to receive lower-quality health services, including for cancer, H.I.V., prenatal care and preventive care, vast research shows. They are also less likely to receive treatment for cardiovascular disease, and they are more likely to have unnecessary limb amputations.

    As part of “The 1619 Project,” Evelynn Hammonds, a historian of science at Harvard, told Jeneen Interlandi of The New York Times: “There has never been any period in American history where the health of blacks was equal to that of whites. Disparity is built into the system.”

    African-American men, in particular, have the worst health outcomes of any major demographic group. In part, research shows, this is a result of mistrust from a legacy of discrimination.

    At age 45, the life expectancy of black men is more than three years less than that of non-Hispanic Caucasian men. According to a study in the Quarterly Journal of Economics, part of the historical black-white mortality difference can be attributed to a 40-year experiment by the U.S. Public Health Service that shook African-Americans’ confidence in the nation’s health system.

    From 1932 to 1972, the Public Health Service tracked about 600 hundred low-income African-American men in Tuskegee, Ala., about 400 of whom had syphilis. The stated purpose was to better understand the natural course of the disease. To do so, the men were lied to about the study and provided sham treatments. Many needlessly passed the disease on to family members, suffered and died.

    As one scholar put it, the Tuskegee study “revealed more about the pathology of racism than it did about the pathology of syphilis.” In fact, the natural course of syphilis was already largely understood.

    The study was publicized in 1972 and immediately halted. To this day, it is frequently cited as a driver of documented distrust in the health system by African-Americans. That distrust has helped compromise many public health efforts — including those to slow the spread of H.I.V., contain tuberculosis outbreaks and broaden provision of preventive care.

    According to work by the economists Marcella Alsan and Marianne Wanamaker, black men are less likely than white men to seek health care and more likely to die at younger ages. Their analysis suggests that one-third of the black-white gap in male life expectancy in the immediate aftermath of the study could be attributed to the legacy of distrust connected to the Tuskegee study.

    Their study relies on interpreting observational data, not a randomized trial, so there is room for skepticism about the specific findings and interpretation. Nevertheless, the findings are consistent with lots of other work that reveals African-Americans’ distrust of the health system, their receipt of less care, and their worse health outcomes.

    The Tuskegee study is far from the only unjust treatment of nonwhite groups in health care. Thousands of nonwhite women have been sterilized without consent. For instance, between the 1930s and 1970s, one-third of Puerto Rican women of childbearing age were sterilized, many under coercion.

    Likewise, in the 1960s and 1970s, thousands of Native American women were sterilized without consent, and a California eugenics law forced or coerced thousands of sterilizations of women (and men) of Mexican descent in the 20th century. (Thirty-two other states have had such laws, which were applied disproportionately to people of color.)

    For decades, sickle cell disease, which mostly affects African-Americans, received less attention than other diseases, raising questions about the role of race in how medical research priorities are established.

    Outside of research, routine medical practice continues to treat black and white patients differently. This has been documented in countless ways, including how practitioners view pain. Racial bias in health care and over-prescription of opioid painkillers accidentally spared some African-Americans from the level of mortality from opioid medications observed in white populations.

    “While African-Americans may not have died at similar rates from opioid misuse, we can be sure needless suffering and, perhaps even death, occurred because provider racism prevented them from receiving appropriate care and pain medication,” said Linda Goler Blount, president and chief executive of the Black Women’s Health Imperative.

    Of course, health outcomes are a result of much more than health care. The health of people of color is also unequal to that of whites because of differences in health behaviors, education and income, to name a few factors. But there is no doubt that the health system plays a role, too. Nor is there question that a history of discrimination and structural racism underlies racial differences in all these drivers of health.

    Reinforcing the fact of racial bias in health care, a recent study found that care for black patients is better when they see black doctors. The study randomly assigned 1,300 African-Americans to black or nonblack primary care physicians. Those who saw black doctors received 34 percent more preventive services. One reason for this, supported by the study, is increased trust and communication.

    The study findings are large. If all black men received the same increase in preventive services as those in the study (and received appropriate follow-up care), it would reduce the black-white cardiovascular mortality rate by 19 percent and shrink the total black-white male life expectancy gap by 8 percent, the researchers said.

    But it is unlikely all black men could see black doctors even if they wished to. Although African-Americans make up 13 percent of the U.S. population, only 4 percent of current physicians — and less than 7 percent of recent medical school graduates — are black.

    This study does not stand alone. A systematic review found that racially matched pairs of patients and doctors achieved better communication. Other studies found that many nonwhite patients prefer practitioners who share their racial identity and that they receive better care from them. They view them as better than white physicians in communicating, providing respectful treatment and being available.

    Racial bias in health care, as in other American institutions, is as old or older than the republic itself.

    Title VI of the 1964 Civil Rights Act stipulates that neither race, color nor national origin may be used as a means of denying the “benefits of, or be subjected to discrimination under any program or activity receiving federal financial assistance.” As nearly every facet of the American health system receives federal financing and support, well-documented and present-day discrimination in health care suggests the law has not yet had its intended effect.


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  • Do We Need New Calorie Labels?

    There’s a lot of media attention on a recent study examining whether labeling food with the amount of exercise that would be needed to then burn it off changes how much people eat. Let’s dig in and see.



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  • Deflating Results of Major Study Point to Better Ways to Cut Health Care Waste

    The following originally appeared on The Upshot (copyright 2020, The New York Times Company). 

    Research has established that as much as a quarter of American health spending is waste.

    There are two basic ways of tackling it, by focusing narrowly on specific types of patients or on the system as a whole. The patient-centered approach starts with this fact: A relatively small group of patients — 5 percent — account for half of all health spending.

    It’s widely believed that making so-called super-utilizers even a little healthier — for example, giving them extra help once they’re out of the hospital to prevent a quick return there — would yield substantial savings. This idea, based on some weak evidence, has received considerable media attention and government support.

    A rigorous study, published Wednesday, makes clear it’s not so easy. In fact, the study’s results are likely to be viewed by many as a major disappointment. Yet they also help guide us to what may be better strategies for cutting waste.

    The study, published in the New England Journal of Medicine, was a big test of the people-focused approach: a randomized trial of a program in Camden, N.J., to reduce super-utilizer spending. About 800 very sick patients were randomly assigned into the program or to usual care. (The program has since expanded to other cities.)

    To try to avoid a repeat hospitalization, the program provided an unusually large amount of care to very sick patients after they left the hospital, including from registered nurses, social workers, licensed practical nurses, community health workers and health coaches.

    In the three months after a hospital stay, an average patient in the program received 7.6 home visits and 8.8 phone calls from staff. In addition, program staff went along on patients’ visits to physicians, which averaged 2.5 per person.

    The result of all this effort?

    For the six months after randomization, patients in the treatment and control groups had about the same chance of returning to the hospital, the same number of return hospital visits, the same amount of time spent in the hospital over all, and the same hospital costs. (It’s possible these measures differed across groups in small ways the study wasn’t large enough to detect.)

    That doesn’t mean it’s impossible to reduce readmissions or health care spending of targeted patients. Some previous randomized evaluations of other programs have found reductions in hospital readmissions of 15 percent to 45 percent, and in some cases reduced spending.

    But it’s important to understand the difference between those studies and the Camden one.

    “The Camden model targets a population that has a much more varied set of medical needs and social complexity, and with higher health care spending, than the existing successful models,” said Amy Finkelstein, a health economist at M.I.T. and a co-author of the Camden study.

    The other approach to fighting wasteful medical spending starts with looking at health care as a system of goods and services: medications and surgical procedures, administrative processes and physical infrastructure. Some of these enhance health and others don’t, while some of it costs more than its benefits warrant. If you can identify wasteful goods and services and deliver effective care at lower prices, you can make the system more efficient for everyone.

    This idea is behind many policies that change how Medicare pays for care.

    One advantage of the systemic approach is that it’s easier to replicate than programs focused on super-utilizers. If eliminating or replacing a drug, procedure or administrative process means that spending at a hospital goes down, it’s relatively simple to adopt that change at other hospitals. But conceptually simple doesn’t mean easy in practice.

    “Directly and systematically reducing wasteful care is hard because the most successful strategies threaten the revenue of dominant health care providers,” said Michael McWilliams, a professor at Harvard Medical School and a general internist with Brigham and Women’s Hospital. “One person’s waste is another’s income.”

    This may be why big health systems are resistant to systemic change and prefer patient-focused approaches. Dr. McWilliams and Aaron Schwartz, a resident at Brigham and Women’s Hospital, wrote a commentary in the New England Journal of Medicine arguing in favor of a systems view of cost cutting. A focus only on the relatively few high spenders could miss a lot of waste, it said. Even though the rest of the population may use less care than super-utilizers, collectively they could account for as much or more waste.

    Another concern is that when cuts are made to health spending, patients could receive lower-quality care and might have worse experiences. Cutting waste without harming quality is hard but not impossible. Some Medicare programs and private insurer initiatives in recent years have succeeded in doing so, if only a little.

    The people-focused approach, on the other hand, is more likely to improve some patients’ experience because it involves additional preventive care. This could manifest itself as less pain or anxiety, and more “satisfaction” with care. But saving money this way requires accurate predictions of who is likelier to use a disproportionately large amount of health care. We don’t yet know how to reliably do this for enough people to make the approach efficient.

    “The prevention myth is that it necessarily saves money,” said Sherry Glied, a health economist and dean and professor at the Wagner School of Public Service at N.Y.U. “Usually you need to provide preventive services to many people to avoid one bad outcome, and that makes it more expensive over all, even if it is better care.”

    In a commentary on the Health Affairs blog, she also points out that high-cost patients are not all alike. They require different mixes of services to avoid costly outcomes. That calls for a lot of fine-tuning, which itself costs money and poses coordination challenges. It’s also harder to replicate.

    The Camden study, unfortunately, did not measure patient experience, which might have improved. If patients did better in some ways and at no statistically significant additional cost, that could make its efforts worthwhile, even cost-effective.

    That’s what an exclusive focus on reducing spending misses. The answer isn’t necessarily to pick a patient- or system-focused approach to reforming health care, but to do both effectively.


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  • Third thought on “So you want to talk about race,” by Ijeoma Oluo

    This post includes my third thought about selected passages of “So you want to talk about race,” by Ijeoma Oluo. All posts in this series are here.

    In several chapters Oluo asks the reader what his or her goals are. In chapter two, “What is racism?” she wrote, “[W]hy are you here?” meaning what do you expect from her book? In chapter three, “What if I talk about race wrong?” she wrote, “Do you know why this matters to you?” meaning why do you want to have a particular race-related discussion?

    These are excellent questions, particularly for white people. They can also be turned around and posed as, “Why are you not here?” and “Do you know why this doesn’t matter to you?” (if indeed it doesn’t, or not so much).

    That’s more confrontational, perhaps good for getting people’s attention. Do I have yours?

    As advised in my first thought post, hold your quick response and actually let these questions sink in. The direction I’d like your mind to go, and the direction my mind is going, is toward exploring what accounts for a white person’s degree of interest in and engagement on race, or lack thereof. As I have best access to my own mind and experience, I will apply this inquiry to myself.

    Before I do, I should stop to assess whether this is tantamount to turning the deeply problematic issues around race to being about me (see my second thought, cautioning against just that). I think the answer is, “no.” This isn’t making racial issues about me. This is itself an important racial issue. It matters a lot how much white people engage in addressing racism. It’s a problem we created and perpetuate! Therefore, it is worth pondering what governs the extent we do so.

    As evidenced by these posts, my interest in racism has dramatically increased recently. Why was it lower before, and why has it increased? I cannot answer definitively, but I can point to factors I think are relevant and generalizable.

    First, there’s the background truth that white people are privileged to be able to avoid consciously focusing on racism. We had and have the power to set things up so we don’t have to. Contrary to claims of reverse racism, we don’t live in a society full of institutions and cultural norms that discriminate against white people. We don’t have 400 years of history of being oppressed.

    Instead, the world we inhabit is, by and large, created by us and for us (and if not us, literally, by our white ancestors). We white people are the beneficiaries of that. In contrast to the experiences of people of color, racism is very rarely thrust upon us and certainly not daily.

    So, one part of why I could be less focused on racism in the past is because I am white. To the extent I noticed racism, I did not have to deal with it because it did not negatively affect my daily life. It wasn’t a problem I needed to solve just to be comfortable in the world. This is obviously generalizable to other white people. I think it’s inherent in being white in America.

    That is not to say I didn’t care about racism or that other white people don’t. I did and others do. But I cared in a way that didn’t matter very much, if at all, to anyone but me. My caring was merely a story about myself I told myself. It didn’t extend very far beyond myself.

    Only white people can do that about racism. We get to tell ourselves our own story about what it means to us. People of color do not entirely own the story of racism. They can’t choose to enter or leave it. White people have a choice.

    This may explain why I could pay less attention to racism in the past but does not explain exactly why I did so then and what changed to cause me to focus more on it now. Here I have few good answers. However, one big thing that changed was becoming more educated, which is an ongoing process. I’m not done. (In this regard, let me recommend Oluo’s book and also the Seeing White podcast series, the New York Times 1619 Project, and White Fragility, which also is in book length though I have not read the longer version.)

    Getting educated is clearly generalizable. Other people can do it. But they need to choose to do it. Why did I choose? Beyond saying that it interested me, I don’t know.

    And why did the education have an impact? Part of the answer is that white privilege (and the converse, discrimination of people of color) makes me uncomfortable — not discussing it, but that it exists. The more I understand injustice the less I am able to implicitly choose to accept it by choosing to ignore it, as I once, mostly did. Maybe the generalizable fact here is that many white people will only pay more attention to racism if it becomes too uncomfortable for them not to. Becoming educated is not the only route to discomfort and may not be an effective route for everyone.

    I’ll wrap up with a really big question that I won’t answer here. I may, perhaps, try to do so in another post in this series if I figure out how. Oluo ends her book with a call to action. Enough with talk, do something! My question to myself is: about racism, what actions will I take?


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