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Racism and Health: Evidence and Needed Research

David r williams, jourdyn lawrence, brigette davis.

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Address correspondence to David R. Williams, Harvard T. H. Chan School of Public Health, 677 Huntington Avenue, 6 th floor, Boston, MA 02115 ( [email protected] )

Issue date 2019 Apr 1.

In recent decades, there has been remarkable growth in scientific research examining the multiple ways in which racism can adversely affect health. This interest has been driven in part by the striking persistence of racial/ethnic inequities in health and the empirical evidence that indicates that socioeconomic factors alone do not account for racial/ethnic inequities in health. Racism is considered a fundamental cause of adverse health outcomes for racial/ethnic minorities and racial/ethnic inequities in health. This article provides an overview of the evidence linking the primary domains of racism – structural racism, cultural racism and individual-level discrimination – to mental and physical health outcomes. For each mechanism, we describe key findings and identify priorities for future research. We also discuss evidence for interventions to reduce racism and needed research to advance knowledge in this area.

There has been steady and sustained growth in scientific research on the multiple ways in which racism can affect health and racial/ethnic inequities in health. This article provides an overview of key findings and trends in this area of research. It begins with a description of the nature of racism and the principal mechanisms -- structural, cultural and individual -- by which racism can affect health. For each dimension, we review key research findings and describe needed scientific research. We also discuss evidence for interventions to reduce racism and needed research to advance knowledge in this area. Finally, we discuss crosscutting priorities across the three domains of racism.

The patterning of racial/ethnic inequities in health was an early impetus for research on racism and health ( 139 ). First, there are elevated rates of disease and death for historically marginalized racial groups, blacks (or African Americans), Native Americans (or American Indians and Alaska Natives) and Native Hawaiians and Other Pacific Islanders, who tend to have earlier onset of illness, more aggressive progression of disease and poorer survival ( 5 , 134 ). Second, empirical analyses revealed the persistence of racial differences in health even after adjustment for socioeconomic status (SES). For example, at every level of education and income, African Americans have lower life expectancy at age 25 than whites and Hispanics (or Latinos), with blacks with a college degree or more education having lower life expectancy than whites and Hispanics who graduated from high school ( 15 ). Third, research has also documented declining health for Hispanic immigrants over time with middle-aged U.S.-born Mexican Americans and Mexican immigrants resident 20 or more years in the U.S. having a health profile that did not differ from that of African Americans ( 56 ).

Racism and Health

Racism is an organized social system, in which the dominant racial group, based on an ideology of inferiority, categorizes and ranks people into social groups called “races”, and uses its power to devalue, disempower, and differentially allocate valued societal resources and opportunities to groups defined as inferior ( 13 , 140 ). Race is primarily a social category, based on nationality, ethnicity, phenotypic or other markers of social difference, which captures differential access to power and resources in society ( 133 ). Racism functions on multiple levels. The cultural agencies within a society socializes the population to accept as true the inferiority of non-dominant racial groups leading to negative normative beliefs (stereotypes) and attitudes (prejudice) toward stigmatized racial groups which undergird differential treatment of members of these groups by both individuals and social institutions ( 13 , 140 ). A characteristic of racism is that its structure and ideology can persist in governmental and institutional policies in the absence of individual actors who are explicitly racially prejudiced ( 7 ).

As a structured system, racism interacts with other social institutions, shaping them and being re-shaped by them, to reinforce, justify and perpetuate a racial hierarchy. Racism has created a set of dynamic, interdependent, components or subsystems that reinforce each other, creating and sustaining reciprocal causality of racial inequities across various sectors of society ( 106 ). Thus, structural racism exists within, and is reinforced and supported by multiple societal systems, including the housing, labor and credit markets, and the education, criminal justice, economic and healthcare systems. Accordingly, racism is adaptive over time, maintaining its pervasive adverse effects through multiple mechanisms that arise to replace forms that have been diminished ( 99 , 140 ).

Racism: A Fundamental Cause of Racial/Ethnic Inequities in Health

The persistence of racial inequities in health should be understood in the context of relatively stable racialized social structures that determine differential access to risks, opportunities, and resources that drive health. We conceptualize this system of racism, chiefly operating through institutional and cultural domains, as a basic or fundamental cause of racial health inequalities ( 74 , 99 , 133 , 136 ). According to Lieberson, fundamental causes are critical causal factors that generate an outcome while surface causes are associated with the outcome but changes in these factors do not trigger changes in the outcome ( 73 ). Instead, as long as the fundamental causes are operative, interventions on surface causes only give rise to new intervening mechanisms to maintain the same outcome. Sociologists argued that socioeconomic status (SES) is a fundamental cause of health ( 53 , 132 ), with Link and colleagues ( 74 , 100 ) providing considerable evidence in support of this perspective. In 1997, Williams argued that alongside SES and other upstream social factors, racism should be recognized as a fundamental cause of racial inequities in health ( 133 ). Evidence continues to accumulate highlighting racism as a driver of multiple upstream societal factors that perpetuate racial inequities in health for multiple non-dominant racial groups around the world ( 99 , 140 ).

Structural or Institutional Racism

We use the terms institutional and structural racism, interchangeably, consistent with much of the social science literature ( 13 , 55 , 106 ). Institutional racism refers to the processes of racism that are embedded in laws (local, state, and federal), policies, and practices of society and its institutions that provide advantages to racial groups deemed as superior, while differentially oppressing, disadvantaging, or otherwise neglecting racial groups viewed as inferior ( 13 , 104 ). We argue that the most important way through which racism affects health is through structural racism. We highlight evidence of the health impact of residential segregation but acknowledge that there are multiple other forms of institutional racism in society. For example, structural racism in the Criminal Justice System ( 84 , 130 , 142 ) can adversely affect health through multiple pathways ( 37 , 130 ).

Racial Residential Segregation

Racial residential segregation remains one of the most widely studied institutional mechanisms of racism and has been identified as a fundamental cause of racial health disparities due to the multiple pathways through which it operates to have pervasive negative consequences on health ( 7 , 38 , 60 , 136 ). Racial residential segregation refers to the occupancy of different neighborhood environments by race that was developed in the U.S. to ensure that whites resided in separate communities from blacks. Segregation was created by federal policies as well as explicit governmental support of private policies such as discriminatory zoning, mortgage discrimination, red-lining and restrictive covenants ( 107 ). This physical separation of races in distinctive residential areas (including the forced removal and relocation of American Indians) was shaped by multiple social institutions ( 83 , 136 ). Although segregation has been illegal since the Fair Housing Act of 1968, its basic structures established by the 1940s remain largely intact.

In the 2010 Census, residential segregation was at its lowest level in 100 years and the decline in segregation was observed in all of the nation’s largest metropolitan areas ( 43 ). However, the recent declines in segregation have been driven by a few blacks moving to formerly all-white residential areas with the declines in segregation having negligible impact on the very high percentage black census tracts, the residential isolation of most African-Americans, and the concentration of urban poverty ( 44 ). Although segregation is increasing for Hispanics, the segregation of African Americans remains distinctive. In the 2000 census middle class blacks were more segregated than poor Hispanics and Asians ( 81 ), and the segregation of immigrant groups has never been as high as the current segregation of African Americans ( 83 ).

Segregation and Health: Pathways

Segregation affects health in multiple ways ( 136 ). First, it is a critical determinant of SES, which is a strong predictor of variations in health. Research has found that segregation reduces economic status in adulthood by reducing access to quality elementary and high school education, preparation for higher education, and employment opportunities ( 136 ). Schools in segregated areas have lower levels of high-quality teachers, educational resources, per-student spending and higher levels of neighborhood violence, crime and poverty ( 91 ). Segregation also reduces access to employment opportunities by triggering the movement of low skill, high pay jobs from areas where racial minorities are concentrated to other areas and by enabling employers to discriminate against job applicants by using their place of residence as a predictor of whether or not the applicant would be a good employee ( 136 ) One national study found that the elimination of segregation would erase black-white differences in income, education and unemployment and reduce racial differences in single motherhood by two-thirds ( 28 ). Thus, segregation is responsible for the large and persistent racial/ethnic differences in SES. In 2016, for every dollar of income that white households received, Hispanics earned 73 cents and blacks earned 61 cents ( 110 ). And racial differences in health are stunningly larger. For every dollar of wealth that white households have, Hispanics have 7 pennies, and blacks have 6 pennies ( 120 ).

Segregation can also adversely affect health by creating communities of concentrated poverty with high levels of neighborhood disadvantage, low quality housing stock, and with both government and private sector demonstrating disinterest or divestment from these communities. In turn, the physical conditions (poor quality housing and neighborhood environments) and the social conditions (co-occurrence of social problems and disorders linked to concentrated poverty) that characterize segregated geographic areas lead to elevated exposure to physical and chemical hazards, increased prevalence and co-occurrence of chronic and acute psychosocial stressors, as well as, reduced access to a broad range of resources that enhance health ( 60 , 87 , 128 , 136 ). The living conditions created by concentrated poverty and segregation make it more difficult for residents of those contexts to practice healthy behaviors ( 7 , 60 , 128 , 136 ). Segregation also adversely affects the availability and affordability of care, contributing to lower access to high quality primary and specialty care and even pharmacy services ( 129 ).

Epidemiological Evidence Linking Segregation to Health

A 2011 review found nearly 50 empirical studies which generally found that segregation was associated with poorer health ( 128 ). A 2017 review and meta-analysis focused on 42 articles that examined the association between segregation and birth outcomes found that segregation was associated with increased risk of low birth rate weight and preterm birth for blacks ( 85 ). Other recent studies show that segregation is associated with increased risk of preterm birth for U.S.-born and foreign-born black women ( 79 ) and of stillbirth for blacks and whites, with the effects being more pronounced for blacks than for whites ( 131 ). A systematic review of 17 papers examining segregation and cancer, found that segregation was positively associated with later-stage diagnosis, elevated mortality and lower survival rates for both breast and lung cancers for blacks ( 65 ). Recent studies highlight variation in the association between segregation and health for population subgroups. One national study found that segregation was associated with poor self-rated health for blacks in high but not lower poverty neighborhoods ( 31 ). It was unrelated to poor health for whites but benefited whites indirectly by reducing the likelihood of their location in high poverty neighborhoods ( 31 ). And a 25 year longitudinal study found that cumulatively higher exposure to segregation was associated with elevated risk of incident obesity in black women but not black men ( 101 ).

Recommendations for Research on Institutional Racism

Several strategies should be implemented to further understanding of how institutional racism adversely affects health. First, there is a need to broaden our conceptualization and assessment of the multiple domains and contexts in which these structural processes are operative and empirically assess their impact on health. In a study of structural racism and myocardial infarction, Lukachko and colleagues ( 75 ) utilized four state-level measures of structural racism: political participation, employment, education and judicial treatment. The analyses revealed that state level racial disparities that disadvantaged blacks in political representation, employment and incarceration were associated with increased risk of MI in the prior year. Among whites, structural racism was unrelated to or had a beneficial effect on the risk of MI.

Second, immigration policy has been identified as a mechanism of structural racism ( 38 ) and systematic attention should be given to understanding how contemporary immigration policies adversely affect population health. Recent research suggests that anti-immigrant policies can trigger hostility toward immigrants leading to perceptions of vulnerability, threat, and psychological distress for both those who are directly targeted and those who are not ( 46 ). One study found that a large federal immigration raid was associated with an increase in low birthweight risk among infants born to Latina but not white mothers in that community a year after the raid ( 90 ). Immigration polices can also adversely affect health by leading to reduced utilization of preventive health services by both documented and undocumented immigrants ( 80 , 117 , 127 ).

Third, some of the methodological limitations of the current literature need to be addressed. Research on structural racism has been limited by the availability of data on structural levels and ecological analyses are limited in capturing the underlying processes. The available evidence suggests that the associations between segregation and health tend to vary based on the choice of a geographic unit of analysis ( 7 , 38 , 60 , 128 ). While smaller units tend to produce the most reliable estimates, the appropriate geographic level may not be consistent across all health outcomes. These analytic challenges are further exacerbated by difficulties disentangling the potential mediating and moderating effects that contribute to observed patterns. Many studies adjust for variables like poverty or other indicators of low SES and the social context which are likely a part of the pathway by which segregation exerts its effects ( 60 , 128 ). Future research needs to identify the proximal mechanisms linking segregation to health by using longitudinal data to establish temporality, and leveraging new statistical techniques ( 60 , 128 ). There is also a need for more complex system modeling approaches that seek to capture the impact of all of the dynamic historical processes that influence each other over time, at multiple levels of analysis ( 30 , 92 ).

Fourth, greater attention should be given to similarities and differences across national and cultural contexts. For example, segregation levels are rising in Europe and are positively associated with darker skinned nationalities and being Muslim but there has been little analysis of the effects of this segregation on SES and health ( 82 ). A study that compared a national sample of Caribbean blacks in the U.S. to those in the U.K. found that, in the U.S., increased black Caribbean ethnic density was associated with improved health while increased black ethnic density was associated with worse health but the opposite pattern was evident for Caribbean blacks in England ( 10 ). Comparative research could enhance our understanding of the contextual factors such as variation in the racialization of ethnic groups that could contribute to the observed associations.

Finally, we need a better understanding of the conditions under which group density can have positive versus adverse effects on health ( 86 ). A national study of Hispanics found that segregation was adversely related to poor self-rated health among US born Hispanics but it had a salutary effect on the health of the foreign-born ( 32 ). We need a clearer understanding of when and how segregation can give rise to health enhancing versus health damaging factors.

Cultural Racism

Cultural racism refers to the instillation of the ideology of inferiority in the values language, imagery, symbols and unstated assumptions of the larger society. It creates a larger ideological environment where the system of racism can flourish, and can undergird both institutional and individual level discrimination. It manifests itself through media, stereotyping and within institutions, and norms ( 49 , 140 ). It can yield inconspicuous forms of racism, such as implicit bias, as a result of the commonplace and continuous negative imagery about racial and ethnic minorities ( 140 ). Cultural forms of racism may serve as the conduit through which views regarding the limitations, stereotypes, values, images and ideologies associated with racial/ethnic minority groups are presented to society, and are consciously or subconsciously adopted and normalized ( 105 , 113 ).

The internalization of racism yields a tendency to focus on individual pathology and abilities rather than examining structural components that give rise to racial inequities. This internalization affects most members of the dominant group and a nontrivial proportion of the marginalized group as well, given that both groups are exposed to key socializing agents of the larger society that perpetuate racist beliefs ( 105 ). Research indicates that negative racial and ethnic stereotypes persist in entertainment, media, and fashion ( 18 , 140 ). A recent national survey of adults who work with children found that whites had high levels of negative racial stereotypes (lazy, unintelligent, violent and having unhealthy habits) towards non-whites, with the highest levels towards blacks followed by Native Americans and Hispanics ( 103 ).

Cultural Racism and Health

Cultural racism can affect health in multiple ways. First, cultural racism can drive societal policies that lead to the creation and maintenance of structures that provide differential access to opportunities ( 140 ). For example, a study of white residents revealed that their negative stereotypes about blacks influenced their housing decisions in ways that would maintain residential segregation ( 64 ). In this study whites rated an all-white neighborhood more positively (on the cost of housing, safety, future property value, and quality of schools) than an identical neighborhood if a black person were pictured in it.

Second, cultural racism can also lead to individual level unconscious bias that can lead to discrimination against outgroup members. In clinical encounters, these processes lead to minorities receiving inferior medical care compared to whites. Research indicates that across virtually every type of diagnostic and treatment interventions blacks and other minorities receive fewer procedures and poorer quality medical care than whites ( 112 ). Recent research documents the persistence of these patterns and reveals that higher implicit bias scores among physicians are associated with biased treatment recommendations in the care of black patients ( 123 ). Providers’ implicit bias is also associated with poorer quality of patient provider communication including provider nonverbal behavior ( 25 ).

Stereotype threat is a third pathway. This term refers to the anxieties and expectations that can be activated in stigmatized groups when negative stereotypes about their group are made salient. These anxieties can adversely affect academic performance and psychological functioning ( 114 ). Some limited evidence indicates that stereotype threat can lead to increased anxiety, reduced self-regulation and impaired decision-making that can lead to unhealthy behaviors, poor patient-provider communication, lower levels of adherence to medical advice, increased blood pressure and weight gain among stigmatized groups ( 6 , 114 , 141 ). Relatedly, a study documented that exposure of American Indian students to Native American mascots, leads to declines in self-esteem, community worth and achievement aspirations ( 35 ). Fourth, as noted, some members of stigmatized racial populations respond to the pervasive negative racial stereotypes in the culture by accepting them to be true. This endorsement of the dominant society’s beliefs about their inferiority is called internalized racism or self-stereotyping. Research indicates that it is associated with lower psychological well-being and higher levels of alcohol consumption, depressive symptoms and obesity ( 139 ).

Recommendations for Research on Cultural Racism

Future research should aim to understand how and why cultural racism, when it is measured as elevated levels of racial prejudice at the community level, is associated with poorer health for racial minorities, and sometimes all persons, who live in that community. Recent studies have found that residing in communities with high levels of racial prejudice is positively associated with overall mortality ( 20 , 67 ), heart disease mortality ( 68 ), and low birthweight ( 21 ). Community-level prejudice against immigrants has also been associated with increased mortality among US-born immigrant adults ( 89 ). However, these studies are ecological in nature and lack adjustment for individual-level factors

Second, we need to better understand how internalized racism can affect health. There is limited understanding of the conditions under which internalized racism has adverse consequences for health, the groups that are most vulnerable, and the range of health and health-related outcomes that may be affected ( 140 ). The optimal measurement of internalized racism is also a challenge. Studies have used scales of internalized racism, minority group endorsement of negative stereotypes and African Americans’ scores on anti-black bias on the IAT. It is currently unclear how these measures correlate with each other and the extent to which they may capture different aspects of internalized racism. Beyond the individual, future work should also examine internalized racism in a more collective form that could facilitate understanding of the cultural and structural pervasiveness of racism at the societal level racial ( 105 ). Research should also assess if and how racist ideologies and oppression become internalized among immigrants in the United States and how these are associated with health outcomes.

Discrimination

Discrimination is the most frequently studied domain of racism in the health literature. It exists in two forms: 1) where individuals and larger institutions, deliberately or without intent, treat racial groups differently, resulting in inequitable access to opportunities and resources (e.g., employment, education, and medical care) by race/ethnicity, and 2) self-reported discrimination, a sub-set of these experiences that individuals are aware of. These latter incidents are a type of stressful life experience that can adversely affects health, similar to other kinds of psychosocial stressors. Considerable scientific evidence, supports of the first pathway, much of it captured through audit studies (those in which researchers use individuals who are equally qualified in every respect but differ only in race or ethnicity) that document the persistence of discrimination in many contexts including employment, education, housing, credit, and criminal justice systems ( 93 ). This discrimination in social institutions contributes to the differential access to resources and opportunities and results in SES and other material disadvantages.

A large proportion of the discrimination literature focuses on the second pathway with the evidence indicating that stigmatized racial and ethnic populations and other socially marginalized groups around the world report experiences of discrimination that are inversely related to good health ( 109 , 139 , 140 ). Researchers refer to these experiences as self-reported discrimination, perceived discrimination, and racial discrimination, and we use these terms interchangeably. Self-reports of discrimination can adversely affect health through triggering negative emotional reactions that can lead to altered physiological reactions and changes in health behaviors, that can increase the risk of poor health ( 41 ). We highlight key patterns and trends in this research on discrimination and health.

A 2015 meta-analysis assessed the scientific evidence for the association between self-reported racial discrimination and health from over 300 articles published between 1983 and 2013 ( 95 ). Eighty one percent of studies were from the U.S. followed by the U.K., Australia, Canada, the Netherlands and 15 other countries. The analyses found that the association between discrimination and mental health was stronger than for physical health. This was inconsistent with a prior review that found similar effect sizes for physical and mental health ( 96 ). Interestingly, ethnicity moderated the effect of self-reported racial discrimination on health with the association between perceived racial discrimination and mental health being stronger for Asian Americans and Latino Americans compared to blacks and the association with physical health being stronger for Latinos than for blacks.

While the review by Paradies and colleagues ( 95 ) is the most comprehensive one published to date, it excluded many studies that are included in other reviews. Because of its focus on experiences of “racism”, it excluded studies using measures of discrimination, bias and unfair treatment where race or ethnicity were not explicitly noted as the reason for discrimination. This included many studies using the Everyday Discrimination Scale and the Major Experiences of Discrimination Scale ( 137 , 143 ) which use a two-stage approach where respondents are first asked about generic experiences of bias and then a follow-up question ascertains the main reason. Many studies that have used these measures have not asked or analyzed the follow-up question. Relatedly, studies were also excluded that used a version of these two instruments that were utilized in the national MIDUS study ( 59 ). It explicitly asked respondents to report only instances where they had been “discriminated against” because of their race or other specific social characteristics ( 59 ). It appears that the use of “discrimination” does not affect the reports of bias by blacks but depresses reports by whites ( 8 ). Importantly, multiple reviews have concluded that the deleterious health effects of discrimination are generally evident with the generic perception of bias or unfair treatment irrespective of which social status category the experience is attributed to ( 70 , 96 , 139 ).

Several recent reviews provide additional evidence of the pervasive negative health effects of exposure to discrimination. A 2015 review indicated that self-reported discrimination is related not only to indicators of mental health symptoms and distress but also to defined psychiatric disorders ( 70 ). Moreover, there is growing evidence that self-reported discrimination is associated with preclinical indicators of disease, including increased allostatic load, inflammation, shorter telomere length, coronary artery calcification, dysregulation in cortisol and greater oxidative stress ( 70 ). Linkages between self-reported racial discrimination and physical health outcomes have been documented in multiple recent reviews with research indicating positive associations between reports of discrimination and adverse cardiovascular outcomes ( 72 ), BMI and incidence of obesity ( 12 ), hypertension and nighttime ambulatory blood pressure ( 33 ), engaging in high-risk behaviors ( 40 ), alcohol use and misuse ( 42 ), and poorer sleep ( 111 ). Research also indicates that experiences of discrimination can shape healthcare seeking behaviors and adherence to medical regiments. A 2017 review and meta-analysis of studies on discrimination and health service utilization revealed that perceived discrimination was inversely related to positive experiences with regards to healthcare (e.g., satisfaction with care or perceived quality of care) and reduced adherence to medical regimens and delaying or not seeking healthcare ( 11 ).

Research on stress and health reveals that in addition to stressful experiences affecting health through actual exposure, the threat of exposure as captured by responses of vigilance, worry, rumination and anticipatory stress can prolong the negative effect of stressors and exacerbate the negative effects of stressful experiences on health ( 17 ). Increased attention has been given to capturing vigilance with regards to the threat of discrimination. Several recent studies have used the Heightened Vigilance scale ( 23 ) or a shortened version of it and have found that vigilance about discrimination was positively associated with depressive symptoms ( 66 ), sleep difficulties ( 50 ), and hypertension ( 52 ) and contributed to racial differences for these outcomes. Another recent study with the same measure also found that heightened vigilance was associated with increased waist circumference and BMI among black but not white women ( 51 ). However, these studies have all been cross-sectional and future research using longitudinal study designs would strengthen the evidence for vigilance as a risk factor for health.

Another trend in recent research on discrimination and health is increasing attention to its negative effects on the health and wellbeing of children and adolescents. A 2013 review of discrimination and the health of persons age zero to 18 years old found 121 studies that had examined this association ( 102 ). There were consistent positive associations between self-reported discrimination and indicators of mental health problems, negative health behaviors and physical health outcomes. There is also accumulating evidence that the adverse health effects of discrimination in childhood and adolescence are evident early in life and are a likely contributor to racial inequities in health in young adulthood. For example, a study of black adolescents found that those who reported high levels of discrimination at age 16, 17, and 18 had elevated levels of stress hormones (cortisol, epinephrine and norepinephrine), blood pressure, inflammation and BMI by age 20 ( 16 ).

Research has documented cumulative effects of discrimination on health with greater negative impact evident with increasing levels of exposure to the stress of discrimination. A longitudinal study of ethnic minorities in the United Kingdom identified a dose-response relationship between the accumulation of experiences of discrimination with the deterioration in mental health, with the greatest degree of mental health deterioration evident among those who reported two or more experiences of discrimination at both time points ( 125 ).

Recommendations for Research on Discrimination and Health

As noted, audit studies and other field experiments document the existence of discrimination in many societal institutions and contexts. More concerted efforts are needed to apply knowledge and insights from these studies on the structuring and persistence of discrimination within institutional settings to understand how such discrimination sustains racial disadvantage in ways that shape health outcomes and impact racial health inequities. More generally, despite the burgeoning literature on self-reported discrimination and health, there are some fundamental questions that remain unanswered, including the conditions under which particular aspects of discrimination are related to changes in health status for specific indicators of health status. Such analyses might shed light on findings where the pattern is not uniform. For example, cohort studies have found a positive association ( 9 ), no association ( 2 ) and an inverse association between discrimination and all-cause mortality ( 34 ). The contribution of differences in the assessment of discrimination and in the populations covered to the observed patterns is not well understood.

Prior reviews indicate that the literature on self-reported discrimination and health has been plagued with multiple measurement challenges that probably lead to an underestimation of the actual effects of discrimination on health ( 62 , 135 ). These challenges include identifying the optimal approaches for accurately and comprehensively measuring discrimination and ensuring adequate assessment of key stressful components of discriminatory experiences such as their chronicity, recurrence, severity and duration and distinguishing incidents that are traumatic from those that are not. These challenges remain urgent issues to address in future research.

A limitation of most prior research on discrimination and health is the focus on singular identities of the study participants. Emerging evidence suggests that utilizing an intersectionality framework that examines associations between discrimination and health, with the simultaneous consideration of multiple social categories (e.g., race, sex, gender, SES), leads to larger associations than when only a single social category is considered ( 71 ). Experiences of discrimination should also be considered both for an individual’s self-identified race, as well as for one’s socially assigned race ( 124 ). Recent studies also provide striking evidence of the persistence of discrimination based on skin color within multiple Latino ethicities ( 97 ) and for blacks ( 88 ) suggesting that skin color should be an essential domain of assessing discrimination in future research.

An enhanced understanding of how discrimination combines with other stressors to shape health and racial/ethnic inequities in health is also needed. Self-reported experiences of discrimination do not fully encompass psychosocial stressors linked to non-dominant racial/ethnic status nor the full contribution of racism-related stressors. A study that measured multiple dimensions of discrimination (everyday, major experiences and work discrimination) along with brief measures of childhood adversity, lifetime traumas, recent life events and chronic stressors in the domains of work, finances, relationships and neighborhood, found a graded association between the number of stressors and multiple indicators of morbidity, with each additional stressor associated with worse health ( 115 ). Moreover, stress exposure explained a substantial portion of the residual effect of race/ethnicity after adjustment had been made for SES. Fully capturing stressful exposures for vulnerable populations should also include the assessment of stressors linked to the physical, chemical, and built environment ( 139 ).

Attention should also be given to understanding the contribution of stressors that, at face value, are not linked to racism but that reflect the effects of racism on health. Research on community bereavement shows that structural conditions linked to racism lead to lower life expectancy for blacks compared to whites ( 122 ). As a result, compared to whites, black children are three times as likely to lose a mother by age 10, and black adults are more than twice as likely to lose a child by age 30, and a spouse by age 60. This elevated rate of bereavement and loss of social ties is a stressor that adversely affects levels of social ties and physical and mental health of blacks across the life course ( 119 ). The death of loved ones is included on standard assessments of life events, but its links to racism typically recognized.

Another priority for future research is to better identify the conditions under which vicarious experiences of discrimination can affect health, The term, vicarious discrimination, refers to discriminatory experiences that were not directly experienced by an individual but were faced by others in their network or with whom they identify ( 47 ). A recent systematic review of 30, mainly longitudinal, studies found that that indirect, secondhand exposure to racism was adversely related to child health ( 47 ). The range of contexts in which vicarious discrimination occurs is broad. Recent studies suggest that online discrimination through social media and frequent reports and visualization of incidents of police violence directed towards black, Latino, and Native American communities may also have negative health consequences ( 121 ). A recent, nationally-representative, quasi-experimental study found that each police killing of an unarmed black male Americans worsened mental health among blacks in the general population ( 14 ).

Increased hostility and resentment towards racial and ethnic minority groups and immigrants in the U.S. as well as political polarization associated with the recent presidential election and its aftermath also deserve more research attention ( 138 ). A recent longitudinal study of high school juniors interviewed before and after the presidential election found that many reported concern, worry or stress regarding the increasing hostility and discrimination of people because of their race, immigrant status, religion, or other social factors. A year later, higher concern about discrimination was associated with increases in cigarette smoking, alcohol use, substance use, and greater odds of depression and ADHD ( 69 ).

Future research also needs to better document the role of discrimination, and other dimensions of racism, in accounting for racial disparities in health. Studies from Australia, New Zealand, South Africa and the U.S. have found that self-reports of discrimination make an incremental contribution over and above income and education in accounting for racial/ethnic inequities in health ( 139 ). However, most studies of discrimination neglect to empirically quantify the contribution of discrimination to the patterns and trends of inequities in health.

Interventions

Future research on racism and health needs to give more sustained attention to identifying interventions to reduce and prevent racism, as well as, to ameliorate its adverse health effects. Research on interventions to address the multiple dimensions of racism is still in its infancy ( 94 , 141 ).

Addressing Institutional Racism

Reskin ( 106 ) emphasizes that because racism is a system that consists of a set of dynamically related components or subsystems, disparities in any given domain is a result of processes of reciprocal causality across multiple subsystems. Accordingly, interventions should address the interrelated mechanisms and critical leverage points through which racism operates, and explicitly design multi-level interventions to get at the multiple processes of racism simultaneously. The systemic nature of racism implies that effective solutions to addressing racism need to be comprehensive and emphasize upstream/structural/institutional interventions ( 142 ). The civil rights policies of the 1960s are prime examples of race-targeted policies that that improved socioeconomic opportunities and living conditions, narrowed the black-white economic gap between the mid 1960s and the late 1970s and reduced health inequities ( 3 , 4 , 26 , 45 , 58 ). Interventions to improve household income, education and employment opportunities, and housing and neighborhood conditions have also demonstrated health benefits ( 141 ).

Additional income to households with modest economic resources suggests that added financial resources are associated with improved health ( 141 ). The Great Smoky Mountains Study was a natural experiment that assessed the impact of extra income received by American Indian households due to the opening of a Casino, on the health of Native youth ( 27 ). The study found declining rates of deviant and aggressive behavior among adolescents whose families received additional income; and increases in formal education and declines in the incidence of minor criminal offenses in young adulthood, and the elimination of Native American-white disparities on both of these outcomes ( 1 ). The Abecedarian project that randomized economically disadvantaged children, birth to 5 years of age, most of them Black, to an early childhood nurturing program also illustrates that interventions efforts at an early age can be beneficial ( 19 ). By their mid 30s, the intervention group had lower levels of multiple risk factors for cardiovascular disease than the controls. Community initiatives and efforts to build community capacity around racism may also have the potential to improve health ( 140 , 141 ). One study demonstrated that cultural empowerment among Native communities, in the form of civil and governmental sovereignty and the presence of a building for cultural activities, had a strong inverse relationship with youth suicide ( 22 ).

Addressing Cultural Racism

Most interventions aimed at reducing cultural racism focus on addressing implicit biases or enhancing cultural competence. A recent review found that cultural competency interventions can lead to improvements in provider knowledge, skills and attitudes regarding cultural competency and health care access and utilization, but there is little evidence that these interventions affect health outcomes and health equity ( 118 ). While extensive evidence documents that healthcare students and professionals have an anti-black there are no effective interventions to reduce this bias among providers ( 76 ). However, Devine and colleagues documented that a comprehensive program that deployed multiple strategies to reduce implicit biases found a sustained reduction in implicit biases in nonblack undergraduate students three months after the program began ( 29 ). Future research needs to assess the generalizability of the effects of this intervention to other groups.

Interventions, targeted at individuals, that seek to neutralize cultural racism have shown positive socioeconomic and health benefits. Values affirmation interventions (in which youth enhance their sense of self-worth by reflecting on and writing about their most important value) and social belonging interventions (which create a sense of relatedness) have been shown to markedly improve academic performance and health of stigmatized racial groups ( 24 ). There is an emerging body of evidence that suggests that similar self-affirmation strategies can enhance an individual’s capacity to cope with stressful situations and lead to improved health behaviors ( 24 ).

Addressing Discrimination

Effective strategies can be deployed to reduce discrimination against individuals that occur within institutional contexts. For example, in the employment domain, research reveals that discrimination can be reduced and the proportion of under-represented groups markedly increased through organizational policy changes that require mandatory programs, or programs with explicit authority and accountability that are supported by organizational leadership and rigorously monitored ( 57 ). Discrimination can also be minimized in employment decisions by having applications reviewed with the names of the applicants removed from the application package ( 61 ). Many interventions targeting interpersonal discrimination focus on reductions in prejudice and stereotyping through increased interracial contact. However, evidence in support of the contact theory of prejudice indicates that reductions in prejudice and discrimination are observed only when groups meet specific conditions: they are equivalent in status, have shared goals, cooperate to achieve shared goals, and have the support of authority figures ( 98 ).

Research on interpersonal discrimination also suggests that coping strategies and resources (such as social ties, religious involvement and optimism) can mitigate at least some of the detrimental effects of racial discrimination on health ( 70 ). Racial identity is another promising strategy but studies have found both protective and exacerbating effects of identity ( 144 ). At the present time, we do not clearly understand the determinants of discrepant findings and the conditions under which specific aspects of identity have positive or negative effects for particular indicators of health for specific population subgroups.

Needed Research On Interventions

Although there is emerging evidence that a broad range of strategies may reduce certain aspects of racism and enhance racial equity, there is still a lot that we do not understand. For example, interventions that have improved neighborhood and housing conditions have been implemented on a small scale and they have yet to seriously address either residential racial segregation or the concentration of poverty in the metropolitan areas in which they have been implemented. Residential segregation has been identified as a leverage point or fundamental causal mechanism by which institutional racism creates and sustains racial economic inequities ( 106 , 136 ). Thus, dismantling the core institutional mechanisms of segregation will require scaling up interventions that address its key underlying mechanisms. Relatedly, we lack the empirical evidence to identify which mechanisms of segregation (e.g., educational opportunity, labor market, housing quality) should be tackled first, would have the largest impact, and is most likely to trigger ripple effects to other pathways.

Research also needs to identify if and when observed health effects of reducing racism would be larger if comprehensive, multi-level intervention strategies (instead of interventions targeted at a single level) were deployed to neutralize the negative impact of the pathogenic effects of racism. For example, we are unaware whether we would observe larger positive effects if interventions focused on upstream interventions (e.g., in housing, education and additional income) were combined with an individual-level targeted strategy such as a self-affirmation intervention ( 24 ). Relatedly, interventions need to be evaluated for the extent to which they may be differentially effective across various subgroups of the population. The cost-effectiveness of interventions also needs to be assessed for population subgroups.

Taking the systemic nature of racism seriously also highlights that it is deeply embedded in other political, economic and cultural structures of society and that many powerful societal actors are likely to be resistant to change because they currently benefit from the status quo. Research to advance an agenda to dismantle racism and its negative effects must invest in studies that delineate how to overcome societal inertia, increase empathy for stigmatized racial/ethnic populations, build political will and identify optimal communication strategies to raise public and stakeholder awareness of the societal benefits of racial equity agenda ( 142 ).

Cross-Cutting Issues

Much of the research described in this review has focused on a single mechanism of racism (structural/institutional, cultural, discrimination) through which racism may influence health. Differentiating between these mechanisms allows researchers to clarify potential pathways, measure outcomes, and explore interventions. However, the impact of addressing a single dimension of racism will be diminished by the system of racial oppression which interacts across sectors and domains of racism. Tying together interconnected data on health and racism will be critical for health disparities researchers moving forward. Some emerging topics lend themselves to this multi-dimensional, cross-cutting research—allowing investigators to better understand and address the systemic nature of racism. Priority topics include studying the effects of racism throughout the life course, understanding the potential intergenerational effects of racism, and the impact of racism on white people.

Understanding Racism across the Life Course

Life course research aims to examine how early exposures, such as lead poisoning in utero, or adversity in early childhood, can impact health in adulthood. This perspective can incorporate early context, sensitivity and latency periods, the accumulation of risk over time, and etiologic origins of disease ( 39 ). When examining racism as an exposure, understanding how individuals encounter racism across the life course is one example of a cross-cutting issue in need of more research ( 38 , 39 , 128 ). A life course approach can begin to unpack how exposures to interpersonal, cultural, and structural racism may evolve and relate to each other across developmental stages, as individuals interact with their neighborhoods and educational systems, and health care systems ( 106 ). A recent study, for example, documented a relationship between early childhood lead exposure and adult incarceration ( 108 ). It is likely that multiple mechanisms of racism could have combined, additively and interactively over time, to undergird this association ( 78 ). Life course approaches are also important for determining how and when it is most opportune to intervene on racism. The Great Smoky Mountains Study found that providing additional income to Native American households led to a reduction in adolescent risk behaviors, but only among those who were the youngest when the income supplements began, and who thus had the longest period of exposure ( 27 ). A life course approach can identify key periods of increased risk as well as opportunities for intervention and resilience.

Intergenerational Transmission of Racism’s Effects

An extension of the life course perspective is a focus on the impact of intergenerational transmission of the effects of racism, from parent to offspring. Though still in its infancy, research on the intergenerational transmission of racism could enhance and clarify observational research which posits that descendants of survivors of mass and targeted trauma experience grief and other mental, behavioral, and somatic symptoms akin to what would might be expected if the trauma was witnessed directly ( 48 ). Long-term adverse health impacts linked to Jim Crow laws illustrate the long reach of institutional racism ( 63 ). Studies of children of Holocaust survivors and multiple generations of Native Americans suggest a link between these racialized traumatic experiences and the well-being of future generations ( 119 ). Possible pathways include the effects of parenting and community norms, the transfer of resources (i.e. wealth, land), and potentially, heritable and non-heritable epigenetic changes caused by external stressors ( 126 ). Differential DNA methylation is one type of epigenetic difference that has been found among adult children of holocaust survivors, which may affect gene expression at the methylated loci ( 119 ). Concerted new research efforts are needed to provide a more nuanced understanding of how racialized experiences are embodied for future generations.

Racism and the Health of Whites

There is growing scientific interest in how the system of racism can have both positive and negative effects on the health of whites ( 77 ). Whites as a whole have better health than the historically oppressed groups in the U.S., but they are less healthy than whites in other advanced economies. Inadequate attention has been given to delineating the ways in which racism could simultaneously advantage whites compared to other racial groups in the U.S. while creating conditions that are inimical to the health of all groups, including disadvantaging large segments of the white population, and imposing ceilings that prevent many middle class whites from attaining a level of good health seen elsewhere ( 77 ). For example, racial animus towards blacks has led to white opposition to a broad range of social programs, including the Affordable Care Act, which would benefit a large proportion of whites ( 116 ). In addition, while research on internalized racism has heavily focused on its potential negative health effects on members of racial and ethnic minority groups, whites also have high levels of internalized racism (that is, internalized racial superiority) that could affect how whites respond to economic adversity perhaps contribute to increasing rates of “deaths of despair” among low SES whites ( 77 , 105 ). Research on self-reported discrimination and hqealth has also observed negative effects of such experiences among whites ( 70 ). It is not clear that all whites are equally vulnerable. One study found that discrimination adversely affected only whites who were male and who belonged to ethnic subgroups with a history of discrimination (Polish, Irish, Italian or Jewish) ( 54 ). Another study found that discrimination based on class helped to explain SES differences in allostatic load in a sample of white adolescents ( 36 ). Concerted attention should be given to the myriad ways in which various aspects of racism can have positive and negative effects on the health of whites and particular subgroups of whites.

Conclusions

The study of contemporary racism and its impact on health is complex, as manifestations of structural, cultural, and interpersonal racism adapt to changes in technology, cultural norms, and political events. This body of research illustrates the myriad ways in which the larger social environment can get under the skin to drive health and inequities in health. While there is much that we yet need to learn, the quality and quantity of research continues to increase in this area and there is an acute need for increased attention to identifying the optimal interventions to reduce and eliminate the negative effects of racism on health. Understanding and effectively addressing the ways in which racism affects health is critical to improving population health and to making progress in reducing large and often intractable racial inequities in health.

Acknowledgments

Preparation of this paper was supported by grant U19 AG 051426 from the National Institute of Aging. We wish to thank Sandra Krumholz for her assistance with preparing the manuscript.

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• Study protocol
• Open access
• Published: 28 March 2019

The impact of racism on the future health of adults: protocol for a prospective cohort study

• James Stanley   ORCID: orcid.org/0000-0002-8572-1047 1 ,
• Ricci Harris 2 ,
• Donna Cormack 2 ,
• Andrew Waa 2 &
• Richard Edwards 1  

BMC Public Health volume  19 , Article number:  346 ( 2019 ) Cite this article

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Racial discrimination is recognised as a key social determinant of health and driver of racial/ethnic health inequities. Studies have shown that people exposed to racism have poorer health outcomes (particularly for mental health), alongside both reduced access to health care and poorer patient experiences. Most of these studies have used cross-sectional designs: this prospective cohort study (drawing on critical approaches to health research) should provide substantially stronger causal evidence regarding the impact of racism on subsequent health and health care outcomes.

Participants are adults aged 15+ sampled from 2016/17 New Zealand Health Survey (NZHS) participants, sampled based on exposure to racism (ever exposed or never exposed, using five NZHS questions) and stratified by ethnic group (Māori, Pacific, Asian, European and Other). Target sample size is 1680 participants (half exposed, half unexposed) with follow-up survey timed for 12–24 months after baseline NZHS interview. All exposed participants are invited to participate, with unexposed participants selected using propensity score matching (propensity scores for exposure to racism, based on several major confounders). Respondents receive an initial invitation letter with choice of paper or web-based questionnaire. Those invitees not responding following reminders are contacted for computer-assisted telephone interview (CATI).

A brief questionnaire was developed covering current health status (mental and physical health measures) and recent health-service utilisation (unmet need and experiences with healthcare measures). Analysis will compare outcomes between those exposed and unexposed to racism, using regression models and inverse probability of treatment weights (IPTW) to account for the propensity score sampling process.

This study will add robust evidence on the causal links between experience of racism and subsequent health. The use of the NZHS as a baseline for a prospective study allows for the use of propensity score methods during the sampling phase as a novel approach to recruiting participants from the NZHS. This method allows for management of confounding at the sampling stage, while also reducing the need and cost of following up with all NZHS participants.

Peer Review reports

Differential access to the social determinants of health both creates and maintains unjust and avoidable health inequities [ 1 ]. In New Zealand, these inequities are largely patterned by ethnicity, particularly for Māori (the indigenous peoples) and Pacific peoples, and intertwined with ethnic distributions of socioeconomic status [ 2 , 3 ]. In models of health, racism is recognised as a key social determinant that underpins systemic ethnic health and social inequities, as is evident in New Zealand and elsewhere [ 4 , 5 ].

Racism can be understood as an organised system based on the categorisation and ranking of racial/ethnic groups into social hierarchies whereby ethnic groups are assigned differential value and have differential access to power, opportunities and resources, resulting in disadvantage for some groups and advantage for others [ 4 , 6 ]. Historical power relationships underpin systems of racism [ 7 ], which in New Zealand relates specifically to our colonial history and ongoing colonial processes [ 8 ].

Racism can be expressed at structural and individual levels, with several taxonomies describing different levels of racism. Institutionalised racism, for example, has been defined as, “the structures, policies, practices, and norms resulting in differential access to the goods, services, and opportunities of society by race[/ethnicity]” (p. 10) [ 6 ]. In contrast, personally-mediated racism has been defined as, “prejudice and discrimination, where prejudice is differential assumptions about the abilities, motives, and intents of others by ‘race[/ethnicity],’ and discrimination is differential actions towards others by ‘race[/ethnicity]’” (p. 10) [ 6 ].

The multifarious expressions of racism can affect health via several recognised direct and indirect pathways. Indirect pathways include differential access to societal resources and health determinants by race/ethnicity, as evidenced by long-standing ethnic inequities in income, education, employment and living standards in New Zealand, with subsequent impacts on living environments and exposure to risk and protective factors [ 4 , 6 , 9 , 10 ]. At the individual level, experience of racism can affect health directly through physical violence and stress pathways, with negative psychological and physiological impacts leading to subsequent mental and physical health consequences. In addition, racism influences healthcare via institutions and individual health providers, leading to ethnic inequities in access to and quality of care. For example, ethnic disparities in socioeconomic status can indirectly result in differential access to care, while health provider ethnic bias can influence the quality and outcomes of healthcare interactions [ 11 ].

There has been considerable recent growth in research supporting a direct link between experience of racism and health. A recent systematic review and meta-analysis summarised the evidence for direct links between self-reported personally-mediated racism and negative physical and mental health outcomes [ 12 ], with the strongest effect sizes demonstrated for mental health. Related work has also shown that experience of racial discrimination is associated with other adverse health outcomes and preclinical indicators of disease and health risk across various ethnic groups and countries, including in New Zealand [ 9 , 13 , 14 , 15 ]. Experience of racism has also been linked to a range of negative health care-related measures [ 16 ].

However, most studies have used cross-sectional designs: very few of the articles in a recent systematic review [ 12 ] used prospective or longitudinal designs ( n  = 30, 9% of total, including multiple articles from some studies), limiting our ability to draw strong causal conclusions as the direction of causality cannot be determined when racism exposure and health outcomes are measured at the same time. Additionally, cross-sectional studies may give biased estimates of the magnitude of association between experience of racism and health: for example, bias may occur if experience of ill health (outcome) increases reporting or perception of racism (exposure) [ 12 ]. This is suggested by meta-analyses where effect sizes for the association between racism and mental health were larger for cross-sectional compared to longitudinal studies [ 12 ]. Longitudinal research on the effects of racism has been particularly limited with respect to physical health outcomes and measures of healthcare access and quality [ 12 , 16 ]. Finally, existing prospective studies have largely been restricted to quite specific groups (e.g. adolescents, females, particular ethnic groups), with a limited number of studies undertaken at a national population level and few with sufficient data to explore the impact of racism on the health of Indigenous populations [ 12 ].

In New Zealand, reported experience of racism is substantially higher among Māori, Asian and Pacific ethnic groupings compared to European [ 3 , 17 ]. In our own research, we have examined cross-sectional links between reported experience of racism and various measures of adult health in New Zealand using data from the New Zealand Health Survey (NZHS), an annual national survey by the Ministry of Health including ~ 13,000 adults per annum [ 2 , 18 , 19 ]. In these studies [ 17 , 20 , 21 , 22 ] we have shown that both individual experience of racism (e.g. personal attacks or unfair treatment) and markers of structural racism (deprivation, other socioeconomic indicators) are independently associated with poor health (mental health, physical health, cardiovascular disease), health risks (smoking, hazardous alcohol consumption) and healthcare experience and use (screening, unmet need and negative patient experiences). Other New Zealand researchers have reported similar findings including studies among older Māori [ 23 ], adolescents [ 24 ], and for maternal and child health outcomes [ 25 ]. However, evidence from New Zealand prospective studies is still limited. The NZ Attitudes and Values study showed that, among Māori, experience of racism was negatively linked to subsequent wellbeing [ 26 ], and the Growing Up in New Zealand study reported that maternal experience of racism (measured antenatally) was linked to a higher risk of postnatal depression among Māori, Pacific and Asian women [ 27 ].

While empirical evidence of the links between racism and health is growing in New Zealand, it remains limited in several areas. There is consistent evidence from cross-sectional studies for the hypothesis that racism is associated with poorer health and health care. This study seeks to build on existing research to provide more robust causal evidence using a prospective design that helps to rule out reverse causality, in order to inform policy and healthcare interventions.

Theoretical and conceptual approaches

Addressing racism as a health determinant is intrinsically linked to addressing ethnic health inequities. In New Zealand, Māori health is of special relevance given Māori rights under the Treaty of Waitangi [ 28 ] and the United Nations Declaration on the Rights of Indigenous People [ 29 ], and in recognition of the inequities for Māori across most major health indicators [ 28 ]. We recognise the direct significance of this project to Māori and understand racism in its broader sense as underpinning our colonial history with ongoing contemporary manifestations and effects [ 8 ]. As such, our work is informed by critical approaches to health research that are explicitly concerned with understanding inequity and transforming systems and structures to achieve the goal of health equity. This includes decolonising and transformative research principles [ 30 ] that influence our approach to the research question, data collection, analysis and interpretation of data, and translation of research findings. The team includes senior Māori researchers as well as advisors with experience in Māori health research and policy.

Aims and research questions

The overall aim is to examine the relationship between reported experience of racism and a range of subsequent health measures. The specific objectives are:

To determine whether experience of racism leads to poorer mental health and/or physical health.

To determine the impact of racism on subsequent use and experience of health services.

Study design

The proposed study uses a prospective cohort study design. Respondents from the 2016/17 New Zealand Health Survey [ 2 , 18 , 19 ] (NZHS) provide the source of the follow-up cohort sample and the NZHS provides baseline data. The follow-up survey will be conducted between one and two years after respondents completed the NZHS. Using the NZHS data as our sampling frame provides access to exposure status (experience of racism), along with data on a substantial number of covariates (including age, gender, and socioeconomic variables) allowing us to select an appropriate study cohort for answering our research questions. Participant follow-up will be conducted by a multi-modality survey (mail, web and telephone modalities).

This study explores the impact of racism on health in the general NZ adult population (which is the target population of the NZHS that forms the baseline of the study).

Participants

Participants were selected from adult NZHS 2016/17 interviewees ( n  = 13,573, aged 15+ at NZHS interview) who consented to re-contact for future research within a 2 year re-contact window (92% of adult respondents). The NZHS is a complex-sample design survey with an 80% response rate for adults [ 18 ] and oversampling of Māori, Pacific, and Asian populations (who experience higher levels of racism), which facilitates studying the impact of racism on subsequent health status. Participants who had consented to re-contact ( n  = 12,530) also needed to have contact details recorded and sufficient data on exposures/confounders to be included in the sampling frame ( n  = 11,775, 93.9% of consenting adults). All invited participants will be aged at least 16 at the time of follow-up, as at least one year will have passed since participation in the NZHS (where all participants were aged at least 15).

Exposure to racism was determined from the five previously validated NZHS items [ 31 ] asked of all adult respondents (see Table  1 ) about personal experience of racism across five domains (verbal and physical attack; unfair treatment in health, housing, or work). Response options for each question cover recent exposure (within the past 12 months), more historical exposure (> 12 months ago), or no exposure to racism.

Identification of exposed and unexposed individuals

Individuals were classified as exposed to racism if they answered “yes” to any question in Table  1 , in either timeframe (recent or historical: referred to as “ever” exposure). This allows for analysis restricted to the nested subset of individuals reporting recent exposure to racism (past 12 months) and those only reporting more historical exposure (> 12 months ago). The unexposed group comprised all individuals answering “No” to all five domains of experience of racism. We selected all exposed individuals for follow-up, along with a matched sample of unexposed individuals. Individuals missing exposure data were explicitly excluded.

Matching of exposed and unexposed individuals

To address potential confounding, we used propensity score matching methods in our sampling stage to remove the impact of major confounders (as measured in the NZHS) of the causal association between experience of racism and health outcomes. Propensity score methods are increasingly used in observational epidemiology as a robust method for dealing with confounding in the analysis stage [ 32 , 33 , 34 , 35 , 36 ] and have more recently been considered as a useful approach for secondary sampling of participants from existing cohorts for subsequent follow up [ 37 ].

All exposed NZHS respondents will be invited into the follow-up survey. To find matched unexposed individuals, potential participants were stratified based on self-reported ethnicity (Māori, Pacific, Asian, European and Other; using prioritised ethnicity for individuals identifying with more than one grouping) [ 38 ] and then further matched for potential sociodemographic and socioeconomic confounders using propensity score methods [ 39 , 40 ]. Stratification by ethnicity reflects the differential prevalence of racism by ethnic group, and furthermore allows ethnically-stratified estimates of the impact of racism [ 22 ].

Propensity scores were modelled using logistic regression for “ever” exposure to racism based on major confounder variables of the association between racism and poor health (Table  2 ), with modelling stratified by ethnic group. Selection of appropriate confounders was based on past work using cross-sectional analysis of the 2011/12 NZHS (e.g. [ 21 , 22 ]) and the wider literature that informed the conceptual model for the project. Some additional variables were considered for inclusion in the matching process but were removed prior to finalisation (details in Table  2 ).

Within each ethnic group stratum, exposed individuals were matched with unexposed individuals (1:1 matching) based on propensity scores to make these two groups approximately exchangeable (confounders balanced between exposure groups). The matching process [ 41 ] used nearest neighbour matching as implemented in MatchIt [ 42 ] in R 3.4 (R Institute, Vienna, Austria). As the propensity score modelling is blind to participants’ future outcome status, the final propensity score models were refined using just the baseline NZHS data to achieve maximal balance of confounders between exposure groups, without risking bias to the subsequent primary causal analyses [ 39 ]. Balance between groups was then checked on all matching variables prior to finalisation of the sampling lists.

Questionnaire development

Development of the follow-up questionnaire was informed by a literature review and a conceptual model (Figs.  1 and 2 ) of the potential pathways from racism to health outcomes (Fig.  1 ) and health service utilisation (Fig.  2 ) [ 4 , 10 , 16 , 43 , 44 ]. The literature review focussed on longitudinal studies of racism and health among adolescents and adults that included health or health service outcomes. The literature review covered longitudinal studies post-dating the 2015 systematic review by Paradies et al. [ 12 ], using similar search terms for papers between 2013 and 2017 indexed in Medline and PubMed databases, alongside additional studies from systematic reviews [ 12 , 16 ].

Potential pathways between racism and health outcomes. Direct pathway: Main arrow represents the direct biopsychosocial and trauma pathways between experience of racial discrimination (Time 1) and negative health outcomes (Time 2) Indirect pathways: Racial discrimination (Time 1) can impact negatively on health outcomes (Time 2) via healthcare pathways (e.g. less engagement, unmet need). Racial discrimination (Time 1) can impact negatively on physical health outcomes (Time 2) via mental health pathways

Potential pathways between racism and healthcare utilisation outcomes. Main pathway: Main arrow represents the pathway between experience of racial discrimination (Time 1) and negative healthcare measures (Time 2), via negative perceptions and expectations of healthcare (providers, organisations, systems) and future engagement. Secondary pathway: Racial discrimination (T1) can impact negatively on healthcare (Time 2) via negative impacts on health increasing healthcare need

We used several criteria for considering and prioritising variables for the questionnaire. The conceptual model also informed prioritisation of variables for the questionnaire. For outcome measures, these included: alignment with study aims and objectives; existing evidence of a relationship between racism and outcome; New Zealand evidence of ethnic inequities in outcome; previous cross-sectional relationships between racism and outcome in New Zealand data; availability of baseline measures (for health outcomes); plausibility of health effects manifesting within a 1–2 year follow-up period; and data quality (e.g. validated measures, low missing data, questions suitable for multimodal administration). Mediators and confounders were considered for variables not available in the baseline NZHS survey, as was recent experience of racism (following the NZHS interview) to provide additional measurement of exposure to recent racism. A final consideration for prioritising items for inclusion was keeping the length of the questionnaire short in order to maximise response rates (while being able to fully address the study aims). The questionnaire was extensively discussed by the research team and reviewed by the study advisors prior to finalisation.

Table  3 summarises the outcome measures by topic domain and original source (with references). The final questionnaire content can be found in the Additional file  1 , and includes: health outcome measures of mental and physical health (using SF12-v2 and K10 scales); health service measures (unmet need, satisfaction with usual medical centre, experiences with general practitioners); experience of racism in the last 12 months (adapted from items in the NZHS); and variables required to restrict data (e.g. having a usual medical centre, type of centre, having a General Practitioner [GP] visit in the last 12 months) or potential confounder and mediator variables not available at baseline (e.g. number of GP visits).

Recruitment and data collection

Recruitment is currently underway. The sampling phase provided a list of potential participants for invitation, and recruitment for the follow-up survey uses the contact details from the NZHS interview (physical address, mobile/landline telephone, and email address if available). Recruitment will take place over three tranches to (1) manage fieldwork capacity and (2) allow tracking of response rates and adaptation of contact strategies if recruitment is sub-optimal.

To maximise response rates, we chose to use a multi-modal survey [ 45 ]. Participants are invited to respond by a paper questionnaire included with the initial invitation letter (questionnaire returned by pre-paid post), by self-completed online questionnaire, or by computer-assisted telephone interview (CATI, on mobile or landline.) A pen is included in the study invitation to improve initial engagement with the paper-based survey [ 46 ]. Participants completing the survey are offered a NZ$20 gift card to recognise their participation. The contact information contains instructions for opting out of the study.

Those participants not responding online or by post receive a reminder postcard mailed out two weeks after the initial letter, containing a link to the web survey and a note that the participant will be contacted by telephone in two weeks’ time.

Two weeks after the reminder postcard (four weeks post-invitation) remaining non-respondents are contacted using CATI processes. For those with mobile phone numbers or email addresses, a text (SMS) or email reminder is sent two days before the telephone contact phase. Once contact is made by telephone, the interviewer asks the participant to complete the survey over the telephone at that time or organises a subsequent appointment (interview duration approximately 15 min). Interviewers make up to seven telephone contact attempts for each participant, using all recorded telephone numbers. Respondents who decline to complete the full interview at telephone follow-up are asked to consider answering two priority questions (self-rated health and any unmet need for healthcare in the last 12 months: questions 1 and 8 in Table  3 and Additional file 1 ).

Past surveys conducted in NZ have frequently noted lower response rates and hence under-representation of Māori [ 47 , 48 ]. Drawing on Kaupapa Māori research principles, we are explicitly aiming for equitable response rates of Māori to ensure maximum power for ethnically stratified analysis. This involves providing culturally appropriate invitations and interviewers for participants, and actively monitoring response rates by ethnicity during data collection to allow longer and more frequent follow-up of Māori, Pacific and Asian participants if required [ 48 , 49 ]. The use of a multi-modal survey is also expected to minimise recruitment problems inherent to any single modality (e.g. lower phone ownership or internet access in some ethnic groups).

We have contracted an external research company to co-ordinate recruitment and data collection fieldwork under our supervision (covering all contact processes described here), which follows recruitment and data management protocols set by our research team.

Statistical analysis

Propensity score methods for the sampling stage are described above: this section focuses on causal analyses for health outcomes in the achieved sample. The sampling frame selects participants based on “ever” experience of racism, which is our exposure definition.

All analyses will account for both the complex survey sampling frame (weights, strata and clusters from the NZHS) and the secondary sampling phase (selection based on propensity scores). Complex survey data will be handled using software to account for these designs (e.g. survey package [ 50 ] in R); propensity scores will be handled in the main analysis by using inverse probability of treatment weights (IPTW) combined with the sampling weights [ 51 ].

Linear regression methods will be used to compare change in continuous outcome measures (e.g. K10 score) by estimating mean score at follow-up, adjusted for baseline. Analysis of dichotomous categorical outcomes (e.g. self-rated health) will use logistic regression methods, again adjusted for baseline (for health outcomes). We will conduct analyses stratified by ethnic group to explore whether the impact of racism differs by ethnic group. Models will adjust for confounders included in creating the propensity scores (doubly-robust estimation) to address residual confounding not fully covered by the propensity score approach [ 52 ]. Analysis for other outcomes will use similar methods.

As we hypothesise that some outcomes (e.g. self-reported mental distress) will be more strongly influenced by recent experience of racism, we will also examine our main outcomes restricted to those only reporting historical (more than 12 months ago) or recent (last 12 months) racism at baseline. These historical and recent experience groups (and corresponding unexposed individuals) form nested sub-groups of the total cohort, and so analysis will follow the same framework outlined above. Experience of racism in the last 12 months (measured at follow-up) will be examined in cross-sectional analyses and in combination with baseline measures of racism to create a measure to examine the cumulative impact of racism on outcomes.

Sensitivity analyses

While the sampling invitation lists are based on matched samples, we have no control about specific individuals choosing to participate in the follow-up survey, and so the original matching is unlikely to be maintained in the achieved sample. We will conduct sensitivity analyses using re-matched data (based on propensity scores for those participating in follow-up) to allow for re-calibration of exposed and unexposed groups in the achieved sample.

To consider potential for bias due to non-response in our follow-up sample, we will compare NZHS 2016/17 cross-sectional data for responders and non-responders on baseline sociodemographic, socioeconomic, and baseline health variables.

Sample size

Based on NZHS 2011/12 responses, we anticipated a total pool of 2100 potential participants with “ever” experience of racism, with approximately 1100 expected to be Māori/Pacific/Asian ethnicity, and 10,000 with no report of racism (at least 2 unexposed per exposed individual in each ethnic group).

For the main analyses (based on “ever” experience of racism) we assumed a conservative follow-up rate of 40%, giving a final sample size of at least 840 exposed individuals. This response rate includes re-contact and agreement to participate, based on past experience recruiting NZHS participants for other studies and the relative length of the current survey questionnaire.

Initial projections (based on NZHS2011/12 data) indicated sufficient numbers of unexposed individuals for 1:1 matching based on ethnicity and propensity scores. This gives a feasible total sample size of n  = 1680, providing substantial power for the K10 mental health outcome (standard deviation = 6.5: > 95% power to detect difference in change of 2 units of K10 between groups.) For the second main health outcome (change in self-rated health), this sample size will have > 85% power for a difference between 8% of those exposed to racism having worse self-reported health at follow-up (relative to baseline) compared to 5% of unexposed individuals.

For analyses of effects stratified by ethnicity, we expect > 95% power for Māori participants ( n  = 280 each exposed and unexposed) for the K10 outcome (assumptions as above); change in self-rated health will have 80% power for a difference between 12% of exposed individuals having worse self-reported health at follow-up (relative to baseline) compared to 5% of unexposed individuals. Stratified estimates for Pacific and Asian groups will have poorer precision, but should still provide valid comparisons.

Ethical approval and consent to participate

The study involves recruiting participants who have already completed the NZHS interview (including questions on racial discrimination) The NZHS as conducted by the Ministry of Health has its own ethical approval (MEC/10/10/103) and participants are only invited onto the present study if they explicitly consented (at the time of completing the NZHS) to re-contact for future health research. The current study was reviewed and approved by the University of Otago’s Human Ethics (Health) Committee prior to commencement of fieldwork (reference: H17/094). Participants provided informed consent to participate at the time of completing the follow-up survey depending on response modality: implicitly through completion and return of the paper survey which stated “By completing this survey, you indicate that you understand the research and are willing to participate” (see Additional file 1 : a separate written consent document was not required by the ethics committee); in the online survey by responding “yes” to a similarly worded question that they understood the study and agreed to take part (recorded as part of data collection, and participation could not continue unless ticked), or by verbal consent in a similar initial question in the telephone interview (since written consent could not be collected in this setting). These consent methods were approved by the reviewing Ethics committee [ 53 ]. Ethical approval for the study included using the same consent processes for those participants aged 16 to 18 as for older participants.

This study will contribute robust evidence to the limited national and international literature from prospective studies on the causal links between experience of racism and subsequent health. The use of the NZHS as the baseline for the prospective study capitalises on the inclusion of racism questions in that survey to provide a unique and important opportunity to build on and substantially strengthen the current evidence base for the impact of racism on health using data spanning the entire New Zealand adult population. In addition, our use of propensity scores in the sampling phase is a novel approach to prospective recruitment of participants from the NZHS. This approach should manage confounding while reducing the need (and cost) of following up all NZHS participants, without compromising the internal validity of the results. The novel methods developed for using the NZHS as the base for a prospective cohort study will have wider application to other health priority areas. One general limitation of this approach is that baseline data (for both propensity score development and baseline health measures) is limited to the data captured in the existing larger survey. We anticipate that this study will assist in prioritising racism as a health determinant and inform the development of anti-racism interventions in health service delivery and policy making.

Current stage of research

Funding for this project began October 1st 2017. The first set of respondent invitations was mailed out on July 12th 2018; fieldwork for the final tranche of invitations was underway at the time of submission and is expected to be completed by 31 December 2018. Analysis and reporting will take place in mid-to-late 2019.

Abbreviations

Computer Assisted Telephone Interview

General Practitioner

General Social Survey

Index of Multiple Deprivation

Inverse Probability of Treatment Weights

• New Zealand

New Zealand Deprivation Index

New Zealand Health Survey

12/36-Item Short Form Survey

short message service

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Acknowledgements

We would like to acknowledge the assistance of the Ministry of Health’s New Zealand Health Survey Team for facilitating access to the NZHS data and respondent lists, and for help with constructing the questionnaire (including providing the Helpline contact template).

We would also like to acknowledge the expertise and input of our project advisory team: Natalie Talamaivao (Senior Advisor, Māori Health Research, Ministry of Health), Associate Professor Bridget Robson (Director, Eru Pōmare Māori Health Research Centre, University of Otago, Wellington), and Dr. Sarah-Jane Paine (Senior Research Fellow, University of Auckland and University of Otago, Wellington). Thanks also to Ms. Ruruhira Rameka (Eru Pōmare Māori Health Research Centre, University of Otago, Wellington) for providing administrative support. Research New Zealand was contracted to undertake the data collection and other fieldwork for the follow-up survey.

This project was funded by the Health Research Council of New Zealand (HRC 17–066). The funding body approved the study but has no further role in the study design or outputs from the study.

Availability of data and materials

Data from the follow-up study is not available to other researchers as participants did not provide their consent for data sharing. The NZHS 2016/17 data used as the baseline for the study described in this protocol is available to approved researchers subject to the New Zealand Ministry of Health’s Survey Microdata Access agreement https://www.health.govt.nz/nz-health-statistics/national-collections-and-surveys/surveys/access-survey-microdata .

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Contributions

JS and RH initiated the project and are co-principal investigators of the study, and jointly led writing of the grant application and this protocol paper. JS designed the sampling plan, led the development of the contact protocol, led the development of the statistical analysis plan, contributed to revising the questionnaire, and is guarantor of the paper. RH designed the questionnaire, contributed to development of the sampling and contact protocol, and co-led the statistical analysis plan. DC led the conceptual plan with support from RH. AW and RE contributed to the contact protocol. DC, AW and RE all contributed to writing the grant application, revising the questionnaire and sampling plans, and revising the draft protocol paper. All authors read and approved the final version of the manuscript.

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Correspondence to James Stanley .

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Ethics approval and consent to participate.

The follow-up study protocol and questionnaire were approved by the University of Otago’s Human Ethics (Health) Committee prior to commencement of fieldwork (reference: H17/094). The NZHS has its own ethical approval as granted to the New Zealand Ministry of Health (NZ Multi-Region Ethics Committee, MEC/10/10/103), and consent for re-contact was gained from participants at the time of their NZHS interview. Participants provided informed consented to participate at the time of completing the follow-up survey: implicitly through completion and return of the paper survey which stated “By completing this survey, you indicate that you understand the research and are willing to participate”; in the online survey by responding “yes” to a similarly worded question that they understood the study and agreed to take part, or by verbal consent in a similar initial question in the telephone interview.

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Competing interests

JS, RH, DC, AW, and RE report funding from the Health Research Council of New Zealand to complete this work. JS and RH report personal fees from the Health Research Council of New Zealand for service as external members on committees (neither are employees of the HRC), outside the scope of the current work.

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Questionnaire used in follow-up survey. (PDF 919 kb)

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Stanley, J., Harris, R., Cormack, D. et al. The impact of racism on the future health of adults: protocol for a prospective cohort study. BMC Public Health 19 , 346 (2019). https://doi.org/10.1186/s12889-019-6664-x

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Received : 28 November 2018

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DOI : https://doi.org/10.1186/s12889-019-6664-x

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