Perceived Discrimination and Increased Odds of Unmet Medical Needs Among US Children

Abstract

Our study examines the association between perceived discrimination due to race and unmet medical needs among a nationally representative sample of children in the United States. We used data from the 2016-2017 National Survey of Children's Health, a population-based cross-sectional survey of randomly selected parents or guardians in the United States. We compared results from the coarsened exact matching (CEM) method and survey-weighted logistic regression to assess the robustness of the results. Using self-reported measures from caregivers, we find that ∼2.7% of US children have experienced racial discrimination with prevalence varying significantly by race. While <1% of non-Hispanic whites have experienced some measure of racism, this increases to 8.8% among non-Hispanic blacks. Perceived discrimination was associated with significantly greater odds of unmet medical needs in the adjusted, survey-weighted multivariate-adjusted model (adjusted odds ratio [OR] = 2.4 and 95% confidence interval [CI] = 1.2, 4.9) as well as in the CEM-model estimate (OR = 2.8 and 95% CI = 1.8, 4.0). Children who have experienced perceived discrimination had higher odds of unmet medical needs. Awareness of discrimination among children may help inform future intervention development that addresses unmet medical needs during childhood.

Keywords

perceived discrimination children unmet medical need

Introduction

Racial discrimination reflects “organized systems within societies that cause avoidable and unfair inequalities in power, resources, capacities and opportunities across racial or ethnic groups.”¹ Race is a social construct that is assigned by others based on physical characteristics or geographical origin. In the United States, race categorization reflects the inequitable distribution of political, economic, and social resources that historically benefitted certain groups while disadvantaging other groups.^2–4 A growing body of research has documented the effects of racial discrimination on individuals’ biological, psychological, and emotional systems and its adverse effects on physical, mental, and behavioral health.^1,5–8 The mechanisms linking discrimination with adverse health outcomes may also potentially lead to larger unmet medical needs, defined as any need for health care that remains because appropriate health care was not received.⁹

Individuals who have experienced discrimination are more likely to adopt unhealthy coping behaviors such as overeating or substance use.¹⁰ Experiences of discrimination may also lead patients to distrust the formal health care system,^11,12 to feel uncomfortable seeking care,^13–16 to delay or forgo care entirely,¹⁷ and to not adhere to recommended treatments.¹⁸

One in 5 children in the United States has unmet medical needs.¹⁹ Research on unmet medical needs has focused on physical barriers (eg, a lack of transportation options or a long geographical distance to the nearest provider) and access factors (eg, a lack of health insurance, prohibitively high copayments or deductibles).^20–22 There is limited research on discrimination and unmet medical needs among children in the United States. A recent study in New Zealand found a dose–response relationship between caregivers’ self-reported experiences of discrimination and child health care utilization.²³ However, the New Zealand study focused on caregivers’ experiences rather than the direct experiences of children. Furthermore, the New Zealand study did not account for other adverse childhood experiences (ACEs).

The “original” ACE items focused on childhood exposures that constituted abuse, household dysfunction, and neglect.²⁴ However, given its role as a toxic stress, exposure to discrimination as a child is now included in the list of expanded ACEs.^25,26 Most research to date has operationalized ACE as an additive count measure reflecting a cumulative measure of stress.^27–30 While more recent research has begun to examine the association between individual ACE measures—domestic violence, parental divorce, and household member who was incarcerated—and poor health outcomes,³¹ no study to date has studied the association between experiences of discrimination as a child and health adjusting for other simultaneous ACEs. Experiences of discrimination differ from other conventional and expanded ACEs because it specifically asks about the child's experiences of unfair treatment due to a personal, individual-level attribute. It is important to examine discrimination, as a potentially policy-amenable factor, while accounting for the cumulative stress associated with highly correlated ACE factors.

Our study addresses these gaps in the literature. We examine the association between experiences of discrimination and unmet medical needs among a nationally representative sample of children in the United States accounting for other ACEs and other important sociodemographic characteristics of the child and the family.

Methods

Data were analyzed from the 2016-2017 National Survey of Children's Health (NSCH), a population-based survey of randomly selected caregivers in the United States. The NSCH is a cross-sectional study based on a probability sample of noninstitutionalized children who are 0 to 17 years of age in the United States. NSCH investigators surveyed a household member with the most information about the selected child to answer an extensive series of questions-regarding a wide array of sociodemographic, familial, and health characteristics of the child and the family over the phone.³² We limited our analytical sample to children with complete information on the exposure and outcome (n = 53,777).

Caregivers reported a child's experience of discrimination, assessed by using the question “To the best of your knowledge, has this child EVER experienced, treated or been judged unfairly because of his or her race or ethnic group.” Children with proxy reports of “yes” were considered to have experienced discrimination. Our outcome measure of child's unmet medical need was based on caregiver's answer to the question “During the past 12 months, was there any time when this child needed health care but it was not received. By health care, we mean medical care as well as other kinds of care like dental care, vision care, and mental health services.” Children with a proxy report of “yes” to the above item were categorized as having an unmet medical need.

Statistical Analysis

Our statistical strategy consisted of comparing results from a survey-weighted multivariate model and a coarsened exact matching (CEM) model. We compared the results between these 2 regression strategies to assess the robustness of our estimates to residual confounding.

Children who experienced discrimination potentially differ substantially from those who have not experienced discrimination. CEM is a matching technique that accounts for potential differences between the exposed and nonexposed groups. In CEM, the researcher preprocesses data to improve the balance in the empirical distribution of preselected covariates associated with the likelihood of the exposure.³³ Only exposed and unexposed individuals who are matched on these preselected covariates are included in the analysis.

The effects of social stratification, “the process that creates a hierarchy of social positions that are unequal with regard to power, property, status, and/or psychic gratification,” are mediated through racism.³⁴ We selected the potential confounders that reflect this social stratification including family structure and indicators of socioeconomic status. In the United States, there is a significant overlap between race and experiences of racism and socioeconomic status.^35,36 Moreover, children from socially disadvantaged backgrounds are more likely to experience ACE,³⁷ suggesting experiences of other ACEs may increase the risk of a child experiencing racism.

Our CEM model matched the following child and family sociodemographic covariates associated with an increased likelihood of experiencing discrimination: child’s age (<5 years old, 5-8 years, 9-12 years, and 13-17 years); family structure (2 parents currently married, 2 parents not currently married, single mother, other family types with and without a parent in the household, missing); household poverty line (0%-99%, 100%-199%, 200%-300%, >300% above the poverty level), child's current health insurance, and the total number of ACEs other than discrimination (none, 1, 2, 3, or more) and residence in a metropolitan statistical area.

These potential confounders were included in the analysis using the categories which they were asked (binary for gender, binary for English language, categorical for family structure, and household poverty). We used age categories that approximately reflected what is known about the increased awareness of racism associated with children's key developmental stages.³⁸ We categorized the total number of ACEs using the standard groupings previous literature has shown to be associated with unfavorable health outcomes.³⁹

NSCH asks the participants to self-identify their race and ethnicity. All participants answered the following questions: “Is this child of Hispanic, Latino, or Spanish origin?” and “What is this child's race?” Response options included white, black, or African American, American Indian or Alaska Native, Asian Indian, Chinese, Filipino, Japanese, Korean, Vietnamese, Other Asian, Native Hawaiian, Guamanian or Chamorro, Samoan, Other Pacific Islander, or some other race. The response categories were collapsed to non-Hispanic white, non-Hispanic black, Hispanic, Asian Pacific Islander (API)/other.

For the total number of ACEs, a parent/guardian indicated whether the child had: (1) experienced divorce/separation of a parent, (2) experienced the death of a parent/guardian, (3) experienced the incarceration of a parent/guardian, (4) witnessed domestic violence, (5) was a victim of violence, (6) lived with someone who was mentally ill or suicidal, or (7) lived with someone with alcohol or drug problem. Each type of trauma counts as 1 so the cumulative measure of ACE reflected the total number of ACE trauma reported.

All data cleaning and analyses were performed in Stata, version 14. Bivariate and multivariate analyses included appropriate survey weights. We conducted a subanalysis that included an interaction term to examine whether the associations of discrimination and unmet medical needs differed by race (non-Hispanic white vs non-white). This study was reviewed by the Montclair State University Institutional Review Board and determined to be exempt.

Results

Approximately 2.7% of children in a nationally representative US sample in 2016-2017 experienced discrimination. The proportion of children who experienced discrimination varied significantly by race, from <1% of non-Hispanic white children compared to 3.7% among Hispanic children, 5.7% among children who are API or other race/ethnicity, and 8.8% among non-Hispanic black children (Table 1). An age gradient was noted with an increasingly larger proportion of children reporting experiences of discrimination with increasing age (<1% for children of <5 years, 1.9% for 5-8 years, 3.6% for 9-12 years, and 4.7% for 13-17 years). The proportion of children who experienced discrimination differed by family structure, ranging from 2.1% among those with a 2-parent, currently married family structure to 4.7% among those with a single-mother family structure, and 5.5% among those with other family structure including those with no parent in the household). The proportion of children who experienced discrimination also differed by other ACEs, ranging from 1.6% among those with 1 other ACE to 4.8% among those with a 2 other ACE, and 7.0% among those with 3 or more ACEs.

Table 1.

Weighted Percentage of Sociodemographic Characteristics by Experienced Discrimination Among US Children who are 0 to 17 Years of Age and NSCH 2016-2017.

		Perceived discrimination %
	Weighted n	Yes	No
Total	50,958,750	2.7	97.3
Unmet needs
No	50,209,292	2.6	97.4
Yes	749,458	11.3	88.8
Age
<5 years	14,153,129	0.8	99.2
5-8 years	11,505,878	1.9	98.1
9-12 years	11,201,040	3.6	96.4
13-17 years	14,098,703	4.7	95.3
Biological sex
Male	25,878,641	2.8	97.2
Female	25,080,108	2.6	97.4
English is the primary household language
Yes	43,356,818	2.7	97.3
No	7,601,932	2.8	97.2
Family description
2 parents currently married	37,675,667	2.1	97.9
2 parents not currently married	3,574,214	3.2	96.8
Single mother	5,660,182	4.7	95.3
Other family type, no parent	3,722,610	5.5	94.5
Missing	326,076	1.1	98.9
Family poverty level
0%-99%	7,636,578	3.2	96.8
100%-199%	9,396,599	2.9	97.1
200%-300%	14,487,707	2.9	97.1
>300%	19,437,867	2.4	97.7
Insurance status
Currently insured	35,745,301	2.4	97.6
Not currently	15,137,408	3.5	96.5
Missing	76,061	2.0	98.0
Parental education
Less than HS	3,786,204	2.7	97.3
HS degree/GED	8,414,722	2.9	97.1
Some college	9,813,700	3.0	97.0
College degree	28,664,549	2.6	97.4
Missing	279,575	6.6	93.4
Race/ethnicity
NH white	27,815,768	0.7	99.3
NH black	5,598,235	8.3	91.7
Hispanic	11,898,423	3.5	96.5
Other	5,531,741	5.7	94.3
Metropolitan area
Yes	39,056,648	2.9	97.1
No	4,603,653	1.8	98.2
Number of adverse childhood experiences
None	15,457,092	2.2	97.8
1	27,011,748	1.6	98.4
2	5,391,516	4.8	95.2
3 and above	1,625,081	7.0	93.0

NSCH, National Survey of Children's Health; HS, high school; NH, non-Hispanic; GED, general education development (high school equivalency exam).

Table 2.

OR Unmet Medical Needs Among Children who Experienced Discrimination Compared to Children Who Have not Experienced Discrimination by Regression Model (95% CI).

	Unadjusted	Adjusted	CEM
Discrimination	4.7 (2.6, 8.5)	2.4 (1.2, 4.9)	2.8 (1.8, 4.0)
n	53,777	51,744	19,674
Weighted n	50,958,750	48,796,732	—

OR, odds ratio; CI, confidence interval; CEM, coarsened exact matching.

Overall, 1.5% of the children in the United States reported an unmet medical need in the 2016-2017 NCHS survey. Among children with an unmet medical need, more than11.3% experienced discrimination compared to 2.6% among those with no unmet medical need (Table 1). In the unadjusted survey-weighted analysis, discrimination was significantly associated with an unmet need (odds ratio [OR] = 4.7 and 95% confidence interval [CI] = 2.6, 8.5). While the multivariate regression model adjusting for sociodemographic characteristics decreased the effect size, the association between discrimination and unmet medical need remained large and statistically significant (adjusted OR = 2.4 and 95% CI = 1.2, 4.9).

Our CEM analysis created 10,891 strata based on the matched covariates that we specified a priori. Our CEM model matched 19,674 children (831 of the exposed with 18,843 unexposed to discrimination) in 573 strata. We found substantial improvement in the overall balance in the distribution of matching covariates between the exposed and unexposed groups after we removed the nonmatches from the dataset. The L1 statistic, a measure of the multivariate distribution, was 0.98 before the CEM matching compared to <0.01 after CEM matching. The children in our CEM analytical sample were on average 11 years of age, 57% were male, 77% non-Hispanic white, and ∼80% had experienced one or more than one ACE. Approximately 4% of the children in the CEM analytical sample experienced discrimination. In the CEM matched analysis, children who experienced discrimination had higher odds (OR = 2.8 and 95% CI = 1.8, 4.0) of having unmet medical needs than children with no experiences of discrimination. Our subanalysis, which included an interaction term between race (non-Hispanic white vs non-white) and discrimination, did not show heterogeneity in the association between discrimination and unmet medical needs by race (P > .10, results not shown).

Discussion

This study found a strong association between perceived discrimination and unmet health needs among children and adolescents in the United States even after controlling for extensive sociodemographic characteristics, health care access, and number of ACEs. These results are similar to the study findings among US adults.¹¹ Our results using survey-weighted multivariate regression were similar to the results from the CEM models, providing consistency in effect estimates by different modeling analysis. These findings reinforce the need to address how discrimination may be experienced at an early age with immediate adverse health consequences.

While ACEs are a strong part of the pathway linking racial discrimination to poor health outcomes among children, these may be mediated by parental exposure to racism and resulting poverty-associated stress. By controlling for ACEs, we provide a more direct measure of the link between a child's experiences and poor health outcomes.

Our results did not find any evidence of effect measure modification in the association between discrimination and unmet medical needs by race/ethnicity. These findings align with previous research indicating that discrimination is a potential source of acute and chronic stress for many racial and ethnic group members.⁴⁰ However, similar to previous studies that used NSCH data from earlier years,⁴¹ we found the prevalence of discrimination to be much greater among racial minorities. The larger prevalence of discrimination among racial and ethnic minorities may contribute to racial/ethnic disparities in the appropriate use of health care services and, by extension, disparities in health outcomes.

Although our study and the NCHS data provide a unique opportunity to examine unmet medical needs associated with discrimination, some important limitations need to be acknowledged. NSCH is completed by the parent or the caregiver, who may not be aware of all of the instances of his/her child's exposure to discrimination or unfair treatment. The NCHS survey question on discrimination did not ask respondents to specify the setting where such experiences occurred. It is plausible that discrimination experienced in a health care setting may especially impact future health care use.⁴² More research developing relevant and psychometrically sound operational measure of discrimination in general and for children is needed.^34,43 Self-reported measures have several well-documented limitations including variations in understanding (eg, participants may have different interpretations of what constitutes discrimination), social desirability bias (eg, specific groups of participants may not want to report experiences of discrimination), and reference bias (eg, participants may not understand what constitutes appropriate medical care). In addition, children may have a different perspective from their adult proxies. Finally, there may be residual confounding from unmeasured behavioral characteristics affecting our reported association between discrimination and unmet needs.

Despite these limitations, this study represents the only work to date on the association between discrimination and unmet health care needs among children in the United States accounting for other ACEs. Unmet medical need results when there is an acknowledged health condition requiring medical attention but, simultaneously, there are substantial barriers preventing access. Discrimination may be operating through the stress pathway to directly increase the likelihood of adverse health conditions (eg, depression) while also contributing to psychological (eg, distrust) and structural barriers (eg, lack of knowledge) that prevent children from accessing the needed care.⁴³ As such, unmet medical needs may be an important mechanism connecting discrimination and a multitude of adverse health outcomes in childhood and in later ages.

As noted by the recent policy issued by the American Academy of Pediatrics, discrimination has large, immediate, and long-term effects on children and adolescents.⁴⁴ Discrimination experienced as a child may be especially detrimental because it occurs during a key developmental period in the life course.

Racism is systemic in many countries besides the United States. Racism is an asymmetrical power-based social relationship between any given dominant racial or ethnic group and racial minority group. This problem persists in nearly many countries.⁴⁵ However, there may be geographical and historical variations, colonialism, and white supremacy, which have led to widespread mechanisms and practices perpetuation of racism in many societies.⁴⁶ This, for example, may have led to health disparities between dominant and racial minority groups in the EU with the most marginalized groups—Roma, migrant workers, and asylum seekers—facing ongoing racism that challenges their health care access.⁴⁷

Future research is needed focusing on the pathways associated with interpersonal discrimination, as well as in conjunction with other (eg, structural and institutional) forms of discrimination, which influence unmet medical needs and more distal health outcomes among children. A deeper understanding of the association between discrimination and the health care service utilization of children is crucial to the creation of evidence-based interventions.

Footnotes

Declaration of Conflicting Interests

The authors declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article.

Funding

The authors disclosed receipt of the following financial support for the research, authorship, and/or publication of this article: RP is funded by a Tier II Canada Research Chair in Social and Health Inequities.

ORCID iD

Sze Yan Liu

Author Biographies

Sze Yan Liu is an Assistant Professor at Montclair State University’s Department of Public Health. Her scholarship focuses on the impact of social policies on health and the role of structural racism in perpetuating health inequities. Her work often uses a life course approach to understand the current patterns of population health.

Roman Pabayo is an Assistant Professor at the University of Alberta’s Department of Epidemiology. His research encompasses the social determinants of health with a focus on adolescents, youth, and infants. He has conducted studies that examined the role of environment on physical activity, smoking, and dietary intake behaviors. Currently, he is studying the relationship between social and economic contextual factors within counties, neighborhoods, and schools, such as income inequality.

Peter Muennig is a Professor at Columbia University’s Department of Health Policy and Management. His research has examined how a broad array of social policies affects population health. These include analyses on reduced class size, pre-kindergarten programs, lead abatement programs, welfare reform, transportation policies, and health insurance.

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