Although systemic inequities, broadly defined, are associated with health disparities in adults, there is a dearth of research linking contextual measures of exclusionary policies or prejudicial attitudes to health impairments in children, particularly among Latino populations. In this study, we examined a composite measure of systemic inequities in relation to the cooccurrence of multiple health problems in Latino children in the United States.
Participants included 17 855 Latino children aged 3 to 17 years from the National Survey of Children’s Health (2016–2020). We measured state-level systemic inequities using a factor score that combined an index of exclusionary state policies toward immigrants and aggregated survey data on prejudicial attitudes toward immigrants and Latino individuals. Caregivers reported on 3 categories of child health problems: common health difficulties in the past year, current chronic physical health conditions, and current mental health conditions. For each category, we constructed a variable reflecting 0, 1, or 2 or more conditions.
In models adjusted for sociodemographic covariates, interpersonal discrimination, and state-level income inequality, systemic inequities were associated with 1.13 times the odds of a chronic physical health condition (95% confidence interval: 1.02–1.25) and 1.24 times the odds of 2 or more mental health conditions (95% confidence interval: 1.06–1.45).
Latino children residing in states with higher levels of systemic inequity are more likely to experience mental health or chronic physical health conditions relative to those in states with lower levels of systemic inequity.
Previous studies have revealed that systemic inequities, including harsh immigrant policies, are associated with poor mental health among Latino adults and adverse birth outcomes for Latino infants. The authors of few studies have examined state-level measures of systemic inequities and children’s health.
Systemic inequities, including exclusionary state policies and prejudicial attitudes, are associated with the occurrence of multiple physical and mental health conditions among Latino children adjusting for sociodemographic characteristics, highlighting the importance of considering macro-level social determinants of child health.
Latino/Latina/Hispanic children (referred to as “Latino children” herein) comprise approximately one-quarter of all children aged <18 in the United States.1 Latino children fare worse than non-Latino white children (referred to as “white children” herein) across several common health conditions, including respiratory illnesses (particularly, Puerto Rican children),2,3 overweight and obesity,4,5 insufficient sleep,6–8 and heightened levels of inflammation.9 Systemic inequities related to structural or cultural racism, discrimination, xenophobia, and stigma (referred to as “systemic inequities” herein) limit access to power and resources for members of marginalized or stigmatized groups10–16 and may contribute to these disparities.17,18 Such inequities can take many forms, including pervasive prejudicial attitudes and rhetoric directed toward racial or ethnic minorities, exclusionary laws designed to exclude individuals from various activities within society (eg, related to education, health care, etc), and criminalizing immigration policies.13
Consistent with research on the effects of discrimination on health in adults,10,19 most research on child health has focused on individual experiences of discrimination,20 despite repeated calls to assess systemic or structural influences.10,21–25 Moreover, the majority of studies that have examined state-level measures of systemic inequities (eg, antiimmigrant policies) in relation to Latino health have focused on adults26–28 or perinatal outcomes,29–33 with less known about children and youth. Previous studies have revealed that harsh immigrant policies are associated with poor mental health26 and reduced use of preventive health care and public assistance among Latino adults,34,35 as well as food insecurity among Latino immigrant families.33,36 In addition, restrictive immigration laws,30,32 sociopolitical events with relevance to immigration policies (eg, the 2016 US election),37,38 and enforcement actions39 have each been linked to adverse birth outcomes among children born to Latina mothers. Although research on state-level systemic inequities and child and adolescent health outcomes is sparse, recent evidence revealed that Latino adolescents in states with greater systemic inequities (measured via a composite index of state immigration policies and aggregate social attitudes toward immigrant and Latino populations) had smaller hippocampal volumes, a brain region associated with chronic stress exposure.40 This work is complemented by research on adolescent responses to immigration actions,41,42 including a study documenting elevated worry and behavioral withdrawal among Latino adolescents with vulnerable versus more secure family immigrant statuses.41
Building on this nascent literature, the authors of the current study examined associations between state-level systemic inequities and the number of reported health problems in Latino children. The cooccurrence of problems is an understudied aspect of child health,43–46 with potential implications for costs and quality of life for parents and children, health and earnings across the life course, as well as approaches to prevention. Systemic inequities may affect a broad range of children’s health conditions, and the clustering of conditions, via chronic stress and associated disruptions to the child’s stress-response system,47,48 or through the deprivation of resources needed to support healthy development (eg, lack of access to safe and secure neighborhoods and schools or affordable, nourishing food).49 These postulated pathways of chronic stress and deprivation of resources suggest potential shared mechanisms for mental and physical health problems among children.
On the basis of previous studies,26–28,40 we hypothesized that greater systemic inequities would be associated with increased reported health problems among Latino children. We include both US-born and foreign-born Latino children in our study based on (1) quantitative research revealing that restrictive immigration policies are associated with poor mental health among Latino adults26 and birth outcomes32 regardless of personal immigration history, and (2) qualitative research revealing few differences between US-born and foreign-born Latino adults in perceptions of vulnerability or psychological distress related to immigration enforcement activities.50 These findings are likely due to several factors, including that 40% of Latino adults live in households with mixed immigration status,51 thus making immigration-related policies salient to a large portion of Latino families.
Methods
Sample
We used data from 17 855 Latino children from the National Survey of Children’s Health (NSCH; 2016–2020), a cross-sectional, nationally representative, weighted probability sample of noninstitutionalized children from birth through age 17. Each year, randomly selected households across the United States are mailed an invitation to complete a household screener and child-level questionnaire via a secured Web site or on paper. The paper and Web instruments are available in both English and Spanish, and additional language support is available via telephone. Parents or guardians familiar with the child’s health and medical care are the respondents. After completing the screener, a single child from each home is randomly selected as the focal child. Details on design, administration, and completion rates are available at https://www.childhealthdata.org/learn-about-the-nsch/NSCH. Our analytic sample included children 3 years of age and older given the health outcomes on which we focus. Children from Washington, DC, notably, considered to be a “sanctuary city,”52 were excluded from our analytic sample because data needed to construct the state-level systemic inequities score were unavailable.
Measures
Child Health
We assessed the number of problems within and across 3 distinct dimensions of child health, following Jackson and colleagues’ approach with the 2016 NSCH.53 Caregiver respondents reported on (1) health difficulties in the past 12 months (6 items: eating or swallowing because of a health condition; digesting food, including stomach or intestinal problems, constipation, or diarrhea; repeated or chronic physical pain, including headaches or other back and body pain; toothaches; bleeding gums; and decayed teeth or cavities), (2) provider-diagnosed, current, chronic physical conditions (6 items: allergies, asthma, blood disorders, diabetes, heart condition, and arthritis), and (3) provider-diagnosed, current mental health conditions (4 items: depression, attention-deficit/hyperactivity disorder [ADHD], anxiety problems, and behavioral or conduct problems). We examined the extent of problems within each health dimension by constructing a 3-level variable to reflect 0, 1, or 2 or more. We also created a 4-level variable to indicate the cooccurrence of problems across dimensions (ie, no health problems and problems within 1, 2, or all 3 dimensions). These outcomes are designed to indicate the pervasiveness of problems within and across multiple dimensions of mental and physical health, for both chronic and temporary conditions.53 As a secondary analysis, we examined outcomes individually as well.
Systemic Inequities
We operationalized systemic inequities via a factor score developed using data-driven methods and used in previous research.40 We included measures of aggregated public attitudes and social policies, and refer to them together as “systemic,” because both policies and attitudes reflect the broader macro-social context, are highly correlated,54 and are consistent with conceptual frameworks from minority stress theory and stigma research.55,56
The factor score was based on 3 measures. First, a state-level summary index reflecting restrictiveness or supportiveness of state policies (related to health services, private sector employment, business licensing, rental housing access, higher education access, driver’s license access, immigration policy enforcement, non-English language use, identification requirements, and discrimination prohibition) toward immigrants as of 2016, with a positive point awarded for each of the items, and a negative point awarded if the state explicitly prohibited the item.57 Second, we used survey responses from the American National Election Study (ANES) to a “feelings thermometer” (ie, a measurement technique in which participants report their feelings toward a target on a scale ranging from 0 (extremely cold or negative feelings) to 100 (extremely warm or positive feelings) reflecting attitudes toward Latino individuals (pooled, 1996 to 2016). Third, we used survey responses from the ANES on a “feelings thermometer” reflecting attitudes toward immigrants (pooled, 2004 to 2016). Responses on the ANES feelings thermometers were standardized for all respondents and then aggregated at the state level. All 3 components were reverse-scored so that higher ratings represented higher levels of structural inequity.
For the ANES feeling thermometer measures, survey years were pooled to maximize the number of respondents per state and to minimize measurement error; this approach is supported by research revealing the stability of states relative to each other in terms of their residents’ attitudes toward marginalized groups (eg, racial minorities and women) over 30 years.58,59 We included attitudes and policies related to immigration for this measure, despite the fact that only a third of Latino individuals in the United States are foreign-born,60 because of the mixed status of many Latino households51 and because non-Latino individuals in the United States often conflate immigrant identity with Latino identity.61 See Supplemental Table 5 for a table describing the component measures.
The model-based factor score was constructed for each state by using exploratory factor analysis, with all 3 measures coded with higher values reflecting higher levels of systemic inequity. We have displayed the distribution of factor scores across states (see Fig 1). Supplemental Table 6 features the scores for each state. The continuous factor score ranged from −1.75 to +1.76, representing the state’s relative standing on the latent factor of systemic inequities for Latino children, with higher values reflecting higher levels of systemic inequity.
Distribution of systemic inequities for Latino populations across the United States. Darker shade reflects higher values of the state-level systemic inequity score.
Distribution of systemic inequities for Latino populations across the United States. Darker shade reflects higher values of the state-level systemic inequity score.
Covariates
Caregivers reported on children’s ethnicity. We selected covariates to be consistent with previous research53 and constructed both minimally and fully adjusted models recognizing that some of the covariates could be on the causal pathway. Our basic set of covariates included child’s age and sex, survey year, family immigration history, mother’s age at child’s birth, and state-level Gini Index, to control for other macro-level characteristics related to income inequality (see Table 1 for variable categories). Our extended set of covariates additionally included highest education level in household, income-to-needs ratio (using the multiple imputed values provided by Census), caregiver report that the child ever resided in an unsafe neighborhood, health insurance status, caregiver self-rated health index (ie, sum of single-item self-reports of physical and mental health), an index reflecting number of social services received (ie, cash assistance, Special Supplemental Nutrition Program for Women, Infants, and Children, Supplemental Nutrition Assistance Program, and free or reduced-price school lunch), and caregiver report of the child’s personal experience of racism.
Descriptive Characteristics of the Sample (n = 17 855)
| % | SE | |
|---|---|---|
| Child sex, male | 50.90 | 0.83 |
| Age cohort, y | ||
| 3–5 | 18.84 | 0.66 |
| 6–11 | 40.38 | 0.83 |
| 12–17 | 40.77 | 0.81 |
| No health insurance | 10.56 | 0.56 |
| Household income-to-needs ratio | ||
| Less than FPL | 29.50 | 0.91 |
| 100% –399% FPL | 45.66 | 0.87 |
| ≥400% FPL | 24.84 | 0.72 |
| Highest household education | ||
| Less than high school | 23.74 | 0.83 |
| High school | 26.93 | 0.74 |
| More than high school | 49.33 | 0.83 |
| Family structure | ||
| Two adults, married | 58.35 | 0.84 |
| Two adults, unmarried | 13.19 | 0.61 |
| Single parent | 22.71 | 0.69 |
| Grandparent or other | 5.75 | 0.43 |
| Family immigration history | ||
| Child or parent born out of US | 54.30 | 0.83 |
| Child born in US, parent data missing | 8.46 | 0.53 |
| Parent and child born in US | 37.24 | 0.78 |
| Count of social services received | ||
| 0 | 39.25 | 0.80 |
| 1 | 31.46 | 0.81 |
| 2 | 19.03 | 0.75 |
| 3 | 8.68 | 0.52 |
| 4 | 1.58 | 0.23 |
| Caregiver health index | ||
| Excellent (score = 2–3) | 36.42 | 0.81 |
| Good (score = 4–6) | 55.23 | 0.84 |
| Fair/poor (score = 7–10) | 8.35 | 0.46 |
| Parent-report, unsafe neighborhood | 7.74 | 0.45 |
| Parent reported unfair treatment of child due to race or ethnicity | 5.66 | 0.34 |
| % | SE | |
|---|---|---|
| Child sex, male | 50.90 | 0.83 |
| Age cohort, y | ||
| 3–5 | 18.84 | 0.66 |
| 6–11 | 40.38 | 0.83 |
| 12–17 | 40.77 | 0.81 |
| No health insurance | 10.56 | 0.56 |
| Household income-to-needs ratio | ||
| Less than FPL | 29.50 | 0.91 |
| 100% –399% FPL | 45.66 | 0.87 |
| ≥400% FPL | 24.84 | 0.72 |
| Highest household education | ||
| Less than high school | 23.74 | 0.83 |
| High school | 26.93 | 0.74 |
| More than high school | 49.33 | 0.83 |
| Family structure | ||
| Two adults, married | 58.35 | 0.84 |
| Two adults, unmarried | 13.19 | 0.61 |
| Single parent | 22.71 | 0.69 |
| Grandparent or other | 5.75 | 0.43 |
| Family immigration history | ||
| Child or parent born out of US | 54.30 | 0.83 |
| Child born in US, parent data missing | 8.46 | 0.53 |
| Parent and child born in US | 37.24 | 0.78 |
| Count of social services received | ||
| 0 | 39.25 | 0.80 |
| 1 | 31.46 | 0.81 |
| 2 | 19.03 | 0.75 |
| 3 | 8.68 | 0.52 |
| 4 | 1.58 | 0.23 |
| Caregiver health index | ||
| Excellent (score = 2–3) | 36.42 | 0.81 |
| Good (score = 4–6) | 55.23 | 0.84 |
| Fair/poor (score = 7–10) | 8.35 | 0.46 |
| Parent-report, unsafe neighborhood | 7.74 | 0.45 |
| Parent reported unfair treatment of child due to race or ethnicity | 5.66 | 0.34 |
FPL, federal poverty level.
Analysis
First, we display the social, demographic, and health characteristics of each group. Second, we used generalized estimating equations62 and multinomial logistic regression to estimate the relative risk of exhibiting a single health problem and multiple problems within each of the 3 health dimensions, and across health dimensions, using systemic inequities as the independent variable. We selected multinomial regression because we conceptualized the cooccurrence of >1 condition as a discrete, qualitative outcome, rather than a count (consistent with previous research using a similar set of outcomes53 ). This approach accounts for the complex sample design and for correlations among children who reside in the same state. We present odds ratios, 95% confidence intervals (CIs), and P values from Wald’s tests, which reveal the significance of the association between the exposure and multicategory outcome, collectively (ie, both categories against 0).63 As sensitivity analyses, we examined each health outcome individually and tested for effect modification by sex.
Descriptive statistics and models were generated by using SUDAAN 11.0.3, and we weighted the results to represent noninstitutionalized US children. To handle missing data, analyses used 6 imputed data sets. The results using the imputed data are nearly identical to those using complete case data.
Results
Demographic Characteristics
Nearly one-third of children (29.50%) lived in households below the federal poverty level, and >1 in 10 (10.56%) did not have health insurance (see Table 1). Slightly more than one-half of the children (54.30%) were either born outside of the United States or had a parent born outside the United States. Table 2 presents the distributions for the number of problems within and across 3 distinct dimensions of child health. See Supplemental Table 4 for the prevalence of each specific health outcome.
Health Characteristics of the Sample (n = 17 855)
| % | SE | |
|---|---|---|
| Health difficulties | ||
| 0 | 70.76 | 0.77 |
| 1 | 19.76 | 0.69 |
| 2+ | 9.48 | 0.48 |
| Chronic physical health conditions | ||
| 0 | 78.22 | 0.64 |
| 1 | 16.86 | 0.58 |
| 2+ | 4.92 | 0.32 |
| Mental health conditions | ||
| 0 | 86.42 | 0.52 |
| 1 | 7.73 | 0.44 |
| 2+ | 5.85 | 0.32 |
| No of health dimensions with 1+ condition | ||
| 0 | 52.89 | 0.83 |
| 1 | 32.42 | 0.79 |
| 2 | 11.89 | 0.51 |
| 3 | 2.80 | 0.23 |
| % | SE | |
|---|---|---|
| Health difficulties | ||
| 0 | 70.76 | 0.77 |
| 1 | 19.76 | 0.69 |
| 2+ | 9.48 | 0.48 |
| Chronic physical health conditions | ||
| 0 | 78.22 | 0.64 |
| 1 | 16.86 | 0.58 |
| 2+ | 4.92 | 0.32 |
| Mental health conditions | ||
| 0 | 86.42 | 0.52 |
| 1 | 7.73 | 0.44 |
| 2+ | 5.85 | 0.32 |
| No of health dimensions with 1+ condition | ||
| 0 | 52.89 | 0.83 |
| 1 | 32.42 | 0.79 |
| 2 | 11.89 | 0.51 |
| 3 | 2.80 | 0.23 |
Health difficulties (past 12 mo) include problems (1) eating or swallowing, (2) digesting food, including stomach/intestinal problems, (3) repeated or chronic physical pain, (4) toothaches, (5) bleeding gums, and (6) cavities. Chronic health problems (current) include caregiver report of health care provider’s diagnosis of (1) allergies, (2) asthma, (3) blood disorder, (4) diabetes, (5) heart condition, and (6) arthritis. Mental health disorders (current) include health care provider or educator report of (1) depression, (2) ADHD, (3) anxiety problems, and (4) behavioral or conduct problems. Number of health dimensions with 1+ condition is a count of the health outcome categories in which a child had 1 or more health conditions (range: 0 to 3).
Systemic Inequities and Number of Health Outcomes
The multinomial models to estimate odds ratios for each health dimension, and across dimensions, were similar when adjusting for a basic set of covariates and when additionally adjusting for a more comprehensive set of social and demographic covariates (see Supplemental Table 7 for values from the basic and fully adjusted models). Figure 2 displays the odds ratios from the fully adjusted models only.
Adjusted odds ratios to display the relationship between state-level systemic inequities and health problems among Latino children (n = 17 855) 3 to 17 years of age. Models are adjusted for child’s age, sex, personal experience of racism, survey year, household income-to-needs ratio, highest education in household, family immigration history, social service use index, mother’s age at child’s birth, neighborhood safety, insurance status, caregiver health, family structure, and state income inequality. See Supplemental Table 7 for numeric values corresponding to estimates presented in the figure and Wald P values.
Adjusted odds ratios to display the relationship between state-level systemic inequities and health problems among Latino children (n = 17 855) 3 to 17 years of age. Models are adjusted for child’s age, sex, personal experience of racism, survey year, household income-to-needs ratio, highest education in household, family immigration history, social service use index, mother’s age at child’s birth, neighborhood safety, insurance status, caregiver health, family structure, and state income inequality. See Supplemental Table 7 for numeric values corresponding to estimates presented in the figure and Wald P values.
In minimally adjusted models, systemic inequities were significantly associated with the number of chronic physical health conditions and the number of mental health problems. Specifically, a 1-unit increase in systemic inequities was associated with increased odds of 1 (adjusted odds ratio [AOR] = 1.13, 95% CI: 1.02–1.25) or 2 or more (AOR = 1.20, 95% CI: 1.00–1.45) chronic physical health conditions, and 2 or more mental health conditions (AOR = 1.27, 95% CI: 1.09–1.48) (see Supplemental Table 7). In models that additionally adjusted for demographic characteristics that could be on the causal pathway, systemic inequities were significantly associated with increased odds of having a chronic physical health condition (AOR = 1.13, 95% CI: 1.02–1.25) and increased odds of having 2 or more mental health conditions (AOR = 1.24, 95% CI: 1.06–1.45). No associations were evident for the outcome of health difficulties in the past 12 months. Although an increasing relationship between systemic inequities and the number of health dimensions with 1 or more health problems was suggested by the point estimates, with AORs increasing in magnitude as the number of dimensions with 1+ health problems increased, associations were not significant at P < .05.
In sensitivity analyses, we disaggregated our health categories to further examine the results (see Table 3). In fully adjusted models, anxiety problems (AOR = 1.24, 95% CI: 1.06–1.46), ADHD (AOR: 1.20, 95% CI: 1.03–1.40), and allergies (AOR = 1.15, 95% CI: 1.04–1.27) were each associated with systemic inequities at the P < .05 threshold. Finally, we did not find evidence for effect modification based on child’s sex (P > .05) across the 4 primary outcomes.
Adjusted Odds Ratios to Describe the Relationship Between the Systemic Inequities Score and Each Outcome Among Latino Children Aged 3 to 17 y
| Systemic Inequities | ||
|---|---|---|
| AOR | 95% CI | |
| Health difficulties, past 12 mo | ||
| Eating or swallowing problems | 1.18 | 0.84–1.65 |
| Digesting food, including stomach or intestinal problems | 1.04 | 0.90–1.20 |
| Chronic or repeated physical pain | 0.96 | 0.83–1.11 |
| Toothaches | 1.01 | 0.83–1.23 |
| Bleeding gums | 0.98 | 0.79–1.23 |
| Decayed teeth or cavities | 0.93 | 0.82–1.04 |
| Any dental problem | 0.92 | 0.82–1.03 |
| Chronic health conditions | ||
| Allergies | 1.15 | 1.04–1.27 |
| Asthma | 1.11 | 0.97–1.28 |
| Mental health conditions | ||
| Depression | 1.05 | 0.82–1.35 |
| Anxiety problems | 1.24 | 1.06–1.46 |
| ADHD | 1.20 | 1.03–1.40 |
| Behavioral or conduct problems | 1.14 | 0.96–1.35 |
| Systemic Inequities | ||
|---|---|---|
| AOR | 95% CI | |
| Health difficulties, past 12 mo | ||
| Eating or swallowing problems | 1.18 | 0.84–1.65 |
| Digesting food, including stomach or intestinal problems | 1.04 | 0.90–1.20 |
| Chronic or repeated physical pain | 0.96 | 0.83–1.11 |
| Toothaches | 1.01 | 0.83–1.23 |
| Bleeding gums | 0.98 | 0.79–1.23 |
| Decayed teeth or cavities | 0.93 | 0.82–1.04 |
| Any dental problem | 0.92 | 0.82–1.03 |
| Chronic health conditions | ||
| Allergies | 1.15 | 1.04–1.27 |
| Asthma | 1.11 | 0.97–1.28 |
| Mental health conditions | ||
| Depression | 1.05 | 0.82–1.35 |
| Anxiety problems | 1.24 | 1.06–1.46 |
| ADHD | 1.20 | 1.03–1.40 |
| Behavioral or conduct problems | 1.14 | 0.96–1.35 |
All models are adjusted for child’s age, sex, survey year, household income-to-needs ratio, highest education in household, family immigration history, social service use index, mother’s age at child’s birth, neighborhood safety, insurance status, caregiver health, family structure, personal experience of racism, and state income inequality. We did not examine uncommon chronic physical health conditions as separate outcomes (ie, blood disorders, diabetes, heart conditions, arthritis) because of data limitations resulting from the low prevalence for these conditions.
Discussion
This study examined whether Latino children who reside in states with higher levels of systemic inequities experience a greater cooccurrence of health problems relative to children who live in states with lower levels of inequity. We used nationally representative data from the NSCH linked to a state-level measure of systemic inequities, generated from aggregated public opinion data about Latino groups and immigrant populations as well as both exclusionary and inclusive policies toward immigrants.
As hypothesized on the basis of previous research,26–28,32,64,65 systemic inequities were associated with a greater cooccurrence of mental health conditions and the occurrence of chronic physical health conditions among Latino children, even after adjusting for a broad set of child and family characteristics and individual experiences of discrimination. Of note, although the observed associations are small in magnitude, research reveals that small effects can be meaningful when scaled across populations, as is the case in our measure of structural inequalities.66,67 For both chronic physical and mental health conditions, we observed a graded relationship in which the estimated associations were larger as the number of health conditions increased. This pattern is consistent with conceptualizations of systemic inequities as a broad, generalizable, risk factor.
Our results reinforce and build on previous studies of personally experienced racism and child health,20,68–70 as well as restrictive immigration policies and adult26–28 and perinatal health,29,30,33,39 in several ways. First, we use a recent, large nationally representative sample of children, which improves the generalizability of our results and the ability to study variation in systemic inequities across states. Second, drawing on evidence that immigration policies and antiimmigrant sentiment are interconnected,54 our measure of systemic inequities combines both aggregated social attitudes and policies, thereby improving construct validity. Third, our analyses consider the cooccurrence of health problems, an understudied aspect of child development that has relevance for health equity research,43 which has rarely been studied in relation to structural contexts in childhood.
There are also limitations to consider in interpreting these study results. First, state-level analyses of systemic inequities are appropriate given the many important legislative activities at that level, but they offer a conservative test because more proximal environments are likely to exert stronger associations. Thus, more localized aspects of place-based inequities and protective factors that influence child health and development should be studied71–73 because there is often substantial heterogeneity within states in terms of social climates surrounding Latino populations (eg, differential enforcement of immigration policies). Also related to our exposure measure, the index of state policies reflects policies in place in 2016,57 and our measures of prejudicial attitudes pool across many years, up to 2016. Although our approach is supported by research showing stability in the rank ordering of state-level attitudes toward marginalized groups,58,59 future studies might benefit from examining time-varying measures of systemic inequities. We also recognize that, despite the aforementioned strengths of using a factor score, one of the limitations of this approach is that there is not a direct interpretation of a 1-unit change in this continuous measure because it combines interrelated components of systemic inequities.
Second, the NSCH has several limitations, such as reliance on caregiver reports of provider-diagnosed mental health conditions; given the disparities in specialized mental health services for Latino children,74,75 these outcomes are likely to be underestimated. Related, the survey was administered via mail and online, which could exclude families without permanent mailing addresses or reliable internet access, which represent some of the highest-risk populations. In addition, our analysis is not inclusive of all relevant child outcomes (eg, we could not include provider-diagnosed overweight or obesity because it was not asked in 2016 and 2017), and our ability to explore potential within-group interactions by country of origin, age, geography, duration of time in the United States among the subset of children born outside of the United States, and other child and family characteristics (eg, interpersonal experiences of racism) was limited by insufficient sample sizes. We were also unable to account for how long a child lived in a state at the time of the survey, which could introduce measurement error, and our cross-sectional design prohibits causal inferences and the examination of both unique and shared mechanisms, all of which represent important areas for future investigation. Finally, while interpreting these results, it is important to keep in mind that odds ratios are overestimates of risk for common outcomes (ie, >10%76 ).
Childhood health provides a foundation for wellbeing across the life course, including the promotion of school attendance and performance,77–79 reducing risk for substance abuse,80,81 and positive health and socioeconomic attainment in adulthood.82–84 Accordingly, our results and related studies have implications for a wide range of health-promoting policies, particularly in the face of persistent structural inequities related to racism, xenophobia, and punitive approaches to immigration. Policy statements from the American Academy of Pediatrics and other reports have called on pediatricians to play a more active role in educating the public about the adverse effects of systemic racism experienced by children of color and immigrant families.17,85–88 This study underscores the importance of addressing the health impacts of state laws as well as the effects of public attitudes that perpetuate racist and/or antiimmigrant sentiments, all of which influence access to opportunities and resources that promote healthy development.89 Previous research has revealed that inclusive immigrant policies can be protective for educational attainment,90,91 labor market outcomes,92 and other measures of socioeconomic wellbeing,93 which directly influence the resources available to minoritized children. Although studies of the potential benefits of inclusive immigrant policies for child health outcomes are limited, 1 quasi-experimental study of children whose mothers received protection from deportation via the US Deferred Action for Childhood Arrivals program (ie, determined on the basis of their birth date) revealed 50% fewer diagnoses of anxiety and adjustment disorders compared with children who did not receive this protection.94 Further investigation is needed to identify policies, administrative practices, and localized programs that are most effective in advancing health equity. In addition, pediatricians working with Latino children and children in immigrant families should be cognizant of major changes to immigrant-related policies or highly visible discriminatory events and can advocate for strategies to minimize structural or cultural racism, including the removal of exclusionary policies.
Conclusions
This study begins to address significant gaps in the empirical literature on the harmful consequences of discriminatory policies and prejudicial social contexts on children’s health. Beyond the need for a strong pediatric voice in educating policymakers and the general public about this threat to child wellbeing, a deeper understanding of the causal mechanisms that explain these findings is essential for moving beyond documenting the consequences of structural inequities and toward accelerating the development of more effective strategies to prevent, reduce, and/or mitigate their harmful effects.
Dr Slopen conceptualized the study, conducted the data analysis, interpreted the results, wrote the first draft of the manuscript, and integrated the critical contributions of all coauthors; Drs Umaña-Taylor, Shonkoff, and Carle assisted with the interpretation of the study results and critically reviewed and revised the manuscript; Dr Hatzenbuehler conceptualized the study, developed the state-level exposure variable, provided guidance on the study design, assisted with the interpretation of the results, and critically reviewed and revised the manuscript; and all authors approved the final manuscript as submitted and agree to be accountable for all aspects of the work.
COMPANION PAPER: A companion to this article can be found online at www.pediatrics.org/cgi/doi/10.1542/peds.2023-062546.
FUNDING: This work was conducted with support from Harvard Catalyst | The Harvard Clinical and Translational Science Center (National Center for Advancing Translational Sciences, National Institutes of Health award #UL1 TR002541) and financial contributions from Harvard University and its affiliated academic health care centers. The content is solely the responsibility of the authors and does not necessarily represent the official views of Harvard Catalyst, Harvard University, and its affiliated academic health care centers, or the National Institutes of Health.
CONFLICT OF INTEREST DISCLOSURES: The authors have indicated they have no potential conflicts of interest to disclose.
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