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. 2024 Oct 18;29(1):42–52. doi: 10.1177/10870547241290673

Examining the Association Between Adverse Childhood Experiences and ADHD in School-Aged Children Following the COVID-19 Pandemic

Emma Boswell 1,✉, Elizabeth Crouch 1, Cassie Odahowski 1, Peiyin Hung 1
PMCID: PMC11585178  PMID: 39422221

Abstract

Background:

Adverse childhood experiences (ACEs) have long been associated with attention-deficit/hyperactive disorder (ADHD) diagnoses in children; but the data used is now over 6 years old (from 2017 to 2018). Understanding the current landscape of their prevalence and association is needed to capture evolving social, environmental, and economic conditions, and ensure interventions remain relevant to addressing current childhood trauma.

Objective:

This study provides an updated analysis of the association between ACEs and ADHD using post-acute-COVID-19 pandemic data.

Participants and Setting:

This cross-sectional study of 10,518 children aged 5 to 17 years old derived data from the 2021 to 2022 National Health Interview Survey (NHIS).

Methods:

Differences in the prevalence of number (0, 1–3, or 4+) and type of ACEs by ADHD diagnosis were evaluated using Rao-Scott chi-square tests and multivariable logistic regression. All analyses incorporate complex survey weights.

Results:

In 2021 to 2022, 2,457 (23.3%) of children experienced ACEs and 1,115 (9.9%) had an ADHD diagnosis. Children with ADHD were more likely to experience every type of ACE and were more likely to have 1 to 3 or 4+ ACEs than children without ADHD. Children with 4+ ACEs had higher odds of having an ADHD diagnosis (aOR: 3.44, 95% CI [2.64, 4.49]) than children without ACEs. Male children, children with fair or poor health, and children living in rural counties were more likely to have an ADHD diagnosis, while children of color and uninsured children were less likely. We found the odds ratio of ADHD diagnosis for children with four or more ACEs, compared to those without ACEs, slightly lower than found in Brown et al., 2017’s estimate of 3.97 (CI [3.29, 4.80]). These results suggest a consistent association between ACEs and ADHD when comparing pre-COVID data to our post-acute-COVID results.

Conclusions:

These findings highlight the need for clinicians to consider traumatic stress in ADHD screening. Policymakers and early childhood organizations should encourage early screening and intervention for ACEs to reduce the impacts of ADHD diagnoses.

Keywords: adverse childhood experiences, attention deficit/hyperactive disorder, child development and behavior, mental health

Introduction

Attention-Deficit/Hyperactive Disorder (ADHD) is one of the most prevalent developmental disabilities amongst children in the United States; in 2015 to 2017, 9.5% of American children aged 3 to 17 had an ADHD diagnosis (Zablotsky et al., 2019). ADHD begins during childhood and is characterized by persistent hyperactivity, inattention, and impulsivity that impairs the functioning of the child (Carbray, 2018). Compared to their peers without ADHD, children with this diagnosis are more likely to experience impaired social functioning, lower educational attainment, and reduced income and participation in the economy as adults (Fleming et al., 2017; Fletcher, 2014; Ros & Graziano, 2018). The annual cost of ADHD in children in the United States may be as much as $72 billion dollars annually, most of which consists of healthcare and education costs (Doshi et al., 2012). Prior research has demonstrated that childhood trauma may be a contributing factor to the diagnosis and severity of ADHD (Alfonso et al., 2024).

Adverse childhood experiences (ACEs) are potentially traumatic events that occur before a person turns 18 and include experiences such as having a caregiver who was incarcerated, verbal abuse, and living with a person who has a mental illness or uses illicit substances (Felitti et al., 1998). Almost 35% of U.S. children have experienced at least one ACE and around 4% have experienced four or more ACEs (Crouch et al., 2020). The most common ACEs experienced by children are parental divorce, economic hardship, exposure to violence, and living in a disrupted household (Crouch et al., 2019). Previous research has shown that children with ACEs are more likely to be diagnosed with ADHD, and to have behavioral problems in middle childhood, and health and developmental issues throughout life (Crouch et al., 2021; Hunt et al., 2017; Webster, 2022). Compared to children with less than four ACEs, children with four or more ACEs have more than twice as high odds of having an ADHD diagnosis (Crouch et al., 2021). Both the number and type of ACEs are known to be associated with an ADHD diagnosis in children (Brown et al., 2017; Crouch et al., 2021). Previous literature has shown that individual ACE type and number of ACEs are significantly associated with an ADHD diagnosis, and that there is a dose-response relationship between ACE count and ADHD severity (Brown et al., 2017; Crouch et al., 2021; Song, 2023; Walker et al., 2021).

The relationship between ACEs and ADHD diagnosis is complex; the traumatic stress potentially felt by those with ACEs may present itself as hyperactivity or other ADHD symptoms (Alfonso et al., 2024). While current ADHD screening guidelines recommend that clinicians eliminate alternative causes of symptoms and recognize the relationship between trauma and ADHD symptoms, they do not provide specific screening instructions for ACEs or other traumatic stress (Wolraich et al., 2019). Approximately 72% of children and adolescents with ADHD are receiving appropriate treatment, and one of the goals of Healthy People 2030 is to increase this proportion (Office of Disease Prevention and Health Promotion, n.d.). A deeper understanding of the way in which ACES and ADHD are related is important to ensure that children are being diagnosed and treated correctly.

While prior studies have examined the relationship between ACEs and ADHD, the data used was collected between 2017 and 2018 or was limited to a single medical center (Alfonso et al. 2024; Brown et al., 2017; Crouch et al., 2020; Song, 2023; Walker et al., 2021). An updated examination of the prevalence of ADHD and ACEs and their association is particularly relevant following the COVID-19 pandemic, as some studies have demonstrated changes in the prevalence of ADHD symptoms have changed (Breaux, Dvorsky, March, et al., 2021; Raghunathan et al., 2022). Therefore, this study seeks to analyze the association between ACEs, both type and summary number, and ADHD diagnoses in a nationally representative sample of American children using 2 years of data (2021–2022) from the sample child interviews of the National Health Interview Survey (NHIS).

Methods

Data Source and Sample Population

Data from this study comes from 2 years of the NHIS (2021–2022), a nationally representative, cross-sectional survey that has taken place every year since 1957 (NCHS, 2023a). This household interview survey takes place in person (with follow-up information occasionally collected via telephone) and collects data on both adults and children. Topics included in the NHIS Sample Child Interview include lived experiences such as ACEs, healthcare access and utilization, and health status. Survey respondents include household members and those living in non-institutional group quarters, such as homeless shelters and group homes. However, incarcerated people, unhoused people without a fixed address, active-duty military personnel, people living in long-term care institutions (such as nursing homes), and U.S. citizens not currently living in the United States are not included.

After a household or group quarter has been chosen to participate via geographically clustered sampling techniques, an adult and child living there are randomly selected (NCHS, 2023a). Information about the child is provided by a knowledgeable adult in the household; this adult may or may not be the parent or caregiver of the selected child, and they may or may not be the sample adult who was chosen to participate in the adult interview. The design and sample weighting utilized by the NHIS ensures that it is nationally representative, but state-level data is suppressed and it is unclear if there are participants from all states included in the survey.

A total of 14,829 children participated in the NHIS Sample Children’s Interview in 2021 to 2022. Of the 10,911 school-aged children in the sample, 314 were removed due to missing responses to questions about ACEs and 35 were removed because they had missing responses regarding their ADHD diagnosis. Forty-eight participants were removed due to missing responses regarding the respondent’s relationship with the child, child sex, general health status, or insurance status. The main analytic sample consisted of child participants aged 5 to 17 who had complete information regarding all variables of interest (n = 10,518; see Figure 1).

Figure 1.

Figure 1.

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Derivation of main analytic sample.

Measures

The key independent variable was exposure to ACEs, including both the type of ACE and the number of ACEs. In 2021 to 2022, the NHIS asked eight questions regarding ACEs, including exposure to neighborhood violence, having an incarcerated caregiver, living with an adult who had mental illness or depression or who used illicit substances, being the victim of verbal abuse, ever having their basic needs not met, or experiencing mistreatment due to race/ethnicity or sexual orientation and gender identity (NCHS, 2022, 2023b). Exposure to mistreatment due to sexual identity was not evaluated in this study because it is only asked for participants aged 12 to 17 years old (NCHS, 2022, 2023b) and therefore would be missing for 60.0% of the study’s sample. Responses to each type of ACE were classified as yes or no; participants with responses of “refused,” “unknown,” or “don’t know” were treated as missing. A participant’s total number of ACEs was determined by counting the number of times they had a response of “yes” to the seven included categories of ACEs and was then categorized as none, one to three ACEs, and four or more ACEs, consistent with similar literature studying ACEs (Crouch et al., 2020, 2021).

The outcome for this study was a current diagnosis of ADHD. Participants were asked if the sample child had ever received a diagnosis of ADHD or Attention-Deficit Disorder (ADD) from a doctor or health professional, and if yes, they were asked if the sample child currently had a diagnosis of ADD or ADHD (NCHS, 2022, 2023b). If the response to both of these questions was yes, the participant was defined as having ADHD.

Covariates

Covariates for this study included survey year, race/ethnicity, age, insurance type, general health status, respondent’s relationship with the sample child, household region, adult educational attainment, poverty/income level, and rural residence and were chosen based on Andersen’s Healthcare Utilization Model (Andersen, 1995). Predisposing or demographic characteristics included race/ethnicity, sex, age, household region, and rural residence (Andersen, 1995). The race/ethnicity of participants was classified as Hispanic, Non-Hispanic White, Non-Hispanic Black, and multiracial or other races. Age was grouped as 5 to 12 years old and 13 to 17 years old. Household region was defined according to Census regions and categorized as Northeast, South, Midwest, and West. Rural residence was defined at the county level as urban (living in a metropolitan county) and rural (living in a non-metropolitan county) based on a NHIS variable which utilizes the 2013 National Center for Health Statistics (NCHS, 2017, 2022, 2023b) Urban-Rural Classification Scheme. The four-level scheme was dichotomized; levels 1 to 3 were classed as metropolitan, and level 4 was classed as metropolitan.

Perceived or actual need of healthcare services was assessed via the variable regarding general health status, through which participants were classified as having good, very good, or excellent health or fair or poor health. Enabling factors included the relationship between the child and the respondent, the highest level of education for an adult in the household, poverty/income level, and insurance status. Based on the distribution of responses, relationship type was categorized as parent, grandparent, or other. The highest level of education for an adult in the household was divided into having a high school diploma or less versus having some college education or more. Poverty/income level was defined according to the federal poverty line (FPL) and separated into being 0% to 99% of the FPL, being 100% to 199% of the FPL, being 200% to 399% of the FPL, or 400% or more of the FPL. Insurance status was described as private, public, other, or none. For all variables, responses of “refused,” “not ascertained,” or “unknown” were treated as missing.

Analyses

All guidelines regarding sample design, weighting, and multiple years of data were followed while conducting the analysis for this study. All analyses were completed using Statistical Analysis Software (SAS; Version 9.4), and a significance level of .05 was used. Bivariate analyses, including the distributions of child and household characteristics by ADHD diagnosis and by whether a child had experienced four or more ACEs, were conducted and compared using chi-square tests. Logistic regression was used to determine the odds of having a current ADHD diagnosis. This model was adjusted for all predisposing, need, and enabling factors. All analysis incorporated relevant weights and strata. This study was deemed exempt by the University of South Carolina Institutional Review Board.

Results

Respondents were evenly distributed amongst survey years (46.7% in 2021, see Table 1) and sexes (51.0% male). They were more likely to have good, very good, or excellent health (97.4%), have an adult in the household with some college education or more (76.9%), have an income level of 400% or more of the FPL (33.7%), and live in an urban county (86.9%). There were no differences in survey year, educational attainment of adults, or poverty/income level by ADHD diagnosis. However, children with ADHD were more likely to be male (65.6% vs. 49.4%, p < .0001), have fair or poor health (6.8% vs. 2.2%, p < .0001) and live in a rural county (16.0% vs. 12.8%, p = .006) than children without this diagnosis.

Table 1.

Characteristics of Child Respondents to 2021 to 2022 National Health Interview Surveys, by ADD/ADHD Diagnosis (n = 10,518).

Characteristic Overall (n = 10,518)
 Current ADHD diagnosis (n = 1,115)
 No ADHD diagnosis (n = 9,403)
 p-Value
% SE % SE % SE
Survey year .1
 2021 46.7 0.6 44.1 1.7 47.0 0.7
 2022 53.3 0.6 55.9 1.7 53.0 0.7
Child characteristics
Sex <.0001
 Male 51.0 0.6 65.6 1.6 49.4 0.6
 Female 49.0 0.6 34.4 1.6 50.6 0.6
Race/ethnicity <.0001
 Hispanic 25.5 1.0 18.0 1.5 26.4 1.0
 Non-Hispanic White 51.7 1.0 68.8 1.7 50.5 1.0
 Non-Hispanic Black 12.1 0.6 11.8 1.4 12.2 0.6
 Multiracial or other race 10.6 0.4 7.3 0.9 11.0 0.4
Age <.0001
 5–12 years old 60.0 0.6 49.1 1.8 61.2 0.6
 13–17 years old 40.0 0.6 50.9 1.8 38.8 0.6
Insurance type .0005
 Private 56.3 0.8 52.2 1.8 56.7 0.8
 Public 36.1 0.8 41.8 1.8 35.5 0.8
 Other 3.4 0.3 3.4 0.7 3.4 0.3
 None 4.2 0.3 2.6 0.5 4.4 0.3
General health status <.0001
 Fair or poor 2.6 0.2 6.8 1.0 2.2 0.2
 Good, very good, or excellent 97.4 0.2 93.2 1.0 97.8 0.2
Family characteristics
Respondent’s relationship to child .001
 Parent 94.9 0.3 92.6 0.9 95.1 0.3
 Grandparent 3.2 0.2 5.2 0.8 3.0 0.2
 Other 2.0 0.2 2.2 0.5 1.9 0.2
Household region <.0001
 Northeast 15.9 0.7 13.7 1.3 16.1 0.7
 Midwest 20.8 0.8 21.5 1.5 20.8 0.8
 South 39.1 1.1 46.2 2.1 38.4 1.1
 West 24.2 1.1 18.7 1.7 24.8 1.1
Caregiver educational attainment 0.7
 High school diploma or less 23.5 0.6 24.1 1.6 23.5 0.7
 Some college or more 76.5 0.6 75.9 1.6 76.5 0.7
Poverty/income level 0.1
 0%–99% FPL 15.0 0.5 17.7 1.6 14.7 0.6
 100%–199% FPL 22.4 0.6 21.8 1.5 22.5 0.6
 200%–399% FPL 29.0 0.5 27.0 1.5 29.2 0.6
 400% FPL or more 33.7 0.7 33.5 1.7 33.7 0.8
Rurality 0.006
 Urban 86.9 0.7 84.0 1.4 87.2 0.7
 Rural 13.1 0.7 16.0 1.4 12.8 0.7
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Children with diagnosed ADHD were more likely to be Non-Hispanic White (68.8% vs. 50.5%, p < .0001), be 13 to 17 years old (50.9% vs. 38.8%, p < .0001) than those without a diagnosis. While private insurance was the most common type of insurance for all participants (56.3%), children with ADHD were more likely to have public insurance (41.8% vs. 35.5%) and less likely to be uninsured (2.6% vs. 4.4%) than children without ADHD (p < .0001). Having the respondent be the parent of the sample child was the most common respondent–child relationship (94.9%) but children with ADHD were more likely to have a respondent who was a grandparent (5.2% vs. 3.0%) or another household member (2.2% vs. 1.9%) than children without ADHD (p = .001). Participants with ADHD were more likely to live in the South (46.2% vs. 38.4%) and less likely to live in the West (18.7% vs. 24.8%) than participants without ADHD (p < .0001).

Children with ADHD were more likely to have experienced each type of ACE and have higher total numbers of ACEs than children without ADHD (Table 2). Children with ADHD had a higher prevalence of witnessing or being a victim of neighborhood violence (13.8% vs. 5.5%, p < .001), having an incarcerated parent or guardian (11.8 vs. 5.9%, p < .0001), living with a person with mental illness or depression (20.8% vs. 7.9%, p < .0001), living with a person with substance abuse issues (17.7% vs. 8.2%, p < .0001), being the victim of verbal abuse (11.1% vs. 3.8%, p < .0001), ever having their basic needs not met (6.5% vs. 2.9%, p < .0001), or experiencing mistreatment due to their race or ethnicity (8.9% vs. 5.0%, p < .0001) than children without ADHD. While the majority of all participants had not experienced any ACEs (76.7%), children with ADHD were more likely to have 1 to 3 ACEs (29.9% vs. 16.9%) or four or more ACEs (11.6% vs. 4.4%) than children without ADHD (p < .0001).

Table 2.

Prevalence of ACE Exposure Among National Health Interview Survey Child Respondents, 2021 to 2022, by ADD/ADHD Diagnosis (n = 10,518).

ACE exposure Overall (n = 10,518)
 Current ADHD diagnosis (n = 1,115)
 No ADHD diagnosis (n = 9,403)
 p-Value
% SE % SE % SE
ACE type
Victim of or witnessed neighborhood violence <.0001
 Yes 6.3 0.3 13.8 1.2 5.5 0.3
 No 93.7 0.3 86.2 1.2 94.5 0.3
Incarcerated parent or guardian <.0001
 Yes 6.5 0.3 11.8 1.2 5.9 0.3
 No 93.5 0.3 88.2 1.2 94.1 0.3
Lived with a person with mental illness or depression <.0001
 Yes 9.1 0.4 20.8 1.3 7.9 0.4
 No 90.9 0.4 79.2 1.3 92.1 0.4
Lived with a person with substance abuse issues <.0001
 Yes 8.9 0.4 15.7 1.2 8.2 0.4
 No 91.1 0.4 84.3 1.2 91.8 0.4
Victim of verbal abuse <.0001
 Yes 4.5 0.3 11.1 1.0 3.8 0.3
 No 95.5 0.3 88.9 1.0 96.2 0.3
Ever a time when basic needs not met <.0001
 Yes 3.3 0.2 6.5 0.8 2.9 0.2
 No 96.7 0.2 93.5 0.8 97.1 0.2
Mistreated because of race/ethnicity <.0001
 Yes 5.4 0.3 8.9 1.0 5.0 0.3
 No 94.6 0.3 91.1 1.0 95.0 0.3
ACE summary score <.0001
 0 ACEs 76.7 0.5 58.4 1.7 78.7 0.6
 1–3 ACEs 18.2 0.5 29.9 1.6 16.9 0.5
 4+ ACEs 5.1 0.3 11.6 1.1 4.4 0.3
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After adjusting for survey year, sex, race/ethnicity, age, insurance, health status, relationship between respondent and child, household region, adult educational attainment, income/poverty level, and rural residence, a higher number of ACEs was associated with greater odds of having a current ADHD diagnosis (Table 3). Children with 1 to 3 ACEs had more than two times greater odds (aOR: 2.28, 95% CI [1.92, 2.71]) of having an ADHD diagnosis than children with no ACEs, and children with four or more ACEs had almost 3.5 times greater odds of having a current ADHD diagnosis (aOR: 3.44, 95% CI [2.64, 4.49]) than children without ACES. The odds of having an ADHD diagnosis did not differ significantly based on survey year, household region, or adult educational attainment. Male participants had greater odds of having an ADHD diagnosis than females (aOR: 2.04, 95% CI [1.76, 2.37]).

Table 3.

Odds of Having an ADHD Diagnosis by ACE Exposure, 2021 to 2022 (n = 10,518).

Characteristic Adjusted odds ratios of ADHD diagnosis [95% CIs]
ACE exposure
 No ACEs Reference Reference
 1–3 ACEs 2.28 [1.92, 2.71]
 4+ ACEs 3.44 [2.64, 4.49]
Survey year
 2021 Reference Reference
 2022 1.08 [0.93, 1.25]
Child characteristics
Sex
 Male 2.04 [1.76, 2.37]
 Female Reference Reference
Race/ethnicity
 Hispanic 0.51 [0.41, 0.63]
 Non-Hispanic White Reference Reference
 Non-Hispanic Black 0.66 [0.51, 0.85]
 Multiracial or other race 0.50 [0.38, 0.65]
Age
 6–12 years old Reference Reference
 13–17 years old 1.48 [1.27, 1.72]
Insurance type
 Private Reference Reference
 Public 1.14 [0.93, 1.40]
 Other 1.18 [0.77, 1.80]
 None 0.59 [0.38, 0.91]
General health status
 Fair or poor 2.79 [1.95, 3.99]
 Good, very good, or excellent Reference Reference
Family characteristics
Respondent’s relationship to child
 Parent Reference Reference
 Grandparent 1.43 [0.92, 1.90]
 Other 0.82 [0.50, 1.33]
Household region
 Northeast Reference Reference
 Midwest 1.11 [0.86, 1.42]
 South 1.34 [1.07, 1.68]
 West 0.84 [0.65, 1.08]
Adult educational attainment
 High school diploma or less 1.00 [0.82, 1.23]
 Some college or more Reference Reference
Poverty/income level
 0%–99% FPL 0.96 [0.72, 1.27]
 100%–199% FPL 0.79 [0.63, 0.98]
 200%–399% FPL 0.83 [0.69, 1.01]
 400% FPL or more Reference Reference
Rurality
 Urban Reference Reference
 Rural 1.24 [1.03, 1.49]
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Hispanic participants (aOR: 0.51, 95% CI [0.41, 0.63]), Non-Hispanic Black participants (aOR: 0.66, 95% CI [0.51, 0.85]), and participants who are multiracial or are other races (aOR: 0.50, 95% CI [0.38, 0.65]) all have lower odds of a current ADHD diagnosis than Non-Hispanic White participants. Children with fair or poor health had greater odds (aOR: 2.79, 95% CI [1.95, 3.99]) of having an ADHD diagnosis than children with good, very good, or excellent health. Only uninsured children had lower odds (aOR: 0.59, 95% CI [0.38, 0.91]) of having a current ADHD diagnosis than privately insured children; compared to privately insured children, the odds of having an ADHD diagnosis among those with public or other forms of insurance were not significant. Children who live at 100%–199% of the FPL had lower odds (aOR: 0.79, 95% CI [0.63, 0.98]) of having a current ADHD diagnosis than those at 400% or more of the FPL, but there were no other significant odds for different income/poverty levels. Children who live in rural counties have higher odds (aOR: 1.24, 95% CI [1.03, 1.49]) of having a current ADHD diagnosis than children living in urban counties.

Discussion

This study is the first to provide an updated analysis of the association between ACEs and ADHD in school-aged children since the COVID-19 pandemic. Prior research has found a higher prevalence of ACEs and ADHD symptoms during the pandemic, but was either limited to adolescent participants, or only examined ADHD symptoms during the pandemic without examining its relationship with ACEs (Anderson et al., 2022; Rogers & MacLean, 2023). Pre-pandemic literature found similar associations between ACEs and ADHD; both type and number of ACEs are associated with an increased likelihood of an ADHD diagnosis (Brown et al., 2017; Crouch et al., 2021; Song, 2023; Walker et al., 2021). We found the odds ratio of ADHD diagnosis of 3.44 (CI [2.64, 4.49]) for children with four or more ACEs, compared to those without ACEs, slightly lower than found in Brown et al., 2017’s estimate of 3.97 (CI [3.29, 4.80]). These results suggest a consistent association between ACEs and ADHD when comparing pre-COVID data to our post-acute-COVID results. Additionally, the odds of having an ADHD diagnosis did not differ by insurance type in this study, as reported in a prior publication (Crouch et al., 2021). In the current study, we found that all types of ACEs examined were associated with a higher likelihood of having a current ADHD diagnosis, and that there was a dose response-relationship between the number of ACEs and the odds of having an ADHD diagnosis; the higher number of ACEs a child has, the greater the odds of one having a current ADHD diagnosis. The association between ACEs and ADHD diagnosis demonstrates the widespread impact that adverse stress has on children.

Our study found lower odds of a current ADHD diagnosis among children of color, similar to some previous literature (Davis et al., 2021; Morgan et al., 2013; Morgan & Hu, 2023). There is mixed evidence about the association between race/ethnicity and ADHD diagnosis; some literature has found that children of color who have ADHD are less likely to receive treatment for the condition (using data from 1998 to 2017; Davis et al., 2021; Morgan et al., 2013; Morgan & Hu, 2023) while other studies (using data from 2016 to 2018) found that non-Hispanic Black children were more likely to have an ADHD diagnosis than non-Hispanic White children (Zablotsky & Alford, 2020). Differences in the prevalence of diagnosis and treatment may be due to different levels of knowledge or views about ADHD among caregivers or biases among healthcare providers (Bailey & Owens, 2005). Unlike previous studies (Crouch et al., 2021; Walker et al., 2021), this study found significant differences in the odds of having an ADHD diagnosis between non-Hispanic Black children and non-Hispanic White children. Future research is needed to better define the association between race/ethnicity and ADHD and examine how this association may have changed after the COVID-19 pandemic, as the pandemic had a disproportionately large impact on families and children of color (Clawson et al., 2021).

Results from this study also demonstrate that male children have greater odds of having a current ADHD diagnosis than female children. This is consistent with prior literature reporting girls have lower odds of ADHD diagnosis and treatment (Morgan & Hu, 2023; Pastor et al., 2015). This may be due to differences in ADHD symptom presentation between boys and girls, differences in the perceptions of these symptoms, or referral bias (girls are less likely to be referred for ADHD treatment) rather than true differences in ADHD prevalence (Mowlem et al., 2019; Rucklidge, 2010). Adolescents (ages 13–17 years old) had greater odds of a current ADHD diagnosis when compared to younger children, possibly due to increasing likelihood of ADHD diagnosis with age, or due to repeated and unresolved exposure to ACEs, which previous studies have shown are more prevalent in older children (Crouch et al., 2019).

Higher ADHD diagnosis among children with ACE exposures suggest that ongoing efforts to improve these children’s quality of life should focus on promoting resiliency in children with ADHD and consider addressing their needs beyond clinical diagnosis. Prior research has shown that children and ACEs that have individual, family, and community resilience had lower odds of being diagnosed with ADHD or other behavioral disorders and that early detection and intervention for children with ACEs is the key to mitigating the impact of ACEs (Adaralegbe et al., 2022; Okwori, 2022). Early childhood organizations, policy makers, and clinicians should encourage the implementation of interventions which promote the development of resilience amongst children with ACEs. Implementing more frequent screenings for ACEs to improve early detection and intervention in children with ACEs could result in a significant reduction in ADHD symptoms, therefore improving quality of life and reducing costs associated with ADHD diagnoses. Program developers should also consider addressing individual or specific types of ACEs, as this study shows that type of ACE is also associated with the likelihood of an ADHD diagnosis. Tailored programming may result in further reduction of symptomology and costs.

The findings from this study are particularly beneficial for clinicians, particularly regarding ADHD screening and care. This study found a positive association between ACE exposure and the odds of a current ADHD diagnosis, which supports the current ADHD screening guidelines on acknowledging traumatic stress and ADHD symptomology (Wolraich et al., 2019). Yet, a lack of specific recommendations on screening for traumatic stress in the current guideline (Wolraich et al., 2019) might result in delays in diagnosis, referral, and treatment. Indeed, despite the higher prevalence of ACEs among children of color (Crouch et al., 2019), this study found that these children had lower odds of a current ADHD diagnosis. These results highlight the need for clinicians to consider implementing ACE screening when evaluating patients for ADHD. Traumatic stress is known to present itself as hyperactivity, and a correct diagnosis is needed to ensure that children are receiving the most appropriate interventions (Alfonso et al., 2024).

Strengths and Limitations

The sampling design and low levels of missingness in the NHIS allow for accurate, nationally representative estimates for analyses. The NHIS collects data about a large number of demographic and household characteristics which may be associated with ACEs and ADHD. Some previous literature lacks an analysis of these factors, and their inclusion in this study results in a more robust evaluation (Brown et al., 2017).

The cross-sectional nature of the NHIS results does not allow for examination of causal and temporal relationships between ACEs and ADHD (NCHS, 2023a). Data from the NHIS Sample Child Interview is reported by an adult in the household who is knowledgeable about the child participant, and therefore is subject to recall and social desirability biases, as most self-reported data. State-level identifiers are suppressed in publicly available NHIS data, so it is unclear if every state is represented in the sample, and state estimates are not able to be created. Compared to similar studies, the number of participants with ADHD is relatively low (n = 1,115), which may limit generalizability (Crouch et al., 2021; Walker et al., 2021). This study did not examine trends in the association between ACEs and ADHD before, during, and after the COVID-19 pandemic, in part due to the NHIS redesign in 2019, which means data from 2018 and earlier cannot be pooled or compared with data from 2019 or later (NCHS, 2023a). Due to small sample sizes, data from 2019 alone does not result in enough participants to be able to examine trends in pre-, peri-, and post-COVID-19. As more data becomes available, future studies should examine trends in the prevalence of ACEs and their known associations in the years during and surrounding the COVID-19 pandemic, with particular emphasis placed on all factors that may result in a change in the prevalence of ACEs, such as death of a loved one. Finally, due to data limitations, this study was not able to evaluate the association between exposure to ACEs and ADHD severity; prior research has found that children with ACEs are more likely to have moderate to severe ADHD (Crouch et al., 2021).

Conclusions

Exposure to ACEs, including type and number of ACEs, is associated with caregiver-reported ADHD diagnosis in school-aged children in the United States. Future research should further investigate the associations between ADHD diagnosis and race/ethnicity, rural residence, insurance status, and positive childhood experiences. Clinicians should consider evaluating traumatic or adverse stress when screening for ADHD in children to ensure correct diagnosis and treatment. Policymakers and early childhood organizations should support the implementation of evidence-based interventions that are known to promote resilience, which may mitigate the impact of ACEs and therefore reduce the cost of ADHD diagnosis and improve the quality of life for those who do receive a diagnosis.

Author Biographies

Emma Boswell is a PhD student in the Department of Health Services, Policy, and Management at the Arnold School of Public Health at the University of South Carolina. Her research interests include rural health, health disparities, and maternal and child health.

Dr. Elizabeth Crouch is the co-director of the Rural and Minority Health Research Center and an associate professor in the Arnold School of Public Health at the University of South Carolina. Her research interests include rural health, health disparities, and childhood experiences.

Dr. Cassie Odahowski is a research assistant professor at the Rural and Minority Health Research Center at the University of South Carolina. Her research interests include spatial epidemiology, rural health, and health disparities.

Dr. Peiyin Hung is the co-director of the Rural and Minority Health Research Center and an associate professor in the Arnold School of Public Health at the University of South Carolina. Her research interests include rural health, health disparities, and maternal and child health.

Footnotes

Author Contributions: Emma Boswell: Methodology, Writing-original draft preparation. Elizabeth Crouch: Conceptualization, Methodology, Writing-Reviewing and Editing. Cassie Odahowski: Writing-Reviewing and editing. Peiyin Hung: Writing-Reviewing and editing, Validation.

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

Funding: The author(s) received no financial support for the research, authorship, and/or publication of this article.

Ethical Approval and Informed Consent: The Institutional Review Board at the University of South Carolina approved this research. Informed consent was not required as this study was based on publicly available data.

Data Availability: Data is publicly available for download from the CDC’s National Health Interview Survey.

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