Introduction
To examine associations between patient characteristics and adverse childhood experiences (ACEs) in a population-based sample of pediatric primary care patients, using electronic health records and clinical, administrative data.
Method
An observational study was conducted in an integrated health care delivery system. Children ages 1–5 years (N = 13,370) were screened for ACEs at routine well-child visits between September 1, 2018 and May 31, 2019 in three pediatrics clinics. Multivariate models examined associations between patient characteristics (age, gender, race/ethnicity, insurance type, neighborhood income and education level, physical, mental health and developmental diagnoses, weight status) and any ACEs, and ≥ 3 ACEs exposure.
Results
Prevalence and severity of ACE exposure varied by race/ethnicity. Older age, Medicaid insurance, epilepsy/seizure disorder, sleeping disorders, adjustment disorders, and feeding disorders were associated with higher odds of ACEs exposure, higher-income with lower odds.
Discussion
Understanding relationships between ACEs and patient features can provide information to clinicians for early detection and appropriate interventions.
KEY WORDS
INTRODUCTION
Adverse childhood experiences (ACEs) are exposures during childhood to traumatic events or circumstances such as abuse and neglect, household dysfunction, or environmental stressors, including neighborhood violence, poverty, and discrimination. ACEs are associated with several common, chronic medical and mental health conditions and earlier mortality in adults, with a strong, graded, dose–response relationship between the number of ACEs and health problems (
Anda et al., 1999
; Anda et al., 2009
; Anda et al., 2008
; Bright and Thompson, 2018
; Brown et al., 2009
; Brown et al., 2010
; Brown et al., 2006
; Chapman et al., 2004
; Dong et al., 2004
; Dong et al., 2003
; Dube et al., 2001
; Dube et al., 2009
; Edwards et al., 2003
; Felitti, 1993
; Felitti, 2009
; Felitti et al., 1998
; Hillis et al., 2000
; Williamson et al., 2002
). Furthermore, there is growing recognition among health care clinicians of the detrimental long-term impact ACEs may have on the health and wellbeing of their patients, adversely affecting not only health but also their social and economic potential (Metzler et al., 2017
).Regarding adverse physical, mental, and developmental outcomes (
Bright et al., 2016
), children exposed to ACEs and chronic, toxic stress may be at increased risk of negative sequelae, including interrupted neurodevelopment, abnormal cortisol levels, poorer cardiovascular health, hyperarousal, diminished executive functioning, educational difficulties, delayed developmental milestones, asthma, infection, somatic complaints, sleep disruption, and obesity (Bucci et al., 2016
; Lynch et al., 2016
; Oh et al., 2018
; Pretty et al., 2013
). ACEs may also exacerbate chronic health conditions in children, including chronic pain (Nelson et al., 2017
), contributing to treatment complications and delayed care (Berg et al., 2018
). Although ACEs occur across the general population, certain subpopulations, including those of lower socioeconomic status, children of mothers who have lower educational attainment, and African American children, may be particularly vulnerable (Hunt et al., 2017
).Understanding the relationship between ACEs, patient characteristics, and pediatric health conditions enable us to improve early detection and intervention efforts which could shift the life trajectory of children with early exposure (
Asmussen et al., 2019
; Barnes et al., 2020
; Gillespie, 2019
; Melville, 2017
). Patient characteristics are easily assessed in clinical settings and could be used to enhance and refine current screening protocols (Finkelhor, 2018
) and provide guidance to pediatric health care clinicians on when to expand their ACEs assessment. Finally, refined screening procedures may improve health care clinicians’ promotion and disease prevention and management efforts, health care delivery decisions, and ultimately, the current and future quality of life of their patients and their families.To gather evidence on potentially important associations of demographic and clinical characteristics and (risk for) ACEs exposure, we examined electronic health record (EHR) data in a large, diverse pediatric primary care patient sample. Specifically, parental ACE reports of children aged 1–5 years were collected at annual well-child visits, in addition to children's sociodemographic characteristics (e.g., gender, race/ethnicity, socioeconomic status based on geocoding); clinical characteristics (e.g., physical, mental health and developmental comorbidities); and administrative data such as insurance product type (Medicaid vs. commercial/other). We also examined overall ACEs prevalence and distribution of ACEs severity among children screening positive. We hypothesized that ACEs exposure and severity would be associated with a higher prevalence of physical, mental health, and developmental problems and investigated associations between ACEs exposure and demographic and socioeconomic status variables.
METHODS
Setting
Kaiser Permanente Northern California (KPNC) is a large, not-for-profit integrated health care delivery system serving the Northern California region. KPNC's 4.3 million members represent about a third of Northern California's population. The membership is insured through employer-based plans, Medicare, Medicaid, and health insurance exchanges, and is highly representative of the U.S. population with access to care: 53% female, 20% Asian/Pacific Islander (API), 7.5% African American, and 17% Hispanic (
Gordon, 2015
).Study Sample
Screening for ACEs was instituted in 2017 in three large KPNC general pediatric clinics. The eligible cohort consisted of all children aged 1–5 years who had a routine well-child visit in these clinics between September 1, 2018 to May 31, 2019. We used EHR and clinical, administrative data to determine whether they were screened for ACEs on the basis of data collected during clinical processes. If the screening occurred at multiple visits within the study period, the index screening was defined as the first visit. This analysis was conducted within the context of an evaluation of the feasibility of implementing routine ACEs screening in children aged 1–5 years.
ACEs Screening Workflow
Children in the KPNC health care system typically have well-child visits, that is, routine health check-ups with their pediatrician, at 1 year, 15–18 months, 2 years, 3 years, 4 years, and 5 years old, at which the clinician conducts an overall assessment of the patient's health, including physical and emotional/mental health, growth and development, and provides anticipatory guidance and advice about parenting skills, healthy habits, and management of health conditions. On presentation at the clinic reception for their child's 1–5-year-old well-child visits, parents were asked to complete a paper and pencil ACEs questionnaire before seeing the clinician (Supplementary Data). Parents could indicate the specific ACEs their child was exposed to or could simply indicate the number of exposures (i.e., they had a choice between answering the questionnaire in an "identified" or "deidentified" manner). The questionnaire was collected by a medical assistant, and the results were reviewed by the pediatrician in the exam room. On the basis of the child's score (0 ACEs = low risk, 1–2 ACEs and asymptomatic = intermediate risk, ≥ 3 ACEs or ≥ 1 ACEs and symptomatic = high risk), an appropriate intervention was provided. Asymptomatic was defined as the clinician not finding any significant behavioral, developmental, sleep issues or evidence of poor disease control; Symptomatic was defined as ≥ 1 of these concerns detected during the visit. Parents of a child with a 0 ACEs score were given reassurance and information about local resources; intermediate-risk families were provided with anticipatory guidance and information about resources within KPNC Child and Adolescent Psychiatry or from local community-based organizations for at-risk families. Clinicians actively referred high-risk families to KPNC Child and Adolescent Psychiatry and/or community organizations for assessment and services as needed.
Measures
ACEs exposure
The ACEs questionnaire, informed by the original ACEs instrument (
Felitti et al., 1998
) as well as one adapted for pediatric populations (), contained items assessing exposure since birth, to physical abuse or neglect, sexual abuse, emotional abuse or neglect, witnessing domestic violence, substance misuse or mental illness within the household, experiencing parental separation or divorce, or having an incarcerated household member, foster care placement, food, housing or clothing insecurity, family separation, life-threatening illness, or neighborhood violence, and generated a count of ACEs exposures. Scores on the ACEs questionnaire were recorded in a clinical database at each site.Patient characteristics
The EHR was used to extract patient age, gender, race/ethnicity, insurance type, neighborhood income and education level, and comorbidities. In the year before each patient's index screening date, the presence of a physical (e.g., asthma, epilepsy, or seizure disorder), mental or behavioral health (e.g., adjustment disorders, behavioral problems, and conduct disorders), and developmental (e.g., autism spectrum disorders and developmental delay) diagnosis (yes/no) was identified on the basis of International Classification of Diseases (ICD)–10 codes (codes available on request). Using U.S. Centers for Disease Control and Prevention criteria (
Centers for Disease Control and Prevention 2018
), weight status was divided into four groups (underweight, normal weight, overweight, and obese) according to body mass index.Statistical Analysis
All analyses were conducted using SAS (version 9.4; Cary, NC). Among those who were screened for ACEs, we examined associations between each of the patient characteristics and having any ACEs exposure, using χ2 tests or Fisher's exact tests. A multivariate logistic regression model was fit predicting having any ACEs exposure, including all the patient characteristics that were significant at p <.05 in the bivariate analyses, while controlling for the study site. Similar analyses were conducted to examine associations between patient characteristics and having ≥ 3 ACEs exposure among those with any ACEs exposure.
Institutional Review Board Approval and Guidelines Followed
The study was approved by the KPNC Institutional Review Board. Informed consent was not required because a routine clinical procedure was evaluated. The report followed the Strengthening the Reporting of Observational Studies in Epidemiology guideline for cross-sectional studies.
RESULTS
From September 1, 2018 to May 31, 2019, a total of 18,021 children aged 1–5 years had a well-child visit at the study sites. The study clinics had participated in a staff training pilot period from May 31, 2018 to August 31, 2018; among the 18,021 children with a well-child visit during the study period, 25 (0.1%) already had a well-child visit with ACEs screening during the pilot study period, and thus were excluded. Out of the remaining 17,996 children, 13,370 (74%) received an ACEs screening, with average screening rates varying from 62% to 86% across the three study sites and no significant trend in screening rates over time. Information about the reason a child was not screened was not consistently documented, and it is unclear whether those not screened were not offered the screener, if there was not enough time to complete it, or if they refused to complete it.
No differences were found in screening rates by children's gender or insurance type; however, significantly higher screening rates were found among children with Black race/ethnicity, aged 3–4 years, and those living in a neighborhood with high levels of deprivation (i.e., census tract with lower education level and lower median neighborhood household income; not shown).
Eighty-nine percent of the sample reported experiencing no ACEs, 8% experienced 1 ACE, 2% experienced 2 ACEs, and 1% experienced ≥ 3 ACEs (Table 1). We found no association between a child's gender and reporting any ACEs. However, we found associations between positive ACE screening and African American or Hispanic racial/ethnic background, older age, living in a neighborhood with lower income and education level, and ever Medicaid insured (Table 2). Among the health conditions examined, we found a higher prevalence of asthma, bone, joint or muscle problems, brain injury or concussion, epilepsy or seizure disorder, obesity, overweight, sleep disorders, adjustment disorders, behavioral problems, conduct disorders, feeding problems, and autism spectrum disorders among those reporting experiencing any ACE exposure (Table 3). The prevalence of atopic dermatitis and underweight was significantly lower among those reporting any ACEs exposure.
TABLE 1dverse childhood experiences (N = 13,370)
| No. of ACEs | Site A | Site B | Site C | All |
|---|---|---|---|---|
| 0 | 3,084 (93.0) | 5,457 (87.6) | 3,381 (88.4) | 11,922 (89.2) |
| 1 | 171 (5.2) | 567 (9.1) | 307 (8.0) | 1,045 (7.8) |
| 2 | 42 (1.3) | 128 (2.1) | 87 (2.3) | 257 (1.9) |
| 3 | 15 (0.5) | 42 (0.7) | 34 (0.9) | 91 (0.7) |
| 4 | 5 (0.2) | 21 (0.3) | 10 (0.3) | 36 (0.3) |
| 5 | 0 (0.0) | 9 (0.1) | 4 (0.1) | 13 (0.1) |
| 6 | 1 (< 0.1) | 1 (< 0.1) | 1 (< 0.1) | 3 (< 0.1) |
| 7 | 0 (0.0) | 1 (< 0.1) | 1 (< 0.1) | 2 (< 0.1) |
| 8 | 0 (0.0) | 0 (0.0) | 0 (0.0) | 0 (0.0) |
| 9 | 0 (0.0) | 1 (< 0.1) | 0 (0.0) | 1 (< 0.1) |
Note. ACEs, adverse childhood experiences. Values are n (%).
TABLE 2Sample characteristics by adverse childhood experience ACE exposure
| Among those who were screened | Among those with any ACEs | |||||
|---|---|---|---|---|---|---|
| Patient Characteristics | No ACE (N = 11,922) | Any ACEs (N = 1,448) | p value | 1-2 ACEs (N = 1,302) | ≥3 ACEs (N = 146) | p value |
| Gender | .3224 | .4421 | ||||
| Female | 48.4 | 49.7 | 49.4 | 52.7 | ||
| Male | 51.7 | 50.3 | 50.6 | 47.3 | ||
| Race/Ethnicity | <.0001 | .0131 | ||||
| API | 44.4 | 19.7 | 20.7 | 10.3 | ||
| AA | 4.9 | 9.2 | 9.1 | 10.3 | ||
| Hispanic | 29.3 | 44.3 | 44.3 | 43.8 | ||
| Other | 6.6 | 6.6 | 6.5 | 7.5 | ||
| White | 14.8 | 20.2 | 19.4 | 28.1 | ||
| Age at index visit | <.0001 | .0494 | ||||
| 1 year | 30.0 | 19.9 | 20.9 | 11.0 | ||
| 2 years | 18.0 | 14.5 | 14.4 | 15.8 | ||
| 3 years | 17.4 | 18.0 | 17.7 | 19.9 | ||
| 4 years | 21.5 | 27.8 | 27.0 | 34.3 | ||
| 5 years | 13.1 | 19.9 | 20.0 | 19.2 | ||
| Median household income | <.0001 | .0289 | ||||
| 1st Quartile | 25.4 | 32.3 | 31.1 | 43.3 | ||
| 2nd Quartile | 25.4 | 28.0 | 28.3 | 24.8 | ||
| 3rd Quartile | 24.7 | 19.6 | 19.9 | 17.0 | ||
| 4th Quartile | 24.5 | 20.1 | 20.7 | 14.9 | ||
| Low education neighborhood | <.0001 | .9090 | ||||
| No | 62.4 | 54.5 | 54.4 | 54.9 | ||
| Yes | 37.6 | 45.5 | 45.6 | 45.1 | ||
| Ever Medicaid insured | <.0001 | .0185 | ||||
| No | 83.5 | 71.0 | 71.9 | 62.5 | ||
| Yes | 16.5 | 29.1 | 28.1 | 37.5 | ||
Note. AA, African American; ACEs, adverse childhood experience; API, Asian/Pacific Islanders.
Table 3Prevalence of physical, mental health and developmental conditions by reported ACEs exposure
| Physical, Mental Health and Developmental Conditions | Among those who were screened | Among those with any ACEs | |||||
|---|---|---|---|---|---|---|---|
| No ACE (N = 11,922) | Any ACEs (N = 1,448) | p value | 1-2 ACEs (N = 1,302) | ≥3 ACEs (N = 146) | p value | ||
| Physical | Abdominal pain | 3.4 | 3.8 | .4704 | 4.1 | 1.4 | .1055 |
| Asthma | 6.6 | 10.0 | <.0001 | 10.2 | 8.2 | .4462 | |
| Atopic dermatitis | 15.6 | 10.1 | <.0001 | 10.7 | 4.8 | .0252 | |
| Bone, joint or muscle problems | 2.2 | 3.2 | .0156 | 3.3 | 2.1 | .6172 | |
| Brain injury or concussion | 0.1 | 0.4 | .0473 | 0.3 | 0.7 | .4127 | |
| Cerebral palsy | 0.1 | 0.1 | .3380 | 0.2 | 0.0 | 1.0000 | |
| Diabetes | <0.1 | <0.1 | .4363 | 0.0 | 0.7 | 0.1008 | |
| Epilepsy or seizure disorder | 0.2 | 0.8 | <.0001 | 0.6 | 2.7 | 0.0258 | |
| Headache | 0.4 | 0.2 | .4771 | 0.2 | 0.0 | 1.0000 | |
| Hearing problems | 0.7 | 0.7 | .9807 | 0.8 | 0.0 | .6113 | |
| Migraine | <0.1 | <0.1 | .2910 | 0.1 | 0.0 | 1.0000 | |
| Motor delay/disorders | 0.9 | 1.2 | .3340 | 1.2 | 0.7 | 1.0000 | |
| Obesity | 7.3 | 10.4 | <.0001 | 9.8 | 15.8 | .0264 | |
| Overweight | 8.7 | 13.4 | <.0001 | 12.8 | 19.2 | .0306 | |
| Underweight | 4.6 | 3.1 | .0101 | 3.0 | 4.1 | .4480 | |
| Sleep disorders | 1.2 | 2.0 | .0104 | 2.2 | 0.0 | .1083 | |
| Somatic symptoms/disorders | 0.1 | 0.1 | 1.0000 | 0.1 | 0.0 | 1.0000 | |
| Vision problems | 0.4 | 0.7 | .0899 | 0.6 | 1.4 | .2670 | |
| Mental/ | ADHD | 0.1 | 0.1 | .6004 | 0.0 | 0.7 | .1008 |
| Behavioral | Adjustment disorders | 0.1 | 0.5 | .0005 | 0.3 | 2.1 | .0259 |
| Health | Anxiety problems | 0.3 | 0.4 | .4384 | 0.5 | 0.0 | 1.0000 |
| Attachment disorders | 0.0 | 0.0 | - | 0.0 | 0.0 | - | |
| Behavioral problems | 0.1 | 0.5 | .0037 | 0.4 | 1.4 | .1514 | |
| Conduct disorders | 0.6 | 1.4 | .0015 | 1.4 | 1.4 | 1.0000 | |
| Depression | 0.0 | 0.0 | - | 0.0 | 0.0 | - | |
| Feeding problems | 0.2 | 0.6 | .0079 | 0.5 | 1.4 | .1891 | |
| Developmental | Autism spectrum disorders | 1.8 | 3.1 | .0008 | 3.0 | 4.1 | .4480 |
| Bed wetting | 0.2 | 0.4 | .3686 | 0.4 | 0.0 | 1.0000 | |
| Communication disorders | 5.5 | 6.1 | .3460 | 6.3 | 4.1 | .2939 | |
| Developmental delay | 1.8 | 2.5 | .0790 | 2.5 | 2.1 | 1.0000 | |
| Down syndrome | 0.1 | 0.0 | 1.0000 | 0.0 | 0.0 | - | |
| Intellectual disability | 0.0 | 0.0 | - | 0.0 | 0.0 | - | |
Note. ACE, adverse childhood experiences; ADHD, Attention deficit hyperactivity disorder.
Results from a multivariate logistic regression model indicated that compared with White children, the likelihood of having at least one ACE was higher among African American children and lower among children with API and other racial/ethnic backgrounds (Table 4). Older age and ever having had Medicaid insurance were both associated with higher odds of ACEs exposure, whereas higher median household income was associated with lower odds of ACEs exposure. Having comorbid diagnoses of epilepsy or seizure disorder, sleeping, adjustment, or feeding disorders were all associated with higher odds of ACEs exposure; after adjusting for other covariates, children with epilepsy or seizure disorder were almost four times as likely, and children with adjustment disorders were more than three times as likely, to have been exposed to ACEs than those without these diagnoses.
Table 4Multivariate logistic regression model on patient characteristics associated with ACEs exposure
| Patient Characteristics | ACEs exposure | ≥3 ACEs exposure among those screened positive | ||||
|---|---|---|---|---|---|---|
| OR | 95% CI | p value | OR | 95% CI | p value | |
| Race/Ethnicity | <.0001 | .0268 | ||||
| API vs. White | 0.35 | (0.30, 0.42) | 0.43 | (0.23, 0.80) | ||
| AA vs. White | 1.26 | (0.99, 1.60) | 0.80 | (0.41, 1.57) | ||
| Hispanic vs. White | 0.96 | (0.82, 1.13) | 0.53 | (0.33, 0.84) | ||
| Other vs. White | 0.69 | (0.54, 0.89) | 0.63 | (0.29, 1.41) | ||
| Age at index visit | <.0001 | .3325 | ||||
| 2 years vs. 1 year | 1.19 | (0.98, 1.45) | 1.80 | (0.89, 3.63) | ||
| 3 years vs. 1 year | 1.52 | (1.26, 1.83) | 1.76 | (0.89, 3.48) | ||
| 4 years vs. 1 year | 1.80 | (1.51, 2.14) | 1.95 | (1.03, 3.69) | ||
| 5 years vs. 1 year | 2.13 | (1.77, 2.58) | 1.52 | (0.77, 3.03) | ||
| Median household income | .0832 | .0172 | ||||
| 2nd Quartile vs. 1st | 1.02 | (0.87, 1.19) | 0.57 | (0.36, 0.91) | ||
| 3rd Quartile vs. 1st | 0.82 | (0.68, 0.99) | 0.55 | (0.32, 0.94) | ||
| 4th Quartile vs. 1st | 0.96 | (0.79, 1.17) | 0.45 | (0.25, 0.81) | ||
| Low education neighborhood, Yes vs. No | 0.97 | (0.84, 1.11) | .6384 | |||
| Ever Medicaid insured, Yes vs. No | 1.62 | (1.42, 1.85) | <.0001 | 1.45 | (0.99, 2.13) | .0570 |
| Physical Conditions | ||||||
| Asthma, Yes vs. No | 1.18 | (0.97, 1.44) | .0988 | |||
| Atopic dermatitis, Yes vs. No | 0.78 | (0.65, 0.94) | .0105 | 0.44 | (0.19, 1.04) | .0615 |
| Bone, joint or muscle problems, Yes vs. No | 1.25 | (0.89, 1.74) | .1998 | |||
| Brain injury or concussion, Yes vs. No | 2.19 | (0.73, 6.60) | .1620 | |||
| Epilepsy or seizure disorder, Yes vs. No | 3.92 | (1.77, 8.67) | .0008 | 4.40 | (1.21, 16.05) | .0248 |
| Obesity vs. Normal | 1.02 | (0.84, 1.24) | .2330 | 1.51 | (0.93, 2.47) | .9484 |
| Overweight vs Normal | 1.16 | (0.97, 1.39) | .0969 | 1.36 | (0.79, 2.36) | .0971 |
| Underweight vs Normal | 0.82 | (0.59, 1.14) | .8417 | 1.03 | (0.38, 2.80) | .2713 |
| Sleep disorders, Yes vs. No | 1.60 | (1.05, 2.43) | .0295 | |||
| Mental Health Conditions | ||||||
| Adjustment disorders, Yes vs. No | 3.45 | (1.11, 10.66) | .0318 | 3.38 | (0.56, 20.62) | .1861 |
| Behavioral problems, Yes vs. No | 2.37 | (0.81, 6.97) | .1168 | |||
| Conduct disorders, Yes vs. No | 1.55 | (0.91, 2.66) | .1084 | |||
| Feeding problems, Yes vs. No | 2.84 | (1.20, 6.72) | .0174 | |||
| Developmental Conditions | ||||||
| Autism spectrum disorders, Yes vs. No | 1.34 | (0.95, 1.90) | .0986 | |||
Note. AA, African American; ACEs, adverse childhood experiences; API, Asian/Pacific Islanders; CI, confidence interval; OR, odds ratio.
We also examined associations of the higher-risk group (score of ≥ 3). Among those with any ACEs exposure (N = 1,448), we found a lower proportion of API children among those who reported ≥ 3 ACEs exposure (Table 2). Older age, living in a lower-income neighborhood, and ever having been insured through Medicaid were all associated with reporting ≥ 3 ACEs exposure. Prevalence rates of epilepsy/seizure disorder, obesity, overweight, and adjustment disorders were significantly higher, whereas the prevalence of atopic dermatitis was significantly lower among those with ≥ 3 or more ACE exposure than those with 1–2 ACEs (Table 3). Results from the multivariate logistic regression model indicated that among those screened positive for any ACEs exposure, children with API or Hispanic racial/ethnic background were less likely to have been exposed to ≥ 3 ACEs than White children (Table 4). Higher median household income was associated with lower odds of exposure to ≥ 3 ACEs. After adjusting for other covariates, only a diagnosis of epilepsy or seizure disorder was associated with higher odds of ≥ 3 ACEs.
DISCUSSION
In this article, we report findings from a study conducted in pediatric primary care that is one of the few large-scale, systematic ACEs screening programs to include very young patients. We examined the relationship between patient characteristics (sociodemographic, clinical, and administrative) and exposure to a variety of ACEs. Our study's unique contribution is that it offers a large sample size and a great variety of characteristics, yielding a comprehensive picture of potential associations between ACEs and patient factors in very young children. The study may not only confirm previous studies but also help improve current assessment procedures and suggest further research.
We found no relationship between gender and ACEs exposure. However, as hypothesized, other factors were related, including race and ethnicity, age, lower socioeconomic status, and several specific health conditions. Parents of API children were less likely, and parents of African American children more likely, to have reported ACEs exposure than White parents. However, among those screening positive, parents of both API and Hispanic children were less likely, than White children to report exposure to three or more ACEs. Other studies have found differences in reported exposure among ethnic groups (
Sacks and Murphey, 2018
), in particular a lower rate among Asian families (Child and Adolescent Health Measurement Initiative 2016
). The rates could reflect both true differences in families’ experiences and a hesitancy to report exposures. Because of historically disproportionate reporting of non-White families to child welfare authorities (Child Welfare Information Gateway 2016
), parents may be reticent about reporting ACEs exposure to authorities when receiving pediatric primary care. In addition, cultural norms may inhibit parents from discussing sensitive and private family information with outsiders (Li et al., 2017
). We need to better understand the cultural factors that impede or facilitate ACEs screening and reporting, particularly in culturally diverse health care systems. For example, more research is needed on the cultural and linguistic appropriateness and validity of screening measures. For all very young children, we must identify the most effective approaches for identifying ACEs exposure.Not surprisingly, our results suggest that socioeconomic factors also play an important role in exposure to ACEs, echoing findings from other studies (
Bethell et al., 2017b
; Halfon et al., 2017
). Children from lower socioeconomic backgrounds were more likely to have exposure to ACEs, and if exposed, to have exposure to ≥ 3 ACEs. Poverty itself may create or exacerbate family pressures that increase the risk of neglect, abuse, interpersonal violence, mental illness, or substance misuse. Our screening questionnaire also explicitly included circumstances associated with poverty, such as food and housing insecurity, fears of deportation, and neighborhood violence. The growing emphasis in many health care settings on social determinants of health should include an explicit focus on early identification of and intervention for ACEs in lower-income children and the routine offer of appropriate services and resources.Several physical, mental/behavioral health, and developmental comorbidities were associated with both ACEs exposure and exposure to ≥ 3 ACEs. Epilepsy/seizure disorder, sleep disorders, adjustment disorders, and feeding problems were positively associated with a report of any ACEs, with epilepsy/seizure disorder also associated with a higher likelihood of reporting ≥ 3 ACEs. Previous research has suggested an association between childhood trauma and seizure disorders (
Reuber et al., 2007
). Asthma was associated with ACEs exposure, and obesity and overweight with both ACEs exposure and reporting ≥ 3 ACEs in bivariate, though not multivariate, analyses. We could not determine the directionality of the associations in our observational study and thus refrained from suggesting causality in either direction.Moreover, it was beyond the scope of this study to determine the chronology of ACEs exposure and the development of health conditions. However, our findings point to important associations consistent with recent studies that also found several pediatric health conditions to be related to ACEs (
Bright and Thompson, 2018
). Other behavioral/mental health conditions were less frequently diagnosed in our sample of very young children, most likely because many of these conditions, for example, attention deficit hyperactivity disorder, are usually diagnosed later. Future longitudinal studies could follow children exposed to ACEs at different ages and examine subsequent health outcomes, including changes in disease management and symptoms, than a matched cohort.Clinicians could use the information on conditions associated with ACEs exposure when evaluating patients’ and families’ need for additional screening, prevention interventions, or capacity for treatment adherence. Intervention strategies for comorbid conditions could recognize the role of ACEs by including educational and preventive resources such as parenting programs, mental health and community resources, supportive case management, or clinical pharmacy consultation. These types of resources are consistent with efforts to address ACEs using holistic, trauma-informed care approaches to health care delivery (
Center for Health Care Strategies 2021
).This study has several limitations. The first is that routine ACEs screening in pediatric health care itself remains controversial among some authors, for example,
McLennan et al., 2019
and Finkelhor, 2018
. They are concerned about possible negative sequelae of screening positive in the absence of adequate interventions, the costs and implications of false positives enhanced training needs for clinicians, limitations of currently available screening tools, and limited intervention resources. ACEs screening for the youngest children rely on parent reports, and as with any such measure, its validity may be limited and some ACEs exposures minimized or not revealed. However, recent studies have shown high acceptability and good feasibility, especially when parents considered the health care clinician as competent and saw the assessment and discussion of ACEs as an opportunity to receive support, or when the assessment procedure was used successfully as an educational tool for engaging and educating families and children about the importance of stable and nurturing family relationships, etc. (Bethell et al., 2017a
).Second, this study was conducted in a private, not-for-profit health care delivery system with an insured population (albeit with a substantial number of members insured through Medicaid), and may not reflect the experiences of a lower-income, public population. This, along with the limited age range of the children, could contribute to the lower overall prevalence of reported ACEs compared with other studies (
Crouch et al., 2019
; Halfon et al., 2017
). Nevertheless, the sample included a very large and racially, ethnically, and sociodemographically diverse sample of children. The study was part of a larger systematic ACEs screening implementation conducted in busy, real-world clinics. Third, to reduce stigma and encourage frank disclosures, a clinical decision was made to allow parents simply to specify the number of ACES rather than which ACEs their child experienced. As we were only able to examine any ACEs exposure and the number of exposures, and not which ACEs, our ability to understand more complicated and nuanced associations between socioeconomic factors, race/ethnicity, and ACEs was limited. We examined the presence of comorbid conditions in the year before the index date for all children in the sample, but older children could have a higher chance of being exposed to ACEs and having health conditions identified.Finally, some study findings may be due to collinearity between patient characteristics. For example, the prevalence of atopic dermatitis was about 20% among API and African American children but about 10% among children with Hispanic, White, and other racial/ethnic background. Because APIs were less likely to report any ACEs exposure, and having atopic dermatitis was associated with race/ethnicity, the surprisingly observed negative association compared with other studies (
McKenzie and Silverberg, 2020
) between atopic dermatitis and any ACEs exposure might be driven by the association between race/ethnicity and ACEs despite adjustment for race/ethnicity. In addition, our analyses on factors associated with ≥ 3 ACEs exposure among those with any ACEs exposure might be underpowered. For example, we have lower than 0.80 power to detect a 5% difference between those who have and have not been insured by Medicaid with the sample size.We found ACEs to be associated with several sociodemographic, and health and mental health conditions, contributing to the growing literature on adverse experiences and young children and strengthening our understanding of the relationship between these factors. Our findings will not only help inform early ACEs identification, as well as the improvement of assessment and intervention approaches in pediatric primary care, but also encourage future research in this very young patient population.
The authors thank Dr. Brigid McCaw for her clinical expertise and guidance and dedication to this field throughout this study, and Agatha Hinman for editorial and bibliographic assistance. The authors also thank all the physicians, medical assistants, nurses, receptionists, managers, and especially the patients and parents of KPNC's Greater Southern Alameda Area and San Jose pediatrics clinics for their participation in the activities related to this study.
Appendix. SUPPLEMENTARY MATERIALS
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Biography
Stacy Sterling, Research Scientist, Division of Research, Kaiser Permanente Northern California, Oakland, CA.
Felicia Chi, Senior Data Consultant, Division of Research, Kaiser Permanente Northern California, Oakland, CA.
Judy Lin, Physician, Department of Pediatrics, Kaiser Permanente Medical Center, San Leandro, CA.
Padmaja Padalkar, Physician, Department of Pediatrics, Kaiser Permanente Medical Center, San Jose, CA.
Uma Vinayagasundaram, Physician, Department of Pediatrics, Kaiser Permanente Medical Center, Fremont, CA.
Esti Iturralde, Research Scientist, Division of Research, Kaiser Permanente Northern California, Oakland, CA.
Kelly Young-Wolff, Research Scientist, Division of Research, Kaiser Permanente Northern California, Oakland, CA.
Verena E. Metz, Staff Scientist, Division of Research, Kaiser Permanente Northern California, Oakland, CA.
Arnd Herz, Physician, Department of Pediatrics, Kaiser Permanente Medical Center, Hayward, CA.
Rahel Negusse, Research Associate, Division of Research, Kaiser Permanente Northern California, Oakland, CA.
Melanie Jackson-Morris, Morris, Research Associate, Division of Research, Kaiser Permanente Northern California, Oakland, CA.
Paul Espinas, Physician, Department of Pediatrics, Kaiser Permanente Medical Center, Hayward, CA.
Article info
Publication history
Published online: July 02, 2021
Footnotes
This work was supported by the Permanente Medical Group Delivery Science Research program.
Conflicts of interest: None to report.
Identification
Copyright
Copyright © 2021 by the National Association of Pediatric Nurse Practitioners. Published by Elsevier Inc. All rights reserved.
