It is known that one’s health can be significantly impacted by social determinants of health (SDOH), but there has been limited research to determine the impact of SDOH on children. “SDOHs are really important in adults, because some of them are associated with poorer health outcomes,” says J. John Mann, MD, a psychiatrist at NewYork-Presbyterian/
Dr. Mann recently worked with a group of international physicians and researchers to assess patterns of multidimensional SDOH in data from 10,504 children from 21 sites enrolled in the Adolescent Brain Cognitive Development (ABCD) Study. The results of the cohort study were published in JAMA Pediatrics and revealed significant disparities in child development health across four SDOH patterns that the research team identified by pioneering a quantitative approach that considered all types of SDOH in children:
- Affluence (SDOH pattern 1)
- High-stigma environment (SDOH pattern 2)
- High socioeconomic deprivation (SDOH pattern 3)
- High crime and drug sales rates coupled with lower education and densely populated areas (SDOH pattern 4)
“The range of outcomes that we then examined in relation to these SDOH patterns was also much broader than previously done,” says Dr. Mann. “The results show the deleterious effect of socioeconomic factors and how they are more pervasive than has been previously realized from other studies.”
Analyzing the Multidimensional Nature of SDOH
The ABCD Study uses primary residential addresses to link population-level SDOH characteristics to children. Data were collected from September 1, 2016 – April 24, 2021, and included children from urban, rural, and mountainous areas in the United States. Using conceptual frameworks from the World Health Organization, Health People 2030, and the U.S. Centers for Disease Control and Prevention, the researchers identified 7 SDOH domains:
- Bias
- Education
- Physical and health infrastructure
- Natural environment
- Socioeconomic status
- Social context
- Crime and drugs
To assess mental health and cognitive performance, the researchers utilized a variety of measures including the caregiver-reported Child Behavior Checklist (CBCL); Diagnostic and Statistic Manual of Mental Disorders Fifth Edition (DSM-5) symptom subscales; the Kiddie Schedule for Affective Disorders and Schizophrenia for DSM-5; and the National Institutes of Health Toolbox Cognition Battery. Additional measures were used to assess physical health outcomes – body mass index (BMI), frequency of regular exercise for 60 minutes, and the Sleep Disturbance Scale for Children.
Social determinants of health domains include bias, education, natural environment, healthcare access and quality, socioeconomic status, social context, and crime and drugs.
The study findings showed clear associations between specific SDOH patterns and domains.
SDOH Pattern 1 (Affluence)
SDOH pattern 1 predominated in 4,078 children (38.8%) and these children lived with a higher socioeconomic status, lower structural stigma, moderate crime rates, and good academic performance. They were primarily White (70.9%) and had the highest household income (60.8% >100,000). Additionally, SDOH pattern 1 had the lowest rate of parents having less than a bachelor’s degree (18.8%), and highest rate of married parents (81.1%). The children in SDOH pattern 1 also had access to health food, a healthy environment, low social vulnerability, and moderate population density and walkability.
SDOH Pattern 2 (High-Stigma Environment)
There were 2,661 children (25.3%) in SDOH pattern 2, and 71% were White, 76.5% had married parents, and the annual household income ranged from 50,000-100,000 and >100,000 (36.3% and 36.4% respectively). In this group, 36.9% had parents with education less than a bachelor’s degree. Children in SDOH pattern 2 experienced the highest implicit bias toward sexual and gender minority groups, low college enrollment, lowest number of white-collar workers, homeowners, and urbanicity. Residences in SDOH pattern 2 included mobile homes and group quarters. Children in SDOH pattern 2 had more exposure to industrial pollutants, ozone, and particulate matter with a diameter of 2.5μm.
SDOH Pattern 3 (High Socioeconomic Deprivation)
In contrast to SDOH pattern 1 and 2, SDOH pattern 3 looked significantly different. Of the 2,653 children (25.3%) assigned to SDOH pattern 3, 37.7% were Black and 28.6% were Hispanic, 66.1% had parents with education less than a bachelor’s degree, and annual household income was <50,000 (51.1%). Children here lived in a high socioeconomic deprivation environment characterized by the highest rates found in the Area Deprivation Index (ADI) and Social Vulnerability Index (SVI), but the lowest Opportunity Atlas social mobility scores. The children in SDOH 3 also experienced the highest levels of racism and discrimination toward immigrants and the most severe lead exposure.
SDOH Pattern 4 (High Crime and Drug Sale Rates, Lower Education, and Densely Populated Areas)
SDOH Pattern 4 included 1,112 children (10.6%) of whom 60.5% were Hispanic, 60.7% had parents with education less than a bachelor’s degree, and annual household income was <50,000 (40.5%). Children residing here had the lowest levels of education, access to a healthy environment, and homeownership rates. They also experienced school poverty, high levels of air pollution, and crowded housing.
Racial and Socioeconomic Differences Play Large Role in Health Outcomes
The study found clear differences between races and socioeconomic backgrounds as well as child developmental outcomes across the SDOH patterns. Children in SDOH pattern 3 had the worst health outcomes compared with the other patterns, including higher rates of mental health issues and suicidal ideations/behaviors, lower cognitive performance, and poorer physical health. Specifically, children in SDOH pattern 3 experienced the most severe internalizing, externalizing, social, and mental health problems than the other patterns. Additionally, children in SDOH pattern 3 had lower cognitive performance, were the least physically active, had a higher BMI, and experienced higher overall sleep issues.
“Socioeconomic disadvantage really matters,” says Dr. Mann. “It makes a different in educational performance, in cognitive function, and in BMI. There are also more mental health problems. It affects kids in a remarkably global fashion. What is alarming is that the impact of these SDOH patterns is not the same in race/ethnicity groups. These children, especially in pattern 3, need the testing of the effectiveness of amelioration of these adverse SDOH, particularly in the domain of socioeconomic deprivation, to improve health outcomes.”
The study results are helping to inform future research and potential public policy. “We need to follow these kids and see if there is a difference in the outcome in the group of kids that are stuck in their adverse environment versus a group of kids that, because of their parents’ success, are able to move out of that environment,” says Dr. Mann. “In other words, does an environmental change reverse these relationships, which can be accomplished by more follow up with these kids? We also need similar studies that compare two groups – one group remains in the environment and one where the research group changes the environment. Such studies have begun to appear, but they tend to be very limited in their range of variables, both on the outcome side and the potential adverse environment.”
Dr. Mann adds that there needs to be a deeper examination of the elements that play into socioeconomic deprivation. “We need to look at that more closely and see if we can achieve an improvement by changing some [of the elements],” he says. “We may not be able to change everything, but we may be able to change some of the critical elements that make a difference, preferably through some sort of empowerment strategy.”
For next steps, Dr. Mann shared that he and his colleagues at NewYork-Presbyterian/
