Investigating the correlation of growth and mental health measures in youth

The COVID-19 pandemic tended to disproportionately affect children’s health and well-being, resulting in higher likelihoods than adults to experience long-term consequences from the shutdowns. Dramatically altered routines, isolation, having family members contracting the virus, and many other factors were likely to have negative effects on children’s mental and physical health.

ARI staff scientist Dr. Ana Lučić and Dr. Amy Christison, a pediatrician at the University of Illinois College of Medicine in Peoria, were awarded a grant through the OSF Jump ARCHES program to study the relationship between psychosocial concerns and childhood accelerated weight changes. The study, which has concluded its first stage, seeks to examine how electronic health record data, such as changes in body-mass index (BMI), social determinants, and other demographic characteristics, may identify children at risk for emotional and behavioral concerns who may benefit from earlier access to intervention.

This project relies on the current research that indicate reciprocal links between childhood obesity and mental health disorders, such as this article published in Nature, as well as increased prevalence of mental health disorders in children after a COVID infection. The focus of the study, however, is not on obesity specifically, but on understanding the relationship between accelerated body weight changes and emotional and behavioral concerns.

This is a retrospective study of health records within a larger regional healthcare system of children ages six to 18 who sought healthcare at least twice between 2018 and 2022. Changes in weight for height were determined using calculated BMI Z-scores (body-mass-index standard deviation based on normative age and sex values), and patient demographic characteristics, underlying mental health diagnoses, and available social determinant screening responses from parents were abstracted. Mental health symptoms were based on scores from the caregiver and the self-reported Pediatric Symptom Checklist (PSC-17).  PSC-17 is a questionnaire that screens for mental health concerns indicating children at risk for mental health diagnoses. The analysis took into account the BMI z-score changes and PSC-17 scores, alongside other social and demographic factors.

Early results show some modest predictive capabilities of patient characteristics, such as wide changes in BMI z-score, social determinant concerns, and sex. The team hopes to apply this modeling to a larger, more diverse population of patient records, which can inform propensity scores that can flag patients who can benefit from mental health screening. The implications could be earlier identification of mental health diagnoses followed by earlier intervention and treatment. Currently, the team is working to publish their initial results and seek funding to for their next phase of investigation.