Abstract
IMPORTANCE: Nearly 40% of US youth aged 2 to 19 years do not have a body mass index (BMI) in the healthy weight category. However, there are no recent estimates for BMI-associated expenditures using clinical or claims data. OBJECTIVE: To estimate medical expenditures among US youth across all BMI categories along with sex and age groups. DESIGN, SETTING, PARTICIPANTS: This cross-sectional study used IQVIA's ambulatory electronic medical records (AEMR) data set linked with IQVIA's PharMetrics Plus Claims database from January 2018 through December 2018. Analysis was performed from March 25, 2022, through June 20, 2022. It included a convenience sample of a geographically diverse patient population from AEMR and PharMetrics Plus. The study sample included privately insured individuals with a BMI measurement in 2018 and excluded patients with pregnancy-related visits. EXPOSURE: BMI categories. MAIN OUTCOMES AND MEASURES: Total medical expenditures were estimated using generalized linear model regression with γ distribution and log-link function. For out-of-pocket (OOP) expenditures, a 2-part model was used that included logistic regression to estimate the probability of positive expenditures followed by generalized linear model. Estimates were shown with and without accounting for sex, race and ethnicity, payer type, geographic region, age interacted with sex and BMI categories, and confounding conditions. RESULTS: The sample included 205 876 individuals aged 2 to 19 years; 104 066 were male (50.5%) and the median age was 12 years. Compared with those with healthy weight, total and OOP expenditures were higher for all other BMI categories. Differences in total expenditures were highest for those with severe obesity ($909; 95% CI, $600-$1218) followed by underweight ($671; 95% CI, $286-$1055) compared with healthy weight. Differences in OOP expenditures were highest for those with severe obesity ($121; 95% CI, $86-$155) followed by underweight ($117; 95% CI, $78-$157) compared with healthy weight. Having underweight was associated with higher total expenditures at ages 2 to 5 years and 6 to 11 years by $679 (95% CI, $228-$1129) and $1166 (95% CI, $632-$1700), respectively; having severe obesity was associated with higher total expenditures at ages 2 to 5 years, 6 to 11 years, and 12 to 17 years by $1035 (95% CI, $208-$1863), $821 (95% CI, $414-$1227), and $1088 (95% CI, $594-$1582), respectively. CONCLUSIONS AND RELEVANCE: The study team found medical expenditures to be higher for all BMI categories when compared with those with healthy weight. These findings may indicate potential economic value of interventions or treatments aimed at reducing BMI-associated health risks.