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Anti-Obesity Medication Prescriptions by Race/Ethnicity and Use of an Interpreter in a Pediatric Weight Management Clinic
Background: Healthcare disparities associated with race/ethnicity and low English proficiency are well established in the US. We sought to determine if there are race/ethnic differences in anti-obesity medication prescription rates among youth with severe obesity (body mass index (BMI) ≥1.2 times th...
Autores principales: | , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Oxford University Press
2021
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8265710/ http://dx.doi.org/10.1210/jendso/bvab048.006 |
Sumario: | Background: Healthcare disparities associated with race/ethnicity and low English proficiency are well established in the US. We sought to determine if there are race/ethnic differences in anti-obesity medication prescription rates among youth with severe obesity (body mass index (BMI) ≥1.2 times the 95(th) percentile and/or BMI ≥35 kg/m(2)) treated in a pediatric weight management clinic (PWMC). We secondarily sought to determine if, among youth from families in whom English was not the primary language, there are differences in prescription rates between those using an interpreter during visits and those not. Methods: We reviewed electronic health records of youth 2–18 years old with severe obesity seen at a PWMC from 2012–2020. Race/ethnicity was self-reported and categorized as Non-Hispanic White (NHW), Hispanic/Latino, Non-Hispanic Black (NHB), Asian, American Indian/Alaska Native and Mixed. Anti-obesity medicines included stimulants (i.e. phentermine, lisdexamfetamine), topiramate, naltrexone (± bupropion), and glucagon-like peptide-1 agonists. We used Poisson regression models with robust standard errors to compare incidence rates of medicine prescription (incidence rate ratio (IRR), accounting for visit frequency) within the first 1 and 3 years of being followed in a PWMC. We controlled for age, baseline degree of obesity (percent of the 95(th) BMI percentile (%BMIp95)), number of obesity-related comorbidities (i.e. insulin resistance, hypertension, fatty liver), area-level socioeconomic status (median household income based on ZIP code), and interpreter use. We repeated similar analyses among families in whom English was not the primary language, comparing those using an interpreter with those not. Results: From 2012–2020, 1258 youth (mean age 11.8 years; %BMIp95 143%) were seen in our PWMC (57% NHW, 19% Hispanic/Latino, 16% NHB) of which 26% were prescribed anti-obesity medication. 86% primarily spoke English and 5.2% used an interpreter. There were no statistically significant differences in the IRR of prescriptions by race/ethnicity at 1 and 3 years; however, although not statistically significant point estimates suggest Hispanic/Latino youth being prescribed medication less often at 1 (IRR 0.71; p=0.08) and 3 (IRR 0.75; p=0.13) years compared to NHW. Among non-primary English speakers, rates of prescriptions were higher at 1 (IRR 5.7; p<0.01) and 3 (IRR 3.5; p<0.01) years in those using an interpreter versus those not. Conclusions: We found no significant race/ethnic differences in anti-obesity medication prescriptions; however, Hispanic/Latino youth received fewer prescriptions, albeit not statistically significant. Among non-primary English speakers, use of an interpreter was associated with increased prescriptions. Our results suggest that addressing healthcare disparities and language barriers may improve care delivery for youth with obesity. |
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