Factors Associated with Attendance after Referral to a Pediatric Weight Management Program

J Pediatr. 2016 May:172:35-9. doi: 10.1016/j.jpeds.2016.02.011. Epub 2016 Mar 2.

Abstract

Objective: To evaluate factors affecting attendance or nonattendance at an initial interprofessional pediatric weight management visit after referral. We hypothesized that increased severity of obesity, farther distance from the program, lower education level of the primary caregiver, public insurance or no insurance, and lower socioeconomic status would all decrease likelihood of attending initial visit after referral.

Study design: We examined referral and visit data over 4 years and 5 months. We used geocoding and multivariable logistic regression to analyze links between attendance and demographic factors, baseline body mass index, insurance type, and distance from patients' homes to the program site.

Results: Over the study period, 41.2% of the 4783 children referred to the pediatric weight management clinic attended at least 1 visit. A total of 4086 children were included in the full analyses. Factors associated with attendance were female sex, higher body mass index severity class, private health insurance, residence in areas with higher median income, and residence in areas with a higher prevalence of high school completion.

Conclusions: The current project expands our understanding of factors linked to children's attendance at an initial pediatric weight management visit. Despite limitations including missing data, results have important implications for pediatric weight management clinics, referring providers, and policymakers to target populations with low attendance and optimize use of these evidence-based programs.

Publication types

  • Research Support, Non-U.S. Gov't

MeSH terms

  • Adolescent
  • Child
  • Female
  • Health Behavior*
  • Humans
  • Logistic Models
  • Male
  • Patient Compliance*
  • Pediatric Obesity / therapy*
  • Referral and Consultation / statistics & numerical data*
  • Risk Factors
  • Weight Reduction Programs / statistics & numerical data*