PT  - JOURNAL ARTICLE
AU  - Richdeep S. Gill
AU  - Shahzeer Karmali
AU  - Ghassan Hadi
AU  - David P. Al-Adra
AU  - Xinzhe Shi
AU  - Daniel W. Birch
TI  - Predictors of attrition in a multidisciplinary adult weight management clinic
AID  - 10.1503/cjs.035710
DP  - 2012 Aug 01
TA  - Canadian Journal of Surgery
PG  - 239--243
VI  - 55
IP  - 4
4099  - http://canjsurg.ca/content/55/4/239.short
4100  - http://canjsurg.ca/content/55/4/239.full
SO  - CAN J SURG2012 Aug 01; 55
AB  - Background: Worldwide, more than 1.7 billion individuals may be classified as overweight and are in need of appropriate medical and surgical treatments. The primary goal of a comprehensive weight management program is to produce sustainable weight loss. However, for such a program to be effective, the patient must complete it. We analyzed attrition rates and predictors of attrition within a publicly funded, multi-disciplinary adult weight management program.Methods: We retrospectively reviewed charts from an urban multidisciplinary adult weight management clinic program database. Patients received medical or surgical treatment with appropriate follow-up. We collected information on demographics and comorbidities. Patients in the surgical clinics received either laparoscopic gastric band insertion or gastric bypass. We conducted univariate analysis and multivariate analyses on predictors of attrition.Results: A total of 1205 patients were treated in the weight management program: 887 in the medical clinic and 318 with surgery and follow-up in a surgical clinic. Overall, 516 patients left the program or were lost to follow-up (attrition rate 42.8%). The attrition rate was 53.9% in the medical clinic and 11.9% in the surgical clinic. Multivariate analyses identified participation in the medical clinic, younger patient age and lower body mass index as predictors of attrition.Conclusion: We found lower attrition rates among surgically than medically treated patients in a multidisciplinary weight management clinic. Further research is needed to understand those variables that lead to improved attrition rates.