Predictors of attrition in a large clinic-based weight-loss program

Obes Res. 2003 Jul;11(7):888-94. doi: 10.1038/oby.2003.122.


Objective: Identifying client factors that predict dropout is critical for the development of effective weight-loss programs. Although demographic predictors are studied, there are few consistent findings. The purpose of this study was to identify predictors of dropout in a large clinic-based weight-loss program using readily attainable demographic variables.

Research methods and procedures: All 866 weight-loss patients in a clinic-based weight-loss program enrolled during 1998 to 1999 were followed. Attrition and retention rates were measured at 8 and 16 weeks. Six variables (sex, race, marital status, age, BMI, and treatment protocol) were evaluated using bivariate and multivariable statistics for relative association with dropout.

Results: The overall attrition rate for the 16-week program was 31%. The retention rate was 69%. Significant risk for dropout, measured as bivariate relative risk (95% confidence interval), was found among patients who were: females, 1.32 (1.01 to 1.73); divorced, 1.54 (1.13 to 2.09); African Americans, 1.68 (1.26 to 2.23); age < 40, 1.66 (1.27 to 2.18); and ages 40 to 50, 1.33 (1.01 to 1.76). There were no significant differences in retention rates by BMI group or program protocol. After logistic regression analysis to control for all variables, young age < 50 years had the only significant association with dropout [odds ratio = 1.39 (1.02 to 1.90)].

Discussion: Multivariable modeling was helpful for prioritizing risk factors for program dropout. These findings have important implications for improving weight-loss program effectiveness and reducing attrition. By knowing the groups at risk for dropout, we can improve or target program treatments to these populations.

MeSH terms

  • Adult
  • Body Mass Index
  • Clinical Protocols
  • Diet, Reducing
  • Energy Intake
  • Female
  • Humans
  • Logistic Models
  • Male
  • Marital Status
  • Middle Aged
  • Obesity / therapy*
  • Patient Dropouts / statistics & numerical data*
  • Weight Loss*