Predictors of drop-out in overweight and obese outpatients.

Auteur(s) :
Inelmen EM., Toffanello ED., Benzi G., Gasparini G., Miotto F., Busetto L.
Date :
Jan, 2005
Source(s) :
Adresse :
Department of Medical and Surgical Science, Division of Geriatrics, University of Padua, Italy.

Sommaire de l'article

OBJECTIVE: To investigate the impact on drop-out rates of several baseline clinical characteristics of a sample of overweight and obese outpatients. DESIGN: Retrospective clinical trial. SUBJECTS: The charts of 383 patients aged 15-82 y attending an outpatient clinic for the treatment of obesity were examined from the first clinical evaluation until 1 y of diet ambulatory treatment. MEASUREMENTS: We characterised the participants at baseline on the basis of their somatic characteristics, socioeconomic status, obesity-related diseases and dietary habits. The most significant factors resulting in univariate statistical analysis (waist, body mass index (BMI), full-time job, depressive syndrome, number of obesity-related diseases, daily frequency of fruit consumption) were then examined as independent variables in direct multiple logistic regression with the dependent variable drop-out. RESULTS: The 1-y drop-out rate was 77.3%. A total of 87 patients completed the follow-up study. The noncompleter patients had slightly lower BMI and waist circumference mean values, and they were further regularly employed in full-time jobs, while the completer patients were principally pensioners and housewives. Drop-outs had a lower number of obesity-related diseases and as a result were less depressed. By the logistic regression, full-time job is the best predictor of premature withdrawal (odds ratio=2.40). Age, gender, anthropometric measurements, lifestyle and dietary habits did not result as significant predictors of drop-out. CONCLUSION: The overweight and obese outpatients at higher risk of ambulatory treatment drop-out are more likely to work full hours, have less obesity-related complications and be less depressed. In our study, the full-time job condition seems to be the strongest predictor of premature withdrawal.

Source : Pubmed