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Predictors of drop-out in overweight and obese outpatients.

Authors :
Inelmen EM
Toffanello ED
Enzi G
Gasparini G
Miotto F
Sergi G
Busetto L
Source :
International journal of obesity (2005) [Int J Obes (Lond)] 2005 Jan; Vol. 29 (1), pp. 122-8.
Publication Year :
2005

Abstract

Objective: To investigate the impact on drop-out rates of several baseline clinical characteristics of a sample of overweight and obese outpatients.<br />Design: Retrospective clinical trial.<br />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.<br />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.<br />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.<br />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.

Details

Language :
English
ISSN :
0307-0565
Volume :
29
Issue :
1
Database :
MEDLINE
Journal :
International journal of obesity (2005)
Publication Type :
Academic Journal
Accession number :
15545976
Full Text :
https://doi.org/10.1038/sj.ijo.0802846