Psychosocial and Behavioral Predictors of Successful Weight Loss in Individuals that are Obese

Hildemar Dos Santos, Henrik Galust, Sylvia Cramer, Colwik Wilson, Susanne Montgomery, Denise Tavares Schwab Dias, Josileide Gaio, (doi: 10.23953/cloud.ijanhs.434)


The objective of this study was to evaluate psychosocial and behavioral predictors of weight loss success in patients that are obese enrolled in a weight loss program. It was a quasi-experimental design, with a convenience sample (n=127) of men and women aged 21-75 years with BMI >30 kg/m2 enrolled in a medically supervised comprehensive clinic-based weight loss program. We performed assessments at baseline and after program completion via behavioral and psychosocial questionnaires exploring correlates of weight loss. The weight loss program included nutritional, physical and behavioral therapies. Surveys and scales assessed baseline major and daily life events as stressors that may affect weight loss. Pre-treatment perceived importance and actual engagement in weight loss behaviors - monitoring of eating behaviors, of meals and physical activity - also assessed. Multiple linear regression models were used, and an alpha (p-value) ≤0.05 determined statistical significance. Participants obtained clinically significant weight loss of 7% from baseline. Pretreatment engagement in weight loss behaviors (p<0.05) was a significant and independent predictor of weight loss; depression was negatively associated with weight loss (p<0.05). Major and daily stressors were not predictive of weight loss success. Baseline weight losing behaviors increase the likelihood of success; baseline depression decreases the likelihood of success in weight loss. Appropriate pre-treatment screening of behaviors and depression treatment may improve weight loss program success.


behavior predictors; obesity; psychosocial predictors; weight loss program

Full Text: PDF


  • There are currently no refbacks.

Creative Commons License
This work is licensed under a Creative Commons Attribution 3.0 License.

*2016 Journal Impact Factor was established by dividing the number of articles published in 2014 and 2015 with the number of times they are cited in 2016 based on Google Scholar, Google Search and the Microsoft Academic Search. If ‘A’ is the total number of articles published in 2014 and 2015, and ‘B’ is the number of times these articles were cited in indexed publications during 2016 then, journal impact factor = A/B. To know More: (