|Das, Sai Krupa|
Submitted to: Obesity
Publication Type: Peer Reviewed Journal
Publication Acceptance Date: 9/26/2012
Publication Date: 3/20/2013
Citation: Batra, P., Das, S., Salinardi, T.C., Robinson, L.M., Dallal, G.E., Saltzman, E., Scott, T., Pittas, A.G., Roberts, S.B. 2013. Eating behaviors as predictors of weight loss in a 6 month worksite weight loss intervention. Obesity. DOI: 10.1002/oby.20404. Interpretive Summary: Overweight and obesity remain at epidemic levels and are associated with increased morbidity and mortality as well as increased health care costs. Behavioral or lifestyle interventions are recommended for weight loss in obese individuals, but the widely suggested goal of 5-10% weight loss is not routinely achieved even in intensive weight loss intervention studies. This study examined the effects of a 6 month worksite weight loss intervention in eating behavior and measures of program adherence and evaluated these variables as predictors of weight loss over time. Higher frequency of self-monitoring, group meeting attendance, and decrease in hunger were predictors of weight loss. The finding that hunger is a significant predictor of success has implications for the design of interventions for weight control in worksites, and potentially other settings. In addition, these findings suggest the prioritization of hunger suppression may facilitate sustainable weight control.
Technical Abstract: The eating behaviors restraint and disinhibition have been suggested to predict weight loss (WL) but there is no information on whether these predictors are valid in worksite WL programs, which are increasingly being recommended for reducing the obesity epidemic. This study examined associations between eating behavior constructs and WL in a 6-month worksite WL intervention. A worksite-randomized controlled trial of a group behavioral WL intervention versus wait-listed control was conducted at 4 worksites. Measures included body weight and the eating behavior constructs restraint, disinhibition, hunger and sub-constructs as determined with the Eating Inventory. In addition, rates of intervention meeting attendance and weight self-monitoring were quantified. WL was greater in the intervention group than controls (deltaI=-8.1+/-6.8kg, deltaC=+0.9+/-3.6kg, p<0.001). Between-group analyses showed that the intervention was associated with increased restraint (deltaI=5.43+/-4.25, deltaC=0.29+/-3.80, p<0.001), decreased disinhibition (deltaI=–2.5+/-3.63, deltaC=0.66+/-1.85, p<0.001) and decreased hunger (deltaI=–2.79+/-3.13, 'C=0.56+/-2.63, p<0.001) and significant changes in all eating behavior subscales. Within the intervention group, WL was negatively correlated with baseline hunger (r=-0.25, p=0.03) and increased restraint (r=-0.35, p=0.001) and positively correlated with decreased disinhibition (r=0.26, p=0.02) and decreased hunger (r=0.36, p=0.001). However, in a multiple regression model including rates of meeting attendance and self-monitoring, hunger was the only significant eating behavior construct that predicted weight loss. In conclusion, decreased hunger, rather than restraint or disinhibition, was the best eating behavior predictor of WL in this worksite study with relatively high mean WL. Further studies are needed to confirm the central role of hunger control in successful WL.