scholarly journals The Association Between Rate of Initial Weight Loss and Long-Term Success in Obesity Treatment: Does Slow and Steady Win the Race?

2010 ◽  
Vol 17 (3) ◽  
pp. 161-167 ◽  
Author(s):  
Lisa M. Nackers ◽  
Kathryn M. Ross ◽  
Michael G. Perri
2020 ◽  
Vol 4 (Supplement_1) ◽  
Author(s):  
Flavio Cadegiani

Abstract Background: Maintenance of weight loss in patients that undergo weight loss interventions is highly challenging, irrespective of the type of approach to obesity (whether surgical, pharmacological, or non-pharmacological). We proposed a protocol of an aggressive clinical treatment for obesity aiming to prevent the need of bariatric surgery, in patients unwilling to undergo this procedure, by proposing a protocol that included the combination of different anti-obesity medications and non-pharmacological modalities, for longer duration, and with an active approach to prevent weight regain. Our initial 2-year data showed that 93% (40 of 43 patients) with moderate and morbid obesity were able to avoid the need of bariatric surgery, with concomitant improvements of the biochemical profile. However, whether these patients would maintain their successful rates after five years was uncertain. Our objective is to describe the efficacy and safety of a long term (5-year data) pharmacological and multi-modal treatment for moderate and severe obesity. Methods: The 40 patients that were successful in the two-year approach in our obesity center (Corpometria Institute, Brasilia, DF, Brazil) were enrolled. A long-term anti-obesity protocol was employed, with continuous or intermittent use of anti-obesity drugs, trimestral body composition analysis, psychotherapy, visit to a nutritionist every four months, and both resistance and endurance exercises at least four times a week. Body weight (BW), total weight excess (TWE), body fat, markers of lipid and glucose metabolism, liver function, and inflammation were analyzed. Subjects that dropped out were considered as weight regain. Therapeutic success for the 5-year follow-up included as the maintenance of >20% loss of the initial BW loss, and no weight regain (or < 20% of the initial weight loss). Results: A total of 27 patients (67.5%) were able to maintain the body weight, seven dropped out, and six regained more than 20% of the initial weight loss. Of these, 21 (77.8%) had significant further increase of muscle mass and decrease of fat loss, while 17 (63.0%) had further weight loss (p < 0.05), compared to the 2-year data. Improvements on the biochemical profile persisted in all 27 patients, and had significant further improvements in 24 (88.9%) of these patients. Conclusion: The risk of weight regain five years after a weight loss treatment for obesity was significantly lower compared to previous literature, and comparable to the long-term outcomes of bariatric procedures. An aggressive, structured, and long-term clinical weight loss approach has been shown to be feasible, even for morbidly obese patients.


2014 ◽  
Vol 210 (1) ◽  
pp. S273
Author(s):  
Thu Quyên Pham ◽  
Philippe Deruelle ◽  
Marie Pigeyre ◽  
Eric Loridan ◽  
Julien Couster ◽  
...  

Obesity ◽  
2012 ◽  
Vol 20 (9) ◽  
pp. 1820-1828 ◽  
Author(s):  
Laura P. Svetkey ◽  
Jamy D. Ard ◽  
Victor J. Stevens ◽  
Catherine M. Loria ◽  
Deb Y. Young ◽  
...  

2021 ◽  
Vol 5 (Supplement_1) ◽  
pp. A489-A490
Author(s):  
Susanne Kuckuck

Abstract Altered levels of hormonal appetite regulators have been observed in obesity (BMI ≥ 30.0 kg/m2), most prominently increases of insulin and leptin (indicating resistance) as well as decreases of adiponectin - all of which are long-term energy regulators and adiposity signals. Disrupted signaling of these hormones may have detrimental effects on metabolism, but may also promote weight gain. Weight loss is often accompanied by normalizations of long-term adiposity signals, but findings concerning short-term appetite regulators after weight loss vary across interventions (e.g. very low calorie diets vs. exercise). Moreover, it is debated whether such weight-loss-induced hormonal changes may reflect a disposition for weight regain. Here, we investigated changes of long- and short-term appetite signals in response to an intensive 75-week combined lifestyle intervention (CLI) comprising a normocaloric healthy diet, physical activity and psychotherapy to promote improved long-term weight management. For 39 patients, data on fasting serum levels of appetite-regulating hormones (leptin, insulin, adiponectin, GIP, PP, PYY, CCK, FGF21) were available. Hormone levels were correlated to BMI at baseline (T0) and compared across three time points: T0, T1 (after 10 weeks; initial weight loss) and T2 (after 75 weeks; weight loss maintenance). T0-T1 hormone changes were correlated to BMI changes between T1 and T2 to investigate whether hormonal alterations during initial weight loss are associated with weight regain. At T0, hormone levels were not associated with BMI. BMI decreased significantly from T0 (40.13 kg/m2 ± 5.7) to T1 (38.2 ± 5.4, p < .001) which was maintained at T2 (38.2 kg/m2 ± 5.9, p < .001). There were no significant changes in GIP, PP, PYY, CCK and FGF21. Leptin decreased from T0 (44.9 ng/nl ± 15.3) to T1 (33 ng/nl ± 14.8, p < .001) and T2 (38.6 ng/nl ± 16.0, p < .01), just like insulin which was significantly decreased at T1 (123 pmol/l ± 65, p < .05) and T2 (128 pmol/l ± 64, p < .05) compared to T0 (160 pmol/l ± 80). Adiponectin did not change between T0 (3.36 ug/ml ± 2.1) and T1 (3.2 ug/ml ± 2.1), but was increased at T2 (3.7 ug/ml ± 2.9, p < .01) compared to T1. T0-T2 BMI decrease correlated positively with T0-T2 decreases in leptin (r = .667, p < .001), insulin (rho = .535, p < .001) and increases of adiponectin (r = .412, p < .01), but no other hormone. T0-T1 hormone changes did not predict T1-T2 BMI changes. Thus, a 75-week CLI was associated with beneficial changes in the long-term energy regulators adiponectin, leptin and insulin, but no changes in short-term appetite-regulating hormones were observed despite significant weight loss. Initial changes in appetite-regulating hormones were not associated with subsequent weight regain. Overall, our data suggest that a CLI does not lead to adverse changes in appetite regulation, but rather long-term improvements such as e.g. increased leptin and insulin sensitivity.


ISRN Obesity ◽  
2012 ◽  
Vol 2012 ◽  
pp. 1-9 ◽  
Author(s):  
A. C. Dubuisson ◽  
F. R. Zech ◽  
M. M. Dassy ◽  
N. B. Jodogne ◽  
V. M. Beauloye

Background. Efforts are needed to improve the long-term efficiency of childhood obesity treatment. To adapt strategies, the identification of subgroups of patients with a greater weight loss may be useful. Objective. To analyze the results of a chronic care program for childhood obesity and to determine baseline factors (medical, dietary, and psychosocial) associated with successful weight loss. Subjects and Method. We set up a family-targeted and individually adapted interdisciplinary long-term care program. We reviewed the medical files of 144 children (59 boys and 85 girls;  y; mean BMI-z-score: ) who had ≥2 interdisciplinary visits and ≥1-year treatment. Results. Mean treatment length was 2.2 y (1–6.7 y) with visits/year. The duration of treatment did not depend on the initial weight loss, but this was predictive of the weight change over time. Furthermore any additional weight loss was observed with time whatever the initial weight change. High levels of physical activity and daily water intake from baseline conditions were associated with a greater weight loss after 9 months of intervention. In contrast, a high baseline consumption of soft drinks resulted in lower weight loss. Family specific factors such as being a single child or the child’s family support were identified as baseline factors which may contribute to better results. Conclusion. Our study suggests that the benefit of a chronic weight control program supports the need for its integration into the current concept of treatment. Better prevention policy and parental support may improve the success of the childhood obesity treatment.


Circulation ◽  
2017 ◽  
Vol 135 (suppl_1) ◽  
Author(s):  
Samantha E Berger ◽  
Gordon S Huggins ◽  
Jeanne M McCaffery ◽  
Alice H Lichtenstein

Introduction: The development of type 2 diabetes is strongly associated with excess weight gain and can often be partially ameliorated or reversed by weight loss. While many lifestyle interventions have resulted in successful weight loss, strategies to maintain the weight loss have been considerably less successful. Prior studies have identified multiple predictors of weight regain, but none have synthesized them into one analytic stream. Methods: We developed a prediction model of 4-year weight regain after a one-year lifestyle-induced weight loss intervention followed by a 3 year maintenance intervention in 1791 overweight or obese adults with type 2 diabetes from the Action for Health in Diabetes (Look AHEAD) trial who lost ≥3% of initial weight by the end of year 1. Weight regain was defined as regaining <50% of the weight lost during the intervention by year 4. Using machine learning we integrated factors from several domains, including demographics, psychosocial metrics, health status and behaviors (e.g. physical activity, self-monitoring, medication use and intervention adherence). We used classification trees and stochastic gradient boosting with 10-fold cross validation to develop and internally validate the prediction model. Results: At the end of four years, 928 individuals maintained ≥50% of their initial weight lost (maintainers), whereas 863 did not met that criterion (regainers). We identified an interaction between age and several variables in the model, as well as percent initial weight loss. Several factors were significant predictors of weight regain based on variable importance plots, regardless of age or initial weight loss, such as insurance status, physical function score, baseline BMI, meal replacement use and minutes of exercise recorded during year 1. We also identified several factors that were significant predictors depending on age group (45-55y/ 56-65y/66-76y) and initial weight loss (lost 3-9% vs. ≥10% of initial weight). When the variables identified from machine learning were added to a logistic regression model stratified by age and initial weight loss groups, the models showed good prediction (3-9% initial weight loss, ages 45-55y (n=293): ROC AUC=0.78; ≥10% initial weight loss, ages 45-55y (n=242): ROC AUC=0.78; (3-9% initial weight loss, ages 56-65y (n=484): ROC AUC=0.70; ≥10% initial weight loss, ages 56-65y (n=455): ROC AUC = 0.74; 3-9% initial weight loss, ages 66-76y (n=150): ROC AUC=0.84; ≥10% initial weight loss, ages 66-76y (n=167): ROC AUC=0.86). Conclusion: The combination of machine learning methodology and logistic regression generates a prediction model that can consider numerous factors simultaneously, can be used to predict weight regain in other populations and can assist in the development of better strategies to prevent post-loss regain.


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