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Introduction. Presently, obesity is endemic in many countries. Many obese patients also suffer from diseases of high social impact, such as type 2 diabetes and cardiovascular disease. Generally, therapies combining energydeficient diets and physical activity protocols are used for treating obesity. Nonetheless, presently, no universal intervention with exact parameters exists. The complexity of the problem is further exacerbated by difficulties associated with long-term weight maintenance following weight reduction therapies. Purpose and objectives of the study. This analysis attempts to assess the impact of duration of combined diet-and-exercise weight reduction protocols on changes in body mass in overweight and obese people. Applied methodology. 3142 publications in total were retrieved by filtering the database of the National Library of Medicine, National Institutes of Health USA by keywords (“weight loss”, “diet” and “exercise”) for the period between 01.01.2008 and 01.01.2018. After a selection procedure was applied, 56 of them were included in this meta-regression analysis and were grouped into three strata according to duration. Achieved major results. The results showed that therapies of short to moderate duration are the most effi cient for weight reduction, with regard to both overall effects and the amount of weight reduced per week. These findings were visualized by graphical representations of the studied data. Conclusions. On our opinion, short or moderately long weight reduction therapies with scheduled interruptions should be used for treating obesity. This strategy would successfully maintain patients’ psychological wellbeing, as well as prevent relapses and “yo-yo” effects. Originality/Value. Obesity is a problem of complex origins and simple approaches such as calorie counting are rarely effective. This study proposes a “spiral” methodology – short to moderately-long hypo-caloric regimens with scheduled interruptions.

LIMITATIONS OF PROLONGED WEIGHT REDUCTION THERAPIES IN OVERWEIGHT AND OBESE PEOPLE: A META-REGRESSION ANALYSIS