Carina Andriatta Blume

Weight‐loss interventions and gut microbiota changes in overweight and obese patients: a systematic review

Imbalances in the gut microbiota, the bacteria that inhabit the intestines, are central to the pathogenesis of obesity. This systematic review assesses the association between the gut microbiota and weight loss in overweight/obese adults and its potential manipulation as a target for treating obesity. This review identified 43 studies using the keywords ‘overweight’ or ‘obesity’ and ‘microbiota’ and related terms; among these studies, 17 used dietary interventions, 11 used bariatric surgery and 15 used microbiota manipulation. The studies differed in their methodologies as well as their intervention lengths. Restrictive diets decreased the microbiota abundance, correlated with nutrient deficiency rather than weight loss and generally reduced the butyrate producers Firmicutes, Lactobacillus sp. and Bifidobacterium sp. The impact of surgical intervention depended on the given technique and showed a similar effect on butyrate producers, in addition to increasing the presence of the Proteobacteria phylum, which is related to changes in the intestinal absorptive surface, pH and digestion time. Probiotics differed in strain and duration with diverse effects on the microbiota, and they tended to reduce body fat. Prebiotics had a bifidogenic effect and increased butyrate producers, likely due to cross‐feeding interactions, contributing to the gut barrier and improving metabolic outcomes. All of the interventions under consideration had impacts on the gut microbiota, although they did not always correlate with weight loss. These results show that restrictive diets and bariatric surgery reduce microbial abundance and promote changes in microbial composition that could have long‐term detrimental effects on the colon. In contrast, prebiotics might restore a healthy microbiome and reduce body fat.

Early reduction of resting energy expenditure and successful weight loss after Roux-en-Y gastric bypass

BACKGROUND Weight loss and body composition changes after Roux-en-Y gastric bypass (RYGB) may influence resting energy expenditure (REE). The effect of lower REE after the procedure on long-term weight remains to be elucidated. OBJECTIVE To evaluate the effects of RYGB on REE and body composition 6 months after RYGB and to find out whether postsurgery REE affects weight at 12 and 18 months SETTING: Tertiary referral hospital, southern Brazil METHOD: A prospective study involving 30 RYGB patients aged>18 years was performed. Body composition was evaluated by X-ray absorptiometry and REE by indirect calorimetry. All patients were assessed before RYGB and 6 months postoperatively. Further analysis of weight was carried out at 12 and 18 months. RESULTS Baseline body mass index was 49±9 kg/m² and mean weight was 128±19 kg, half of which comprised fat mass (50±5%). Baseline mean REE was 2297±182 kcal/d. The percent total weight loss was 26±7%, 32±9%, and 34±9% at 6, 12, and 18 months, respectively. The percent excess weight loss gradually increased from 54 ± 12% at 6 months, to 67 ± 18% at 12 months, and 71 ± 19% at 18 months. REE was significantly lower at follow-up (-405±108 kcal/d; P<.001). Furthermore, an inverse correlation between REE at 6 months and percent excess weight loss at 18 months (r =-.612; P = .035) was observed in the subgroup of patients whose REE decreased>405 kcal/d at 6 months. CONCLUSION Patients undergoing RYGB who had a substantial drop in REE at 6 months may exhibit less long-term weight loss.

Energy expenditure changes after Roux-en-Y Gastric Bypass

Background Weight loss usually decreases energy expenditure (EE) because of changes in body composition (BC). The reduction in EE may contribute, in part, to long-term weight regain. Patients undergoing bariatric surgery might experience a decrease in EE, mainly due to reduced resting metabolic rate (RMR), explained by a decreased lean body mass (LBM), similarly to what occurs to patients after diet-induced weight loss.

Performance of resting metabolic rate estimation equations in obese patients

Background Weight gain may be associated with an imbalance between energy intake and energy expenditure. The resting metabolic rate (RMR) is the main component of total energy expenditure, and is related mainly to lean mass (LM), as well as to other factors such as fat mass (FM), age, sex and genetic factors. A RMR lower than expected may be a risk factor for weight gain. RMR is estimated by equations that use patients weight, sex, age and height to calculate energy needs. Several studies have shown that these equations have a poor agreement with RMR measured by indirect calorimetry (IC) in obese patients once their excess fat-free mass (FFM) is usually not taken into account.