Changes in malondialdehyde and C-reactive protein concentrations after lifestyle modification are related to different metabolic syndrome-associated pathophysiological processes.

AIMS: Metabolic syndrome (MetS) is often accompanied by pro-oxidative and pro-inflammatory processes. Lifestyle modification (LiSM) may act as primary treatment for these processes. This study aimed to elucidate influencing factors on changes of malondialdehyde (MDA) and C-reactive protein (CRP) concentrations after a LiSM intervention. METHODS: Sixty subjects (53 yrs, 84% women) clinically approved to attend a 20 weeks LiSM-program were submitted to weekly nutritional counseling and physical activities combining aerobic (3 times/week) and resistance (2 times/week) exercises. Before and after intervention they were assessed for anthropometric, clinical, cardiorespiratory fitness test (CRF) and laboratory markers. Statistical analyses performed were multiple regression analysis and backward stepwise with p<0.05 and R(2) as influence index. RESULTS: LiSM was responsible for elevations in CRF, healthy eating index (HEI), total plasma antioxidant capacity (TAP) and HDL-C along with reductions in waist circumference measures and MetS (47-40%) prevalence. MDA and CRP did not change after LiSM, however, we observed that MDA concentrations were positively influenced (R(2)=0.35) by fasting blood glucose (ß=0.64) and HOMA-IR (ß=0.58) whereas CRP concentrations were by plasma gamma-glutamyltransferase activity (ß=0.54; R(2)=0.29). CONCLUSIONS: Pro-oxidant and pro-inflammatory states of MetS can be attenuated after lifestyle modification if glucose metabolism homeostasis were recovered and if liver inflammation were reduced, respectively.

Pathological and behavioral risk factors for higher serum C-reactive protein concentrations in free-living adults--a Brazilian community-based study.

Low-grade chronic systemic inflammation is often associated with chronic non-communicable diseases, and its most frequently used marker, the C-reactive protein (CRP), has become an identifier of such diseases as well as an independent predictor for cardiovascular disorders and mortality. CRP is produced in response to pro-inflammatory signaling and to individual and behavioral factors, leading to pathological states. The aim of this study was to rank the predicting factors of high CRP concentrations in free-living adults from a community-based sample. We evaluated 522 adults (40-84 years old; 381 women) for anthropometric characteristics, dietary intake, clinical and physical tests, and blood analysis. Subjects were assigned to groups, according to CRP concentrations, as normal CRP (G1; <3.0 mg/L; n = 269), high CRP (G2; 3.0-6.0 mg/L; n = 139), and very high CRP (G3; >6.0 mg/dL; n = 116). Statistical comparison between groups used one-way ANOVA or Kruskal-Wallis tests, and prediction of altered values in increasing CRP was evaluated by proportional hazard models (odds ratio). CRP distribution was influenced by gender, body mass index, body and abdominal fatness, blood leukocytes, and neutrophil counts. The higher CRP group was discriminated by the above variables in addition to lower VO(2max), serum metabolic syndrome components (triglycerides, glucose, and HDL cholesterol), higher insulin, homeostasis assessment of insulin resistance, uric acid, gamma-GT, and homocysteine. After adjustments, only fatness, blood leukocytes, and hyperglycemia remained as independent predictors for increased serum CRP concentrations. Intervention procedures to treat low-grade chronic inflammation in overweight women would mainly focus on restoring muscle mass and functions in addition to an antioxidant-rich diet.

Comparison of predictive equations for resting energy expenditure in overweight and obese adults.

Objective. To compare values from predictive equations of resting energy expenditure (REE) with indirect calorimetry (IC) in overweight and obese adults. Methods. Eighty-two participants aged 30 to 60 years old were retrospectively analyzed. The persons had a body mass index ≥25 kg/m(2). REE was estimated by IC and other five equations of the literature (Harris and Benedict, WHO1, WHO2, Owen, Mifflin). Results. All equations had different values when compared to those of IC. The best values were found by Harris and Benedict, WHO1, and WHO2, with high values of intraclass correlation coefficient and low values of mean difference. Furthermore, WHO1 and WHO2 showed lower systematic error and random. Conclusion. No predictive equations had the same values of REE as compared to those of indirect calorimetry, and those which least underestimated REE were the equations of WHO1, WHO2, and Harris and Benedict. The next step would be to validate the new equation proposed.