Association between magnesium-deficient status and anthropometric and clinical-nutritional parameters in posmenopausal women.

Background: During menopause occurs weight gain and bone loss occurs due to the hormone decline during this period and other factors such as nutrition. Magnesium deficiency suggests a risk factor for obesity and osteoporosis. OBJECTIVE: To evaluate the clinical and nutritional magnesium status in a population of postmenopausal women, assessing intake and serum levels of magnesium in the study population and correlation with anthropometric parameters such as body mass index(BMI) and body fat, and biochemical parameters associated. SUBJECTS AND METHOD: The study involved 78 healthy women aged 44-76, with postmenopausal status, from the province of Grenade, Spain. The sample was divided into two age groups: group1, aged < 58, and group 2 aged >/= 58. Anthropometric parameters were recorded and nutritional intake was assessed by 72-hour recall, getting the RDAs through Nutriber(R) program. To assess the biochemical parameters was performed a blood sample was taken. Magnesium was analyzed by flame atomic absorption spectrophotometry (FAAS) in erythrocyte and plasma wet-mineralized samples. RESULTS: Our results show that 37.85% of the total subjects have an overweight status. Magnesium intake found in our population is insufficient in 36% of women,while plasma magnesium deficiency corresponds to 23% of the population and 72% of women have deficient levels of magnesium in erythrocyte. Positive correlations were found between magnesium intake and dietary intake of calcium, of phosphorus,and with prealbumin plasma levels, as well as with a lower waist / hip ratio Magnesium levels in erythrocyte were correlated with lower triglycerides and urea values. CONCLUSION: It is important to control and monitor the nutritional status of magnesium in postmenopausal women to prevent nutritional alterations and possible clinical and chronic degenerative diseases associated with magnesium deficiency and with menopause.

Association of irisin with fat mass, resting energy expenditure, and daily activity in conditions of extreme body mass index.

FNDC5/irisin has been recently postulated as beneficial in the treatment of obesity and diabetes because it is induced in muscle by exercise, increasing energy expenditure. However, recent reports have shown that WAT also secretes irisin and that circulating irisin is elevated in obese subjects. The aim of this study was to evaluate irisin levels in conditions of extreme BMI and its correlation with basal metabolism and daily activity. The study involved 145 female patients, including 96 with extreme BMIs (30 anorexic (AN) and 66 obese (OB)) and 49 healthy normal weight (NW). The plasma irisin levels were significantly elevated in the OB patients compared with the AN and NW patients. Irisin also correlated positively with body weight, BMI, and fat mass. The OB patients exhibited the highest REE and higher daily physical activity compared with the AN patients but lower activity compared with the NW patients. The irisin levels were inversely correlated with daily physical activity and directly correlated with REE. Fat mass contributed to most of the variability of the irisin plasma levels independently of the other studied parameters. Conclusion. Irisin levels are influenced by energy expenditure independently of daily physical activity but fat mass is the main contributing factor.

Changes in Body Composition in Anorexia Nervosa: Predictors of Recovery and Treatment Outcome.

The restoration of body composition (BC) parameters is considered to be one of the most important goals in the treatment of patients with anorexia nervosa (AN). However, little is known about differences between AN diagnostic subtypes [restricting (AN-R) and binge/purging (AN-BP)] and weekly changes in BC during refeeding treatment. Therefore, the main objectives of our study were twofold: 1) to assess the changes in BC throughout nutritional treatment in an AN sample and 2) to analyze predictors of BC changes during treatment, as well as predictors of treatment outcome. The whole sample comprised 261 participants [118 adult females with AN (70 AN-R vs. 48 AN-BP), and 143 healthy controls]. BC was measured weekly during 15 weeks of day-hospital treatment using bioelectrical impedance analysis (BIA). Assessment measures also included the Eating Disorders Inventory-2, as well as a number of other clinical indices. Overall, the results showed that AN-R and AN-BP patients statistically differed in all BC measures at admission. However, no significant time×group interaction was found for almost all BC parameters. Significant time×group interactions were only found for basal metabolic rate (p = .041) and body mass index (BMI) (p = .035). Multiple regression models showed that the best predictors of pre-post changes in BC parameters (namely fat-free mass, muscular mass, total body water and BMI) were the baseline values of BC parameters. Stepwise predictive logistic regressions showed that only BMI and age were significantly associated with outcome, but not with the percentage of body fat. In conclusion, these data suggest that although AN patients tended to restore all BC parameters during nutritional treatment, only AN-BP patients obtained the same fat mass values as healthy controls. Put succinctly, the best predictors of changes in BC were baseline BC values, which did not, however, seem to influence treatment outcome.

A Nested Case-Control Study of Metabolically Defined Body Size Phenotypes and Risk of Colorectal Cancer in the European Prospective Investigation into Cancer and Nutrition (EPIC).

BACKGROUND Obesity is positively associated with colorectal cancer. Recently, body size subtypes categorised by the prevalence of hyperinsulinaemia have been defined, and metabolically healthy overweight/obese individuals (without hyperinsulinaemia) have been suggested to be at lower risk of cardiovascular disease than their metabolically unhealthy (hyperinsulinaemic) overweight/obese counterparts. Whether similarly variable relationships exist for metabolically defined body size phenotypes and colorectal cancer risk is unknown. METHODS AND FINDINGS The association of metabolically defined body size phenotypes with colorectal cancer was investigated in a case-control study nested within the European Prospective Investigation into Cancer and Nutrition (EPIC) study. Metabolic health/body size phenotypes were defined according to hyperinsulinaemia status using serum concentrations of C-peptide, a marker of insulin secretion. A total of 737 incident colorectal cancer cases and 737 matched controls were divided into tertiles based on the distribution of C-peptide concentration amongst the control population, and participants were classified as metabolically healthy if below the first tertile of C-peptide and metabolically unhealthy if above the first tertile. These metabolic health definitions were then combined with body mass index (BMI) measurements to create four metabolic health/body size phenotype categories: (1) metabolically healthy/normal weight (BMI < 25 kg/m2), (2) metabolically healthy/overweight (BMI ≥ 25 kg/m2), (3) metabolically unhealthy/normal weight (BMI < 25 kg/m2), and (4) metabolically unhealthy/overweight (BMI ≥ 25 kg/m2). Additionally, in separate models, waist circumference measurements (using the International Diabetes Federation cut-points [≥80 cm for women and ≥94 cm for men]) were used (instead of BMI) to create the four metabolic health/body size phenotype categories. Statistical tests used in the analysis were all two-sided, and a p-value of <0.05 was considered statistically significant. In multivariable-adjusted conditional logistic regression models with BMI used to define adiposity, compared with metabolically healthy/normal weight individuals, we observed a higher colorectal cancer risk among metabolically unhealthy/normal weight (odds ratio [OR] = 1.59, 95% CI 1.10-2.28) and metabolically unhealthy/overweight (OR = 1.40, 95% CI 1.01-1.94) participants, but not among metabolically healthy/overweight individuals (OR = 0.96, 95% CI 0.65-1.42). Among the overweight individuals, lower colorectal cancer risk was observed for metabolically healthy/overweight individuals compared with metabolically unhealthy/overweight individuals (OR = 0.69, 95% CI 0.49-0.96). These associations were generally consistent when waist circumference was used as the measure of adiposity. To our knowledge, there is no universally accepted clinical definition for using C-peptide level as an indication of hyperinsulinaemia. Therefore, a possible limitation of our analysis was that the classification of individuals as being hyperinsulinaemic-based on their C-peptide level-was arbitrary. However, when we used quartiles or the median of C-peptide, instead of tertiles, as the cut-point of hyperinsulinaemia, a similar pattern of associations was observed. CONCLUSIONS These results support the idea that individuals with the metabolically healthy/overweight phenotype (with normal insulin levels) are at lower colorectal cancer risk than those with hyperinsulinaemia. The combination of anthropometric measures with metabolic parameters, such as C-peptide, may be useful for defining strata of the population at greater risk of colorectal cancer.