Standardisation of the waist circumference (WC) for each range of body mass index (BMI) in adult outpatients attended to in Endocrinology and Nutrition departments

By this study we seek the expectable range of waist circumference (WC) for every degree of body mass index (BMI), which will serve to studies targeting ascertaining the health risk. We studied 2,932 patients (39.6% men and 60.4% women, between 18 and 96 years ) of the same ethnic group who consecutively attended outpatient departments of our clinics between 2000 and 2004. BMI correlated linearly with the WC (cc: 0.85; p < 0.001). The men, the obese, and diabetics were older (p < 0.001). BMI was greater in women and WC in men. The women had a greater WC if they had diabetes (p < 0.01), being equal to diabetic males. The men had greater WC when they had diabetes (p < 0.001). Waist at risk was detected (men > or = 102 cm and women > or = 88 cm) in 94.3% of the obese, in 32.3% of overweight patients, in 3.8% of patients with BMI < 25, in 84.3% of diabetics, and in 72.6% of patients without diabetes. We made graphic standardisation of WC with regard to BMI, and we calculated the percentiles 10, 25, 50, 75 and 90, grouping in ranges of 2 kg/m(2) of BMI. The diabetic patients are grouped in ranges of 4 kg/m(2). As conclusion we present a standardisation of the WC measurement of patients attended to in our Endocrinology and Nutrition practices distributed in percentiles as a clinically usable tool to define the ranges of WC for every BMI value.

Compliance with dietary and nutrient recommendations in the European Prospective Investigation into Cancer and Nutrition (EPIC)-Granada cohort at recruitment

BACKGROUND: The overall intake of energy and nutrients in the Granada EPIC-cohort (European Prospective Investigation into Cancer and Nutrition) is examined in order to assess compliance with the Spanish Nutritional Objectives (NO) and the Recommended Intakes (RI). METHODS: During recruitment (1992-1996), 7,789 participants, aged 35-69, were asked about diet through a validated diet history questionnaire. Nutrient intake is compared to the NO and RI that were valid at that time. Risk of inadequate intake is estimated as the percentage of the sample with intakes: ≤ 1/3 RI (high risk), ≤ 2/3 RI- > 1/3 RI (moderate risk), ≤ RI- > 2/3 RI, > RI. Differences in intakes have been analyzed by sex and age, and by smoking status and BMI. RESULTS: The daily intake of nutrients did not meet the NO as the total contribution of energy from proteins and fats exceeded these guidelines. Whilst intake of most nutrients was above the RI, the amount of iron, magnesium and vitamins D and E provided by the diet was not enough to meet the RI: in women aged 20-49 years, about 55% were at moderate risk for iron inadequacy, and a 20% of women for magnesium. Both sexes were at high risk of inadequacy for vitamin D, although sunlight exposure may supply adequate amounts. Never smokers showed a higher compliance to the NO. CONCLUSION: At recruitment, the nutrient profile of the diet was unbalanced. The observed nutrient inadequacy for iron, magnesium and vitamin E might be attributed to inappropriate dietary habits, and may have implications for future disease risk.

Implementation of a nutrition education program in a handball team; consequences on nutritional status.

OBJECTIVE: To evaluate nutritional status and dietary habits after implementation of a nutritional education program in professional handball players. RESEARCH METHODS AND PROCEDURES: Longitudinal study of 14 handball players evaluated with 72-h recall, a questionnaire on food consumption and anthropometric measures during 4 months. The intervention consisted of a nutrition education program. RESULTS: Energy intake was consistently below the recommended allowances. Macronutrient intakes as a percentage of total energy intake were below the recommended allowances for carbohydrates, and above recommended allowances for fats. Nutritional education was followed by a significant increase (p < 0.01) in total energy and macronutrient intakes, with no significant changes in macronutrient or micronutrient intakes after adjustment for energy intake. DISCUSSION: The imbalance in nutrient intake in handball players suggests that detailed re-analysis is needed to determine specific recommendations for this population. Nutritional education with continuous follow-up to monitor athletes' dietary habits may lead them to adopt appropriate nutritional habits to optimize dietary intakes. The lack of specific recommendations for micronutrient intakes in athletes leads to confusion regarding appropriate intakes; biochemical tests that yield normal values (albeit approaching cut-off values for deficiency) may disguise deficient status for some nutrients when strenuous exercise is involved. CONCLUSION: In-depth studies with nutrition education programs that include long-term follow-up are advisable to avoid deficiencies that can lead to irreversible damage in competitive athletes.

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.