Is body mass index a measure of adiposity in elderly women?

OBJECTIVE: To evaluate the accuracy of body mass index (BMI) as a predictor of body fat in elderly women. RESEARCH METHODS AND PROCEDURES: A total of 1423 women aged 67 +/- 5 (mean +/- SD, range: 60 to 88) years were consecutively enrolled into the study. Fat mass (FM) was measured using DXA. RESULTS: BMI explained 72.9% of FM variance (p < 0.0001), with a root mean square error of estimate (RMSE) of 3.5 kg. After standardization of RMSE on the dependent variable as RMSE%, the prediction error equaled 15%. BMI explained 54.8% of FM% variance (p < 0.0001), with an RMSE of 4.1%, corresponding to an RMSE% of 11%. DISCUSSION: The relatively high RMSE% of the FM and FM%-BMI associations caution against the use of BMI as an adiposity index in individual elderly women. However, an error corresponding to 11% of FM% may be accepted for population studies of body fat in elderly women.

Is fasting insulin associated with blood pressure in obese children?

PRIMARY OBJECTIVE: We tested whether fasting insulin levels are associated with blood pressure in a large sample of obese children. SUBJECTS AND METHODS: Three hundred and fifty obese children (F:M ratio = 1.03) of 10.1 +/- 2.7 y of age (mean +/- SD) were consecutively enrolled at an Outpatient Paediatric Clinic. Obesity was diagnosed on the basis of a relative weight for age > 120% and hypertension on the basis of a systolic (SBP) or diastolic (DBP) blood pressure > 95th percentile for age after adjustment for height (Ht). MAIN OUTCOME AND RESULTS: Insulin was significantly higher in hypertensive (n = 202, 58%) than normotensive (n = 148, 42%) children (16 vs 14 microU mL(-1), geometric mean, p < 0.01, ANOVA) but the difference was not clinically relevant. Moreover, (log-transformed) insulin explained only 7 and 4% of SBP and DBP variance, respectively (p < 0.0001 for both) and this contribution disappeared after the confounding effects of age, weight or other anthropometric dimensions were taken into account (p = ns, ANCOVA). CONCLUSIONS: This study does not support the hypothesis of a clinically relevant association between fasting insulin and blood pressure in obese children.

Effects of home-based food preparation practices on the micronutrient content of foods.

We studied the effects of cooking on the vitamin and mineral content of vegetables (vegetable soup, cauliflower), meat (beefsteak) and fish (sole) and those of cutting (fruit salad) and squeezing (orange juice) on the vitamin content of fruits. In cooked dishes, vitamin retention ranged between 0 (folic acid, all dishes) and 94% (retinol, sole) and mineral retention between 63 (copper, cauliflower) and 96% (iron, vegetable soup). In orange juice, ascorbic acid appeared to be protected from oxidation for at least 12 h as compared with fruit salad. Our study shows that preparation of foods with techniques available at home may be responsible for losses of vitamins and minerals. Further studies are needed to ascertain the effects of these losses on nutritional status.

Use of bioelectric impedance analysis (BIA) in children with alterations of body water distribution.

Validation studies of bioelectric impedance analysis (BIA) were performed in children with obesity, Duchenne muscle dystrophy and juvenile rheumatoid arthritis. BIA allowed an accurate assessment of total body water in all groups (CV from 4.1 to 5.1%). However, the prediction of extracellular water by BIA was not always satisfactory (CV from 8.5 to 12.5%), being better in the groups of children with the lowest variability in body water distribution.

Effects of cooking and storage methods on the micronutrient content of foods.

Food processing has the potential to alter the nutrient quality of foods. This review deals with the effects of home-based cooking and storage practices on the micronutrient content of foods. It describes the effects of cooking, freezing and refrigeration on the vitamin and mineral content of meats, fish, fruit, vegetables and cereals. Based on this review, we suggest that the consumer should be aware of the possibility that losses in nutritional quality of foods may result from an improper use of cooking and storage techniques available at home.

The prediction of total body water and extracellular water from bioelectric impedance in obese children.

OBJECTIVES: To assess the reliability of bioelectric impedance analysis (BIA) for predicting total body water (TBW) and extracellular water (ECW) in obese children. DESIGN: Comparison of five prediction models based on: (i) body weight (Wt), (ii) the impedance (Z) index (ZI = height2/Z), (iii) the association of Wt and ZI, (iv) the body surface area (SA) to impedance ratio (SA:Z) and, (v) the body volume (V) to impedance ratio (V:Z). SUBJECTS: Thirty obese and 25 control children of 11.2 +/- 1.8 y of age. MEASUREMENTS: TBW and ECW were assessed by deuterium and bromide dilution; Z was measured at frequencies of 5,50 and 100 kHz. RESULTS: In controls, Wt explained 11% more variance of TBW than ZI (r2 = 0.977, SEE = 0.9 I, CV = 3.8%) and the association of Wt and ZI improved the prediction of TBW only slightly (r2 = 0.982, SEE = 0.8 I, CV = 3.5%). The SA:Z and V:Z indexes explained 6 and 33% less variance of TBW respectively as compared to Wt alone. In obese subjects, ZI explained 4% more variance of TBW than Wt (r2 = 0.914, SEE = 1.8 I, CV = 6.4%) and the SA:Z ratio was the most accurate predictor of TBW (r2 = 0.959, SEE = 1.2 I, CV = 4.4%). However, the increase in the explained variance of TBW associated to the use of the SA:Z ratio was of only 1% as compared to the association of ZI and Wt. The V:Z ratio explained 9% less of variance of TBW as compared to ZI. In both control and obese subjects, the association of Wt and ZI offered the best prediction of ECW (r2 = 0.807, SEE = 1.564 I and r2 = 0.826, SEE = 1.035 I, respectively). However, the values of CV were much higher in controls than in obese children (17.5% vs 8.4%) owing to their lower ECW and greater variability in ECW%. ZI was the most accurate predictor of TBW on the pooled sample (n = 55; r2 = 0.910, SEE = 1.932 I; CV = 7.4%). However, it was a poor predictor of ECW on the same sample owing to its high CV (n = 55; r2 = 0.866, SEE = 1.806 I, CV = 17.0%). CONCLUSIONS: The body surface area to impedance ratio is the most accurate predictor of TBW in obese children but the association of ZI and Wt may be of more interest when BIA is used to estimate both TBW and ECW. The impedance index offers a good prediction of TBW but not of ECW in children with different levels of fatness.

Altered body water distribution in subjects with juvenile rheumatoid arthritis and its effects on the measurement of water compartments from bioelectric impedance.

OBJECTIVE: To assess the reliability of bioelectric impedance analysis (BIA) for predicting total body water (TBW) and extracellular water (ECW) in children affected by juvenile rheumatoid arthritis (JRA). SUBJECTS: Thirty-nine children affected by JRA and 23 healthy children of similar age (11.0 +/- 3.6, range 3.0-19.0 y) were recruited for the study. METHODS: TBW and ECW were measured by deuterium oxide and bromide dilution, respectively. Bioelectric impedance (Z) was measured at frequencies of 5, 50 and 100 kHz. The prediction of TBW and ECW from BIA was based on the impedance index (ZI = height2/Z, cm2/omega). RESULTS: TBW standardized per kg of body weight and ECW standardized per litre of TBW were significantly higher in JRA as compared to control patients (59.7 +/- 2.4 vs 57.7 +/- 2.7% and 44.5 +/- 4.6 vs 38.1 +/- 7.9%, with P < 0.005 and P < 0.0001, respectively). Moreover, intracellular water standardized per litre of TBW was significantly lower in JRA than in control subjects (55.5 +/- 4.6 vs 62.5 +/- 8.1, with P < 0.0001). In both controls and patients, the use of ZI at 5kHz offered the more accurate prediction of ECW. However, the use of ZI at 100 kHz did not offer a better prediction of TBW as compared to its value of 50 kHz. Control-generated formulae for predicting water compartments from BIA [TBW = 0.716 x ZI at 100 kHz-1.504, r = 0.934, s.e.e. = 2.2 l;:ECW = 0.430 x ZI5-3.652, r = 0.869(7) s.e.e. = 1.7 l] underestimated TBW and ECW in JRA patients. However, population-specific formulae [TBW (1) = 0.766 x ZI at 100 kHz-0.053, r = 0.939, s.e.e. = 2.8 l; ECW (l) = 0.399 x ZI at 5 kHz-0.283, r = 0.886, s.e.e. = 1.7 l] allowed an accurate prediction of TBW and ECW in JRA patients, taking into account their altered body water distribution. CONCLUSIONS: Altered water distribution impedes the use of formulae developed on healthy children to predict TBW and ECW from BIA and JRA patients. It is hypothesized that chronic inflammation and subclinical malnutrition may be responsible for the altered body water distribution of JRA patients. Traditional body composition models may require adjustments for use in JRA children due to their altered body hydration and water distribution.