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E O Diaz

Publications and source records attributed to E O Diaz.

5 recordsLinked to original sources
PubMed1992

Metabolic response to experimental overfeeding in lean and overweight healthy volunteers.

Possible adaptive mechanisms that may defend against weight gain during periods of excessive energy intake were investigated by overfeeding six lean and three overweight young men by 50% above baseline requirements with a mixed diet for 42 d [6.2 +/- 1.9 MJ/d (mean +/- SD), or a total of 265 +/- 45 MJ]. Mean weight gain was 7.6 +/- 1.6 kg (58 +/- 18% fat). The energy cost of tissue deposition (28.7 +/- 4.4 MJ/kg) matched the theoretical cost (26.0 MJ/kg). Basal metabolic rate (BMR) increased by 0.9 +/- 0.4 MJ/d and daily energy expenditure assessed by whole-body calorimetry (CAL EE) increased by 1.8 +/- 0.5 MJ/d. Total free-living energy expenditure (TEE) measured by doubly labeled water increased by 1.4 +/- 2.0 MJ/d. Activity and thermogenesis (computed as CAL EE--BMR and TEE--BMR) increased by only 0.9 +/- 0.4 and 0.9 +/- 2.1 MJ/d, respectively. All outcomes were consistent with theoretical changes due to the increased fat-free mass, body weight, and energy intake. There was no evidence of any active energy-dissipating mechanisms.

Basal Metabolism↗
PubMed1992

Body mass index, body composition and the chronic energy deficiency classification of rural adult populations in Guatemala.

The present study tested the hypotheses that: (a) individual body composition estimates obtained with the Durnin-Womersley (D-W) equations have low validity in certain populations in developing countries; (b) there exists a poor relationship between the body mass index (BMI) and body composition estimates (fat mass (BFM) and fat-free mass (FFM)), and (c) BMI cut-off estimates (fat mass (BFM) and fat-free mass (FFM)), and (c) BMI cut-off points provide an invalid classification of chronic energy deficiency (CED) in adults. The study involved four samples of rural men and women in Guatemala, who had mean BMI of approximately 21 kg/m2. Body composition estimates were obtained by densitometry in three of the samples. Mean body fat (%) and mean FFM (kg) were: men: 11.6 (+/- 4.7) and 47.7 (+/- 4.9); and women: 21.6 (+/- 5.3) and 35.8 (+/- 3.5), respectively. The D-W equations based on various combinations of skinfold measurements consistently overestimated body fat content with low precision and validity. The BMI was more related to BFM and FFM than to fat proportion, but explained little of the variation in both body components, particularly at low BMI levels. A small number of men and women had BMI values below 18.5 kg/m2, and only one woman fell below 16 kg/m2. The power coefficients of height in the weight/height ratio which provided the strongest correlations with BFM and FFM were: BFM: women: 1.0; men: 1.5; FFM: 0.5 for both women and men. We conclude that the Quetelet index should not be recommended as a universally valid indicator to classify CED in adult groups similar to the study population.

Adipose Tissue↗
PubMed1989

Bioimpedance or anthropometry?

The ability of bioimpedance (BIA) to predict body composition in comparison with anthropometric measurements (weight and height) was assessed on three groups of adult young women (n = 99) and one group of adult young men (n = 49). Body fat (BF) and fat-free mass (FFM) by densitometry were used as the reference data. Resistance and reactance separately or together were poor predictors of BF and FFM, explaining from 0 to a maximum of 21 per cent of the FFM variation in the different groups. BF followed the same pattern, though the percentage of variance explained by both variables was even lower. Height squared divided by resistance (H2/R) explained from 22 to 68 per cent of the FFM variation and from 0 to 40 per cent of BF variation. Height alone was comparable to H2/R explaining from 11 to 53 per cent of the FFM variance in the four groups studied. Body weight was found to be the best single predictor of body composition; it explained from 56 to 78 per cent of FFM and 37 to 82 per cent of BF variability. Using stepwise regression analysis with all women combined, weight accounted for 70 per cent of the total FFM variation, with height and H2/R contributing only another 5 per cent. The same was found in men (68 vs 73 per cent respectively). The reported equation of Segal et al. was applied to our group, yielding almost the same high FFM prediction (r2 greater than 0.7 and SEE less than 2.5 kg).(ABSTRACT TRUNCATED AT 250 WORDS)

Adipose Tissue↗
PubMedDate not supplied

[Statistical techniques for developing equations for impedance measurement].

The use of impedance analysis is becoming increasingly widespread as a safe, non-invasive and quick method to assess body composition. Numerous equations, based on variables derived from anthropometric variables as well as from impedance measurements analysis, have been developed to predict the alipidic mass from the resulting analysis. The most frequently used statistical method is the least squares technique. The inadequate reliability of this statistical technique is examined in this study and the use of the technique known as "ridge regression" is suggested.

Adipose Tissue↗