Grade of adiposity affects the impact of fat mass on resting energy expenditure in women.

Body fat mass (FM) adds to the variance in resting energy expenditure (REE). However, the nature and extent of this relationship remains unclear. Using a database of 1306 women and a linear regression model, we systematically analysed the contribution of FM to the total variance in REE at different grades of adiposity (ranges of body %FM). After adjusting for age, the relative contribution of FM on REE variance increased from low (10- 30- 40- # 50 %FM) and very high (>50 %FM) grades of adiposity according to the ratio between regression coefficients. These data suggest that the specific metabolic rate of fat tissue is reduced at high adiposity. This should be considered when REE is normalized for FM in obesity.

Eight-year trends in food, energy and macronutrient intake in a sample of elderly German subjects.

Time trends in the food and the corresponding energy and macronutrient intake between 1994 and 2002 are investigated as part of the longitudinal study on nutrition and health status in an ageing population in Giessen, Germany (GISELA study). The dietary intake is assessed via a 3 d estimated dietary record especially developed and validated for this study. A total of 2135 records from 532 subjects, aged 60 years and over, are analysed separately according to sex and age groups (born 1904-1928 and born 1929-1942). Results show that the food, energy and macronutrient intake of the GISELA subjects stayed fairly stable over the study period. However, some significant changes in the consumption pattern are observed, predominantly in the women and the younger age groups, which correspond to the national trends in Germany. Most obvious changes observed among the GISELA subjects are the increased intake of water (between +21.05 and +41.61 ml/d per year) and vegetables (between +2.94 and +3.38 g/d per year) and a reduced consumption of coffee and tea (between -10.65 and -15.99 ml/d per year) as well as of meat (between -1.79 and -2.56 g/d per year). The healthier food choices and the ability to change food habits could be related to the relatively high health-awareness of the GISELA subjects compared to the federal average of equivalent age groups.

World Health Organization equations have shortcomings for predicting resting energy expenditure in persons from a modern, affluent population: generation of a new reference standard from a retrospective analysis of a German database of resting energy expenditure.

BACKGROUND: Reference standards for resting energy expenditure (REE) are widely used. Current standards are based on measurements made in the first part of the past century in various races and locations. OBJECTIVE: The aim of the present study was to investigate the application of the World Health Organization (WHO) equations from 1985 in healthy subjects living in a modern, affluent society in Germany and to generate a new formula for predicting REE. DESIGN: The study was a cross-sectional and retrospective analysis of data on REE and body composition obtained from 2528 subjects aged 5-91 y in 7 different centers between 1985 and 2002. RESULTS: Mean REE varied between 5.63 and 8.07 MJ/d in males and between 5.35 and 6.46 MJ/d in females. WHO prediction equations systematically overestimated REE at low REE values but underestimated REE at high REE values. There were significant and independent effects of sex, age, body mass or fat-free mass, and fat mass on REE. Multivariate regression analysis explained up to 75% of the variance in REE. Two prediction formulas including weight, sex, and age or fat-free mass, fat mass, sex, and age, respectively, were generated in a subpopulation and cross-validated in another subpopulation. Significant deviations were still observed for underweight and normal-weight subjects. REE prediction formulas for specific body mass index groups reduced the deviations. The normative data for REE from the Institute of Medicine underestimated our data by 0.3 MJ/d. CONCLUSIONS: REE prediction by WHO formulas systematically over- and underestimates REE. REE prediction from a weight group-specific formula is recommended in underweight subjects.

Effect of age on plasma homocysteine concentrations in young and elderly subjects considering serum vitamin concentrations and different lifestyle factors.

OBJECTIVES: The aim of this study was to investigate whether an increase in total homocysteine (tHcy) concentration with increasing age is due to diminishing serum concentrations of pyridoxal-5-phosphate (PLP), vitamin B-12, and folate. The possible influence of different lifestyle factors on tHcy concentration was considered. METHODS: Plasma tHcy, serum concentrations of pyridoxal-5-phosphate, vitamin B-12, and folate, intake of coffee and tea, alcohol, and methionine, as well as cigarette smoking, were determined in 252 elderly subjects (60-87 years old) of the longitudinal study on nutrition and health status in an aging population in Giessen (GISELA) and 99 young adults (20-34 years old) of the study on health and nutrition of young adults (GEJE). RESULTS: Mean plasma tHcy concentrations were significantly higher in elderly than in young female subjects (9.7 +/- 1.9 micromol/L vs. 9.0 +/- 1.6 micromol/L, p < 0.05), but there was no difference between elderly and young men (10.6 +/- 2.1 micromol/L vs. 10.7 +/- 2.6 micromol/L). No differences in tHcy were observed between young and elderly subjects after adjustment for serum concentrations of PLP, vitamin B-12, and folate. Multiple linear regression analysis revealed a significant influence of age only in elderly, but not in younger subjects. CONCLUSION: Higher tHcy concentrations in the elderly, in comparison to younger women, are due to lower serum concentrations of PLP, vitamin B-12, and folate, whereas within the age group of elderly subjects alone tHcy concentrations increase with age irrespective of serum vitamin concentrations.

Complex correlation structure in consumption rates of major food groups: implications for the assessment of radiation exposure.

OBJECTIVE: An extensive dataset on individual food consumption was analysed in order to study all pairwise correlations between the consumption rates of 11 major food groups. Additionally, the project aimed to examine and quantify the accuracy of a recently proposed estimator of total food consumption to be used for the estimation of radiation exposure by food. Such an inquiry seems justified, because the proposed estimator implicitly presumes an essentially positive correlation structure in food consumption rates. DESIGN: Statistical analysis using representative data gathered in Germany in a nation-wide food consumption survey. SETTING: Germany. SUBJECTS: Individuals aged between 4 and 94 years namely 10,901 males and 12,308 females. RESULTS: The consumption rates of 11 major food categories showed several significantly positive, but also a number of significantly negative, correlations. Negative associations between cereal and potato products persisted consistently over all age groups, independent of sex. Other significantly negative correlations were limited to certain age groups. Reflecting these negative correlations, a subsequent analysis of relative ranks of consumption revealed that no person in the sample had the highest consumption rates in all food groups simultaneously. Based on representative samples, overestimations of 34 to 53% were obtained if--as recently suggested in the context of radiation exposure prediction--the 95th percentiles of total food consumption were determined as sums of the corresponding percentiles of the food groups. CONCLUSIONS: The complex correlation structure of food group consumption rates, as identified in this study, bears important implications for various health-related issues. Ignoring them could lead to overly conservative estimations of radiation exposure due to food ingestion or to confounding effects in epidemiological studies on nutritional risk factors of diseases. The results also indicate that a distinction into different dietary patterns might be useful in characterising different consumption habits.

A new equation especially developed for predicting resting metabolic rate in the elderly for easy use in practice.

BACKGROUND: Equations published in the literature for predicting resting metabolic rate (RMR) in older individuals were exclusively derived from studies with small samples of this age group. AIM: of the present investigation was therefore to compare the measured RMR of a relatively large group of older females and males with values for RMR calculated from the most commonly used WHO [1] equations. Furthermore, on the basis of the data collected by our study group a new equation for calculating RMR in the elderly was to be developed. Variables used in this equation should be easily and exactly determinable in practice. SUBJECTS AND METHODS: RMR was measured by indirect calorimetry after an overnight fast in a sample of 179 female (age 67.8 +/- 5.7 y, BMI 26.4 +/- 3.7 kg/m(2)) and 107 male (age 66.9 +/- 5.1 y, BMI 26.3 +/- 3.1 kg/m(2)) participants in the longitudinal study on nutrition and health status in an aging population of Giessen, Germany. The subjects were at least 60 years old, did not suffer from thyroid dysfunction, and were not taking thyroid hormones. Stepwise multiple linear regression analysis was used to estimate the best predictors of RMR. RESULTS: In females there was no significant difference between our measured RMR (5504 +/- 653 kJ/d) and RMR predicted with the WHO [1] equation (5458 +/- 440 kJ/d), whereas in males measured RMR (6831 +/- 779 kJ/d) was significantly higher than calculated RMR (6490 +/- 550 kJ/d). Results of regression analysis, considering body weight, body height, age, and sex, showed that RMR is best calculated by the following equation: RMR [kJ/d]= 3169 + 50.0 x body weight [kg] - 15.3 x age [y] + 746 x sex [female = 0, male = 1]. The variables of this equation accounted for 74 % (R(2)) of the variance in RMR and predicted RMR within +/- 486 kJ/d (SEE). CONCLUSION: On the basis of the data determined in a large group of older individuals, we offer a new equation for calculating RMR in the elderly that is both easy and accurate for use in practice.