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Objectives: To investigate the relationship between vegetable intake, knowledge of recommended vegetable servings and self-assessed achievement of vegetable intake recommendations. Design and setting: Cross-sectional nutritional study in a university setting. Method: Students answered a set of standardised questions. Vegetable intake was assessed using a food frequency questionnaire (FFQ). Knowledge of recommended vegetable servings was determined by asking how many servings of vegetables should be part of the daily diet. Self-assessed achievement of vegetable recommendation was operationalised using the behavioural stages of the Health Action Process Approach (HAPA). Results: Mean vegetable intake was 176 ± 165 g/day for women and 179 ± 153 g/day for men. Overall, 7.3% of women and 9.8% of men achieved the recommended vegetable intake. Recommended vegetable servings were correctly identified by 68.5% of women and 47.1% of men. About 34.1% of women and 23.5% of men believed they could achieve the recommended intake of vegetables. However, of these, only 18.7% and 33.3% actually achieved the recommended intake. These students did not differ with respect to their knowledge of recommended vegetable servings from those who stated they achieved the recommended intake but in fact did not. Conclusion: Our study identified a potential target group who did not know that their vegetable intake was below the recommended level. It may be concluded that students have difficulty correctly estimating amounts of vegetables. From a health promotion perspective, this creates the need for the practice-oriented communication of dietary recommendations.

Aim: A balanced diet is important for health and well-being. The aim of this study was to investigate dietary intake and physical activity in German university students. Subjects and methods: A cross-sectional nutrition study was conducted at the University of Education, Schwäbisch Gmünd (Germany). Food consumption (3-day estimated dietary record) and physical activity level (PAL, standardized questionnaire) were assessed in 329 female (f) (age 22.7±3.4 years) and 60 male (m) students (age 24.0±3.1 years) and compared with recommendations (one-sample t-test, α = 0.05). Results: On average, students consumed less vegetables (f: 177±119, m: 152±163 g/day), fruit (f: 169±117, m: 146±158 g/day), and potatoes/grain products (f: 303±126, m: 362±163 g/day) than recommended. Meat consumption was too high in men (1155±651 g/week), but not in women (490±455 g/week). The consumption of milk/dairy products was slightly too low in women (190±129 g/day), but in the recommended range for men (279±253 g/day). Nutrient recommendations were almost achieved (exceptions: fiber, vitamin D and folate [f, m], fat, iron and vitamin E [f], carbohydrate [m]). Leisure time physical activity was 259±222 min/week (f) and 359±236 min/week (m), and PAL was 1.60±0.11 (f) and 1.65±0.12 (m). Conclusions: Dietary intake and physical activity in university students is roughly equivalent to that in the average German population and needs to be improved. [ABSTRACT FROM AUTHOR]

Aim: Identifying risk factors for low bone stiffness index (SI) might be one crucial strategy for osteoporosis prevention. Purpose was to characterize healthy schoolchildren across tertiles of SI. Subject and methods: In 248 girls (13.4 ± 1.9 years, BMI: 20.2 ± 4.8 kg/m2) and 231 boys (13.6 ± 1.7 years, BMI: 19.3 ± 3.3 kg/m2), the following parameters were assessed: calcaneal SI (quantitative ultrasound), body composition (bioelectrical impedance analysis), Bone Healthy Eating Index (BoneHEI; food frequency questionnaire), and physical activity level (PAL; activity questionnaire). Participants were classified according to age- and sex-specific SI tertiles (low, medium, and high). Between-group comparisons were achieved by Kruskal–Wallis-H-tests (α = 0.05). Results: Girls with low SI had significantly lower body mass (49.2 ± 16.7 vs 54.8 ± 12.2 kg; p < 0.01), BMI (19.6 ± 5.4 vs 21.3 ± 3.9 kg/m2; p < 0.0001), fat-free mass (36.3 ± 8.3 vs 39.5 ± 6.0 kg; p < 0.01), and fat mass (23.7 ± 9.1 vs 26.8 ± 7.2%; p < 0.05) compared to those with high SI. In boys, significant differences between low and high SI were obtained for PAL (1.49 ± 0.12 vs 1.56 ± 0.14; p < 0.01). BoneHEI was not significantly different between tertiles in both sexes. Conclusion: Girls with low body mass and boys with low PAL have a higher risk for low SI. Schoolchildren should strive for normal body mass and perform regular physical activity. [ABSTRACT FROM AUTHOR]

ABSTRACT BACKGROUND Evidence suggests that an insufficient fluid intake impairs cognitive performance. Drinking policies at schools-especially drinking during lessons-is a point of controversy. To provide a scientific base for this debate, more empirical evidence is needed on which aspects of fluid intake are crucial for cognitive performance. This study makes a contribution by investigating associations between quantitative and temporal aspects of fluid intake and cognitive performance in everyday school life. METHODS The study comprised 125 children (age: mean = 10.98 years, SD = 0.38). Amount of fluid intake and time span between fluid intake and completion of cognitive tests were determined on basis of self-reports. Cognitive performance was assessed by standardized tests. RESULTS Quantitative and temporal aspects were associated with cognitive performance: The more fluid the children consumed and the shorter the time span between their last fluid intake and test completion, the better they performed. CONCLUSIONS The amount of fluid intake should be adequate and moreover the time span between intake and cognitive efforts should be as short as possible. Schoolchildren are thus recommended to drink at regular intervals and also during lessons. [ABSTRACT FROM AUTHOR]

Background: Bone density in the young-adult life is associated with risk for osteoporosis in later life. Next to genetic factors, lifestyle seems to play an important role for bone health. Aim of the study was to clarify the relationship between various lifestyle factors and bone parameters in university students., Methods: In 233 women and 52 men (age: 22.7±3.1 vs. 24.0±3.2 years; BMI: 22.2±2.9 vs. 24.2±3.1 kg∙m -2 ) the following parameters were assessed: calcaneal Stiffness Index ([SI]; quantitative ultrasound), body composition (bioelectrical impedance analysis), actual and past physical activity level ([PAL]; standardized questionnaire), and food/nutrient intake (3-day dietary record). Sex differences (Mann-Whitney-U-tests), relationships between SI and lifestyle factors (Spearman's rank correlation), and the influence of the factors on the variance of SI (multiple linear regression) were tested (α=0.05)., Results: 6.9% of the women and 5.8% of the men were classified as osteopenic (-2.5< T score <-1). Significant correlations between SI and BMI, absolute fat mass and fat-free mass, actual PAL, and physical activity during adolescence were found in women (r=0.18-0.24, all P<0.05), but not in men. Food/nutrient parameters did not significantly correlate with bone outcomes (P>0.05). In multiple regression analysis physical activity during adolescence, actual PAL, and BMI explained 8% of the variance of SI (P<0.0001): SI=32.2+3.5∙physical activity during adolescence [1: very low, 2: low, 3: medium, 4: high, 5: very high] +28.5∙PAL+0.8∙BMI [kg∙m -2 ]., Conclusions: Parameters of physical activity seem to be more important for bone health than nutrition factors. Therefore, high levels of physical activity during childhood, adolescence, and early-adult life are highly recommended to improve bone parameters.

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.

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.

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.