19 resultados para Nutritional status


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Measurement of height or length is essential in the assessment of nutritional status. In some conditions, for example cerebral palsy (CP), such measurements may be difficult or impossible. Proxy measurements such as knee height have been used to predict height in such cases. We have evaluated two equations in the literature that predict stature from knee height in a group of 17 children with CP and 20 non-disabled children. The two equations performed well on average in the non-disabled children, with the mean predicted height being within 1% of the mean measured height. Nevertheless, the limits of agreement were relatively large. This was also the case for the children with CP. Thus the equations may be accurate at the group level; however they may lead to unacceptable error at the individual level. © 2006 Informa UK Ltd.

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Aim: The aim of this report was to assess the strength and influence of periodontitis as a possible risk factor for pre-term birth (PTB) in a cohort of 81 primiparous Croatian mothers aged 18-39 years. Methods: PTB cases (n=17; mean age 25 +/- 2.9 years; age range 20-33 years) were defined as spontaneous delivery after less than 37 completed weeks of gestation that were followed by spontaneous labour or spontaneous rupture of membranes. Controls (full-time births) were normal births at or after 37 weeks of gestation (n=64; mean age 25 +/- 2.9 years; age range 19-39 years). Information on known risk factors and obstetric factors included the current pregnancy history, maternal age at delivery, pre-natal care, nutritional status, tobacco use, alcohol use, genitourinary infections, vaginosis, gestational age, and birth weight. Full-mouth periodontal examination was performed on all mothers within 2 days of delivery. Results: PTB cases had significantly worse periodontal status than controls (p=0.008). Multivariate logistic regression model, after controlling for other risk factors, demonstrated that periodontal disease is a significant independent risk factor for PTB, with an adjusted odds ratio of 8.13 for the PTB group (95% confidence interval 2.73-45.9). Conclusion: Periodontal disease represents a strong, independent, and clinically significant risk factor for PTB in the studied cohort. There are strong indicators that periodontal therapy should form a part of preventive prenatal care in Croatia.

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Bioenergetics differ between males and females of many species. Human females apportion a substantial proportion of energy resources towards gynoid fat storage, to support the energetic burden of reproduction. Similarly, axial calcium accrual is favoured in females compared with males. Nutritional status is a prognostic indicator in cystic fibrosis (CF), but girls and young women are at greater risk of death despite equivalent nutritional status to males. The aim of this study was to compare fat (energy) and calcium stores (bone density) in males and females with CF over a spectrum of disease severity. Methods: Fat as % body weight (fat%) and lumbar spine (LS) and total body (TB) bone mineral density (BMD) were measured using dual absorption X-ray photometry in 127(59M) control and 101(54M) CF subjects, aged 9–25 years. An equation for predicted age at death had been determined using survival data and history of pulmonary function for the whole clinic, based on a trivariate normal model using maximum likelihood methods (1). For the CF group, a disease severity index (predicted age at death) was calculated from the derived equations according to each subjects history of pulmonary function, current age, and gender. Disease severity was classified according to percentile of predicted age at death (‘mild’ ≥75th, ‘moderate’ 25th–75th, ‘severe’ ≤25th percentile). Wt for age z-score was calculated. Serum testosterone and oestrogen were measured in males and females respectively. Fat% and LSBMD were compared between the groups using ANOVA. Results: There was an interaction between disease severity and gender: increasing disease severity was associated with greater deficits in TB (p=0.01), LSBMD (p

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Milk protein production can be influenced by several factors, including environment, disease status, parity, stage of lactation, breed, genetic merit and the nutritional status of the animal (DePeters and Cant 1992). A combination of, or an interaction between, these factors can significantly affect milk protein production. Our study aims to identify the main factors affecting milk protein concentration in dairy cattle in the south-east Queensland region.