Search

Low-carbohydrate high-fat (LCHF) diets can be just as effective as high-carbohydrate, lower-fat (HCLF) diets for improving cardiovascular disease risk markers. Few studies have compared the effects of the UK HCLF dietary guidelines with an LCHF diet on lipids and lipoprotein metabolism using high-throughput NMR spectroscopy. This study aimed to explore the effect of an ad libitum 8-week LCHF diet compared to an HCLF diet on lipids and lipoprotein metabolism and CVD risk factors. For 8 weeks, n = 16 adults were randomly assigned to follow either an LCHF (n = 8, <50 g CHO p/day) or an HCLF diet (n = 8). Fasted blood samples at weeks 0, 4, and 8 were collected and analysed for lipids, lipoprotein subclasses, and energy-related metabolism markers via NMR spectroscopy. The LCHF diet increased (p < 0.05) very small VLDL, IDL, and large HDL cholesterol levels, whereas the HCLF diet increased (p < 0.05) IDL and large LDL cholesterol levels. Following the LCHF diet alone, triglycerides in VLDL and HDL lipoproteins significantly (p < 0.05) decreased, and HDL phospholipids significantly (p < 0.05) increased. Furthermore, the LCHF diet significantly (p < 0.05) increased the large and small HDL particle concentrations compared to the HCLF diet. In conclusion, the LCHF diet may reduce CVD risk factors by reducing triglyceride-rich lipoproteins and improving HDL functionality. [ABSTRACT FROM AUTHOR]

Changes in world-wide population trends have provided new demands for new technologies in areas such as care and rehabilitation. Recent developments in the the field of robotics for neurorehabilitation have shown a range of evidence regarding usefulness of these technologies as a tool to augment traditional physiotherapy. Part of the appeal for these technologies is the possibility to place a rehabilitative tool in one's home, providing a chance for more frequent and accessible technologies for empowering individuals to be in charge of their therapy.Objective: this manuscript introduces the Supervised Care and Rehabilitation Involving Personal Tele-robotics (SCRIPT) project. The main goal is to demonstrate design and development steps involved in a complex intervention, while examining feasibility of using an instrumented orthotic device for home-based rehabilitation after stroke.Methods: the project uses a user-centred design methodology to develop a hand/wrist rehabilitation device for home-based therapy after stroke. The patient benefits from a dedicated user interface that allows them to receive feedback on exercise as well as communicating with the health-care professional. The health-care professional is able to use a dedicated interface to send/receive communications and remote-manage patient's exercise routine using provided performance benchmarks. Patients were involved in a feasibility study (n=23) and were instructed to use the device and its interactive games for 180 min per week, around 30 min per day, for a period of 6 weeks, with a 2-months follow up. At the time of this study, only 12 of these patients have finished their 6 weeks trial plus 2 months follow up evaluation.Results: with the “use feasibility” as objective, our results indicate 2 patients dropping out due to technical difficulty or lack of personal interests to continue. Our frequency of use results indicate that on average, patients used the SCRIPT1 device around 14 min of self-administered therapy a day. The group average for the system usability scale was around 69% supporting system usability.Conclusions: based on the preliminary results, it is evident that stroke patients were able to use the system in their homes. An average of 14 min a day engagement mediated via three interactive games is promising, given the chronic stage of stroke. During the 2nd year of the project, 6 additional games with more functional relevance in their interaction have been designed to allow for a more variant context for interaction with the system, thus hoping to positively influence the exercise duration. The system usability was tested and provided supporting evidence for this parameter. Additional improvements to the system are planned based on formative feedback throughout the project and during the evaluations. These include a new orthosis that allows a more active control of the amount of assistance and resistance provided, thus aiming to provide a more challenging interaction. [ABSTRACT FROM PUBLISHER]

Background Accurate estimates of energy expenditure are required in clinical nutrition in order to determine the requirements of individuals and to inform feeding regimes. Calorimetry can provide accurate measurements but is often impractical in clinical or community settings; prediction equations are widely used to estimate resting energy expenditure ( REE) but have limited accuracy. A portable, self-calibrating, handheld calorimeter ( HHC) may offer an alternative way of determining REE. The aim of the study was to evaluate whether estimates of REE derived using an HHC are closer to accurate measurements than values calculated using selected prediction equations. Methods REE was measured in 36 healthy adults aged 21-58 years using a flow-through indirect calorimeter ( FIC) and HHC. Estimated REE was calculated using three predictive equations ( Harris & Benedict; Schofield; Henry). Differences in REE between the 'gold standard' values derived using the FIC and those derived using the HHC and equations were examined using paired t-tests and Bland Altman plots. Results Mean REEHHC was significantly lower than mean REEFIC [4556 ± 1042 kJ (1089 ± 249 kcal) versus 6230 ± 895 kJ (1489 ± 214 kcal), P = 0.000] and also significantly lower than mean values calculated using all three equations. The mean difference between REEHHC and REEFIC [1674 ± 908 kJ (400 ± 217 kcal)] was significantly greater ( P = 0.000) than the mean differences between the values calculated using the three prediction equations [272 ± 490 kJ (65 ± 117 kcal) (Harris-Benedict), 264 ± 510 kJ (63 ± 122 kcal) (Schofield), 84 ± 502 kJ (20 ± 120 kcal) (Henry)]. Conclusions The HHC provides estimates of REE in healthy people that are less accurate than those calculated using the prediction equations and so does not provide a useful alternative. [ABSTRACT FROM AUTHOR]

Objective: To estimate the phytate intake and molar ratio of phytate to zinc in the diet of the people in the United Kingdom. Design: Tables of the phytate content of foods were developed from twenty-eight published and unpublished studies. They were then applied to the nutrient databank of the National Diet and Nutrition Survey (NDNS). The study is a retrospective analysis of data on daily consumption of foods and drinks from the NDNS of children, adolescents, adults and the elderly based on 4-7 d weighed intakes. Subjects: A total of 6786 British participants aged 1·5 years and above, who participated in the NDNS, 1992-2001. Setting: England, Scotland and Wales. Results: The median daily intakes of phytate for children, adolescents, adults and the elderly population were 496, 615, 809 and 629 mg/d, respectively. Although there were differences in phytate intakes between men and women, and for children, adolescents and elderly populations, after adjusting for differences in energy intake, there was no significant variation. The median phytate-to-zinc molar ratios for children, adolescents, adults and the elderly population were 11·8, 10·4, 9·7 and 8·7, respectively. Overall, the main sources of phytate were cereal and cereal products (e.g. breakfast cereals and breads), vegetables, potatoes and savoury snacks (e.g. chips and crisps), hot drinks and miscellaneous foods (e.g. commercial toddler foods and drinks, chocolate and soups), fruits and nuts. Conclusions: The present study estimated the dietary intake of phytate and the phytate-to-zinc molar ratio of the diet of the UK population, which can be used for estimating the average requirement of zinc. Further research should focus on the completion and validation of the tables of phytate content of UK foods, to assess (and if necessary improve) the accuracy and precision of these findings. [ABSTRACT FROM AUTHOR]

The Foresight report (Butland et al., 2007) has identified that risk perception is an area where additional evidence is needed to improve the understanding of obesity. The Department of Health (2009) reports university students as a group vulnerable to weight gain and therefore future programs for obesity could be informed by the knowledge of the target group. The aim of this project was to investigate the knowledge of Coventry University students regarding the health risks associated with obesity. Non-probability convenience sampling was used to recruit 40 participants from Coventry University. Data was collected using a 'pen-and-paper' questionnaire format and the validated Obesity Risk Knowledge-10 scale (ORK-10 scale) was used to assess level of knowledge (Swift 2006). The ORK-10 Scale consists of 10 brief questions covering obesity related co-morbidities such as diabetes, cancer, life expectancy and high blood pressure, with the option of answering true, false or don't know. Each correct answer scored 1 point, therefore a higher score indicated greater knowledge. Socio-demographic data including gender, age, ethnicity, course and faculty were also collected. Because of the small sample size of the study, these independent variables were dichotomised; gender into male and female, age groups into <20 and >20 years, ethnicity into Caucasian and non-Caucasian, course into undergraduate and postgraduate and faculty into health and life sciences compared with other faculties. A Kolmogorov-Smirnov test was used to assess the normality of the distribution of ORK-10 scale scores. The results indicated normal distribution of ORK-10 score for gender, ethnicity, course and faculty groups, supporting the use of a t-test. For comparing scores between age groups, the data was not normally distributed, supporting the use of a nonparametric Mann-Whitney U-test. The study received approval from the Coventry University Ethics Committee. The participant population consisted of 16 males and 24 females, 13 < 20 and 27 > 20 years of age, 25 Caucasians and 15 non-Caucasians, 36 undergraduates and four postgraduates, and 20 in the health and life sciences faculty and 20 in other faculties including engineering and computing, art and design, business, environment and society, and lifelong learning. No significant differences were found in ORK-10 scores between gender ( P = 0.276), ethnicity ( P = 0.179), course ( P = 0.310), or faculty ( P = 0.168). However, a statistically significant difference was found in ORK-10 scores between age groups, participants >20 years of age had a greater level of knowledge (median = 6, interquartile range = 4), compared to those <20 years of age (median = 4, interquartile range = 2), P = 0.031. Significant differences were observed in ORK-10 scores according to age with older students scoring higher. This agrees with the finding of Swift (2006) and may be explained by the increased exposure of this age group to health messages. In contrast to previous findings (Swift 2006), studying health and life sciences was not associated with increased knowledge of health risks. This may be explained by the limited sample size of the study, the students may have been in the early stages of their course, sampling bias may have meant that only students interested in health took part, and the sampling technique may not have been representative of the population. This study found a statistically significant relationship between knowledge of health risk associated with obesity and age of the students. There is a need for further research in this area, and future studies of larger randomly selected students would help to confirm the need for targeted obesity education programs. The results conclude that students <20 years of age should be considered as a target population for future obesity education programs, in order to make a positive impact on heath behaviour and dietary choices. Butland, B., Jebb, S., Kopelman, P., McPherson, K., Thomas, S., Mardell, J., & Parry, V. (2007) Foresight Tackling Obesities: Future Choices - Project Report. 2nd edn.Government Office for Science, Department of Innovation Universities and Skills. Department of Health (2009) Obesity [online] Available at: [Accessed on 13 September 2009]. Swift, J.A., Glazebrook, C. & Macdonald, I. (2006) Validation of a brief, reliable scale to measure knowledge about the health risks associated with obesity. Int. J. Obesity, 661-668. [ABSTRACT FROM AUTHOR]

An increase in the prevalence of obesity has been observed throughout the world (WHO 2010), which is thought to be due to many factors including psychological, physiological and environmental influences which are demonstrated in the obesity system map (Butland et al., 2007). University students may be susceptible to weight gain, with evidence suggesting a decline in physical activity (PA) and adherence to poor dietary habits during university life (Hoffman et al., 2006). It has not been determined whether university students of differing courses adhere to different dietary and PA habits. The aim of this study was to investigate the dietary and PA habits of students on health related courses (HRC) versus those on non-health related courses (NHRC). Non-probability convenience sampling was used to recruit university students. The study comprised of a 30 min structured interview, which assessed dietary and PA habits. Dietary habits were assessed through a current diet history for whilst studying at university, which was documented and validated in a sub sample of the population ( n = 25) through a 7-day weighed food diary. Anthropometric variables including weight, height, and waist circumference were measured by the interviewer before proceeding with the interview questions. Energy and macronutrient intakes were analysed using Dietplan-6 dietary analysis software program (Forestfield Software, Horsham, UK). Fruit and vegetable (FV) intakes were assessed by portions according to UK recommendations (DH 2010). All variables were found to be normally distributed and so independent T-tests were used using SPSS (v.17.0.2). Significance was accepted at P < 0.05. Ethics approval was obtained from the Coventry University Ethics committee. One hundred and thirty-nine students (HRC n = 81; NHRC n = 58) participated in the study (males n = 56, females n = 83; average age = 24 ± 7 years). Individuals on HRC reported a higher FV intake than NHRC students (4.3 ± 1.5 versus 3.2 ± 1.8 portions per day; P < 0.001) and a lower waist circumference was observed in HRC students (76.4 ± 8.8 cm), compared with NHRC students (83.2 ± 9.5 cm; P < 0.001). However, no significant differences were found in energy intake from macronutrients: protein ( P = 0.787), carbohydrate ( P = 0.657), fat ( P = 0.458), total fat ( P = 0.298), saturated fat ( P = 0.383), sugars ( P = 0.285), and PA ( P = 0.404). HRC students had a significantly higher intake of FV, and a significantly lower waist circumference compared to NHRC students. This is likely to be attributed to their enrolment on HRC, which potentially promotes a greater exposure to the awareness on the impact of healthy behaviours through teaching activities and clinical placements (Swift et al., 2007). No significant differences were found in other dietary and PA habits between HRC and NHRC students, which are contrary to previous studies conducted in differing countries (Irazusta et al., 2006). Irazusta et al. (2006) found that the level of PA among first-year female nursing students was lower than that of other first-year female students. The contradictory results may be due to inadequate sampling. This could have led to NHRC students who have an underlying interest in health taking part. HRC students consumed more FV and presented lower waist circumferences than NHRC students. No other differences in dietary and PA habits were observed. This study suggests that it may be beneficial to target some nutritional messages such as increasing FV intake, at those on NHRCs. Larger randomised studies of this population will be needed to confirm these conclusions. Butland, B., Jebb, S., Kopelman, P., McPherson, K., Thomas, S., Mardell, J. & Parry, V. (2007) Foresight Tackling Obesities: Future Choices - Project Report, 2nd edn.Government Office for Science, Department of Innovation Universities and Skills. Department of Health (2010) Available at [Accessed on 19 September 2010]. Hoffman, D., Policastro, P., Quick, V. & Lee, S. (2006) Changes in body weight and fat mass of men and women in the first year of college. J. Am. Coll. Health , 45-45. Irazusta, A., Gil, S., Ruiz, F., Gondra, J., Jauregi, A., Irazusta, J. & Gil, J. (2006) Exercise, Physical fitness, and dietary habits of first-year female nursing students. Biol. Res. Nurs., 175-186. Swift, J.A., Sheard, C. & Rutherford, M. (2007) Trainee health care professionals' knowledge of the health risks associated with obesity. J. Hum. Nutr. Diet., 599-604. World Health Organisation. (2010) Obesity Available at [Accessed on 10 September 2010]. [ABSTRACT FROM AUTHOR]

The Foresight report (Butland et al., 2007) has identified that risk perception is an area where additional evidence is needed to improve the understanding of obesity. The Department of Health (2009) reports university students as a group vulnerable to weight gain and therefore future programs for obesity could be informed by the knowledge of the target group. The aim of this project was to investigate the knowledge of Coventry University students regarding the health risks associated with obesity. Non-probability convenience sampling was used to recruit 40 participants from Coventry University. Data was collected using a 'pen-and-paper' questionnaire format and the validated Obesity Risk Knowledge-10 scale (ORK-10 scale) was used to assess level of knowledge (Swift 2006). The ORK-10 Scale consists of 10 brief questions covering obesity related co-morbidities such as diabetes, cancer, life expectancy and high blood pressure, with the option of answering true, false or don't know. Each correct answer scored 1 point, therefore a higher score indicated greater knowledge. Socio-demographic data including gender, age, ethnicity, course and faculty were also collected. Because of the small sample size of the study, these independent variables were dichotomised; gender into male and female, age groups into <20 and >20 years, ethnicity into Caucasian and non-Caucasian, course into undergraduate and postgraduate and faculty into health and life sciences compared with other faculties. A Kolmogorov-Smirnov test was used to assess the normality of the distribution of ORK-10 scale scores. The results indicated normal distribution of ORK-10 score for gender, ethnicity, course and faculty groups, supporting the use of a t-test. For comparing scores between age groups, the data was not normally distributed, supporting the use of a nonparametric Mann-Whitney U-test. The study received approval from the Coventry University Ethics Committee. The participant population consisted of 16 males and 24 females, 13 < 20 and 27 > 20 years of age, 25 Caucasians and 15 non-Caucasians, 36 undergraduates and four postgraduates, and 20 in the health and life sciences faculty and 20 in other faculties including engineering and computing, art and design, business, environment and society, and lifelong learning. No significant differences were found in ORK-10 scores between gender ( P = 0.276), ethnicity ( P = 0.179), course ( P = 0.310), or faculty ( P = 0.168). However, a statistically significant difference was found in ORK-10 scores between age groups, participants >20 years of age had a greater level of knowledge (median = 6, interquartile range = 4), compared to those <20 years of age (median = 4, interquartile range = 2), P = 0.031. Significant differences were observed in ORK-10 scores according to age with older students scoring higher. This agrees with the finding of Swift (2006) and may be explained by the increased exposure of this age group to health messages. In contrast to previous findings (Swift 2006), studying health and life sciences was not associated with increased knowledge of health risks. This may be explained by the limited sample size of the study, the students may have been in the early stages of their course, sampling bias may have meant that only students interested in health took part, and the sampling technique may not have been representative of the population. This study found a statistically significant relationship between knowledge of health risk associated with obesity and age of the students. There is a need for further research in this area, and future studies of larger randomly selected students would help to confirm the need for targeted obesity education programs. The results conclude that students <20 years of age should be considered as a target population for future obesity education programs, in order to make a positive impact on heath behaviour and dietary choices. Butland, B., Jebb, S., Kopelman, P., McPherson, K., Thomas, S., Mardell, J., & Parry, V. (2007) Foresight Tackling Obesities: Future Choices - Project Report. 2nd edn.Government Office for Science, Department of Innovation Universities and Skills. Department of Health (2009) Obesity [online] Available at: [Accessed on 13 September 2009]. Swift, J.A., Glazebrook, C. & Macdonald, I. (2006) Validation of a brief, reliable scale to measure knowledge about the health risks associated with obesity. Int. J. Obesity, 661-668. [ABSTRACT FROM AUTHOR]

An increase in the prevalence of obesity has been observed throughout the world (WHO 2010), which is thought to be due to many factors including psychological, physiological and environmental influences which are demonstrated in the obesity system map (Butland et al., 2007). University students may be susceptible to weight gain, with evidence suggesting a decline in physical activity (PA) and adherence to poor dietary habits during university life (Hoffman et al., 2006). It has not been determined whether university students of differing courses adhere to different dietary and PA habits. The aim of this study was to investigate the dietary and PA habits of students on health related courses (HRC) versus those on non-health related courses (NHRC). Non-probability convenience sampling was used to recruit university students. The study comprised of a 30 min structured interview, which assessed dietary and PA habits. Dietary habits were assessed through a current diet history for whilst studying at university, which was documented and validated in a sub sample of the population ( n = 25) through a 7-day weighed food diary. Anthropometric variables including weight, height, and waist circumference were measured by the interviewer before proceeding with the interview questions. Energy and macronutrient intakes were analysed using Dietplan-6 dietary analysis software program (Forestfield Software, Horsham, UK). Fruit and vegetable (FV) intakes were assessed by portions according to UK recommendations (DH 2010). All variables were found to be normally distributed and so independent T-tests were used using SPSS (v.17.0.2). Significance was accepted at P < 0.05. Ethics approval was obtained from the Coventry University Ethics committee. One hundred and thirty-nine students (HRC n = 81; NHRC n = 58) participated in the study (males n = 56, females n = 83; average age = 24 ± 7 years). Individuals on HRC reported a higher FV intake than NHRC students (4.3 ± 1.5 versus 3.2 ± 1.8 portions per day; P < 0.001) and a lower waist circumference was observed in HRC students (76.4 ± 8.8 cm), compared with NHRC students (83.2 ± 9.5 cm; P < 0.001). However, no significant differences were found in energy intake from macronutrients: protein ( P = 0.787), carbohydrate ( P = 0.657), fat ( P = 0.458), total fat ( P = 0.298), saturated fat ( P = 0.383), sugars ( P = 0.285), and PA ( P = 0.404). HRC students had a significantly higher intake of FV, and a significantly lower waist circumference compared to NHRC students. This is likely to be attributed to their enrolment on HRC, which potentially promotes a greater exposure to the awareness on the impact of healthy behaviours through teaching activities and clinical placements (Swift et al., 2007). No significant differences were found in other dietary and PA habits between HRC and NHRC students, which are contrary to previous studies conducted in differing countries (Irazusta et al., 2006). Irazusta et al. (2006) found that the level of PA among first-year female nursing students was lower than that of other first-year female students. The contradictory results may be due to inadequate sampling. This could have led to NHRC students who have an underlying interest in health taking part. HRC students consumed more FV and presented lower waist circumferences than NHRC students. No other differences in dietary and PA habits were observed. This study suggests that it may be beneficial to target some nutritional messages such as increasing FV intake, at those on NHRCs. Larger randomised studies of this population will be needed to confirm these conclusions. Butland, B., Jebb, S., Kopelman, P., McPherson, K., Thomas, S., Mardell, J. & Parry, V. (2007) Foresight Tackling Obesities: Future Choices - Project Report, 2nd edn.Government Office for Science, Department of Innovation Universities and Skills. Department of Health (2010) Available at [Accessed on 19 September 2010]. Hoffman, D., Policastro, P., Quick, V. & Lee, S. (2006) Changes in body weight and fat mass of men and women in the first year of college. J. Am. Coll. Health , 45-45. Irazusta, A., Gil, S., Ruiz, F., Gondra, J., Jauregi, A., Irazusta, J. & Gil, J. (2006) Exercise, Physical fitness, and dietary habits of first-year female nursing students. Biol. Res. Nurs., 175-186. Swift, J.A., Sheard, C. & Rutherford, M. (2007) Trainee health care professionals' knowledge of the health risks associated with obesity. J. Hum. Nutr. Diet., 599-604. World Health Organisation. (2010) Obesity Available at [Accessed on 10 September 2010]. [ABSTRACT FROM AUTHOR]

A letter to the editors is presented in response to their article on zinc intake adequacy in Great Britain in the February 2004 issue.