backward elimination approach was used to obtain a parsimonious model, following which FFG was included as an additional explanatory variable. Results: The participant's characteristics were age: 45 (1.67) yrs, FM: 31 (1.42) kg, RMR: 5763 (151) kJ/d, RQ: 0.83 (0.005) and FFG: +0.65 (0.30) o C. The final parsimonious model significantly predicted RMR from age, FM, FFM, ethnicity, McA ISI and FFG. The b coefficient of FFG on RMR was 50.3 kJ/d (95%CI: 2.5, 98.2, p < 0.05). There was no relationship of FFG to RQ. Conclusions: FFG maybe an unrecognized factor that contributes to interindividual variations in RMR even within TNZ. Funding source(s): N/A.Background/Aims: The 2003 Dietary Guidelines for Children and Adolescents in Australia stated that in a healthy diet, total sugar consumption should not exceed 20% of daily energy intake. This study examined total sugar consumption in a cohort of school children and compared the results to these guidelines. Method: Currently 81 children aged 9-12 y (10.5 ± 1.1 y; 51% Male) have been recruited through South Australian schools and community. Questionnaire data assessing demographics and energy and nutrient intake (Food Frequency Questionnaire) was obtained via child and parent report. Results: Daily energy consumption ranged between 3,012kJ e 19,402 kJ. Males (8596 ± 2915 kJ) and females (8768 ± 3769 kJ; p ¼ 0.818) did not differ in energy consumption. There was a strong correlation between total energy consumption and sugar intake r ¼ 0.904, p < 0.001. Sugar consumption ranged between 23.6 g e 368.8 g (140.2 ± 78.0g) and sugar as a percentage of energy ranged between 8.2% e 44.6% (26.4 ± 7.3%). Age was not related to sugar consumption as a percentage of energy, p ¼ 0.25. In this sample 21% were within the healthy sugar consumption guidelines while 79% exceeded. Amongst those who exceeded the sugar consumption guidelines there were no mean differences between genders in terms of sugar as a percentage of energy (p ¼ 0.36).
Conclusions:The results indicate a large amount of sugar consumption among children aged 8-12 y, with majority of the children consuming more than recommended. The food sources contributing to the high sugar intake should be further explored. Funding source(s): N/A.Background/Aims: The aim of this study was to compare a higher-protein diet (HP) and a higher-carbohydrate diet (HC) on psychological wellbeing outcomes in a T2DM population during weight loss and weight maintenance. Methods: Adults (n ¼ 61, aged 55 ± 8 years, BMI 33.5 ± 4.8 kg/m 2 ) with T2DM (HbA1c 8.1 ± 1.4%) were randomised to a HP diet (30% protein, 38% carbohydrate, 29% fat) or a HC diet (21%:53%:23%) for a 12 week weight loss phase (WL) followed by a 12 week weight maintenance phase (WM). BMI, HbA1c and self-administered psychological wellbeing questionnaires (Problems Areas in Diabetes, PAID; Perceived Stress Scale, PSS-10) were assessed at baseline and at the end of each phase. Data was analysis using a
Previous studies have shown that pulse (or legume) consumption can improve lipid and glucose control, and there is emerging evidence that pulses may improve peripheral vascular function. It is unclear whether cerebral blood vessel function can also be improved. The aim of the present study was to determine whether regular consumption of pulses could improve cerebrovascular vasodilator responsiveness in older, overweight adults. Sixty‐eight adults (64.6 6.7 years, BMI 31.2 4.0 kg/m2) who were habitually low pulse consumers (i.e. 蠄 ½ cup of pulses per week) were randomized to incorporate pulse‐enriched foods (~100g/day [i.e. ¾ cup/day] pulses) or energy‐matched control foods into their usual diet for 12 weeks. Cerebral vasodilator responsiveness (CVR) was assessed by transcranial Doppler ultrasonography in response to acute hypercapnia (5%CO2 inhalation) at baseline, 6 and 12 Weeks. Five‐day weighed food records captured dietary data at baseline (prior to commencing) and Week 12. Pulse intake increased significantly in the Pulse vs Control group by Week 12 (115 33g vs. 3 8g, respectively P<0.001). CVR did not change by Week 12 in either group (Pulse: 0.89% 7.7, Control 3.6% 10.6, P>0.31). Regular pulse consumption does not appear to influence cerebrovascular vasodilator responsiveness. More sensitive methods may be required to detect changes in cerebrovascular health.
Grant Funding Source: Grain Research Development Corporation
ObjectiveTo compare the effects of a higher‐protein (HP) diet and a higher‐carbohydrate (HC) diet on cardiometabolic risk factors in type 2 diabetes (T2DM) in phases of weight loss and weight maintenance.
MethodsOverweight/obese adults (n = 61, BMI 33.5 ± 4.8kgm2, aged 37 – 67 years) with T2DM were randomized to a hypocaloric HP diet (38% carbohydrate, 30% protein, 29% fat) or an isocaloric HC diet (53%,21%,23%) for 12 weeks, after which energy was adjusted to maintain a stable weight for a further 12 weeks. Outcomes were measured at baseline and the end of each phase.
ResultsForty four participants completed the study (HP n=23, HC n=21). Following weight loss, there were significant (p<0.05) reductions in body mass (‐7.7 ± 4.0kg), waist circumference (‐7.6 ± 4.5cm), blood pressure (‐9.6/‐7.2 ± 9.7/6.1mmHg), HbA1c (‐1.4 ± 1.1%), fasting glucose (‐2.5 ± 2.8mmol/L), fasting insulin (‐8.5 ± 10mU/L) and triglycerides (‐0.6 ± 1.1mmol/L). In the weight maintenance phase there were small increases (p<0.05) in total cholesterol (0.2 ± 0.5mmol/L) and HDL (0.1 ± 0.2mmol/L); no other outcomes changed (p>0.05). There were no significant differences between diets in either phase.ConclusionSubstantial improvements in cardiometabolic risk factors were achieved with weight loss in both diets and continued during weight maintenance.
Study was funded by a grant from the Pork Co‐operative Research Center.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.