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Department of Sport and Health Sciences
Faculty of Health and Life Sciences
+44 (0) 1865 483245
Headington, Gipsy Lane, GIP - S3.09
I am the Programme Lead for Nutrition and Director of the Oxford Brookes Centre for Nutrition and Health (OxBCNH). I am also the Postgraduate Research Tutor for the Department of Sport, Health Sciences and Social Work (SHSSW).
I have a first class honours degree in Home Economics and Resource Management from South Bank University, London. I completed my PhD in nutrition, from the same University, focusing on iodine in the vegan diet. I was a member of the Editorial Board for the British Journal of Nutrition (2008-2012) and I am a reviewer for several international nutrition and health journals. I am a Registered Nutritionist and was a member of the Accreditation Committee for the Association for Nutrition (AfN).
My work to date has particularly focused on energy metabolism and carbohydrate metabolism. My research has included the influence of the menstrual cycle on basal metabolic rate and food intake, the effect of food structure on the glycaemic response of foods and the effect of low-glycaemic index ingredients on 24-hour glucose profile. I have extensive experience of conducting intervention studies and randomised control trials (RCTs), in particular in the area of weight loss, body weight regulation and glycaemic control.
Module Leader for:
Other modules taught:
Currently supervising seven PhD students
Supervised nine PhD students to successful completion
My research interests include women's health and nutrition (with a particular focus on the hormonal and behavioural basis for menstrual cycle-related changes in energy metabolism), energy and glucose metabolism, glycaemic and insulinaemic response, weight loss/body weight regulation and appetite control.
My research also focuses on appetite and food intake in older adults as well as nutrition and cancer survivors.
Written information can be an essential source of support in the promotion of lifestyle changes after a cancer diagnosis. This study aimed to identify and assess the quality of available online Patient Information Materials (PIMs) in relation to diet and nutrition for pelvic cancer patients. The online sources of the National Health Service, cancer centres and charitable organisations throughout the UK were searched. Content was assessed using an evidence-based checklist, and readability with two validated formulas. Consumer feedback was sought through Patient and Public Involvement (PPI) groups. Forty PIMs were identified; four were designed specifically for pelvic cancers (bladder, bowel, prostate) and 36 were generic (relevant for all cancers). Most PIMs had a good content score, with PIMs from charities scoring higher overall than PIMs from cancer centres [32 (4) Vs 23 (11), P<0.001]. Seventy-three percent of PIMs had a readability score within acceptable levels (6th-8th grade; reading ability of 11-14 year-olds). PPI contributors found most PIMs useful and comprehensive but lacking specific information needed to meet individual needs. There is limited availability of online PIMs for cancer survivors and even fewer tailored to pelvic cancers. Most materials have comprehensive content and acceptable readability. Some PIMs may require improvement
Consumption of a low glycemic index (GI) diet may be helpful in the management and prevention of diabetes and cardiovascular disease. The investigation of GI has been predominantly confined to white subjects. We hypothesized that differences in glycemic response (GR) may be observable in subjects of different ethnic origin. The objective of the present study was to determine GR to a high GI (glucose) and low GI (maltitol) test drink in subjects of different ethnic origin. In a randomized, single-blind crossover trial, 10 whites, 10 South Indians and 10 Chinese subjects consumed either glucose or maltitol test drink containing 50 g of one of the test products on different occasions. Capillary blood glucose samples were taken at 15 and 10 minutes before and 0, 15, 30, 45, 60, 90, 120, 150, and 180 minutes after consumption of the test drink. The incremental area under the curve of glucose and maltitol were not significantly different between the 3 groups. The mean GR for maltitol was 33.5% in whites, 32.9% in Chinese, and 23.1% in South Indians. The results presented here confirmed that there are no observable differences noted in GR to a high-GI or low-GI test drink between the 3 ethnically diverse groups. We conclude that different ethnic groups exhibit similar GR to low- and high-GI drinks, and GR to maltitol is similar irrespective of ethnic background.
Aim: To examine the role of overweight and obesity on the glycaemic response to foods across the whole population. Design: Randomised, repeated measures design. Setting: Oxford, UK. Subjects and Methods: Twenty-seven healthy volunteers, 9 Caucasian, 9 Asian, and 9 African, voluntarily participated in the study. The glycaemic response to two breakfast cereals and two bread types was determined in obese and overweight subjects. Results: The current study shows that a very strong correlation exists between fasting blood glucose, peak change in glucose and the IAUC for glucose with each of BMI and WC (r = 0.88, 0.92; 0.82, 0.82; 0.91, 0.81; p = 0.01, respectively) for the Caucasian group. In addition, there was a strong significant negative association between the mean GI values of the four foods and the BMI for the Caucasian subjects (r = 0.61, p < 0.05). Furthermore, there was a strong positivesignificant association between the mean GI values of the four foods and the percentage body fat mass for the Asian subjects (r = 0.67, p < 0.05). Conclusions: This study has shown that the GI values of foods are affected by body composition in Asian and Caucasian subjects.
The objective of the present paper is to provide glycaemic index (GI) and gglycaemic load (GL) values for a variety of foods that are commonly consumed in Hong Kong and expand on the international GI table of Chinese foods. Fasted healthy subjects were given 50 g of available carbohydrate servings of a glucose reference. which was tested twice. and test foods of various brands of noodles (n 5), instant cereals (n 3) and breads (n 2), which were tested once, on separate occasions. For each test food, tests were repeated in ten healthy subjects. Capillary blood glucose was measured via finger-prick samples in fasting Subjects (- 5.0 min) and at 15, 30. 45, 60 90 and 120 min after the consumption of each test food. The GI of each test food was calculated geometrically by expressing the incremental area under the blood glucose response curve (IAUC) of each test food as a percentage of each subject's average IAUC for the reference food. GL was calculated as the product of the test food's GI and the amount of available carbohydrate in a reference serving size. The majority of Gl values of foods tested were medium (a GI value of 56-69) to high (a GI value of 70 or more) and compared well with previously published values. More importantly, our dataset provides GI values of ten foods previously untested and presents values for foods commonly consumed in Hong Kong
The glycaemic response to nine types of rice (white basmati, brown basmati, white and brown basmati, easy-cook basmati, basmati and wild rice, long-grain rice, easy-cook long-grain rice, Thai red rice, Thai glutinous rice) and two types of rice vermicelli (Guilin rice vermicelli, Jiangxi rice vermicelli) commercially available in the United Kingdom were compared against a glucose standard in a non-blind, randomized, repeated-measure, crossover design trial. Fourteen healthy subjects (six males, eight females), mean age 38 (standard deviation 16) years and mean body mass index 21.3 (standard deviation 2.3) kg/m(2), were recruited for the study. Subjects were served portions of the test foods and a standard food (glucose), on separate occasions, each containing 50 g available carbohydrates. Capillary blood glucose was measured from finger-prick samples in fasted subjects (- 5 and 0 min) and at 15, 30, 45, 60, 90 and 120 min after the consumption of each test food. For each type of food, its glycaemic index (GI) was calculated geometrically by expressing the incremental area under the blood glucose curve as a percentage of each subject's average incremental area under the blood glucose curve for the standard food. The 10 foods exhibited a range of GI values from 37 to 92. The study indicated that rice noodles, long-grain rice, easy-cook long-grain rice and white basmati rice were low-GI foods, whilst all of the other foods were medium-GI and high-GI foods. The information presented in this paper may be useful in helping people select low-GI foods from the customary foods consumed by the British and Asian populations.