The feasibility of analysing food consumption combinations of weight loss clinical trials

Transcription

1 The feasibility of analysing food consumption combinations of weight loss clinical trials Vivienne GUAN, Yasmine PROBST, Elizabeth NEALE, Allison MARTIN and Linda TAPSELL School of Medicine, Faculty of Science, Medicine and Health, University of Wollongong, Australia

2 Overweight and Obesity Overweight & obesity A global epidemic No reported successful population-based case 1 Food consumption combinations based on meals Manage overweight and obesity

3 Food intake assessment and data Detailed food intake data Advanced analytical methods A detailed dietary assessment method Diet history interview 2 Food items Food quantity Food frequency (Defined time period) Combined food intake data

4 Analytical method Food items Associations Food consumption combinations based on meals Association rules Apriori algorithm 3 Frequency item sets Association rules (support, confidence and lift)

5 Analytical method Food intake data Previous studies 4,5 Food intake data Daily intake data Pre-defined food groups/combinations VS. food items

6 Aim To explore the feasibility of using detailed food intake data to investigate food consumption combinations based on meals

7 Objectives 1. To determine whether food consumption combinations can be identified 2. To examine challenges

8 Sample and Food intake data A 10% random sample (n=62) From 3 registered clinical trials (n=617) A 10-15% sample Test the feasibility of a study 6 Food intake data Baseline paper-based diet history records Reflect combined 7 days intake Food item check list

9 Food consumption combinations The nested hierarchical food groups of the AHS food classification system 7 Food consumption combinations Consumed at the same time/occasion Groups by meals The USDA Food Combination Codes 8

10 The nested hierarchical food groups At the major food group level Identified At the sub-major & minor food group levels Breakfast, lunch, mid-meals and beverages Identified Dinner Unidentified (n=13/21%) Variations in meat The food classification system

11 USDA Food Combination Codes Breakfast 84% (n=52) Cereal with additions 55% (n=34) Bread/baked products with additions Lunch 92% (n=57) Sandwiches Dinner Variations in food consumption combinations

12 Challenge Assessing the combination of foods & beverages Beverages reporting With food Alone With food and alone Food frequency checklist 8 With food, alone and in the food checklist Number of cases

13 Conclusion Sufficiently detailed information Breakfast, lunch, mid-meals and beverages Additional food combination codes categories Challenges Meat-containing food consumption combinations Grouping beverage consumption

14 Next step Complexity of preparing food intake data Usual weekly food intake Define meals Beverage Applications Meal-based food consumption habits Data entry and analysis

15 Next step

16 Reference 1. Ng, M., et al., Global, regional, and national prevalence of overweight and obesity in children and adults during : a systematic analysis for the Global Burden of Disease Study 2013, The Lancet 384(9945) (2013), Martin, G.S., et al., Relative validity of a diet history interview in an intervention trial manipulating dietary fat in the management of Type II diabetes mellitus, Preventive Medicine 36(4) (2003), Agrawal, R. and R. Srikant. Fast algorithms for mining association rules, in Proc. 20th int. conf. very large data bases, VLDB Burden, S., et al., Identification of food groups for use in a self-administered, computer-assisted diet history interview for use in Australia, Journal of Food Composition and Analysis 22(2) (2009), Woolhead, C., et al., A generic coding approach for the examination of meal patterns, The American Journal of Clinical Nutrition 102(2) (2015), Hertzog, M.A., Considerations in determining sample size for pilot studies, Research in Nursing & Health 31(2) (2008), Food Standard Australia New Zealand. AUSNUT classification of foods and dietary supplements. Available from: /classificationofsupps/pages /default.aspx. Accessed 08/07/ Centers for Disease Control and Prevention, Combination Code in Task 2: Key Concepts about the United States Department of Agriculture Food Coding Scheme. Available from: Accessed 30 May 2016

17 Acknowledgements The HEAL study team The SMART study team The HealthTrack study team

18 Vivienne Guan Contact details