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Characterising very early diet exposures: development of a complementary feeding index

Characterising very early diet exposures: development of a complementary feeding index. Rebecca K Golley PhD APD. Research Fellow Public Health Group Sansom Institute for Health Research University of South Australia, Adelaide. Acknowledgements.

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Characterising very early diet exposures: development of a complementary feeding index

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  1. Characterising very early diet exposures: development of a complementary feeding index Rebecca K Golley PhD APD Research Fellow Public Health Group Sansom Institute for Health Research University of South Australia, Adelaide

  2. Acknowledgements Lisa G Smithers2, Murthy N Mittinty2, Laima Brazionis2, Pauline Emmett3, Karen Campbell4, Sarah McNaughton4, Kate Northstone3, John W Lynch2,3 1University of South Australia, 2University of Adelaide, Australia, 3University of Bristol, England, 4Deakin University, Australia Funding support: RKG is supported by the National Health and Medical Research Council of Australia.

  3. Why the Complementary Feeding Period? • Nutritionally sensitive period • Breastfeeding duration • Age of introduction of solids • Type, amount and composition of food • Supply of energy and nutrients • Establishment of lifelong dietary behaviours • Food habits • Taste and texture preferences • Implications for later diet, health and development

  4. What’s the Challenge? • Three studies ‘diet quality’ <12 mo age Smithers et al Nutr Reviews 2011 • Nutrient adequacy, Diet diversity • Child Feeding Index • Complementary feeding guidelines • Sufficient nutritious food for growth, development & health (amount, quality, variety, moderation) • Developmentally appropriate (timing, texture) • ‘How’ to feed (responsive feeding, persistence)

  5. Study Aim • To development an index to characterise quality of the complementary feeding period • adherence to complementary feeding guidelines • developed country context • address (some) methodological challenges • To examine the face validity of the Complementary Feeding Utility Index (CFUI) • Food and nutrient intake • sociodemographic characteristics • Dietary patterns in childhood

  6. Summary of Diet Index Construction Selection of index components Quantification of component scores Summing of component scores Adapted Kourlabaet al 2009 TOTAL SCORE ‘Diet quality’

  7. CFUI: 14 components Breastfeeding (months) 0 1 2 3 4 5 6 7 8 9 10 11 12 0 5 10 Energy dense nutrient poor foods (types) 0 1 2 3 4 5 6 0 5 10 Fed on demand (categorical ) N S Y 0 5 10

  8. Quantification of component scores: Conversion to Probabilities Variety of Protein foods = # children having 1 to 3 types protein foods - # having 1 or 2 or 3 types # children having 1 to 3 types protein foods = 9747 - # children having 1 type protein foods i.e. 4735 9747 = 0.51

  9. Quantification of component scores: Theoretical Derived Probabilities

  10. How to derive a total score? • Each component has score of 0 to 1 • Sum or mean: various pathways=same score • Inverse Euclidian norm: how each component score varies from guideline adherence

  11. Mean CFUI score = 0.48±0.1 N=6065 6 mo

  12. Association with energy-adjusted nutrient intake Nutrient intake at 8 months of age for Children In Focus sub-sample (n=989)

  13. Socio-demographic factors • Higher Complementary Feeding Utility Index scores were associated with • older maternal age • higher maternal education level • Healthy maternal weight status. • Higher Complementary Feeding Utility Index scores were not associated with • Number of siblings

  14. Association with Dietary Patterns at 3 y N=6065 Adjusted models; dietary pattern scores, child, maternal and family socio-demographics

  15. Conclusions • The Complementary Feeding Utility Index • reflects adherence to early feeding guidelines • has face validity as a composite measure of early diet quality • scores were associated with food and nutrient intake largely in the expected direction • Methodological challenges addressed • components that are unit free • Scoring range based on observed/ theoretical preferences • Contribution of components to total score • Next steps • Predictive validity: association with child health and development outcomes

  16. Questions? Thank you!

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