1. School of Population Health & Clinical Practice Life Impact | The University of Adelaide Diet pattern trajectories from 6 to 24 months and IQ at 8 years Lisa Smithers PhD RNutr Postdoctoral Research Fellow in Early Life Nutrition University of Adelaide lisa.smithers@adelaide.edu.au

2. Life Impact | The University of Adelaide Research Objective Diet during brain growth spurt RCT: breastfeeding, iron in early life influences later IQ Measure influence of the whole diet over the 6-24 months on IQ at 8 years Challenge: how to capture diet over time Slide 1 IQ at 8 y Diet 6-24 mo

3. Life Impact | The University of Adelaide Methods ALSPAC cohort FFQ at 6, 15 & 24 months –6 mo (43 FFQ items), 15 mo (70 items), 24 mo (72 items) Outline of analysis: 1.Identify major diet pattern (at 6, 15, 24 months) - Multiple imputation for missing diet pattern & covariable 2.Connect patterns over time to create trajectories 3.Regression; effect of trajectories & IQ Slide 2

4. Life Impact | The University of Adelaide Principal Component Analysis (PCA) Identify major (latent) diet patterns Each individuals pattern score is based on; 1) the frequency of consuming each food (e.g. times/wk) 2) the loading of foods on each pattern Oblimin rotation PAWS Version 17.0 Four patterns extracted at each age (6, 15, 24 mo) Slide 3 6 mo PCA Scree Plot

5. Life Impact | The University of Adelaide Mapping of diet patterns onto trajectories Trajectory6 months (n=7052) * 15 months (n=5610) * 24 months (n=6366) * Healthy Breastfeeding Breastfeeding (0.80) Formula(-0.76) Raw fruit (0.38) Raw veg (0.35) Healthy Herbs (0.60) Legumes (0.58) Raw fruit (0.50) veg(0.54) Cheese (0.47) Healthy Herbs (0.49) Legumes (0.57) Raw fruit (0.49) veg(0.27) Cheese (0.41) Discretionary Chocolate (0.57) Biscuits (0.56) Sweets (0.44) Crisps (0.31) Discretionary Chocolate (0.55) Cola (0.54) / fizzy (0.53) Sweets (0.52) Crisps (0.49) Discretionary Chocolate (0.55) Cola (0.55) / fizzy (0.57) Sweets (0.59) Crisps (0.64) Traditional Potato (0.83) Vegetables (0.83) Meat (0.75) Fruit pudding (0.59) Traditional Potato (0.68) Vegetables (0.59) Meat (0.60) Fruit pudding (0.47) Traditional Potato (0.75) Vegetables (0.69) Meat (0.64) Fruit pudding (0.26) Convenience Baby foods (BF) BF meat (0.72) BF veg (0.71) BF fruit pudding (0.71) BF milk pudding (0.62) Baby foods BF meat (0.75) BF veg (0.78) BF fruit pudding (0.75) BF milk pudding (0.70) Convenience Biscuits (0.66) Bread (0.61) Breakfast cereal (0.56) RM Milk pudding (0.30) *Complete case analysis

6. Life Impact | The University of Adelaide Generating trajectories: mixed effects models Predictors: age (6, 15, 24 months) Outcomes: pattern scores at 6, 15, 24 months Individuals observations are not independent, mixed effects models account for clustering of scores Generate intercept and slope for each individual & trajectory –Random effects (i.e. intercept and slope can vary by individual) –Error terms, slopes & intercepts normally distributed Slide 5

7. Life Impact | The University of Adelaide Generalized Linear Models (GLM) Exposure = Intercept and slope of trajectory Outcome = IQ at 8 years of age Adjusted for other diet pattern trajectories and Confounders –Perinatal (sex, GA, BW, ethnicity, maternal age, parity, singleton) –Sociodemographic (maternal social class, education, income, smoking history, home environment) Slide 6

8. Life Impact | The University of Adelaide Fully adjusted model (n=7097) Full Scale IQ * Trajectoryβ95% CIp HealthyIntercept Slope 1.95 0.92 1.10, 2.79 0.26, 1.58 <0.001 0.007 DiscretionaryIntercept Slope -2.44 -1.28 -3.86, -1.01 -2.59, 0.03 0.001 0.055 TraditionalIntercept Slope 1.13 -0.10 -0.18, 2.45 -0.57, 0.36 0.091 0.655 ConvenienceIntercept Slope -2.94 1.31 -0.86, 2.74 -4.90, 7.51 0.304 0.675 Slide 7 * IQ measured by Wechsler Intelligence Scale for children β coefficient scaled to the effect of diet trajectory over 6-24 month period n=20 imputed datasets of n=7097 participants who had IQ measured, combined using Rubins rules

9. Life Impact | The University of Adelaide Foods and the healthy trajectory Slide 8 At 6 months (times/wk) At 24 months (times/wk) 6mo PCA score ~ -1 Formula fed Infant cereal 5.0 Raw fruit0.3 Raw veg0.03 Bread0.6 24mo PCA ~ 0 Fish1.0 Legumes<0.2 Raw fruit7.2 Vegetables * 5.8 Cheese3.2 Yoghurt4.1 6mo PCA ~ 1 Mixed breast & formula Infant cereal4.5 Raw fruit1.8 Raw veg0.6 Bread1.8 24mo PCA ~ 2 Fish2.9 Legumes1.7 Raw fruit11.6 Vegetables * 7.1 Cheese4.5 Yoghurt5.0 *Does not include potato

10. Life Impact | The University of Adelaide What to make of these results? Latent diet pattern trajectories –Association with IQ is modest and remains after adjustment Healthy – positive effect Discretionary – negative effect Traditional – no effect Convenience – no effect, wide CI Public health message for change in diet over 6-18 month period Makes use of repeated measures of diet FFQ – not validated, nor quantitative (based on frequencies) Slide 9

11. Life Impact | The University of Adelaide Conclusion We have captured a longitudinal measure of latent diet patterns that shows change in diet from 6-24 months may have a measureable association with IQ at 8 years Slide 10 Acknowledgements Team from Adelaide (Australia): Dr Lisa Smithers Prof John Lynch Dr Rebecca Golley Dr Murthy Mittinty Dr Laima Brazionis Collaborators at ALSPAC: Dr Kate Northstone (Bristol Uni, UK) Dr Pauline Emmett (Bristol Uni, UK)

12. Life Impact | The University of Adelaide Diet patterns at 6 months – foods with loadings |>0.3| Slide 11 Home-made (HM) Traditional DiscretionaryReady-madeBreastfeeding HM vegetables0.83Chocolate0.57BF meat0.72Breastfeeds0.80 HM potato0.83Biscuits0.56BF veg0.71Formula-0.76 HM meat0.75Tea0.50BF fruit pudding0.72Raw fruit0.38 HM fish0.60Sweets0.44BF milk pudding0.62Raw vegetables0.35 HM fruit pudding0.59Cola / fizzy0.42BF fish0.48 HM milk pudding0.45Bread/toast0.38 HM egg0.32Crisps0.31 HM=home-made BF=baby food Diet patterns at 6 months – foods with loadings |>0.3|

13. Life Impact | The University of Adelaide Slide 12 Diet patterns at 15 months – foods with loadings |>0.3| TraditionalHealthy Contemporary DiscretionaryReady-made Meat-0.60Herbs0.60Chocolate0.55BF meat0.75 Fish-0.31Legumes0.58Biscuits0.34BF veg0.78 Gravy-0.40Spices0.48Tea0.36BF fruit pudding0.75 Potato-0.68Cheese0.47Sweets0.52BF milk pudding0.70 Other veg-0.59Ckd Vegetables0.39Cola / fizzy0.54BF fish0.61 Green peas-0.39Raw carrot0.37Crisps0.49Rice cereal0.36 Yoghurt-0.35Other raw veg0.54Gravy0.32Other baby cereal0.43 Milk pudding-0.47Raw apple0.43Ketchup0.44Rusks0.40 Fruit pudding-0.45Other raw fruit0.50Baked beans0.32 Apple juice0.35Added sugar0.30 Fish0.30 Nuts/products0.39

14. Life Impact | The University of Adelaide Slide 13 TraditionalHealthy Contemporary DiscretionaryConvenience Potato0.75Fish & products0.59Crisps0.64Biscuits0.66 Other veg0.69Legumes0.57Sweets0.59Bread0.61 Meat & products0.64Raw fruit0.49Cola / fizzy0.56Breakfast cereal0.56 Green beans0.55Herbs0.49Chocolate0.55Milk pudding0.30 Gravy/soy sce0.54Raw apple0.46Ketchup0.48 Fish & products0.33Cheese0.41Savoury snacks0.41 Apple juice0.35Baked beans0.33 Egg0.35 Diet patterns at 24 months – foods with loadings |>0.3|

15. Life Impact | The University of Adelaide Trajectory slope MeanSDRange Healthy-0.0020.028-0.12, 0.24 Discretionary0.0030.022-0.14, 0.38 Traditional-0.0010.023-0.14, 0.23 Convenience0.0030.011-0.10, 0.06 Slide 14 Proportion in remaining in same quartile at 6 & 24 months Highest Q % Lowest Q % Healthy4233 Discretionary4038 Traditional3330 Convenience2724 Complete case data