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Tracking dietary patterns in longitudinal studies Gina Ambrosini PhD Senior Research Scientist MRC Human Nutrition Research, Cambridge EUCCONET International Workshop, Bristol October 2011. Dietary Patterns: Longitudinal Studies.
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Tracking dietary patterns in longitudinal studies Gina Ambrosini PhD Senior Research Scientist MRC Human Nutrition Research, Cambridge EUCCONET International Workshop, Bristol October 2011
Dietary Patterns:Longitudinal Studies How can we measure empirical dietary patterns (RRR, PCA, Factor) over time ? • Longitudinal analyses require repeated measures of adherence to same dietary pattern (usually a z-score) How do disease-specific dietary patterns track over time ? • Similar dietary patterns can be observed over time, but levels of adherence are subject to change • Tracking is important for identifying: • aspects of dietary intake susceptible to change • critical times for intervention • Very few studies have measured or tracked dietary patterns over > 2 time points • None have examined tracking of RRR dietary patterns … until now … Policy Implications Gina Ambrosini
z-score T1 z-score T3 z-score T4 Dietary Patterns: Longitudinal Measurements • Very few studies measured dietary patterns longitudinally • Can treat dietary patterns as a template or measuring tool i.e. measure adherence to pattern at several time points • Assumes that the dietary pattern is ‘feasible’ over time i.e. consider changes in food supply, food choices • Confirmatory RRR can ‘project’ a dietary pattern onto data collected at different time points (or different populations) z-score T2 Time
Exploratory RRR T1 T2 T3 T4 T5 Confirmatory RRR Uses scoring coefficients or weights (produced in RRR output) to calculate ‘applied scores’: Dietary pattern z-score = linear combination of weighted food intakes = W1(Food1 Intake) + W2(Food2 Intake) + … Scoring coefficients from RRR at T1 applied to food intakes at later time points Time
How to measure tracking ? • Tracking= stability of dietary intake or dietary pattern z-score = adherence to a dietary pattern over time • Generalised estimating equation: • Regress repeated measures of the dietary pattern z-score against baseline DP score • Tracking coefficient = standardised regression coefficient for the baseline DP score • Tracking coefficient falls between 0 (no tracking) and 1 (perfect tracking)Adjusted for time between each measurement; can include covariates Standardised tracking coefficient For detailed description See appendix: Twisket al. 1997 Am J Epi 145 [10] p888-898
Conclusions • Is possible to ‘measure’ adherence to dietary patterns over time • Tracking coefficients are useful for comparing levels of tracking (any continuous variable) • RRR dietary patterns track modestly from 7 to 13 y in ALSPAC Gina Ambrosini
Acknowledgements Dr Pauline Emmett, Dr Kate Northstone, & the ALSPAC Study Team Ms Geeta Appannah, PhD scholar, MRC Human Nutrition Research Mr David Johns, PhD scholar, MRC Human Nutrition Research Dr Anna Karin Lindroos, Swedish Food Authority, Uppsala (prev. HNR) Funding from:
Gina.Ambrosini@mrc-hnr.cam.ac.uk MRC Human Nutrition Research Cambridge, UK
The Swedish Obese Subjects (SOS) Study: an energy-dense, high saturated fat, low fibre dietary pattern Very similar loadings at study registration and at 8 points during 10 years of follow up David Johns MRC Human Nutrition Research
Average dietary pattern z-scores (applied) over 10y in SOS control subjects 0.2 0 -0.2 Dietary Pattern score -0.4 -0.6 -0.8 -1 R = Registration (recruited) 0 = Baseline (assigned as case/control) 6 R 0 ½ 1 3 4 8 2 10 Year David Johns MRC HNR
SOS Dietary Pattern Tracking Coefficients * adjusted for age and smoking David Johns MRC HNR
SOS Average Food Intakes (standardised) David Johns MRC HNR
SOS Food Intake Tracking David Johns MRC HNR