Tracking dietary patterns in 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.

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Tracking dietary patterns in longitudinal studies Gina Ambrosini PhD Senior Research Scientist

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Tracking dietary patterns in longitudinal studies gina ambrosini phd senior research scientist

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

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


Dietary patterns longitudinal measurements

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


Confirmatory rrr

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


Alspac energy dense high fat low fibre dietary pattern

ALSPAC energy-dense, high fat, low fibre dietary pattern


How to measure tracking

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


Tracking the alspac dietary pattern 7 to 13 y of age

Tracking the ALSPAC Dietary Pattern: 7 to 13 y of age


Tracking dietary patterns in longitudinal studies gina ambrosini phd senior research scientist

Food intakes standardised before analysis


Conclusions

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

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:


Tracking dietary patterns in longitudinal studies gina ambrosini phd senior research scientist

[email protected]

MRC Human Nutrition Research

Cambridge, UK


The swedish obese subjects sos study an energy dense high saturated fat low fibre dietary pattern

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


Tracking dietary patterns in longitudinal studies gina ambrosini phd senior research scientist

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

SOS Dietary Pattern Tracking Coefficients

* adjusted for age and smoking

David Johns MRC HNR


Sos average food intakes standardised

SOS Average Food Intakes (standardised)

David Johns MRC HNR


Sos food intake tracking

SOS Food Intake Tracking

David Johns MRC HNR


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