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Longitudinal analysis of diet in ALSPAC. Laura D Howe EUCCONET, Bristol, October 2011. Outline. Trajectories of energy intake and macro-nutrients Planned analysis Very preliminary results. Data issues. Different # measures per individual Exact ages of measurement vary
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Longitudinal analysis of diet in ALSPAC Laura D Howe EUCCONET, Bristol, October 2011
Outline • Trajectories of energy intake and macro-nutrients • Planned analysis • Very preliminary results
Data issues • Different # measures per individual • Exact ages of measurement vary • FFQ and diary data • Want a full trajectory that is comparable for all individuals • Want to reduce the dimensionality of the data
Multi-level models:Random-slopes model yij= a + u0i + (b+u1i)tij+ eij yij=weight for individual i at occasion j, time tij • Effect of time varies between individuals (u1i) • The model estimates: • The regression coefficients a and b • Individuals intercepts (a + u0i) • Individual slopes (b+u1i) • The covariance between the intercept and slope
Multi-level models in pictures! kCal Average regression line Age
Multi-level models in pictures! kCal Age
But the real world isn’t always linear... • Model the data as a curve? • Model the data as piecewise linear?
Next steps • Include adjustment for over-reporting • Repeat for fat, protein, carbs, unhealthy sugars • Repeat for energy-adjusted fat, protein, carbs, unhealthy sugars
Using the models: diet as the exposure • Individual-level residuals = how an individual deviates from the normal • Use in standard regression techniques • Obesity • NAFLD • Cardiovascular risk factors • etc
Using the models: diet as the outcome • Include the exposure in the multilevel models • e.g. SEP • For each category of SEP, allow: • Different intercept • Different slope in each period
Acknowledgements • Emma Anderson • Kate Tilling • Debbie Lawlor • ALSPAC nutrition team