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. Author manuscript; available in PMC: 2012 Apr 3.
Published in final edited form as: Epidemiology. 2010 May;21(3):360–365. doi: 10.1097/EDE.0b013e3181d5bff5

TABLE 1. Analysis of Deviance for nested Models in Men and Women.

The ObEpi (“Enquête épidémiologique nationale sur le surpoids et l’obésité”) studies.

Residual df Residual Deviance Nested Model comparisons Tested effect Df Deviance Difference P-values
men women men women men women
model 1 Age 57 131.5 249.6
model 1a Age-drifta 56 51.9 62.5 1 and 1a Linear effect of cohort or period adjusted for age 1 79.5 187.1 <0.0001 <0.0001
model 2a Age-cohort 38 25.8 26.7 1a and 2a Nonlinear cohort effect adjusted for age 18 26.1 35.7 0.09 0.008
model 3 Age-period-cohort 36 23.5 25.7 2a and 3 Nonlinear period effect adjusted for age and cohort 2 2.3 1.0 0.32 0.59
model 2b Age-period 54 49.3 61.7 2b and 3 Nonlinear cohort effect adjusted for age and period 18 25.8 35.9 0.10 0.007
model 1b Age-drift 56 51.9 62.5 1b and 2b Nonlinear period effect adjusted for age 2 2.6 0.8 0.27 0.66
a

The linear evolution of obesity prevalence observed during the survey period, cannot be specifically attributed to cohort or to period, and is called the “drift.” This model includes the period effect, or the cohort effect, as a quantitative variable. Whatever the variable (period of cohort), the fit and the estimation of the drift effect are identical.