Latent variables and structural equation models for longitudinal relationships: an illustration in nutritional epidemiology.
BACKGROUND
The use of structural equation modeling and latent variables remains uncommon in epidemiology despite its potential usefulness. The latter was illustrated by studying cross-sectional and longitudinal relationships between eating behavior and adiposity, using four different indicators of fat mass.


METHODS
Using data from a longitudinal community-based study, we fitted structural equation models including two latent variables (respectively baseline adiposity and adiposity change after 2 years of follow-up), each being defined, by the four following anthropometric measurement (respectively by their changes): body mass index, waist circumference, skinfold thickness and percent body fat. Latent adiposity variables were hypothesized to depend on a cognitive restraint score, calculated from answers to an eating-behavior questionnaire (TFEQ-18), either cross-sectionally or longitudinally.


RESULTS
We found that high baseline adiposity was associated with a 2-year increase of the cognitive restraint score and no convincing relationship between baseline cognitive restraint and 2-year adiposity change could be established.


CONCLUSIONS
The latent variable modeling approach enabled presentation of synthetic results rather than separate regression models and detailed analysis of the causal effects of interest. In the general population, restrained eating appears to be an adaptive response of subjects prone to gaining weight more than as a risk factor for fat-mass increase.
Chavance
Michel
M
Biostatistics, CESP Centre for research in Epidemiology and Population Health, U1018, Inserm; F94807, Villejuif, France. michel.chavance@inserm.fr
Escolano
Sylvie
S
Romon
Monique
M
Basdevant
Arnaud
A
de Lauzon-Guillain
Blandine
B
Charles
Marie Aline
MA
D050154:Adiposity / Q000502:physiology; D000328:Adult; D015992:Body Mass Index; D049628:Body Size; D005247:Feeding Behavior / Q000502:physiology / Q000523:psychology*; D005260:Female; D005602:France; D006801:Humans; D008137:Longitudinal Studies; D008297:Male; D008875:Middle Aged; D015233:Models, Statistical; D011594:Psychometrics; D012885:Skinfold Thickness; D015430:Weight Gain / Q000502:physiology