title: Evidence of commingling in human eating behavior.
abstract: This investigation tested whether distributions of certain aspects of eating behavior were consistent with the notion of a "mixture model;" that is, two or more distinct commingled component distributions, consistent with the possibility of major gene action. Undergraduates (n=901) completed self-report trait measures of hunger, disinhibition, and dietary restraint. Variables were residualized for gender and age and transformed to remove skewness. Residualized transformed distributions were tested for departure from unimodality with Hartigan's dip statistic. The distributions of all three aspects of eating behavior were significantly non-unimodal. Next, component multivariate normal distributions were estimated via maximum likelihood. Likelihood ratio tests were employed to compare nested models. A mixture of four distributions with unequal variance-covariance matrices fit significantly better than any more parsimonious model. In sum, these data strongly suggest that the distributions of several measures of eating behavior are composed of four component distributions. This finding is consistent with the possibility of major gene effects for eating behavior.
authors.affiliation: Obesity Research Center, St. Luke's/Roosevelt Hospital Center, Columbia University College of Physicians and Surgeons, New York, NY 10025, USA.
authors.forename: D B
authors.initials: DB
authors.lastname: Allison
authors.forename: S
authors.initials: S
authors.lastname: Heshka
authors.forename: B S
authors.initials: BS
authors.lastname: Gorman
authors.forename: S B
authors.initials: SB
authors.lastname: Heymsfield
mesh_terms: D000293:Adolescent; D000328:Adult; D000367:Age Factors; D004435:Eating / Q000523:psychology; D002149:Energy Intake; D005247:Feeding Behavior; D005260:Female; D006801:Humans; D006815:Hunger; D016013:Likelihood Functions; D008297:Male; D015233:Models, Statistical; D015999:Multivariate Analysis; D012528:Satiety Response; D012737:Sex Factors; D013997:Time Factors