‘He's got his father's bias’: Parental influence on weight bias in young children

Our aim was to explore the role of parents in the transmission of stereotypical body size attitudes and awareness of weight loss strategies to preschool children. Participants were 279 3‐year‐old children and their parents, who provided data at baseline and 1 year later. Parents completed self‐report body size attitude and dieting measures. Child weight bias and awareness of weight loss strategies were assessed through interview. Over time, negative associations with large bodies and awareness of weight loss strategies increased. Fathers’ attitudes prospectively predicted boys’ weight bias and awareness of weight loss strategies. Among girls, parental attitudes were less predictive. Findings confirm the importance of fathers in the development of boys’ body attitudes and inform prevention programmes.     

A cost-benefit analysis of demand for food.

Laboratory studies of consumer demand theory require assumptions regarding the definition of price in the absence of a medium of exchange (money). In this study we test the proposition that the fundamental dimension of price is a cost-benefit ratio expressed as the effort expended per unit of food value consumed. Using rats as subjects, we tested the generality of this "unit price" concept by varying four dimensions of price: fixed-ratio schedule, number of food pellets per fixed-ratio completion, probability of reinforcement, and response lever weight or effort. Two levels of the last three factors were combined in a 2 x 2 x 2 design giving eight groups. Each group was studied under a series of six FR schedules. Using the nominal values of all factors to determine unit price, we found that grams of food consumed plotted as a function of unit price followed a single demand curve. Similarly, total work output (responses x effort) conformed to a single function when plotted in terms of unit price. These observations provided a template for interpreting the effects of biological factors, such as brain lesions or drugs, that might alter the cost-benefit ratio.     

A general structural equation model with dichotomous,ordered categorical,and continuous latent variable indicators

A structural equation model is proposed with a generalized measurement part, allowing for dichotomous and ordered categorical variables (indicators) in addition to continuous ones. A computationally feasible three-stage estimator is proposed for any combination of observed variable types. This approach provides large-sample chi-square tests of fit and standard errors of estimates for situations not previously covered. Two multiple-indicator modeling examples are given. One is a simultaneous analysis of two groups with a structural equation model underlying skewed Likert variables. The second is a longitudinal model with a structural model for multivariate probit regressions.This research was supported by Grant No. 81-IJ-CX-0015 from the National Institute of Justice, by Grant No. DA 01070 from the U.S. Public Health Service, and by Grant No. SES-8312583 from the National Science Foundation. I thank Julie Honig for drawing the figures. Requests for reprints should be sent to Bengt Muthén, Graduate School of Education, University of California, Los Angeles, California 90024.     

Forced classification: A simple application of a quantification method

This study formulates a property of a quantification method, the principle of equivalent partitioning (PEP). When the PEP is used together with Guttman's principle of internal consistency (PIC) in a simple way, the combination offers an interesting way of analyzing categorical data in terms of the variate(s) chosen by the investigator, a type of canonical analysis. The study discusses applications of the technique to multiple-choice, rank-order, and paired comparison data.This study was supported by the Natural Sciences and Engineering Research Council of Canada (Grant No. A7942). Comments on the earlier drafts from anonymous reviewers and the editor were much appreciated.     

Interpreting canonical correlation analysis through biplots of structure correlations and weights

This paper extends the biplot technique to canonical correlation analysis and redundancy analysis. The plot of structure correlations is shown to the optimal for displaying the pairwise correlations between the variables of the one set and those of the second. The link between multivariate regression and canonical correlation analysis/redundancy analysis is exploited for producing an optimal biplot that displays a matrix of regression coefficients. This plot can be made from the canonical weights of the predictors and the structure correlations of the criterion variables. An example is used to show how the proposed biplots may be interpreted.     

I'll Start My Diet Tomorrow: A Solution-Focused Approach to Weight Loss

This article illustrates through a personal case example how Solution-Focused Brief Therapy concepts can help people lose weight and keep it off.     

AN INDEX FOR ASSESSING WEIGHT CHANGE IN CHILDREN: WEIGHT/HEIGHT RATIOS1

Weight and height data from two studies were recomputed, and original data were computed using a Weight Index formula that accounts for the interaction of actual weight/height changes in growing children and compares this ratio with that of normed weight/height ratios for equal-aged children. Recomputing the data of one study showed that the Weight Index is a more sensitive procedure for assessing long-term behavioral treatment of obesity for girls than weight alone. Recomputing the data of a second study showed that the Weight Index formula is consistent for boys and girls and is a more sensitive procedure for assessing long-term effects of a variety of medical treatments for obesity than the Ponderal Index or weight alone. Computation of the data for 17 “normal” children in a preschool class showed a zero Weight Index score before and after a six-month interval elapsed without treatment. The procedure may be useful in assessing ponderosity or anorexia over intervals of six months or more with growing children or difference between actual and normed weight over shorter intervals.     

A note on partitioned determinants

A formula for the determinant of a partitioned matrix, possibly with singular submatrices, is derived and applied to some psychometric and numerical problems.     

Canonical analysis of longitudinal and repeated measures data with stationary weights

When measuring the same variables on different occasions, two procedures for canonical analysis with stationary compositing weights are developed. The first, SUMCOV, maximizes the sum of the covariances of the canonical variates subject to norming constraints. The second, COLLIN, maximizes the largest root of the covariances of the canonical variates subject to norming constraints. A characterization theorem establishes a model building approach. Both methods are extended to allow for Cohort Sequential Designs. Finally a numerical illustration utilizing Nesselroade and Baltes data is presented.The authors wish to thank John Nesselroade for permitting us to use the data whose analysis we present.