Relating body mass index to figural stimuli: population-based normative data for Caucasians

OBJECTIVE: To establish body mass index (BMI) norms for standard figural stimuli using a large Caucasian population-based sample. In addition, we sought to determine the effectiveness of the figural stimuli to identify individuals as obese or thin. DESIGN: All Caucasian twins born in Virginia between 1915 and 1971 were identified by public birth record. In addition, 3347 individual twins responded to a letter published in the newsletter of the American Association of Retired Persons (AARP). All adult twins (aged 18 and over) from both of these sources and their family members were mailed a 16 page 'Health and Lifestyle' questionnaire. SUBJECTS: BMI and silhouette data were available on 16 728 females and 11 366 males ranging in age from 18- 100. MEASUREMENTS: Self-report information on height-weight, current body size, desired body size and a discrepancy score using standard figural stimuli. RESULTS: Gender- and age-specific norms are presented linking BMI to each of the figural stimuli. Additional norms for desired body size and discrepancy scores are also presented. Receiver operating curves (ROC) indicate that the figural stimuli are effective in classifying individuals as obese or thin. CONCLUSIONS: With the establishment of these norms, the silhouettes used in standard body image assessment can now be linked to BMI. Differences were observed between women and men in terms of desired body size and discrepancy scores, with women preferring smaller sizes. The figural stimuli are a robust technique for classifying individuals as obese or thin.

Laser-derived particle size data from CRP-3, Victoria Land Basin, Antarctica: Implications for sequence and seismic stratigraphy

Seven hundred and nineteen samples from throughout the Cainozoic section in CRP-3 were analysed by a Malvern Mastersizer laser particle analyser, in order to derive a stratigraphic distribution of grain-size parameters downhole. Entropy analysis of these data (using the method of Woolfe and Michibayashi, 1995) allowed recognition of four groups of samples, each group characterised by a distinctive grain-size distribution. Group 1, which shows a multi-modal distribution, corresponds to mudrocks, interbedded mudrock/sandstone facies, muddy sandstones and diamictites. Group 2, with a sand-grade mode but showing wide dispersion of particle size, corresponds to muddy sandstones, a few cleaner sandstones and some conglomerates. Group 3 and Group 4 are also sand-dominated, with better grain-size sorting, and correspond to clean, well-washed sandstones of varying mean grain-size (medium and fine modes, respectively). The downhole disappearance of Group 1, and dominance of Groups 3 and 4 reflect a concomitant change from mudrock- and diamictite-rich lithology to a section dominated by clean, well-washed sandstones with minor conglomerates. Progressive downhole increases in percentage sand and principal mode also reflect these changes. Significant shifts in grain-size parameters and entropy group membership were noted across sequence boundaries and seismic reflectors, as recognised in others studies.

From aesthetic principles to collective sentiments: The logics of everyday judgements of taste

Contemporary research into the sociology of taste has, following Bourdieu (1984), primarily emphasised the role of social position, or more broadly as implicated int he reproduction of social inequality. We argue that although important, such a preoccupation with the social distribution of objectified tastes--for example in music, literature, and art--has been at the expense of investigating the everyday perceptual schemes and resources used by actors to accomplish a judgement of taste. Our argument is traced using a range of classical and contemporary literature which deals with the personal/collective tension in taste, aesthetics and fashion. We use data from a recent national survey to investigate how a sample of ordinary fashion. We use data from a recent national survey to investigate how a sample of ordinary actors understand the categories of 'good' and 'bad' taste. The analysis shows a strong collective strand in everyday definitions of taste, often linked to moral codes of interpersonal conduct. Also, taste is largely defined by people as a strategy for managing relations with others, and as a mode of self-discipline which relies on the mastery of a number of general principles that are resources for people to position their own tastes within an imagined social sphere. This paper proposes a schematic model which accounts for the range of discriminatory resources used to make judgements of taste.

Population pharmacokinetics of perhexiline from very sparse, routine monitoring data

Using NONMEM, the population pharmacokinetics of perhexiline were studied in 88 patients (34 F, 54 M) who were being treated for refractory angina. Their mean +/- SD (range) age was 75 +/- 9.9 years (46-92), and the length of perhexiline treatment was 56 +/- 77 weeks (0.3-416). The sampling time after a dose was 14.1 +/- 21.4 hours (0.5-200), and the perhexiline plasma concentrations were 0.39 +/- 0.32 mg/L (0.03-1.56). A one-compartment model with first-order absorption was fitted to the data using the first-order (FO) approximation. The best model contained 2 subpopulations (obtained via the $MIXTURE subroutine) of 77 subjects (subgroup A) and 11 subjects (subgroup B) that had typical values for clearance (CL/F) of 21.8 L/h and 2.06 L/h, respectively. The volumes of distribution (V/F) were 1470 L and 260 L, respectively, which suggested a reduction in presystemic metabolism in subgroup B. The interindividual variability (CV%) was modeled logarithmically and for CL/F ranged from 69.1% (subgroup A) to 86.3% (subgroup B). The interindividual variability in V/F was 111%. The residual variability unexplained by the population model was 28.2%. These results confirm and extend the existing pharmacokinetic data on perhexiline, especially the bimodal distribution of CL/F manifested via an inherited deficiency in hepatic and extrahepatic CYP2D6 activity.

Fitting a mixture model to three-mode three-way data with missing information

When the data consist of certain attributes measured on the same set of items in different situations, they would be described as a three-mode three-way array. A mixture likelihood approach can be implemented to cluster the items (i.e., one of the modes) on the basis of both of the other modes simultaneously (i.e,, the attributes measured in different situations). In this paper, it is shown that this approach can be extended to handle three-mode three-way arrays where some of the data values are missing at random in the sense of Little and Rubin (1987). The methodology is illustrated by clustering the genotypes in a three-way soybean data set where various attributes were measured on genotypes grown in several environments.

Exploratory spatial data analysis techniques for examining urban crime

Regional planners, policy makers and policing agencies all recognize the importance of better understanding the dynamics of crime. Theoretical and application-oriented approaches which provide insights into why and where crimes take place are much sought after. Geographic information systems and spatial analysis techniques, in particular, are proving to be essential or studying criminal activity. However, the capabilities of these quantitative methods continue to evolve. This paper explores the use of geographic information systems and spatial analysis approaches for examining crime occurrence in Brisbane, Australia. The analysis highlights novel capabilities for the analysis of crime in urban regions.

Treatment of lupus nephritis: art or science? [Editorial]

No Abstract

Probabilistic modelling of CO2 corrosion laboratory data using neural networks

The present paper addresses two major concerns that were identified when developing neural network based prediction models and which can limit their wider applicability in the industry. The first problem is that it appears neural network models are not readily available to a corrosion engineer. Therefore the first part of this paper describes a neural network model of CO2 corrosion which was created using a standard commercial software package and simple modelling strategies. It was found that such a model was able to capture practically all of the trends noticed in the experimental data with acceptable accuracy. This exercise has proven that a corrosion engineer could readily develop a neural network model such as the one described below for any problem at hand, given that sufficient experimental data exist. This applies even in the cases when the understanding of the underlying processes is poor. The second problem arises from cases when all the required inputs for a model are not known or can be estimated with a limited degree of accuracy. It seems advantageous to have models that can take as input a range rather than a single value. One such model, based on the so-called Monte Carlo approach, is presented. A number of comparisons are shown which have illustrated how a corrosion engineer might use this approach to rapidly test the sensitivity of a model to the uncertainities associated with the input parameters. (C) 2001 Elsevier Science Ltd. All rights reserved.