Gender,marital status,and body weight in older U.S. adults

Marital terminations are life transitions that may lead to changes in diet, activity, and body weight. This investigation examined how marital status was associated with relative body weight, underweight, overweight, and obesity among men and women in the United States using cross-sectional nationally representative data from the 1992 HRS cohort age 51–61 and the 1993 AHEAD cohort age 70 and older. Results in the HRS cohort revealed that even when adjusting for demographic and behavioral variables, widowed women were significantly more likely to be obese than married women, while men who were never married, divorced, or separated were more likely to be underweight. Results in the AHEAD cohort showed few significant associations between marital status and weight for either men or women when demographics were controlled. Clear gender variations appeared to exist in how marriage is related to body weight among unmarried older adults, with widows in their 50s being obese and divorced/separated/never married men being underweight. However, marital status differences in weight were not present among much older adults of either gender. Jeffery Sobal is a asociologist who is an associate professor at the Division of Nutritional Sciences at Cornell University. He has studied food systems, food choice, and is currently examining social aspects of body weight and obesity, particularly marriage and body weight. Barbara S. Rauschenbach is a sociologist who is a research associate in the Division of Nutritional Sciences at Cornell University. She has studied food insecurity and food assistance, and is currently examining marital status and body weight.     

A cross-national look at married women's earnings dependency

Using the Luxembourg Income Study data we examine married women's dependency on their husbands' earnings in nine Western industrialized countries: Australia, Belgium, Canada, Finland, Germany, the Netherlands, Norway, Sweden, and the United States. When we examine the level and degree of dependency, and the labor force participation of married women across countries, the nine countries fall into the three clusters delineated in Esping-Andersen's welfare states typology. But when we examine the determinants of the dependency within each country, the clustering disappears. Wives' dependency increases with age, the presence of young children, and the number of children. It is reduced when wives' labor force participation and education are high relative to their husbands' and in families that rely more on unearned sources of income. The similarity of patterns across countries suggests that gender differences in the work-family nexus are deeply entrenched in all countries and continue even in the face of very active social policy to minize their effects. This is a revised version of a paper presented at the annual meeting of the American Sociological Association, August 1995, Washington DC. Her current research focuses on gender inequality and parents' time allocation between work and family. She conducts research on various aspects of family demography, including household and family characteristics, co-resident grandparent families, cohabitation, and child care. With Suzanne Bianchi, she is completing a research monograph on trends in the American family. Her research focuses on gender, work, and family issues.     

Die Auswirkungen von Neid auf individuelle Leistungen: Ergebnisse einer Panelanalyse

Relative income differences are likely to lead to envy within a reference group. Envy in turn influences social behavior and individual performance. While positional concerns are apparent in daily life, empirical evidence is rare in the economic literature. This paper investigates the impact of the relative income position on individuals’ performance or productivity. As ?performance“ is difficult to measure we turn to soccer players whose performance has been well documented. The broad sample covers eight seasons of the German premier soccer league (Bundesliga) between 1995 and 2004, and includes 1040 players, a salary proxy and several performance variables. The results show that player performance is strongly affected by relative income position. A disadvantage in the relative income position reduces productivity. The larger the income differences within a team, the stronger are the effects of positional concern. Team composition also significantly affects behaviour.     

Alternative Methods for Computing the Sensitivity of Complex Surveillance Systems

Stochastic scenario trees are a new and popular method by which surveillance systems can be analyzed to demonstrate freedom from pests and disease. For multiple component systems—such as a combination of a serological survey and systematically collected observations—it can be difficult to represent the complete system in a tree because many branches are required to represent complex conditional relationships. Here we show that many of the branches of some scenario trees have identical outcomes and are therefore redundant. We demonstrate how to prune branches and derive compact representations of scenario trees using matrix algebra and Bayesian belief networks. The Bayesian network representation is particularly useful for calculation and exposition. It therefore provides a firm basis for arguing disease freedom in international forums.     

Pandemic Recovery Analysis Using the Dynamic Inoperability Input-Output Model

Economists have long conceptualized and modeled the inherent interdependent relationships among different sectors of the economy. This concept paved the way for input-output modeling, a methodology that accounts for sector interdependencies governing the magnitude and extent of ripple effects due to changes in the economic structure of a region or nation. Recent extensions to input-output modeling have enhanced the model's capabilities to account for the impact of an economic perturbation; two such examples are the inoperability input-output model^{( 1 , 2 )} and the dynamic inoperability input-output model (DIIM).^{( 3 )} These models introduced sector inoperability, or the inability to satisfy as-planned production levels, into input-output modeling. While these models provide insights for understanding the impacts of inoperability, there are several aspects of the current formulation that do not account for complexities associated with certain disasters, such as a pandemic. This article proposes further enhancements to the DIIM to account for economic productivity losses resulting primarily from workforce disruptions. A pandemic is a unique disaster because the majority of its direct impacts are workforce related. The article develops a modeling framework to account for workforce inoperability and recovery factors. The proposed workforce-explicit enhancements to the DIIM are demonstrated in a case study to simulate a pandemic scenario in the Commonwealth of Virginia.     

ON SELECTING VARIABLES AND ASSESSING THEIR PERFORMANCE IN LINEAR DISCRIMINANT ANALYSIS

Linear discriminant analysis between two populations is considered in this paper. Error rate is reviewed as a criterion for selection of variables, and a stepwise procedure is outlined that selects variables on the basis of empirical estimates of error. Problems with assessment of the selected variables are highlighted. A leave-one-out method is proposed for estimating the true error rate of the selected variables, or alternatively of the selection procedure itself. Monte Carlo simulations, of multivariate binary as well as multivariate normal data, demonstrate the feasibility of the proposed method and indicate its much greater accuracy relative to that of other available methods.     

Evaluating Probabilistic Forecasts with Bayesian Signal Detection Models

We propose the use of signal detection theory (SDT) to evaluate the performance of both probabilistic forecasting systems and individual forecasters. The main advantage of SDT is that it provides a principled way to distinguish the response from system diagnosticity, which is defined as the ability to distinguish events that occur from those that do not. There are two challenges in applying SDT to probabilistic forecasts. First, the SDT model must handle judged probabilities rather than the conventional binary decisions. Second, the model must be able to operate in the presence of sparse data generated within the context of human forecasting systems. Our approach is to specify a model of how individual forecasts are generated from underlying representations and use Bayesian inference to estimate the underlying latent parameters. Given our estimate of the underlying representations, features of the classic SDT model, such as the receiver operating characteristic (ROC) curve and the area under the ROC curve (AUC), follow immediately. We show how our approach allows ROC curves and AUCs to be applied to individuals within a group of forecasters, estimated as a function of time, and extended to measure differences in forecastability across different domains. Among the advantages of this method is that it depends only on the ordinal properties of the probabilistic forecasts. We conclude with a brief discussion of how this approach might facilitate decision making.     

Complying with voluntary codes of conduct: Corporate strategies for the Valdez Principles

The Valdez Principles is the latest of a series of voluntary codes of conduct that have been enunciated by various advocacy groups to guide the behavior of business enterprises. These principles provide guidelines on corporate conduct towards the environment and present a corporation with critical choices. This study suggests alternative strategies that firms may adopt to cope with this new code. Experience with the Sullivan and MacBride Principles is analyzed to serve as the basis to predict corporate response to the Valdez Principles.     

Final report of the Color Additive Scientific Review Panel

The Color Additives Scientific Review Panel considered whether there was information sufficient to perform a carcinogenic risk assessment on the colors D&C Red No. 19 (R-19), D&C Red No. 37 (R-37), D&C Orange No. 17 (O-17), D&C Red No. 9 (R-9), D&C Red No. 8 (R-8) and FD&C Red No. 3 (R-3) and to evaluate the assessments sent to FDA as part of the petitions for use of the colors for drug and external uses by the Cosmetic, Toiletry and Fragrance Association (CTFA). There is a lack of human data concerning the colors for making a human health assessment, so the assessments are based upon the extrapolation of animal data. The risk assessments are determined for exposure to single chemicals. Excluded from consideration are possible effects from exposure to multiple chemicals, such as co-carcinogenesis, promotion, synergism, antagonism, etc. In the light of recent efforts in establishing a consensus in risk assessment, the Panel has determined that the CTFA assessments for R-10, O-17, and R-9 are consistent with present acceptable usages, although it questions some of the assumptions used in the assessments. The Panel identified a number of general assumptions made, and discusses their validity, their impact on total uncertainty, and the potential options to address the gaps in understanding that necessitate the assumption. The Panel also derived revised risk estimates using more "reasonable" assumptions than "worst-case" situations, for 90th percentile and average exposure. For those assumptions that are easily quantifiable, the Panel's estimates are less than an order of magnitude lower than the CTFA risk estimates, indicating that the underestimates and overestimates of the CTFA risk estimates tend to balance each other. The impact of most of the assumptions is not quantifiable. The assessment for R-3 is complicated by the fact that there is no good skin penetrance study for this color. It was assumed that the penetrance is similar to that of another water-soluble xanthene color, R-19. It is expected that the absorption of the color is not likely to exceed that of the smaller molecule, R-19. Therefore, the risk estimates are similar to the CTFA estimates, but with different reasoning. The estimates for R-8 and R-37 are different from the others in that there is a lack of any exposure or toxicological information on these colors.(ABSTRACT TRUNCATED AT 400 WORDS)     

Scenarios in Europe—Who uses them and why?

The authors of this article describe a study of European companies the aim of which was to review the extent of multiple scenario analysis in company planning. They describe the differences in planning between users and non-users of the system, and analyse the benefits and drawbacks of using the system.