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Methodology for making cross-national comparisons is an area of increasing interest in social and public health related research. When studying socio-economic differences in health outcomes cross-nationally, there are several methodological issues of concern, especially when data is derived from self-reported questionnaires. Health Behaviour in School-aged Children (Currie et al. ) is a WHO cross-national study using school samples. HBSC provides comparable data, and thereby a unique opportunity to study associations between social indicators and health outcomes within an international perspective. In 2001/02 data was collected from a total of 162,323 children in 32 countries (Austria, Belgium, Canada, Croatia, Czech Republic, Denmark, Estonia, Finland, France, Germany, Greece, Greenland, Hungary, Ireland, Israel, Italy, Latvia, Lithuania, Macedonia, Malta, Netherlands, Norway, Poland, Portugal, Russia, Slovenia, Spain, Sweden, Switzerland, Ukraine, United Kingdom, USA.). Studies of social inequalities requires that a comparable measure of socio-economic position (SEP) is in use. HBSC has developed a proxy for social position measuring material wealth, the Family Affluence Scale (FAS). This paper studies FAS and whether it is comparable across population subgroups defined by country, age and gender. Initial analysis revealed that an item measuring perceived family wealth was a valid FAS item. Including this item in the FAS score will improve the reliability of FAS. Graphical log-linear Rasch models (GLLRM) showed that FAS contain differential item functioning (DIF) with respect to country, age, and gender as well as local dependency (LD) between items. During the analysis, test equating techniques where used to adjust for the test bias generated by DIF. We recommend that the equated scores are used whenever FAS is included as a variable. This study suggests that HBSC-FAS should contain five items (additional item: perceived family wealth) when analysing data from HBSC 2001/02, and furthermore that each country should adjust for the DIF or make use of the converted FAS scores provided. If using FAS as a proxy for social position at an international level, it is not advised to compare the absolute levels of FAS, but weigh the scale by ridit transformation. [ABSTRACT FROM AUTHOR]

In this article, we report statistical properties of two classes of generalized Gini coefficients (G1 and G2). The theoretical results were assessed via Monte Carlo simulations. Further, we used G1 and G2 on life expectancy to measure health inequalities among the provinces of China and the states of the United States. For China, the results indicated that there was statistically significant health inequality by both G1 and G2. However, for the US, the results showed that there was significant health inequality by G1 but no statistical significance was found in health inequality by G2. Overall, from our study, China has higher health inequality than the United States. [ABSTRACT FROM AUTHOR]

This paper extends and further validates the quality-of-life/ community-healthcare model and measures developed by Rahtz and Sirgy (2000). The quality of life (QOL) model is based on the theoretical notion that community residents' satisfaction with healthcare services available within their community affects community quality of life and life satisfaction. This study extends the model and, in keeping with past research, posits that the bottom-up spillover from community QOL to life satisfaction is greater for those individuals with low personal health satisfaction, lower income, and old age. Data were collected from 1094 community residents in the East-Coast area of the United States. The results provide good support of the new model. Managerial implications and applications for the new model are discussed. [ABSTRACT FROM AUTHOR]

The goals of this study were to validate a number of available collective social capital measures at the US state and county levels, and to examine the relative extent to which these social capital measures are associated with population health outcomes. Measures of social capital at the US state level included aggregate indices based on the Annenberg National Health Communication Survey and the Behavioral Risk Factor Surveillance System (BRFSS), Petris Social Capital Index (PSCI), Putnam's index, and Kim et al.'s scales. County-level measures consisted of PSCI, Rupasingha et al.'s social capital index, and a BRFSS-derived measure. These measures, except for the PSCI, showed evidence of acceptable validity. Moreover, we observed differences across the social capital measures in their associations with population health outcomes. The implications of the findings for future research in this area were discussed. [ABSTRACT FROM AUTHOR]