The right-to-die movement: extrapolating from the National Hemlock Society U.S.A. membership survey

A national membership survey of Hemlock Society USA was conducted by Fox and Kamakahi (1995). Respondents (N=6398) were asked a variety of questions, but in this paper we perform a longitudinal analysis of the characteristics of Hemlock Society USA members. Hemlock Society USA members are divided into three 5-year cohorts: Early Joiners (11 or more years of membership), Middle Joiners (6 to 10 years membership), and Late Joiners (5 or fewer years of membership). Differences between cohorts are examined and extrapolations made regarding Hemlock Society USA and the Right-to-Die Movement. A series of one-way ANOVAs were used with Scheme post-hoc comparisons as heuristic tools for assessing between-cohort differences. Late Joiners are different from earlier members, but are more like other Hemlock Society USA members than the adult U.S. population at large. Hemlock Society USA members are essentially societal "elites" (based on socio-demographic variables) who work in social environments that are decidedly split on the issue of voluntary suicide and euthanasia.     

LESSONS FOR RESEARCHERS AND FUNDING AGENCIES FROM HURRICANE KATRINA: A RESEARCH NOTE FROM MISSISSIPPI

We surveyed National Science Foundation (NSF)-funded research in Mississippi to determine the economic extent of research damage and delays due to Hurricane Katrina. While several facilities were physically damaged, we found that the largest effects were time delays and missed opportunities. While psychological factors were not part of the original economic impact study, it became clear that they played an important role. Specifically, the Principal Investigator's (PI's) attitude of “just another delay” was one cultural barrier to fully accounting for the cost of these research delays. We concluded that Principal Investigators, with the assistance of funding agencies, should be better trained to measure time and opportunity costs associated with their research, so future disaster recovery efforts can more fully address those needs.     

Research note: imputing large group averages for missing data,using rural-urban continuum codes for density driven industry sectors

Understanding the effects and consequences of missing data imputation is vital to the ability to obtain meaningful and reliable statistics and coefficients in the examination of any quantitatively-based phenomena. Over time a series of sophisticated methods have been developed to handle the issue of missing data imputation however, these sophisticated methods may not always be appropriate or attainable. In these specific cases more traditional approaches to missing data imputation must be employed and driven by the research project, theoretical framework, and the data. In this research note we offer a brief account of one such instance, implementing a large-group mean imputation approach to handling missing data. The analysis is drawn from a much larger project and shows the effect of proper group selection in terms of mean imputation using a cross-validation approach based on the imputed data’s relation to known values. Ultimately, the results show that the use of Rural-Urban Continuum codes are superior to currently used group-means in the U.S., thus introducing a new, and more efficient, approach to the handling of missing data using group-mean imputation.     

Race,Class, and Support for the Welfare State*

Two competing approaches to the study of African Americans—the race and class perspectives—have dominated attempts to explain their views on contemporary issues. To examine the race versus class debate, this study uses African Americans' views on government spending for five social welfare concerns: (1) improving and protecting the nation's health, (2) solving the problems of big cities, (3) halting rising crime rates, (4) dealing with drug addiction, and (5) improving the nation's education system. Data from the 1972–1990 General Social Surveys are used to compare middle-class blacks with both working-class blacks and whites and middle-class whites in terms of their support for government spending for those five social welfare issues. Examining group means, we found no significant difference between the two black classes but a significant difference between the black middle class and the white middle class on support for government spending in all areas except halting the rising crime rates (where there were no significant differences among the four groups). Similarly, using logistic regression analysis we found that race continued to have a significant effect on support for spending even after controlling for class, year, age, gender, education, income, and occupational prestige. In respect to social welfare spending, the results indicate support for the race, as opposed to the class, perspective; that is, race is better than class for predicting African American attitudes on government spending.     

Multiple Meanings of Minority Concentration: Incorporating Contextual Explanations into the Analysis of Individual-Level U.S. Black Mortality Outcomes

Prior research on mortality for U.S. blacks focuses on the detrimental effects of minority concentration and residential segregation in metropolitan areas on health outcomes. To date, few studies have examined this relationship outside of large U.S. central cities. In this paper, we extend current research on the minority concentration and mortality relationship to explain the rural advantage in mortality for nonmetropolitan blacks. Using data from the 1986–1994 linked National Health Interview Survey/National Death Index, we examine the rural-urban gap in mortality for U.S. blacks. Our findings indicate that blacks in nonmetropolitan areas experience a lower risk of mortality than metropolitan central city blacks after indicators of socio-economic and health status are controlled. Our findings also point to the importance of accounting for contextual factors. Net of individual level controls, minority concentration exerts differential effects across metropolitan and nonmetropolitan areas, such that nonmetropolitan black residents experience a lower risk of mortality in high minority concentration areas than blacks in metropolitan central city areas. This finding suggests a reconceptualization of the meaning for minority concentration with respect to studies of health outcomes in nonmetropolitan communities.     

Reconsidering the Rural–Urban Continuum in Rural Health Research: A Test of Stable Relationships Using Mortality as a Health Measure

Health researchers commonly use existing rural–urban continua based on population size and adjacency to metro areas to categorize counties. When these continua are collapsed into simple rural-versus-urban aggregations, significant differences within the categories are masked. We show that when the entire range of the 10-category Rural–Urban Continuum Codes (RUCC) is used, the direction of the coefficients may differ and the fit of the model varies substantially across contiguous categories. However, collapsing contiguous categories masks variations within the continuum. To the extent that health policy decisions are made based on such aggregations, inappropriate policy choices may result (e.g., low payments to counties with relatively high needs). Given Congressional calls to address rural health, and the new Office of Management and Budget (OMB) statistical area classification system, debate over appropriate categorizations schemes is timely. We regress age-adjusted all-causes of death on various socioeconomic factors to assess the appropriate use of variants of the rural–urban continuum for health research. Our findings support two main conclusions. First, researchers collapsing urban–rural categorization schemes may be masking important categorical differences, inadvertently influencing policymaking predicated on their work. Second, finer classification of settlements yields uneven results. That is, coefficients shift signs across the continuum, indicating that collapsed models may be inappropriate. Results derived using collapsed variants of the RUCC may be too unstable to use as health research and funding categorization schemes. We suggest that a health status or outcomes categorization scheme is likely to be a more appropriate metric for rural health research. Reavis was at the SSRC, MSU while drafting this article.     

Socioeconomic Status and Health Well-Being during Later Life: Potential Mediating Factors

This study explores the socioeconomic status (SES)-perceived health association, with special attention on living arrangements. It improves upon existing explanations of causal mechanisms underlying the impact of SES on health among the elderly. Using Health and Retirement Study to run ordered logistic regression, it addresses the importance of living arrangements for self-reported health. Income and education are both important predictors of self-reported health and that after controlling them, living arrangements also affect self-reported health. Future research should highlight nuanced measures of living arrangements and should explore longitudinal analyses to determine the long-term effects of these factors on self-reported health.     

Does regional variation affect ecological mortality research? An examination of mortality, income inequality and health infrastructure in the Mississippi Delta

Mortality research has often focused on individual-level, socioeconomic, and demographic factors indicating health outcomes. Consistent with a recent trend in the public health field, this research examines mortality at the aggregate, contextual level. Based on Wilkinson’s relative income hypothesis, specifically being manifest through an underinvestment in social goods including health infrastructure, the focus of this study is a regional examination in the effects of income inequality on mortality at the county level. Health infrastructure is included as a mediating variable in the relationship between income inequality and mortality, relating back to Wilkinson’s work. Unlike previous research, regional differences in this relationship are examined to identify variation at the county level in health outcomes. The Mississippi Delta is an adequate test bed to examine the relationship between these variables based on its socioeconomic, demographic, and high inequality characteristics. It is hypothesized that Delta-designated counties within the three-state Delta region distinguish a significant positive relationship between income inequality and mortality, that this relationship is stronger than in non-Delta classified counties, and that health infrastructure significantly mediates the relationship between income inequality and mortality.