Estimation and interpretation of models of absolute risk from epidemiologic data,including family-based studies

Absolute risk is the chance that a person with given risk factors and free of the disease of interest at age a will be diagnosed with that disease in the interval (a, a + τ]. Absolute risk is sometimes called cumulative incidence. Absolute risk is a “crude” risk because it is reduced by the chance that the person will die of competing causes of death before developing the disease of interest. Cohort studies admit flexibility in modeling absolute risk, either by allowing covariates to affect the cause-specific relative hazards or to affect the absolute risk itself. An advantage of cause-specific relative risk models is that various data sources can be used to fit the required components. For example, case–control data can be used to estimate relative risk and attributable risk, and these can be combined with registry data on age-specific composite hazard rates for the disease of interest and with national data on competing hazards of mortality to estimate absolute risk. Family-based designs, such as the kin-cohort design and collections of pedigrees with multiple affected individuals can be used to estimate the genotype-specific hazard of disease. Such analyses must be adjusted for ascertainment, and failure to take into account residual familial risk, such as might be induced by unmeasured genetic variants or by unmeasured behavioral or environmental exposures that are correlated within families, can lead to overestimates of mutation-specific absolute risk in the general population.     

Combining Occurrence and Toxicity Information to Identify Priorities for Drinking-Water Mixture Research

Characterizing all possible chemical mixtures in drinking water is a potentially overwhelming project, and the task of assessing each mixture's net toxicity even more daunting. We propose that analyzing occurrence information on mixtures in drinking water may help to narrow the priorities and inform the approaches taken by researchers in mixture toxicology. To illustrate the utility of environmental data for refining the mixtures problem, we use a recent compilation of national ground-water-quality data to examine proposed U.S. Environmental Protection Agency (EPA) and Agency for Toxic Substances and Disease Registry (ATSDR) models of noncancer mixture toxicity. We use data on the occurrence of binary and ternary mixtures of arsenic, cadmium, and manganese to parameterize an additive model and compute hazard index scores for each drinking-water source in the data set. We also use partially parameterized interaction models to perform a bounding analysis estimating the interaction potential of several binary and ternary mixtures for which the toxicological literature is limited. From these results, we estimate a relative value of additional toxicological information for each mixture. For example, we find that according to the U.S. EPA's interaction model, the levels of arsenic and cadmium found in U.S. drinking water are unlikely to have synergistic cardiovascular effects, but the same mixture's potential for synergistic neurological effects merits further study. Similar analysis could in future be used to prioritize toxicological studies based on their potential to reduce scientific and regulatory uncertainty. Environmental data may also provide a means to explore the implications of alternative risk models for the toxicity and interaction of complex mixtures.     

CALIBRATING MEASURES OF FAMILY ACTIVITIES BETWEEN LARGE- AND SMALL-SCALE DATA SETS

Two studies of working families are combined to demonstrate a strategy for producing reliable estimates from the combination of self-reported (large N) and observational (small N) data. Both studies examine where and how dual-career families spend time at home. The 500 Family Study is sociological and uses self-reported time diary data from a national sample; the CELF study is anthropological and uses observational scan sampling data from a regional sample of 32 families. The data are combined as if they constitute one sample, and an analytic solution for establishing the reliability of the resulting composite estimates of time use is provided. Merging the data sets provides validation for each study, neither of which is without potential methodological weaknesses. The advantages of combining data from the independent data collection methods are discussed, and selected substantive findings on families' activities are highlighted, illustrating similarities and differences between findings in the independent and combined data sets. Results show that working families spend significant time in a small spectrum of home spaces, particularly kitchens and living rooms, with leisure activities prevailing, but mothers, fathers, and children differ in where and how they spend their time. Overall, a template for merging data from different disciplines and methods is provided.     

The Attributes of Effective NGOs and the Leadership Values Associated with a Reputation for Organizational Effectiveness

Building on prior research characterizing organizational effectiveness as a social construction, this article identifies the perceived attributes of effective transnational nongovernmental organizations (NGOs) and the leadership values associated with higher reputations for organizational effectiveness. Results are based on an in‐depth, mixed‐method interview study of 152 NGO leaders located in the United States and representing all major sectors of organizational activity. Among the twenty‐nine attributes that leaders identified in peer organizations that they regarded as particularly effective, leaders stressed instantiation of sound principles or strategy, a grassroots approach, large organizational size and resources, being collaborative, singleness of focus, campaigning abilities, funding and fundraising prowess, global scope, and quality people. Furthermore, statistical analysis reveals that NGOs with leaders who value similarities with peer organizations, grassroots approaches, diversity of strategies, dedication, professionalism, and distributed organizational structures have significantly higher reputations for effectiveness.     

Labour Underutilisation and Gender: Unemployment Versus Hidden-Unemployment

As labour markets have become more complex there has been increasing interest among researchers in understanding the ways that social and labour market processes and contexts impact on various labour market states. One important area has been in understanding the differences between unemployment and hidden unemployment. This paper considers the ways in which these two labour market states differ for a sample of male and female respondents to the Household Income and Labour Dynamics Australia (HILDA) survey. It presents data related to the reasons why respondents in these two labour force states consider they are jobless and analyses the characteristics of male and female respondents in the two labour market states to consider differences in outcomes. The findings suggest that there are differences in the two states of labour market outcomes and that these are further complicated when one considers processes for males and females.     

Gambling in Western and Eastern Europe: The Example of Hungary

The history of gambling in post-socialist countries is noticeably different from that of other countries in Europe. The goal of this study was therefore twofold: Firstly, to systematically review all European epidemiological studies related to excessive gambling in the general adult population, and secondly, to provide an overview of the state of gambling in Hungary based on the first ever nationwide representative survey, setting the results against the backdrop of the earlier European studies. A systematic review was carried out of European gambling studies which focus on a representative adult general population. Hungarian data was obtained from the National Survey on Addiction Problems in Hungary general adult population survey (N = 2,710). Pathological gambling was measured by the South Oaks Gambling Screen. Lifetime prevalence of excessive gambling (problem and pathological gambling) in the general adult population of European countries varies between 1.1% (Italy and Spain) and 6.5% (Estonia). In Hungary, the prevalence of problem gambling is 1.9%, with pathological gambling at 1.4%. The socio-demographic characteristics of the results are similar to those of other European countries. Using epidemiological data from the general adult populations of two post-socialist nations, it was possible to compare the results with data from 12 other European countries. Based on the data available, the extremely rapid liberation of the gambling market in the post-socialist countries has led to a similarly swift escalation in associated gambling problems.