Simultaneous analysis of individual and aggregate responses in psychometric data using multilevel modeling.

Psychometric data on risk perceptions are often collected using the method developed by Slovic, Fischhoff, and Lichtenstein, where an array of risk issues are evaluated with respect to a number of risk characteristics, such as how dreadful, catastrophic or involuntary exposure to each risk is. The analysis of these data has often been carried out at an aggregate level, where mean scores for all respondents are compared between risk issues. However, this approach may conceal important variation between individuals, and individual analyses have also been performed for single risk issues. This paper presents a new methodological approach using a technique called multilevel modelling for analysing individual and aggregated responses simultaneously, to produce unconditional and unbiased results at both individual and aggregate levels of the data. Two examples are given using previously published data sets on risk perceptions collected by the authors, and results between the traditional and new approaches compared. The discussion focuses on the implications of and possibilities provided by the new methodology.

Multi-level modelling of geographically aggregated health data: a case study on malignant melanoma mortality and UV exposure in the European Community.

A multi-level modelling approach is used to examine the variance in mortality rates from malignant melanoma at different geographical scales within nine European nations with reference to exposure to ultraviolet light (UVB). For males and females, the greatest variations in the relationship between UVB exposure and mortality are seen between nations, rather than regions and sub-regions within nations. This suggests that factors and characteristics acting at a national scale, such as genetic and behavioural differences, are of importance. Multi-level modelling is used to show how a previous suggestion of a quadratic association between UVB exposure and malignant melanoma across Europe is unlikely to be true. The general usefulness of multi-level modelling in the analysis of disease data which is structured in a hierarchy is discussed, with particular reference to geographical analyses of small area data.

Mortality from non-Hodgkin lymphoma and UV exposure in the European Community.

There has been a large, unexplained rise in the incidence of non-Hodgkin's lymphoma (NHL) in many countries. It has been hypothesised that increased exposure to solar ultraviolet (UV) radiation may have been a factor in this increase. The hypothesis that exposure to ultraviolet radiation is a factor in NHL can be tested by examining whether geographical variations in UV and in the incidence of the disease are positively correlated. Previous studies have given mixed results but some of these have failed to take into account confounding by socio-economic factors and the multilevel structure of data derived from several different countries. It was therefore decided to carry out a study using data on NHL mortality for the period 1971-80 for level II administrative units in 9 countries in the European Community. Estimated levels of solar UV and per capita GDP were also derived. Poisson regression models of the relationship between NHL mortality, UV and per capita GDP, taking into account the multilevel structure of the data, were fitted using the MLn package. Simple models that did not adjust for the effects of variations in per capita GDP or account adequately for the structure of the data produced apparent negative or quadratic associations between NHL and UV. However, further models show that there is a highly significant positive association between NHL and per capita GDP. Once this is included in the fixed and random parts of the multilevel model the association between NHL and UV becomes positive although non-significant (p = 0.081) at the conventional 0.05 level. These results underline the need to control for socio-economic factors and to take into account the multilevel structure of the data. Studies using international data that do not do this run the risk of producing misleading results.

The future of community nursing in the United Kingdom: district nursing, health visiting and school nursing.

This paper examines the future of community nursing, within the wider framework of a rapidly changing National Health Service. The research was commissioned by the Community Performance Review Network, as part of a series of comparative studies between community healthcare NHS trusts. Three questionnaires were sent to 24 trusts, covering three of the community nursing services; district nursing, health visiting and school nursing. Of the 24 trusts involved in the network, 22 responded to some or all of the questionnaires. A wide range of management structures and working practices were found between trusts, but several common themes and issues of concern emerged. For district nurses, these included the shift from secondary to primary care and the changing demands of the client population served, with increasing numbers of elderly and chronically disabled patients. This led to anxiety over the communication between different providers of care, such as community, acute and social services, and the skills mix and training requirements for nurses. Health visitors and school nurses were concerned about being marginalized in the move towards integrated primary health care teams. As the emphasis changes from treating illness to health promotion, concern was expressed about how performance could be measured on the less quantifiable outcomes of preventative care, and hence how jobs could be justified to purchasers of health care. A central theme was the potential role of the nurse practitioner in provision of primary care, and this formed a focus for other anxieties concerning both the current situation and future of community nursing services.

Carcinogens in food: priorities for regulatory action.

A pragmatic possible approach to the prioritization of chemical carcinogens occurring as food contaminants is described, based on the carcinogenic risk to the population. This should be of value in ensuring that resources for assessment and management of carcinogens in food are directed to the most important areas with regard to carcinogenic risk to the population. Key components of this approach are an assessment of the carcinogenic hazard to humans combined with estimations of intakes per person and of the proportion of the population exposed. These are used to derive an index referred to as the Population Carcinogenic Index. Concerning the hazard assessment expert judgement is used to place the chemical in one of five categories. The highest category is for chemical carcinogens that are believed to act by a genotoxic mechanism. It is recognised that such compounds may vary enormously with respect to their potency and various approaches to ranking carcinogens on the basis of potency are reviewed. The approach adopted is to subdivide the genotoxic carcinogens category into high, medium and low potency based on the TD50 value. Methods of estimating intakes and exposed populations are considered and an approach which groups these into broad categories is developed. The hazard and exposure assessments are then combined to derive the Population Carcinogenicity Index.