Craig Duncan’s research while affiliated with Office for National Statistics and other places

In studying the links between income and mortality we need to recognise two key hypotheses. In the absolute income hypothesis, the higher an individual income, the lower the risk of mortality. In the relative income hypothesis, the individual's health is additionally affected by the distribution of income within society so that living in a place with grossly unequal income distribution is anticipated to lead to a worse health experience (see Chapter 5 of this volume). This chapter attempts to review the evidence for the importance of both these hypotheses using data from the UK- representative Health and Lifestyle Survey employing both individual and ecological measures of income. ,,,,,,, . In conclusion, there appears to be evidence that mortality outcomes cannot be simply reduced to individual characteristics. There is an ecology of mortality that is related to the mean income of the local area. Mortality is related to poverty at both the household and area level. It seems to us that such results for mortality at least can support a materialist explanation without any specific need to develop explanations based on psychosocial processes, social cohesiveness or social capital.

This chapter begins by outlining the conceptual motivation behind multilevel analyses and by identifying a core set of research questions that this approach addresses. It then introduces the idea of multilevel structures and discusses simple and complex multilevel models. It emphasizes that the key strength of multilevel models lies in modeling heterogeneity at different levels and shows how multilevel models can be extended to additional contextual levels (e.g., neighborhoods nested within regions). The estimation procedures underlying such models are discussed, showing how a multilevel framework can provide a general, unified approach to data analysis and how this can be achieved by extensions to the basic hierarchical structure of individuals nested within contexts. The chapter concludes with a discussion of issues that researchers should be aware of when applying multilevel methods.

Following the move to a ‘post–medical’ geography, a large amount of research has come to focus on public health issues. This paper explores these current geographies of public health and argues for the development of a more critical perspective. In particular, it draws on commentary that has emerged out of debates that have taken place within a body of literature usually identified as the critical ‘new’ public health. The paper goes on to argue that such scholarship offers crucial insights for the production of a critical geography of public health.

This paper provides a succinct overview of some recent trends in geography of health in Britain since 1998. We consider how the research we have reviewed illuminates the relationships between geographies of health and three fundamental processes which are widely recognized as being important for contemporary human geography as a whole: globalization, urbanization and polarization. We also consider the contribution of health geography to agendas in cultural geography agenda which we refer to here as 'geographies of imagination'. These perspectives all relate to dynamic and diverse processes operating in Britain and throughout the world. We explore how health geography is responding to change, and what the agenda for future research will be. By considering these themes, we also seek to show how the geography of health is contributing to a wider discourse, shared to some extent in human geography as a whole, and we discuss the themes which are likely to feature in the future health geography research agenda.

Since most census data are released for spatial aggregates, the microscale of people and the macroscale of places are confounded in analyses. Although regrettable, this situation is usually tolerated owing to the other obvious attractions of census data. In this paper, we consider how multilevel statistical procedures offer a solution to this problem. Importantly, we show how they allow places to be considered in terms of several different scales simultaneously. As we demonstrate, this provides important connections with recent moves towards performance review in several areas of public policy. An analysis of data on illiteracy from the 1991 Indian Census provides an illustration of multilevel approach and its usefulness.

In the opening to this paper we concern ourselves with the concept of health as it is currently understood in the now reformulated 'geography of health'. We focus on countering the assumption that the desire for health is the main drive behind individual patterns of consumption. To this end, we turn to a more culturally informed analysis which identifies the importance of understanding the complex relations between the body, identity, consumption and risk. To illustrate our ideas and arguments, we draw on current anti-smoking debates, particularly those relating to passive smoking, and what we see as evidence of alternatives to such health-related or 'healthist' rhetoric: the rise of cigar smoking and cigar bars in London, England.

Using data from the 1994 Health Survey for England, logistic multivariate multilevel modelling techniques are used to investigate the simultaneous effect of individual demographic characteristics and socio-structural factors on self-reported problem drinking as revealed by CAGE scores and 'unsafe' levels of alcohol consumption. Whilst the influence of key socio-structural variables is broadly similar for both unsafe alcohol consumption and high CAGE scores, there are notable exceptions when results are examined by tenure group: those in the rented sector are more likely to be problem drinkers as revealed by CAGE, but less likely to consume 'unsafe' amounts of alcohol. Both dimensions of drinking behaviour are influenced by the consumption patterns of others in the household, with both likelihoods increasing as the average consumption of others in the household rises. After taking into account individual compositional variables, the research indicates that there is very little evidence for geographical variation remaining in these two dimensions of drinking behaviour. It is found that the proportion of the population whose drinking behaviour may be classed as (potentially) problematic via the CAGE responses is substantially less than the proportion consuming above recommended 'safe' levels. The research concludes, however, that the two measures are broadly similar in their relationship to social and structural variables. Tenure provides an exception to this conclusion and indicates a continuing need to take account of housing circumstances in developing an understanding of drinking behaviour.

Within the last few years, geographers and researchers in other cognate disciplines with geographic concerns have begun to use multilevel models. While there are several useful existing introductory accounts of these models in the geographical literature, this paper seeks to extend them in three main ways to clarify and emphasize further the substantial opportunities they afford. First, it focuses on how multilevel models are centrally concerned with modeling population heterogeneity as a function of predictor variables. Second, it considers and illustrates a number of specific interpretive issues that can arise when conducting multilevel analyses of place effects. Lastly, it traces some more general, conceptual issues surrounding the use of multilevel models in geographical research. The arguments made are illustrated through an analysis of variations in drinking behavior using data from a typically complex, large-scale survey; particular attention is given to the inclusion of categorical predictors.

This paper examines geographic variations in illiteracy in India, both at the district and state levels, based on 1991 Census data. Multilevel regression modelling techniques are applied in order to establish whether variations relate to the type of people in particular places (compositional effects) or to the characteristics of the places themselves (contextual effects). Results show significant differences between places, which cannot be accounted for solely by compositional effects. These differences are complex and contextual effects are found to be different for different types of people. The analysis provides substantial empirical evidence that policy interventions in the context of illiteracy need to take account of spatial complexity.