Research aim and objectives

The strands of literature reviewed together w ith the existing research lim itations identified in the problem definition have led to the form ation of the following overarching aim for this thesis:

To develop and explore an alternative framework for m easuring and dissem inating health outcome indicators of inequality, to be used in social marketing and public health interventions.

This thesis will present a m ore straightforw ard yet effective alternative to exploring the m easurem ent of inequalities in health outcom es, by using geodem ographic classifications to develop standardised neighbourhood risk indices. Exploration of these inequality gradients through social and

geographical space will provide a new and detailed insight and provide greater understanding of local neighbourhoods for health practitioners and lay com m unity members.

The developm ent of an alternative fram ew ork for m odelling inequalities according to the social similarity of neighbourhoods is justified for the

following reasons. Alternative m easures based on sim ilarity m ove aw ay from the traditional 'container' approach of m easurem ent by adm inistrative units and m oves tow ards a m odern social m easurem ent basis for analysis; "social m easurem ents translate observed characteristics of individuals, events, relationships, organizations, societies, etc into symbolic classifications that enable reasoning of a verbal or logical or m athem atical nature" (Heise, 2001).

Such an approach should provide a useful and systematic m ethod to the complexity of social differentiation.

G eodem ographics provide m easures that incorporate com positional and contextual influences on health need, which on completion of the thesis will realise:

a) An enriched picture of local neighbourhood health need beyond standard deprivation m easures;

b) A fram ew ork for identifying neighbourhoods at risk;

c) A m eans of highlighting neighbourhood variation in likely health outcomes;

d) An alternative tool for understanding service equity (services reaching those w ith the greatest need);

e) Proxy indicators of social capital;

f) An intelligence led solution for social m arketing campaigns;

g) A m eans of describing the health trajectories of small localities to explore how lifestyle m ay be represented using geodem ographic indicators.

As yet, little use has been m ade of geodem ographic indicators to differentiate population conditions of health outcomes, unhealthy lifestyles, behaviours th at lead to poor health. Geodem ographic classifications study population types and their behaviour as they vary by geographical area, typically clustering small areas by postcodes, combining variables from the census of population and other socio-economic data such as housing, financial and lifestyle inform ation to classify neighbourhoods into different types.

Residents are then assigned particular characteristics according to the neighbourhood Type w ithin w hich they live.

The m easurem ent of health needs and their associated outcom es form s a fundam ental com ponent of evidence-based policy, strategy and delivery of health care services at local scales, each of which aims to reduce overall inequalities. Exploring the use of a geodem ographic based fram ew ork

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alongside national health datasets and surveys of population health, should facilitate the differentiation betw een local variations in health behaviours across neighbourhoods, enabling the developm ent of expected m easures/risk indices of health needs for local populations. This realises a requirem ent highlighted from the literature review, which should im prove the specificity of social m arketing cam paigns in order to maximise efficiency.

Variability in health outcom es are often ascribed to tw o m ain causes.

Com positional variables refer to the individual or the household e.g. age, gender or m arital status. Contextual variables describe differences arising from a group, w hich cannot be reduced to an individual, for exam ple absence of facilities in a neighbourhood; they can be associated to place effects of health inequalities. The fram ew ork and m easures developed in the course of this thesis will explore the developm ent of readily intelligible statistics that are com parable across neighbourhoods and to a national baseline th at uses contextual neighbourhood variables to develop health need profiles for predicting some compositional variables.

To harness effectively the pow er of social capital through social m arketing the new m easures need to be accessible both to a range of public health

professionals and lay communities. There is a need to ensure th at com m unity profile inform ation for both com m unities and public health departm ents is accessible, informative, safe (anonymous) and easy to use (Rhind, 1992).

Currently, limited inform ation is available for com m unities to use and

traditional indicators of inequalities and deprivation are firm ly em bedded in public health departm ents. A num ber of different approaches will be

explored and evaluated. They will determ ine the m ost effective m ethods of communication, for im parting new tools and techniques in organisations, to im prove the interfacing of research projects w ith routine w ork practices.

The theme of this research is to extend the health inequalities research and its associated data fram ework to explore variability in the spatial and social dom ain encom passing notions of social m easurem ent and the identification of social facts related to health. This will be carried out by exploring the feasibility of a geodem ographic fram ework for analysing health inequalities using the two tier m ethod illustrated in Figure 11. The first tier will explore how a geodem ographic fram ework can be extended to a variety of health datasets commonly used in health analysis. The second tier appraises this fram ework and explores appropriate m ethods of dissem ination and sharing of best practice, through the evaluation of appropriate m ethods of

communication to investigate the interface betw een research and know ledge transfer. This will enable the assessment of the effectiveness of turning research know ledge into professional and comm unity knowledge.

Social Capital

Local Strategic Partnerships/

Health Professionals

Social Marketing Strategy

Local Communities

Communication and dissemination tools

Tier 2

Variability measures (risk indices) of health outcomes /inequalities

Geodemographic framework for health and social marketing (local spatial data infrastructure)

K:y:

Figure 11: Research fram ew ork

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In the first phase of the research (tier one is denoted by the yellow box in Figure 11) the organising fram ew ork for geodem ographics in public health (Figure 13) will be adopted. Using an inductive approach, a geodem ographic fram ew ork, through the developm ent of a local spatial data infrastructure will be used to: (a) create new predictions of health risk and (b) explore and review these new health risk indicators across different neighbourhoods. On com pletion of Tier one of the research fram ework, new insightful health facts can be used to develop inform ation about distributions of diseases of com fort am ong the local population, combining both professional health know ledge and research know ledge.

Tier one will be com pleted through the developm ent of a series of case studies w hich slow ly builds on the research know ledge in the field of

geodem ographics and public health practice. In this context the case studies p resent an inductive m ethod for review ing and solving practical social m arketing dilem m as. This approach is preferable to deductive analysis because th at w ould require a predefined set of patterns, b u t since the variations are unkn o w n s and a portfolio of new indicators are being produced for this research, a deductive approach is n o t appropriate.

The spirit w ith in w hich this thesis w as conceived w as one of know ledge transfer. The research w as completed as p a rt of an official K now ledge

Transfer P artnership (KTP) betw een U niversity College L ondon and C am den PCT. For this reason, in the quest of know ledge transfer, tier tw o (tier tw o is denoted by the orange box in Figure 11) of the research fram ew ork em bodies the research transference of acquired research know ledge corresponding to social m arketing, public health and geodem ographics into professional research. C om m unication and dissem ination tools will be produced to share results and build professional health know ledge.

In line w ith the research fram ework outline in Figure 11, a m odular approach is adopted for the completion of this thesis, associated w ith the com pletion of each of the objectives set out below, as shown in Figure 12. Each m odule explores the potential of a practical GIS and geodem ographic fram ew ork and a set of tools to explore the acquisition and diffusion of geodem ographics for exploring health disparities and developing and harnessing social capital for public health use.

To fit w ith this m odular, inductive approach three research objectives have been identified. On completion these objectives will contribute to the

achievement of the underlying aim of this research. The three objectives are outlined in Figure 12 and directly line up w ith the structure presented in Figure 11. In Figure 12 the first two objectives fit w ith the first tier of the research fram ework, and the third objective fits w ith the second tier of the research fram ework. Each objective is discussed in m ore detail below.

Thesis To explore an alternative framework for measuring inequality and disseminating results for application to social

marketing and public health interventions.

Tier one of research framework Tier two of research framework

Explore framework for Substantiate health variability Embed and evaluate framework extension of Geodemographics using framework in real world in Public H ealth- transferring

to health inequalities and setting and to enable research knowledge to

outcomes investigation of measure professional knowledge

— scalability and validity.

Objective two

Objective one Objective three

Figure 12: O utline of research aim s and objectives

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