Estimating Census Health Geographies: using synthetic estimation with secondary survey and census data

The 2011 Population Census was almost certainly the last to be undertaken using traditional methods of survey completion. It is acknowledged however that there will continue to be a requirement for comprehensive data on small area variations on a range of topics for service planning, evaluation and many other needs. This continuing need extends across the public and private sectors. Alternative approaches to the provision of small area data exist. Most attention, in the context of post 2011 census debates, has focussed on the potential for record linkage arguing that much present census data is available, in some form, in other databases. An alternative, less-explored approach is small area synthetic estimation (SASE). Essentially two approaches to SASE are available: microsimulation and multilevel SASE (ML-SASE). Both approaches entail the integration of secondary data from survey sources and subsequent statistical modelling.
This proposal focusses, in line with expertise of the investigators, on ML-SASE. It will assess the effectiveness of linking secondary survey data with ML-SASE as an alternative route to the production of census-equivalent small area data. It builds on ESRC's secondary data investment in the 2011 census and exploits ESRC managed access to a range of national surveys. It also builds on earlier work in developing the small area estimation techniques that form the basis for the proposal. We will compare and contrast different approaches to ML-SASE, generating estimates for four health indicators present in all national versions of the 2011 UK census using survey data collected at the same time as the Census. Further comparison will then be made between the generated estimates and the actual results of the 2011 census to examine the extent to which estimates match census 'reality'.
The originality of the proposal lies in addressing the relative neglect ML-SASE in current work on census futures. The proposal will also develop and enhance ML-SASE methodology to move beyond now standard approaches and draw benefit from recent advances in multilevel modelling. The substantive practical and policy contribution flowing from the proposed research will be a significant enhancement to the the evidence base underpinning policy debates on approaches to the replacement of the traditional census. The data generated will be relevant to the key ESRC strategic challenges on influencing behaviour and developing a free and fair society

The proposed research will achieve academic impact through the completion of high quality research demonstrating the potential of linked survey datasets and ML-SASE in producing small area health indicators. This research will feed into academic and policy level debates on future census replacement strategies. This academic impact will flow from the dissemination of project results in leading journals and at relevant conferences. Key disciplines to be impacted include geography, social statistics, social epidemiology and public health.

We will promote impact with non-academic bodies through public engagement and communication with key stakeholders, and through direct involvement of non-academic agencies in the final phase of the project. The intention will be to ensure wide awareness of alternative future strategies for generating small area data and an appreciation of the potential uses of linked survey data. Non-academic imapct will be a specific emphasis in the end-of project workshop and there will also be specific consideration of non-academic bodies in the design of the project website. Through these strategies we hope to contribute indirectly to future policies and practice concerned with increasing the effectiveness of public services and enhancing health. Specific targets for impact include:
- private sector market research companies seeking alternative approaches to add value to their existing data and target new markets, from data linkage and new forms of catchment data, as well as the opening up of potential new markets.
- public sector agencies using census data and concerned about the future provision of such data, for example public health observatories and equivalents in the reformed NHS. There will be regular contact with the Office for National Statistics (ONS) throughout the lifetime of the project to ensure potential impact on future post census debate.
- international agencies with interests in the provision of small area data; we have preliminary interest from the EU (DG SANCO) and Statistics New Zealand.