Using migration microdata from the samples of anonymised records and the longitudinal studies

Norman, P. & Boyle, P. (2010) In Stillwell, J, Duke-Williams, O & Dennett, A (eds), 'Technologies for Migration and Commuting Analysis: Spatial Interaction Data Applications' Chapter 7, pp133-152. IGI Global. ISBN: 9781615207558 [SLS][ONS LS][NILS]

Other information:

In this chapter we describe the Samples of Anonymised Records (SARs) and Longitudinal Studies (LSs). The SARs are cross-sectional data like the area and interaction data, but the LSs track people over time. These datasets differ from the United Kingdom’s other census outputs being individual-level ‘microdata’ and population samples. The microdata files are very versatile, allowing multi-way crosstabulations and statistical techniques and enabling application-relevant re-coded variables and study populations to be defined. The SARs files offer UK coverage although a UK-wide study is challenging because data for each country may be in separate files with different access arrangements and variable detail may be country specific. The Office for National Statistics (ONS) Longitudinal Study for England and Wales has underpinned a wide range of research since the 1970s. This well-established source is now complemented by longitudinal data for Scotland and Northern Ireland. Largely driven by the need to ensure respondent confidentiality, the SARs and LSs have some drawbacks for migration-related research. In addition to stringent access arrangements, the geographical area to which individuals are located in the SARs tend to be coarse and although the LS databases record the small area in which the LS member was living at each census, specific ‘place’ information is unlikely to be considered non-disclosive unless for large geographies. However, generic, contextual information about the ‘space’ in which people live is useful even though actual places are not identified. Whilst the SARs and LSs are samples, they are, however, very large samples in comparison with other national surveys and represent first rate resources to complement other sources. In the course of this chapter, along with other references to SARs and LS-based migration research, we review work which utilised these sources to investigate inter-relationships between health, deprivation and migration. The SARs data show that migration is health-selective by age and distance moved and that those persons living in the public housing tenure who are moving into or within deprived areas are most likely to be ill. The role of migration in changing health inequalities between differently deprived areas can be explored using longitudinal data on both origins and destinations. The ONS LS reveals that migrants into and between the least deprived areas have better health than non-migrants, but migrants into and between the most deprived areas have the worst health. The effect of these changes has been to increase the inequality in health between differently deprived areas. A sorting, largely driven by selective migration occurs.

Available online: 'Technologies for Migration and Commuting Analysis: Spatial Interaction Data Applications'
Output from project: 10347


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