Abstracts - longitudinal studies

Strand organiser: Shayla Goldring, Office for National Statistics

Abstracts are listed in the order scheduled for presentation. Please refer to the programme for timings.

An investigation into the usefulness of synthetic measures of occupation based wage for self-reported general health
Tom Clemens, Department of Geography and Geoscience, University of St Andrews

Background: Obtaining accurate and unbiased measurements of individual income in many surveys is difficult owing to the sensitive nature of the information. Studies that do collect income often report differential missing data or mis-measurement and may also impact on overall survey response rates. These concerns formed part of the reason to reject calls to include an income question in the latest UK census in 2011. Lack of income information is problematic in many sociodemographic studies of health and mortality owing to the importance of income as a determinant of, for example mental and self-assessed health as well as mortality.
Aims: This paper investigates the potential utility of a synthetic occupation based estimate of wages. Methods The study uses the SOC2000 classification of occupation to derive a hierarchical mixed model using data from the labour force survey which is then validated using self-rated health data from the Scottish Health Survey (SHS) 2003 and wave one (2009) of the UK Household Longitudinal Study (UKHLS).
Findings: Our estimates compare favourably with the survey income measurements. This suggests that this approach could be used to account for income disparities in self-rated general health in those surveys where income is not directly measured including census based longitudinal studies.

Email: Tom Clemens: tc245@st-andrews.ac.uk

Patterns of Social Mobility by NS-SEC: England and Wales 1981-2001
Suzanne Fry, Alaa Al-Hamad, Chris White, Office for National Statistics

The significance of social mobility is well documented. The strategy Opening Doors, Breaking Barriers refers to it as the principal goal of social policy. The importance of social mobility reflects the cross-cutting benefits associated with it. Fundamentally, in a fair society, every individual should have the opportunity to succeed. Universal opportunities also create a highly skilled workforce, which drives economic growth. There are also equality benefits, as studies provide evidence that social mobility into favourable circumstances contributes to health improvement. Using linked ONS Longitudinal Study (LS) records, the National Statistics Socio-Economic Classification (NS-SEC) analytic class designations will be used to measure population level transitions. Uniquely, we examine transitions over an extended period, through the use of a classification model developed by ONS to assign NS-SEC to 1981 responses. Our research at this stage consists of three strands. We first consider NS-SEC distribution at each Census year between 1981-2001, separately for men and women, to gain an initial understanding of the proportion assigned to each group, and to consider any changes over time. We then examine mobility more closely, by using changes in members\' classification as the basis for our consideration of social mobility, and testing a number of assumptions for determining what constitutes stable, favourable and unfavourable transitions. Finally, we analyse common destinations between groups. The ability to calculate and provide social mobility indicators over an extensive period, which in further work can be used to examine the impact upon health outcomes, is likely to be of increasing interest.

Email: Dr. Suzanne Fry: suzanne.fry@ons.gsi.gov.uk

Understanding the impact of fertility history on outcomes in mid-life in Scotland, a longitudinal approach using the Scottish Longitudinal Study (SLS)
Lee Williamson and Chris Dibben, Longitudinal Studies Centre - Scotland (LSCS), University of St Andrews

This study is part of the research programme involving data linkage within the Scottish Health Informatics Programme (SHIP). The research draws on and extends work on reproductive histories and life outcomes. Previous studies have shown that the number of children (parity) can be linked to specific health outcomes in mid and later life for women (references can be provided). We aim to extend this research specifically for Scotland based on Scottish data, namely the Scottish Longitudinal Study (SLS) linked to health data from the NHS Scottish Morbidity Record (SMR) datasets, including the maternity dataset SMR02 (as parity is only recorded for married women at birth registration in Scotland). The aim of this SHIP project, involving data linkage and health outcomes, is to gain a full understanding of the impact of both fertility histories and childlessness on health outcomes and mortality. In addition, we plan to compare findings with previous research where applicable. This research is only for specific female SLS birth cohorts, as it is acknowledged that we are not able to follow-up all SLS members or SLS members to old ages since the SMR02 is only available from 1975. Nevertheless, the SLS allows follow-up of the specific SLS birth cohorts from the 1991 Census until 2009 (the most recent year death data is available linked to the SLS). From preliminary modelling, in line with previous research, we find high birth parity to be an important factor in relation to mortality.

Email: Dr. Lee Williamson: lee.williamson@st-andrews.ac.uk

Understanding address accuracy: an investigation of the social geography of mismatch between census and health service records
Ian Shuttleworth, Queens University Belfast; David Martin, University of Southampton

Address listing plays a key role in the design of contemporary census enumeration and in quality assessment by matching to administrative data. Further, the recording of individual addresses underpins the delivery of healthcare services and is central to the potential replacement of a conventional census by use of linked administrative records. Little is currently understood about the accuracy of address recording on administrative systems - and hence their potential effectiveness in capturing the entire population - across different population subgroups. This paper describes an initial investigation using the unique Northern Ireland Longitudinal Study (NILS). NILS is a 28% sample of the Northern Ireland population, matched between the census and health register maintained by the HSC Business Service Organization (BSO), equivalent to the National Health Service register. Anonymised unique property reference numbers, linked from the LPS database, have been matched between the 2001 census and corresponding health register for NILS members, allowing the consistency of addressing in the two sources to be investigated. This analysis explores household and neighbourhood determinants of address inaccuracy, including the geographical distances between mismatched addresses for the same individual, and reveals patterns of address quality in terms of individual characteristics, household composition and dwelling type.

Email: Dr. Ian Shuttleworth: i.shuttleworth@qub.ac.uk