The English Longitudinal Study of Ageing (ELSA) is a longitudinal study that collects multidisciplinary data from a representative sample of the English population aged 50 and older. The study started in 2002 and there are currently 7 waves of completed data and an eighth wave is currently being collected. The survey data are designed to be used for the investigation of a broad set of topics relevant to understanding the ageing process. Both objective and subjective data are collected covering themes such as health trajectories, disability and healthy life expectancy, the determinants of economic position in older age; the links between economic position, physical health, cognition and mental health; the nature and timing of retirement and post-retirement, labour market activity; household and family structure, social networks and social supports; patterns, determinants and consequences of social, civic and cultural participation and predictors of well-being. ELSA is led by Professor Andrew Steptoe and is jointly run by teams at University College London (UCL), the Institute for Fiscal Studies (IFS), National Centre for Social Research and the University of Manchester.
Current funding for ELSA continues until 2020. ELSA is funded jointly by the National Institute on Aging in the US and a consortium of UK government departments coordinated by the Economic and Social Research Council. For the current grant, covering waves 7, 8, and 9, the departments making up the UK government funding consortium are: Department of Health; Department for Work and Pensions; Department for Transport.
Study design and data collection
The first wave of ELSA achieved a sample comprising 11,050 respondents aged 50 and over on 1 March 2002. Sample members are drawn from respondents to the Health Survey For England (HSE) and the initial data collected for that survey are subsequently linked to the ongoing ELSA measurements. For waves 3, 4, 6 and 7 refreshment samples selected from HSE 2001–04; 2006; 2009-2011; and 2011-2012 were added, respectively. The main interview takes the form of a personal interview using CAPI (computer-assisted personal interview) followed by a short self-completion questionnaire. Other components of the study include: a nurse visit involving measurements of physical function, anthropometric measurements and blood/saliva samples; a life-history interview collecting information on lifetime family circumstances, place of residence, employment and major health events prior to the baseline interview; and an end of life interview, initially adapted from US Health and Retirement Study (HRS), carried out by close friends/relatives of an eligible ELSA respondent who has died to collect information about the respondent’s circumstances in the period since the final interview and their death.
Over the course of the study to date, the following data have been collected:
- March 2002 – March 2003: Wave 1 Interview
- June 2004 – June 2005: Wave 2 Interview + Nurse visit
- May 2006 – August 2007: Wave 3 Interview
- March 2007 – October 2007: Life-history interview
- May 2008 – June 2009: Wave 4 Interview + Nurse visit
- June 2010 – June 2011: Wave 5 Interview
- May 2012 – June 2013: Wave 6 Interview + Nurse visit
- June 2014 – June 2015: Wave 7 Interview
- May 2016 – June 2017: Wave 8 Interview + Nurse visit
- Expected to start in September 2017 – Health Cognitive Ageing Project substudy
Data and findings
Users registered with the Economic and Social Data Service (ESDS) can access the ELSA datasets via a web-based download service. A list of publications using ELSA data is maintained on the ELSA website. A selection of descriptive findings from each wave of the study are published every 2 years
ELSA GWAS data
ELSA possess both genome-wide genotyping data as well as a large array of phenotypic data. The inclusion of such information in ELSA has great potential to augment what is already known about how genomic variation is linked to disease risk and how certain characteristics interact to modify genetic susceptibility. In 2013/2014, the Illumina Omni 2.5–8 chip (Illumina Inc, San Diego, Ca., 560
USA) was used to perform genome-wide genotyping of around 2.5 million single nucleotide polymorphisms (SNPs) and related genomic features for approximately 7,400 ELSA participants. The same genotyping chip had previously been used in HRS, enabling direct comparisons of the ELSA and HRS samples to be carried out without the need for imputation-based meta-analysis. The ELSA GWAS data have been deposited in the European Genome-phenome Archive (EGA) and are available to bona fide researchers. Data access is regulated by the Managing Ethico-social, Technical and Administrative issues in Data Access METADAC committee.
ELSA data is designed to be directly comparable with data from the US Health and Retirement Study (HRS) and the Survey of Health, Ageing and Retirement in Europe (SHARE). There are a number of other analogous studies around the world that are concerned with aspects of ageing:
- New Zealand Health, Work and Retirement Survey
- Korean Longitudinal Study of Aging
- WHO’s Study on Global Ageing and Adult Health (SAGE)
- Mexican Health and Aging Study (MHAS)
- The Irish Longitudinal Study on Ageing – TILDA (TILDA)
- The Longitudinal Aging Study in India (LASI)
- The Japanese Study of Aging and Retirement (JSTAR)
- China Health and Retirement Longitudinal Study (CHARLS)
- The Health and Retirement Study (HRS)
Health differences between England and the USA
ELSA and HRS data were used to directly compare measures of health, income, and education amongst 55- to 64-year-olds in England and the US. The rates of disease (specifically heart disease, diabetes and cancer) across income groups (low, middle and high income) were significantly higher in the US than England. Differences were found not to be due to measurement or study design, risk factors such as current levels of obesity, drinking and smoking, (which were controlled for) did not explain very much of the international differences. Biomarker data confirmed that these differences in disease were real and not a result of differential reporting behaviour across countries.