UCL CeLSIUS Blogs
Who will fill in the internet census?
A blog on the UCL CeLSIUS website by Oliver Duke-Williams
“This weekend (Sunday March 21, 2021) we will all be asked to fill in our census forms. There’s a key difference this time: the Office for National Statistics, which runs the operation, is aiming for at least 75 per cent of our returns to be submitted online, and the early signs are that millions of people have already responded.” Published on March 19th, 2021
https://blogs.ucl.ac.uk/linking-our-lives/2021/03/19/who-will-fill-in-the-internet-census/
The ONS Longitudinal Study: how does it work?
A blog on the UCL CeLSIUS website by Nicola Shelton
“Back in the late 1960s there was concern that policymakers had too little information about births and deaths: death certificates recorded only limited information and even the occupation of the deceased could be recorded inconsistently. Similarly it was impossible to use information from birth registrations to look at patterns of fertility – how were children spaced within families, for instance? And so the ONS Longitudinal Study was born.” Published on March 18th, 2021
https://blogs.ucl.ac.uk/linking-our-lives/2021/03/18/the-ons-longitudinal-study-how-does-it-work/
The 2021 Census: What will it tell us about life after Covid-19?
A blog on the UCL CeLSIUS website by Nicola Shelton
“When the 2021 census was first planned, we thought some of the biggest research questions to emerge from it would be around the effects of Brexit. But while those are still live, researchers and others will be watching with interest to see what this snapshot of Britain in 2021 will tell us about the effects of Covid-19.” Published on March 9th, 2021.
Dawn Everington, SLS-DSU
SLS-DSU have been working on an exciting new data development which will soon be available to researchers. We have been given access to postcode of residence and date of each NHS GP registration since 1 January 2000. This provides users with a means of locating their SLS sample continuously rather than only once every 10 years at the time of the censuses.
Besides projects primarily interested in internal migration, these data will be also useful to those investigating how the local environment affects outcomes, such as the recent project which looked at proximity to green space, forests and health services. The length of time spent at each address could be incorporated into analyses, or location might be explored in relation to wider policy measures or events such as the economic recession.
An early test dataset was supplied to project 2016_003 ‘Economic change and internal population dynamics: an innovative study of new residential mobilities in Scotland’. Results from these analyses have been presented at several seminars and conferences (see list at the bottom of the project page) and there are plans to publish papers.
The online data dictionary has now been updated with Table E10 which contains the raw data and some derived variables. Although many of these cannot be accessed by researchers due to the risk of disclosure (marked as restriction level 2), we are in the process of producing further derived variables such as flags, which users can access. We will soon produce a working paper which will document the data sources and processing of the data, describe the variables in table E10, compare the enumeration postcodes with the postcodes recorded in the NHS data, and provide other information that will be helpful when using and interpreting these data.
For further information see this blog post or contact SLS-DSU at sls@lscs.ac.uk.
Zengyi Huang, SLS-DSU
The SLS Birth Cohort of 1936 (SLSBC1936) is now available to external researchers. This cohort is structured around the existing SLS. We took the SLS birth date sample from the Scottish Mental Survey of 1947 (a cognitive ability test that included almost all Scottish children born in 1936) and linked it to the 1939 National Register, the NHS Central Register and the SLS. The outcome of the project is a powerful life-course dataset containing information from childhood to old age.
A new SLS Technical Working Paper 7: ‘The Scottish Longitudinal Study 1936 Birth Cohort’ describes the methodology used in creating the SLSBC1936, the quality of linkage and the data included in this cohort. A short description of this data linkage project can be found on the poster: The creation of an administration data based 1936 Birth Cohort Study.
The SLSBC1936 is a general-purpose resource, which is available for researchers via the SLS administration. Anyone interesting in accessing this dataset should contact the SLS-DSU at sls@lscs.ac.uk.
More detail: SLS Technical Working Paper 7
(download as a PDF 958kB)
Overview
The Northern Ireland Longitudinal Study, ONS Longitudinal Study (England and Wales), and Scottish Longitudinal Study include a vast range of data relevant to many different types of research question. Their combination of administrative, census and health data across time make them a rich and unique set of resources. Examples of the types of research enabled by these features of the LSs include: The role of subject choices in secondary education on further education studies and labour market outcomes and Population characteristics of stigma, condition disclosure and chronic health conditions.
As an exploration of the many ways in which the LSs have been used, CALLS have conducted an analysis of the journal papers produced by LS researchers.
This citation analysis demonstrates the impressive range of academic fields to which LS-based research has contributed in the last 6 years. Research featured in almost 60 journals, and spanned more than 40 Scopus subject categories.
Research based on the LSs is regularly published in top quality international peer reviewed journals such as Demography, the International Journal of Epidemiology and Population, Space and Place. Fifteen papers in the citation analysis were published in journals ranked within the top 5 for their field (articles ranked by SJR Impact Rating for the relevant subject category in the publication year).
LS | n papers published | Total citation count |
| NILS | 29 | 119 (avg 4.1) |
| ONS LS | 51 | 264 (avg 5.2) |
| SLS | 32 | 259 (avg 8.1) |
| All LSs | 106 | 588 (avg 5.6) |
Papers had excellent citation rates indicating the acknowledgement of the unique contributions LS data offer. Papers published within the last 2-3 years were amongst the most highly cited. Eighteen papers had been cited 10 or more times.
The subject areas of papers using the LSs reflect the strengths of the data that they offer: SLS and NILS had a higher proportion of health-related papers, likely due to their excellent linkages with health data. Looking at subject categories for the LSs also reflect these variations: whilst the categories were very similar, ONS LS’s top 5 included ‘Demography’, whereas the SLS and NILS included ‘Health(social science)’.
Overall the analysis shows the valuable contribution of the NILS, ONS LS and SLS to a diverse range of academic fields including medicine, demography, geography, economics, business, psychology, environmental science and more.
Although we only focus on publications in academic journals here, LS research has considerable impact in other formats such as briefing notes, books and presentations to government, and has also formed part of a variety of PhD Theses. The full list of outputs can be explored in our Outputs database.
The raw data for the analysis can be downloaded at the bottom of this page.
Methods
Using the CALLS Hub outputs database a total of 106 published papers from the period January 2010 – May 2016 were identified from the three LSs. It should be noted that whilst CALLS and the RSUs actively solicit LS users to record all outputs, and also conducts literature searches to maximise capture, it is possible that some further papers exist.
All papers published in journals or regularly produced official publications – such as ONS Population Trends – were included. We did not include working papers in this analysis. Citation counts were gathered from Scopus, taking the final counts as of 30 June 2016. Impact Factors were taken from the Scopus project SCImago using the SJR2 indicator.
Results
The LSs combined
Of the 106 papers identified, 16 were from non-peer-reviewed journals such as Population Trends. Four papers used more than one LS for their analysis. (see figure 1)
figure 1. Number of published papers per LS, Jan 2010 – May 2016. n = 106
Papers from the three LSs were published in a total of 59 different journals, spanning 41 SCImago Subject Categories in 11 Subject Areas (figure 2). SJR Impact Factors for the papers ranged from 0.128 to 9.893, with an average of 1.577.
figure 2: Number of LS papers published by SCImago Subject Area [CLICK TO ENLARGE]
The 5 most frequent subject categories for LS papers were:
- Public Health, Environment & Occupational Health (30 papers)
- Medicine(misc) (25 papers)
- Geography, Planning & Development (20 papers)
- Epidemiology (17 papers)
- Health(social science) (16 papers)
The ten most cited papers from the three LSs were:
Northern Ireland Longitudinal Study
During the period January 2010 to May 2016, a total of 29 journal papers were found which had used NILS data, including one paper which had used all 3 LSs. Five NILS publications appeared journals with top-5 ranked impact factor.
NILS journal papers were published in 18 different journals, spanning 8 SCImago Subject Areas and 22 Subject Categories (see below). SJR Impact Factors for the papers ranged from 0.219 to 4.381, with an average of 1.632.
figure 3: Number of NILS papers published by SCImago Subject Area [CLICK TO ENLARGE]
The 5 most frequent subject categories for NILS papers were:
- Public Health, Environmental & Occupational Health (11 papers)
- Geography, Planning & Development (7 papers)
- Health(social science) (7 papers)
- Epidemiology (6 papers)
- Medicine(misc) (5 papers)
The 10 most cited NILS papers were:
ONS LS
During the period in question, 51 journal papers were identified as having been produced from ONS LS projects (including 4 papers which also used other LSs). Of these, 14 appeared in non peer-reviewed journals. Seven papers appeared in top-5 ranked journals.
ONS LS papers appeared in 33 journals, and covered 20 SCImago Subject Categories in 7 Subject Areas. SJR Impact Factors for ONS LS papers ranged from 0.128 to 9.893 with an average of 1.453.
figure 4: Number of ONS LS papers published by SCImago Subject Area [CLICK TO ENLARGE]
The most frequent subject categories in which ONS LS papers appeared were:
- Medicine(misc) (14 papers)
- Public Health, Environmental & Occupational Health (11 papers)
- Epidemiology (8 papers)
- Geography, Planning & Development (7 papers)
- Demography (7 papers)
The most cited ONS LS papers were:
Scottish Longitudinal Study
During the period January 2010 – May 2016, 32 SLS-based journal papers were identified (including 4 papers which also used other LSs). Of these, 2 appeared in non peer-reviewed journals. Three papers were published in top-5 ranked journals.
The SLS papers were published in 26 different journals, spanning 23 SCImago Subject Categories in 8 Subject Areas. Impact Factors for the papers ranged from 0.226 to 5.667, with an average of 1.6.
figure 5: Percentage of SLS papers published by SCImago Subject Area [CLICK TO ENLARGE]
SLS papers appeared most frequently under the following subject categories:
- Public Health, Environmental & Occupational Health (9 papers)
- Medicine(misc) (8 papers)
- Geography, Planning & Development (6 papers)
- Health(social science) (5 papers)
- Epidemiology (3 papers)
The 10 most cited SLS papers were:
Explore the full database of LS outputs
Raw data (Excel, 82kB)
On Friday 18th March we held the largest of our UK LS Roadshows to date and we hope the audience enjoyed the day as much as we did.
The first part of the Roadshow showcased research examples from all three LSs – the Scottish Longitudinal Study, Northern Ireland Longitudinal Study and ONS LS, and you can download slides here:
| Pathways between socioeconomic disadvantage and growth in the Scottish Longitudinal Study, 1991-2001 (PDF 4MB) Dr Richard Silverwood, London School of Hygiene and Tropical Medicine |
| Ethnic differences in intragenerational social mobility between 1971 and 2011 Dr Saffron Karlsen, University of Bristol |
| Are Informal Caregivers in Northern Ireland more likely to suffer from Anxiety and Depression? A Northern Ireland Longitudinal (NILS) Data Linkage-Study Dr Stefanie Doebler, Queen’s University Belfast |
On Nov 10th, our UK LS Roadshow moved to Bristol as part of the ESRC Festival of Social Science.
The first part of our Roadshow showcased some of the different types of research that the ONS LS for England & Wales has been used for, and you can download the slides here:
| Family size and educational attainment in England and Wales Prof Tak Wing Chan, University of Warwick |
| Overall and Cause-specific Mortality differences by Partnership status in 21st Century England and Wales (PDF 645 kB) Sebastian Franke, University of Liverpool |
| Ethnic differences in intragenerational social mobility between 1971 and 2011 Dr Saffron Karlsen, University of Bristol |
On October 26th and 28th CALLS Hub hosted two exciting roadshow events in Aberdeen and Glasgow to promote the UK Census-based Longitudinal Studies. The events were well attended and feedback from the audience was very enthusiastic! It was great to be able to share our excitement about the potential of the datasets.
The first part of our Roadshows showcased some of the different types of research that the Scottish Longitudinal Study has been used for, and you can download the slides here:
| Protective effects of nurses’ health literacy: evidence from the Scottish Longitudinal Study Dr Ian Atherton, Edinburgh Napier University |
| NEETs in Scotland: a longitudinal analysis of health effects of NEET experience (PDF 5MB) Dr Zhiqiang Feng, University of Edinburgh |
| Population Ageing in Scotland: Implications for Healthcare Expenditure Projections (PDF 312kB) Dr Claudia Geue, University of Glasgow |
| How spatial segregation changes over time: sorting out the sorting processes (PDF 285kB) Prof Nick Bailey, University of Glasgow |
| Using the Scottish Longitudinal Study to analyse social inequalities in school subject choice (PDF 766kB) Prof Cristina Ianelli, University of Edinburgh |
| Inequalities in young adults’ access to home-ownership in Scotland: a widening gap? (PDF 1MB) Prof Elspeth Graham, University of St Andrews |
Tom Clemens, SLS-DSU
Asking questions about income in surveys or in the census in the UK is a difficult and controversial issue. Although people in places like the US and Scandinavia are less protective about the amount of money that they earn, in the UK it is often considered private and sensitive so that many people choose to refuse to answer questionnaires and surveys that ask for income information, including the UK census. Despite regular debates about its inclusion in the years leading up to previous censuses, a question about income has never been included. This creates a problem for researchers interested in using the census (and other data sources) for social research purposes because income is often an extremely important piece of information when trying to understand the effect of poverty on the population. Other measures have often been used instead of income, including area-based measures of deprivation or other measures of socio-economic position such as education or social class, but often they are measuring something different and do not capture very well the particular effects of living on a low income.
At the Scottish Longitudinal Study, we have developed a method to address this problem through the calculation of a “synthetic” measure that estimates individual weekly wage. The method is based on the detailed occupation information contained in the Standard Occupation Classification or SOC. SOC is a hierarchical variable and contains descriptions for around 350 different types of job which are nested within a hierarchy of broader job description categories. This approach is different to previous occupation-based measures such as occupation based social class, because it utilises all of this highly detailed SOC information to calculate a continuous estimate of weekly wage. Other approaches waste this information by aggregating to higher level occupation information. More details about the precise methodology used to derive the estimates, and of their performance against other measures of socio-economic position can be found in a journal article (open access) and an SLS working paper.
As part of the project, a Stata program has been written in order to allow users to produce the estimates in their own research projects; all that is needed in your dataset is the following variables and associated coding:
- Individual single year of age
- Sex (0 for females and 1 for males)
- SOC coded occupation (3 digit format for SOC90 version which was introduced in 1990 or the four digit SOC2000 version which was introduced in 2001)
Once you have these variables you will need to download the Stata program “salaryest20” and “salaryest90” which are simply Stata ado files. These will be available from SLS support officers on request and can be installed by selecting the text in the ado files and running them in Stata which will automatically install the program. Once you have done this you can use the following syntax commands to use the programs:
For estimating weekly wage based on SOC90:
salaryest90 newvarname, age(age varname) sex(sex varname) soc(soc90 varname)
For estimating weekly wage based on SOC2000:
salaryest20 newvarname, age(age varname) sex(sex varname) soc(soc2000 varname)
Where newvarname, age varname, sex varname, soc90 varname and soc20 varname should be replaced with, respectively, the name that you want the new wage variable to be, the name of your age variable, the name of your sex variable and the names of the SOC90 and SOC2000 variables in your dataset. The command will then produce a new variable containing estimated weekly wage information and will output descriptive information about this new variable. The commands can be used in any dataset which is missing income but includes information about age, sex and SOC occupation. Anyone who is interested in using these commands in an SLS project should talk to their support officer who can assist you.
On Tuesday 4th November 2014, the SLS-DSU (supported by National Records of Scotland and CALLS Hub), held a launch event to announce the linkage of 2011 Census data to the Scottish Longitudinal Study.
The event was held at Royal College of Physicians, Edinburgh, and around 70 people attended to hear about the new data, as well as examples of how it could be used. The welcome was given by Prof Andrew Morris, Scottish Government Chief Scientist.
UPDATE: We are pleased to now offer you the option of downloading full audio-plus-slide movies of the presentations as well as PDF copies of the slides.
Introduction
- Programme (PDF 463KB)
- Welcome – Prof Andrew Morris, Chief Scientist, Scottish Government (audio only m4a 18.5MB)
- Introduction and the 2011 Census Link – Mrs Susan Carsley, Project Manager, SLS-DSU (Slides only PDF 3MB; Audio+Slides m4v 125.2MB)
Research using the 2011 link – the data in practice
- Examining the occupational scarring of young people not in education, employment or training (NEET) in 1991 – Dr Kevin Ralston, Support Officer, SLS-DSU (Slides only PDF 918KB; Audio+Slides m4v 73.1MB)
- Stability and change in ethnic groups in Scotland – Dr Zhiqiang Feng, Support Officer, SLS-DSU (Slides only PDF 1MB; Audio+Slides m4v 100.3MB)
- Demographic Change in the Scottish Jewish Community 2001 – 2011 – Prof Gillian Raab, Statistician, SLS-DSU (Slides only PDF 820KB; Audio+Slides m4v 108MB)
- Understanding the impact of fertility history on health outcomes in later life – Prof Chris Dibben, Director, SLS-DSU (Slides only PDF 1MB; Audio+Slides m4v 139.2MB)
Looking forward
- CALLS Hub and the UK Context – Dr Fiona Cox, Project Manager, CALLS Hub (Slides only PDF 5MB; Audio+Slides m4v 92.7MB)
- Synthetic Data Estimation for the UK Longitudinal Studies – SYLLS – Dr Beata Nowok, University of Edinburgh (Slides only PDF 862KB; Audio+Slides m4v 91MB)
- The ADRC-S & Future Developments – Prof Chris Dibben, Director, ADRC-Scotland (Slides only PDF 2MB; Audio+Slides m4v 145.2MB)
Fiona Cox, CALLS Hub
Results from an SLS-based study have been featured in several news outlets this week including Medical News Today, Oncology Nurse Advisor and Science Daily.
Hannah Dale and colleagues from the University of St Andrews have found some key markers for vulnerability to psychological problems in men experiencing cancer. Their results were presented at the Annual Conference of the British Psychological Society’s Division of Clinical Psychology in Glasgow on Dec 3rd 2014.
For their research, a group of 127 men aged 18 and over with a cancer diagnosis were recruited through the National Health Service and cancer charities between April 2009 and April 2011.
The participants were assessed for demographic factors, social support, anxiety and depression, and distress (Distress Thermometer). Data for cancer patients from the Scottish Longitudinal Study were examined to make sure the sample was representative of men with cancer as a whole.
The findings indicated that participants who were separated and divorced had lower social support and greater depression. Younger age was related to higher anxiety, and distress. Living in an area of higher deprivation indicated greater depression and anxiety. Social support was also a key indicator of psychological health.
Given these findings, they say it is important to target those at greatest risk of psychological problems following a diagnosis of cancer for psychosocial support.
Hannah Dale says:
“Men typically have smaller networks than women and often rely on their wives for support. Some men who are separated or divorced lack such support, which can leave them more vulnerable to depression.
“Other findings suggest that age and living in an area of higher deprivation are associated with men with cancer being more vulnerable to poor psychosocial health. More research is needed to confirm these findings, but this study highlights an area that has historically been neglected in the literature.”
SLS-DSU Project page: 2010_002
BPS press release
