Centre for Longitudinal Studies Birth Cohort Studies Data Linkage: 1970 British Cohort Study

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Datasets: + HES-ID to MPS-ID HES Admitted Patient Care; + HES-ID to MPS-ID HES Outpatients

Objective for processing

[3 paragraphs unchanged] It was not for another 5 years that it was decided that [93 words unchanged] to the impact of the COVID-19 pandemic, but re-commenced in early 2021. The main survey is now complete and those who didn’t respond as well as cohort members living abroad have been invited to take part in a short web version of the survey. This will finish in January 2024. Subsequent sweeps* of the study will likely take place every five years. [24 paragraphs unchanged] 3) The CLS will promote and make possible wider use of this linked data set, through providing wider access to the linked NHS England HES / (HES/ECDS) to CLS BCS70 data to the research community via the UK Data Service (UKDS) Secure Lab under sublicensing agreements subject to the following access arrangements. [20 paragraphs unchanged] The anticipated volume / number of Licenses is 1-2 sub-licences per month. Sub-licences shall not exceed a term of 12 months at a time and may be extended/renewed if appropriate. The sub-licences any sub-licence will remain valid only while UCL retains the right to hold and share the data from NHS England. Sub-licences may be extended/renewed but only under the same terms as just stated. [12 paragraphs unchanged]

Processing activities

[1 paragraph unchanged] NHS England data will provide the relevant records from the HES and ECDS datasets to UCL. The data will contain no direct [16 words unchanged] the data with other record level data already held by the recipient. The CLS will carry out validation of the administrative pseudonymised data received (linked HES/ECDS (HES/ECDS data) and combined the supplied administrative data with the information collected from the participant as part of the BCS70 study using the study ID. [13 paragraphs unchanged] UCL only request data for those individuals who have given consent to [15 words unchanged] to NHS England, for the matching of consenting participants to the NHS England HES/ECDS England' datasets, the data manager will check for withdrawals and will remove participants who- [3 paragraphs unchanged] The HES/ECDS data provided by NHS England, which are linked to the CLS cohort [27 words unchanged] highly identifiable variables and altering other variables by top-coding or truncating them. [1 paragraph unchanged] Only staff who are permitted to work at the UKDS (and are [74 words unchanged] subject to statistical disclosure control procedure. Access to the Secure Lab is only available to ESRC accredited researchers who are based at a UK academic institution or an ESRC-funded research centre and are an ESRC Accredited Researchers. institution. PhD and research students can request access but must apply jointly with their supervisors from established organisations. Access will also be available to non-academic, non-commercial research organisations. [3 paragraphs unchanged]

Expected output

Following the data quality and validation work, the first output will be the addition of the refreshed data to the existing linked NCDS/HES dataset which is now available for researchers to apply. The data requested under this Agreement will refresh this already rich linked dataset. CLS will publicise the data release on the CLS website. This data linkage opens new research opportunities by combining reliable administrative data with detailed survey data. This linkage increases the number of variables available for research in the dataset and complements the health information provided by the participants in the survey. Combined, these data sources enhance each other, making it possible to capture detailed information regarding an individual’s health and well-being. Health events can be experienced over an extended period, tracking all relevant events over such a long period may not be feasible in a single database. Using HES/ ECDS data which records such information can improve the accuracy of the data collected in the survey, offering huge potential for scientific and policy-related The second output will be a methodological paper titled: “Examining the linkage quality and sample representativeness of the linked 1970 British Cohort Study”. This is planned to be published by the end of 2024. The target journals for publication are : research. CLS at UCL actively promotes the use of their data among the research community through publications and events (e.g. training and workshops on each data set to help researchers better use the data), as well as providing extensive documentation, guidance on the use of the data and so ultimately benefit health and social care. The second output will be health-related research, alongside methodological papers on the linked dataset, published in peer-reviewed journals. The methodological assessments are expected to finish three years after obtaining the data. Outputs will contain only aggregate-level data with small numbers suppressed in line with HES analysis guide. CLS researchers doing research and/or methodological work will access this data via the UCL Data Safe Heaven. The methodological paper will be titled: “Examining the linkage quality and sample representativeness of the linked BCS70”. This is planned to be published by the end of 2026. The target journals for publication are : [3 paragraphs unchanged] In this paper, researchers will examine the quality of the linkage in [60 words unchanged] linked sample using external data (hospital admission rates in the general population). The methodological project above mentioned is currently being carried out for CLS’s other study, the 1958 National Child Development Study (NCDS) and it is near completion. The findings suggest that the linkage quality of the NCDS-HES data is high and that the linked sample maintains an excellent level of population representativeness. Researchers hope that these analyses will both improve the quality and transparency of research using this linked data resource and encourage providers and users of other linked data resources to undertake and publish similarly thorough evaluations. This paper is expected to be published during 2023. CLS has not yet published any methodological papers reviewing the linkage. No papers have been published since earlier versions of this Agreement were approved because CLS have a policy of not using data internally for research when not available to external users and the original approval did not allow CLS to share the data with external users. Thus, CLS have focused on getting the necessary permission for sub-licencing the data. The methodological project above mentioned was carried out for CLS’s other study, the 1958 National Child Development Study (NCDS) and it is now complete. The findings suggest that the linkage quality of the NCDS/HES data is high and that the linked sample maintains an excellent level of population representativeness. The creation of this refreshed HES/ECDS-BCS70 database including this and the methodological papers are the first steps in establishing a robust research database which will be of benefit to health and social care. Researchers hope that these analyses will both improve the quality and transparency of research using this linked data resource and encourage providers and users of other linked data resources to undertake and publish similarly thorough evaluations. This paper can be found herehttps://cls.ucl.ac.uk/wp-content/uploads/2017/02/Examining-the-quality-and-sample-representativeness-of-linkedsurvey- and-administrative-data-CLS-Working-Paper-2022-5.pdf CLS actively promotes the use of their data among the research community through publications and briefings, working papers, webinars, social media, public reports, hosted events, as well as providing extensive documentation, guidance, training and workshops on each data set to help researchers better use the data and so ultimately benefit health and social care. There are currently two projects accessing the linked data: Project 1 Title: Physical activity, sedentary behaviour, and diet: impact on cardiometabolic and women’s health Project 2 Title: Hospital use over the life course

Expected measurable benefits

The BCS70 surveys include questions relating to health outcomes and hospitalisations. CLS will use these responses to compare with their data available on HES to obtain a better understanding of relationship between self-reporting and administrative data. This will be shared via methodological information which will assess the data quality and comparability of two important data sources. This will help both improve the quality and transparency of research using this linked data resource and encourage providers and users of other linked data resources to undertake and publish similarly thorough evaluations. This will also be of benefit to research looking at health and social care issues. The linked BCS70/HES dataset received under previous versions of this agreement is now available for researchers to use for research that could potentially influence policy and benefit health and social care as well as improve people's lives. The projects listed under the 'Outputs section' are evidence of how this rich dataset can be used to benefit society. The specific benefits to society, using the data accessed through the sub-license, would be stated by each applicant as part of their application (as required in the Accredited research form and Research proposal – e.g. ‘How your findings is expected to benefit society?’, ‘How does the project provide a public benefit?’, ‘Contribution towards public policy or journal publications’). CLS is expected to further require the applicant to describe the benefits of their intended research to health and social care. The main purpose is to provide access to the linked 1970 British Cohort Study (BCS70) survey data with NHS England Health Episode Statistics (HES) data to enhance the research resource for secondary users. Linking this data with the survey data greatly widens the value of research offering an opportunity to use the HES data alongside rich survey information covering a range of different domains of people's lives. This information is not possible to directly access via NHS England. It provides an invaluable opportunity to better understand some of the social determinants of health. Releasing the data through the UKDS secure lab as outlined in this application is expected to allow the linked data to be used more widely to maximise societal benefit while maintaining high levels of data security. The BCS70 surveys include questions relating to health outcomes and hospitalisations. CLS will use these responses to compare with their data available on HES/ECDS to obtain a better understanding of relationship between self-reporting and administrative data. This will be shared via methodological information which will assess the data quality and comparability of two important data sources. This will help both improve the quality and transparency of research using this linked data resource and encourage providers and users of other linked data resources to undertake and publish similarly thorough evaluations. This will also be of benefit to research looking at health and social care issues. [17 paragraphs unchanged]

Benefits reported

It is difficult to predict in advance the type of research question that might be put forward to use the linked BCS70/HES dataset. Below are four examples of existing publications using BCS70 data benefiting public health. The first yielded benefit is the creation of the refreshed linked BCS70/HES dataset which will include most recent data. The dataset, which covers up to the year 2017 is now available for researchers to use via the UKDS. A link to the dataset is provided The research papers below have been written using data from the CLS cohorts and COVID19 surveys: https://beta.ukdataservice.ac.uk/datacatalogue/studies/study?id=8733 David Bann, Aase Villadsen, Jane Maddock, View ORCID ProfileAlun Hughes, George B. Ploubidis, Richard J. Silverwood, Praveetha Patalay (2020) ‘Changes in the behavioural determinants of health during the coronavirus (COVID-19) pandemic: gender, socioeconomic and ethnic inequalities in 5 British cohort studies’. CLS has produced an NCDS/HES user guide. This document provides researchers with a complete guide to the linked data and information on the application process. See: https://doc.ukdataservice.ac.uk/doc/8733/mrdoc/pdf/bcs_hes_user_guide_v1.pdf Using data from five nationally representative British cohort studies (born 2000-2, 1989-90, 1970, 1958, and 1946), researchers investigated sleep, physical activity (exercise), diet, and alcohol intake (N=14,297). Using measures of each behaviour reported before and during lockdown, researchers investigated change in each behaviour, and whether such changes differed by age/cohort, gender, ethnicity, and socioeconomic position (SEP; childhood social class, education attainment, and adult reporting of financial difficulties). The results showed changes in these outcomes occurred in both directions, i.e. shifts from the middle part of the distribution to both declines and increases in sleep, exercise, and alcohol use. For all outcomes, older cohorts were less likely to report changes in behaviours compared with younger cohorts. In the youngest cohort (born 2001), the following shifts were more evident: increases in exercise, fruit and vegetable intake, sleep duration, and less frequent alcohol consumption. Widening inequalities in sleep during lockdown were more frequent amongst females, socioeconomically disadvantaged groups, and ethnic minorities. For other outcomes, inequalities were largely similar before and during lockdown, yet ethnic minorities were increasingly likely during lockdown to undertake less exercise and consume lower amounts of fruit and vegetables doi: https://doi.org/10.1101/2020.07.29.20164244 CLS delivered a webinar "An Introduction to linked health administrative data in four cohort studies" on the 11th of February 2021 to introduce the HES linked datasets and provide information to researchers on how to access them. Constantin-Cristian Topriceanu, Andrew Wong, James C Moon, View ORCID Profile Alun D Hughes, David Bann, Nish Chaturvedi, Praveetha Patalay, Gabriella Conti, Gabriella Captur (2020), ‘Inequality in access to health and care services during lockdown’ – Findings from the COVID-19 survey in five UK national longitudinal studies Researchers studied whether COVID19 further deepened existing health inequalities. Access to health services and adequate care is influenced by sex, ethnicity, socio-economic position (SEP) and burden of co-morbidities. However, it is unknown whether the COVID-19 pandemic further deepened these already existing health inequalities. Participants were from five longitudinal age-homogenous British cohorts (born in 2001, 1990, 1970, 1958 and 1946). A web and telephone-based survey provided data on cancelled surgical or medical appointments, and the number of care hours received during the UK COVID-19 national lockdown. Using binary or ordered logistic regression, researchers evaluated whether these outcomes differed by sex, ethnicity, SEP and having a chronic illness. The findings showed that Females and those with a chronic illness experienced significantly more cancellations during lockdown. Ethnic minorities and those with a chronic illness required a higher number of care hours during the lockdown . Age was not independently associated with either outcome in meta-regression. SEP was not associated with cancellation or care hours. No Yielded Benefits can yet be evidenced from the data received and accessed for research under previous version of this agreement, however there is 2 project accessing this linked data for research on health and we hope that some of these future publications will result in successful yielded benefits. https://doi.org/10.1101/2020.09.12.20191973 MARCH 2024 ACR UPDATE: CABLE, N, KELLY, Y, BARTLEY, M, SATO, Y and SACKER, A. (2014) Critical role of smoking and household dampness during childhood for adult phlegm and cough: a research example from a prospective cohort study in Great Britain. BMJ Open, 4(4), e004807. First Output: Cable, Kelly, Bartley, Sato, and Sacker (2014) findings from BCS70 data give support to current public health interventions for adult smoking and raise concerns about the long-term effects of a damp home environment on the respiratory health of children. The authors examined the associations between childhood exposures to smoking and household dampness (at age 10), and phlegm and cough in adulthood (29 years of age), and found that childhood smoking and exposure to marked household dampness at age 10 were associated with phlegm (childhood smoking: relative risk ratio (RRR) =1.45, 95% CI 1.02 to 2.05; dampness: RRR=2.05, 95% CI 1.07 to 3.91) and co-occurring cough and phlegm (childhood smoking: RRR=1.35. 95% CI 1.08 to 1.67; dampness: RRR=2.73, 95% CI 1.88 to 3.99), while exposure to two or more adult smokers in the household was associated with cough-related symptoms (cough only: RRR=1.28, 95% CI 1.04 to 1.58; phlegm and cough: RRR=1.32, 95% CI 1.06 to 1.64). The first output is the BCS70/HES dataset which is now available to the research community. These associations were independent from adult smoking, childhood phlegm and cough, early social background and sex. Smoking at age 29 contributed to all symptom patterns, however, a substantial association between household dampness and co-occurring phlegm and cough suggest long-term detrimental effects of childhood environmental exposures. https://beta.ukdataservice.ac.uk/datacatalogue/studies/study?id=8733 The authors findings support current public health interventions to reduce adult smoking, but also indicate that the management of childhood risk factors such as exposure to smoke (active or second-hand) and household dampness can be a way to prevent adults experiencing poor respiratory health (CABLE, N, KELLY, Y, BARTLEY, M, SATO, Y and SACKER, A. (2014) Critical role of smoking and household dampness during childhood for adult phlegm and cough: a research example from a prospective cohort study in Great Britain. BMJ Open, 4(4), e004807). And the creation of the BCS70/HES user guide. This document provides researchers with a complete guide to the linked data and information on the application process. https://doc.ukdataservice.ac.uk/doc/8733/mrdoc/pdf/bcs_hes_user_guide_v1.pdf SMITH, L, GARDNER, B, AGGIO, D and HAMER, M. (2015) Association between participation in outdoor play and sport at 10 years old with physical activity in adulthood. Preventive Medicine, 74(May 2015), 31–35. Second Output: GREENE, G, GREGORY, A.M, FONE, D and WHITE, J. (2015) Childhood sleeping difficulties and depression in adulthood: the 1970 British Cohort Study. Journal of Sleep Research, 24(1), 19-23. The second output will be health-related research, alongside methodological papers on the linked dataset, published in peer-reviewed journals. The methodological papers: ‘Examining the linkage quality and sample representativeness of the linked data’ are planned to be published by the end of 2026. In these papers, researchers will examine the quality of the linkage in terms of the associations between key cohort member sociodemographic characteristics and successful linkage and compare the levels of successful linkage within strata of each study variables which may be expected to be associated with hospital attendance, and hence with successful HES linkage (self-reported hospital attendance, self-rated general health, self-reported long-term illness). The researchers would like to additionally evaluate the population representativeness of the linked sample using external data (hospital admission rates in the general population). Greene, Gregory, Fone and White (2015), for example, investigated the relationship between childhood sleeping difficulties (at age 5) and depression in adulthood (age 34), to conclude that severe sleeping problems in childhood may be associated with increased susceptibility to depression in adult life. Adjusting for the potential confounding influences of maternal depression and sleeping difficulties, parental reports of severe sleeping difficulties at 5 years were associated with an increased risk of depression at age 34 years [odds ratio (OR) = 1.9, 95% confidence interval (CI) = 1.2, 3.2] whereas moderate sleeping difficulties were not (OR = 1.1, 95% CI = 0.9, 1.3). Further research, however, is needed to explore whether screening and the treatment of children for poor sleeping patterns might impact upon their mental health in adulthood. Third Output: Sublicence applications- Persistent sleep problems are an increasing health concern. In addition, poor sleep in adulthood has been linked with hypertension, diabetes, depression and obesity, as well as from cancer and increased mortality (Colten and Altevogt, 2006). Therefore, successful identification and treatment for children with sleeping difficulties could, if the association identified by the authors is causal, have large dividends across many aspects of health in the future (GREENE, G, GREGORY, A.M, FONE, D and WHITE, J. (2015) Childhood sleeping difficulties and depression in adulthood: the 1970 British Cohort Study. Journal of Sleep Research, 24(1), 19-23.). The specific benefits to society of using the data accessed through the sub-license, would be stated by each applicant as part of their application to CLS. E.g. researchers applying to use the data will need to complete a project proposal and among other questions, will need to provide a response to the following question “How are your project findings expected to benefit society?”. Project 1 -“Derived variables of mental health-related health services use in NCDS and BCS70” The aim of this project is to derive user-friendly variables for wider data sharing to the scientific community. Although early life socioeconomic indicators and adverse childhood experiences (ACEs) are related to poorer mental health outcomes during adulthood, the extent to which they are related to mental health hospitalisations in adulthood has not been yet studied. Data linkages between the British birth cohorts and data on hospital admissions and treatment length provide a unique opportunity to investigate this and other relevant research questions. However, variables capturing the cohort members’ health services that are user-friendly for the scientific community are not readily available in the linked datasets but rather have to be derived. The value of these derived user friendly variables for research will be exemplified by exploring their relationship with early life socioeconomic indicators and ACEs. Project 2- “Physical activity, sedentary behaviour, and diet: impact on cardiometabolic and women’s health” Many different health outcomes are influenced by lifestyle behaviours such as physical activity, sleep, and diet. This research focuses on two main health clusters: cardiovascular related health and women’s health. Lifestyle behaviours, that are often interlinked and influenced by the social environment, may have both synergistic and specific effects on health across the life course in ways we do not completely understand. The researchers will investigate how lifestyle behaviours (physical activity, sleep, diet, alcohol, smoking) as well as specific components of each behaviour (e.g., activity type, duration, frequency, context, intensity) across the life course influence HES-data derived health outcomes including diagnoses and healthcare use. The researchers have two main work packages in this project. First, they intend to examine cardiometabolic related conditions (diabetes, stroke, heart disease etc) and second, to examine outcomes related to women’s health. These findings will have direct benefits for society as it enables researchers to identify specific components of health behaviours that improve health, whilst having the robustness of HES data. Project 3- “Hospital use over the life course”. Frailty is a valuable concept, widely used to inform and guide the clinical care of older people. Still, its relevance in people aged less than 65 is not clear. This research examines different approaches to frailty measurement that could be applied across the NHS to see if they usefully identify the risk of future poor outcomes. This project will use nationally representative studies following people since birth (‘birth cohorts’) to make a ‘frailty index’. This is a means of measuring the level of frailty and can be applied to different patient groups and over time. Frailty indices work by identifying common factors associated with frailty and determining how many are present in any individual. This gives rise to a frailty index, which has been shown to link to adverse outcomes in studies of older - and some younger - people. Because data have been collected since birth, we can explore the life course factors that may influence the development of frailty at any age of adulthood. In parallel, this research will test a Hospital Frailty Risk Score (HFRS). This can be automatically created from NHS electronic records for all people admitted to a hospital in England. Researchers will assess the ability of this risk score to predict how long people stay in hospital and whether they die. Creating a frailty index and an HFRS in the same individuals through linked birth cohort and NHS electronic records, researchers can then see how the two different approaches to frailty measurement compare for hospital outcomes such as length of stay and death, but also outcomes such as quality of life, physical or cognitive function. Once the researchers understand the factors associated with frailty in younger adults, they can think about treatments that could be applied over the life course to slow or prevent the development of frailty. Project 4- This project investigates how psychological distress, encompassing symptoms of depression, anxiety, and stress, affects physical health as people reach middle age. The researchers employ a novel research approach known as 'outcome-wide design,' which enables them to comprehensively examine how a single factor – in this case, mental health – impacts various physical health outcomes. This methodology offers insights into the interplay between mental and physical health and could identify physical health problems that may be alleviated through improved mental health care. This analysis uses data from the 1970 British Cohort Study, with a particular focus on mental and physical health information gathered during participants' middle age. A key aspect of this research involves contrasting the health conditions reported by individuals with their medical diagnoses from HES records. This comparison aims to highlight potential biases in how people recall and report their health issues, which is crucial for the accuracy of research findings. Additionally, this project will contribute to refining statistical methods used in outcome-wide designs, thereby enhancing the quality of future studies in this area.

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Objective for processing

The Centre for Longitudinal Studies (CLS) at University College London (UCL) is an academic resource centre responsible for producing and disseminating requires access to NHS England data resources for the scientific community. CLS manages four world-renowned birth cohort studies; the National Child Development Study 1958, purpose of the 1970 British Cohort study and the Millennium Cohort Study 2000 and now have the Next Steps cohort in their portfolio. (BCS70). The Centre for Longitudinal Studies (CLS) is an Economic and Social Research Council (ESRC) Centre, based at the Department of Quantitative Social Science, UCL Institute of Education. It is responsible for three of Britain's internationally renowned birth cohort studies, the 1958 National Child Development Study, the 1970 British Cohort Study and the Millennium Cohort Study (MCS). All these studies are 'birth' studies, following the groups of participants from cradle to grave. As such, this group of studies is unique and has, and still is, providing a wealth of information used in the policy decisions affecting society's health and well-being. [2 paragraphs unchanged] It was not for another 5 years that it was decided that [76 words unchanged] 2004/5, 2008 2012, 2016. The Age 50 survey commenced in January 2020 but is currently where it was paused due to the impact of the COVID-19 pandemic. It is expected to re-commence pandemic, but re-commenced in early 2021. Subsequent sweeps sweeps* of the study will likely take place every five years. During the 2012 survey, CLS obtained informed consent from cohort members for their health data to be linked to the data collected in the study. In total consent was obtained from 6,181 cohort members who at the time were in England. *The term sweep is used to refer to a round of data collection in the longitudinal study. Linking health data from Hospital Episodes Statistics (HES) to the Next Steps survey data has greatly increased the possibilities for using the cohort to study how health outcomes impact on the individual and aspects of their life such as work, relationships and family life and, likewise, how health outcomes relate to the individual behaviours and lifestyles choices such as drug and alcohol use, sexual health, diet and exercise, which are all documented as part of the study. The successful inclusion of HES data has enriched these data by revealing which cohort members have been admitted to or attended hospital and the reasons for this, e.g. drug and alcohol treatment, accident and emergency, maternity and mental health services which have helped CLS better understand how health conditions could be better treated or supported. This Agreement sets out three distinct elements for which relevant information is subsequently given for each: Data about health behaviours are more accurate when obtained from administrative records because of misreporting of complex health conditions, under-reporting of health problems or due to perceived sensitivities around certain behaviours and lifestyle choices. So, this offers an interesting methodological opportunity to validate the data collected in the survey and vice versa. 1) The CLS will receive linked data for the cohort and will use that data to validate, enhance and improve the quality of the cohort data, in this way creating a uniquely rich administrative/survey-linked data set. At this stage the aim of the researchers is to; The following NHS England data will be accessed, 1. Validate and improve the quality of the cohort data • Hospital Episode Statistics 2. Produce methodological papers describing the quality of the data and its benefit to health and social care o Admitted Patient Care 3. Develop and create a useful and rich HES linked (Age 42) BCS70 data set o Accident & Emergency 4. Advance learning in the research community by providing access to the linked NHS Digital HES / CLS BCS70 data to the research community via the UK Data Service (UKDS) Secure Lab, through a sub-licensing agreement agreed between CLS and NHS Digital. o Critical Care THE SUB-LICENCE: o Outpatients CLS are permitted to include onward sharing of the linked HES and Next Steps data with the UK Data Service (UKDS), where data can be accessed by accredited researchers in a Secure Research Environment, known as Secure Lab, following a “Sub-licensing model”. • Emergency Care Data Set (ECDS) The UKDS is funded by the Economic and Social Research Council (ESRC) with contributions from the University of Essex, the University of Manchester and Jisc (Jisc is a United Kingdom not-for-profit company whose role is to support post-16 and higher education, and research, by providing relevant and useful advice, digital resources and network and technology services, while researching and developing new technologies and ways of working). The UKDS provides access to high-quality data to meet the data needs of researchers, students and teachers from all sectors including academia and central and local government. Linking health data from Hospital Episodes Statistics (HES)/Emergency Care Data Set (ECDS) to the BCS70 survey data has greatly increased the possibilities for using the cohort to study how health outcomes impact the individual and aspects of their life such as work, relationships and family life and, likewise, how health outcomes relate to the individual behaviours and social or economic determinations of health behaviours such as drug and alcohol use, sexual health, diet and exercise, which are all documented as part of the study. The UKDS is based at, and hosted by, the University of Essex. Although the researchers at the UKDS are substantively employed by the University of Essex, only staff who are permitted to work at the UKDS will access the data. The successful inclusion of HES/ECDS data has enriched these data by revealing which cohort members have been admitted to or attended hospital and the reasons for this - e.g. drug and alcohol treatment, accident and emergency, maternity and mental health services which have helped CLS better understand how health conditions could be better treated or supported. Under the “Sub-licensing model”, NHS Digital shares data with CLS, who are in turn licensed to share these data with other organisations, subject to agreed controls, scoped in this agreement between NHS Digital and UCL. In line with this onward sharing model, the data sharing controls in place between NHS Digital and CLS are replicated between CLS and the other organisations. UCL, which houses CLS at the UCL Institute of Education, is fully accountable for the actions of the parties involved in subsequent data share and use. The agreement mirrors the Data Sharing Framework Contract in place between NHS Digital and UCL. It also requests information about the research proposal, benefits to health and/or social care, organisational security assurance and terms and conditions regarding onward sharing of data, responsibilities and processing activities etc. Data about health behaviours are more accurate when obtained from administrative records because of misreporting of complex health conditions, under-reporting of health problems or due to perceived sensitivities around certain behaviours and social or economic determinations of health. This offers an interesting methodological opportunity to validate the data collected in the survey and vice versa. Under the sub-licensing model CLS will deposit the linked data with UK Data Service, who will serve as a data repository. Access to the deposited data will be granted to approved researchers within a Secure Research Environment on behalf of CLS, as outlined in this document. NHS Digital will retain the ability to directly audit UKDS’s compliance with the outlined and agreed data access arrangements. The level of data required is identifiable - necessary to enable linkage of the data with data collected from other sources, including the participants themselves. There will be no charge applied to Licence supplied by CLS. The data will be minimised as follows: The territory of use in the sub-licence will be the same or narrower than the territory of use stated in this DSA, namely UK. - Limited to a study cohort of approximately 6,902. Of these, UCL only linked those members of the cohort who gave their permission to add information from health records held by the NHSE during the 2012 Age 42 Survey. In this sharing model of the linked data, CLS will be a data controller, determining the purposes for which and the manner in which the linked data are processed. The UKDS will be the data processor, as they will be processing the data on behalf of CLS. This includes holding the linked data in a secure environment, screening for completeness of applications for data access, providing training for use of linked data securely, entering into contractual agreements with approved researchers, extraction of approved data and setting up access systems, and approving statistical outputs, following a statistical disclosure control procedure. 2) The CLS will use this data set to produce methodological papers on the quality of the data (e.g. around measurement, and representativeness) and research papers helping to showcase its benefits for healthcare, adult social care, or the promotion of health. The approved organisations and researchers, who are granted an access to the linked data via the UKDS Secure Lab, agree to terms and conditions of use, their rights and responsibilities as users of the linked data, as defined by the UKDS. In addition to the agreements signed with the UKDS, the organisation of the researcher applying to use the linked data will enter into a Licence agreement with UCL. Access will be restricted to CLS researchers who meet the following requirements: ORGANISATIONAL AGREEMENTS i. The researcher must be substantively employed in the CLS by UCL; CLS will provide a sub-licence to UK organisations undertaking research that will be of benefit to the public (this will be assessed in the project proposal form submitted to the UKDS and to CLS). Applicants (potential licencees) will need to show in Schedule 1 Section 18 (a) and (b) that the provision of the sub licencing will be in the public interest and that that the data will be used either (i) for the provision of health care or adult social care; or (ii) for the promotion of health. CLS will not provide data access to commercial organisations for research for commercial purposes. Additionally, the CLS Licence agreement, Schedule 1 Section 18, will assess the project proposal against its assessment criteria to determine the details of the project, the people who will be accessing the data, and what the data will be requested. Applicants will need to be accredited researchers or agree to undertake training and become accredited, prior to accessing the data. Additionally, applicant’s organisation will need to provide evidence that they have IG and security assurances in place (covered in Schedule 1, Section 15 of the CLS Licence agreement). Members of the CLS Data Access Committee (DAC) will review and decide if the evidence provided satisfy the criteria requirements. ii. The researcher must have completed NHS England’s Data Security Awareness course; Applicants (licencees) and their organisations will have to sign two agreements to obtain a sub-licence, one with the UKDS and another with CLS, in both cases the licencee will agree with the terms stated in the Confidentiality Section of the CLS Licence Agreement and with the Confidentiality Terms stated in the Secure Access Agreement which will be signed with the UKDS. By signing these agreements the licencee agrees to adhere to these terms, including respecting the privacy of health services users data they will receive. Licencees are also be reminded of the penalties they are likely to incur if they do not comply with the terms they have agreed. In addition to the above, the UKDS agreement stipulates that data users must complete mandatory training before they are allowed to access the data. iii. The researcher must have submitted a project proposal for review by the CLS Data Access Committee (DAC) and the CLS DAC must have approved the access request; To ensure the security of the linked information, shared with CLS by NHS Digital, and subsequently shared by CLS with the UKDS, where data could be accessed by approved researchers in a Secure Lab, CLS envisage the following controls employed at the different steps of the process of depositing, approving and sharing of the linked information: iv. Once, approved, the researcher will sign a licence agreement with CLS and will then be granted access to the relevant subset of data via the UCL Data Safe Haven (DSH). • An agreement between NHS Digital and CLS to onwardly share linked HES and CLS information under “Sub-licencing model”, which outlines the terms and conditions of use of the linked data via the UKDS Service Secure Lab as the data repository, and the full accountability of UCL (housing CLS at the UCL Institute of Education) to the actions of the parties involved in subsequent access to the linked data. The level of data required is pseudonymised. • An agreement between CLS (as a data controller) and UKDS (as a data processor), which outlines the terms and conditions under which the linked data can be accessed via the UKDS Secure Lab. The data will be minimised to variables and potential cases relevant to the purpose. • An agreement between UKDS and the approved researcher, which outlines the terms and conditions of use of the linked data in the UKDS’s Secure Lab. 3) The CLS will promote and make possible wider use of this linked data set, through providing wider access to the linked NHS England HES / CLS BCS70 data to the research community via the UK Data Service (UKDS) Secure Lab under sublicensing agreements subject to the following access arrangements. • An Agreement between UCL and the organisation requesting to use the linked data via the UKDS, which outlines the terms and conditions of use of the linked data. With the exception of individuals substantively employed by UCL in the CLS, all other access will be via the UKDS only. Access to the data via the UKDS will only be granted to third party researchers who meet the following requirements: i. The researcher must be registered with the UKDS; ii. The researcher must successfully apply for approval by the CLS DAC via the process outlined below. The process for applying for approval is as follows: i. The researcher submits an application, including an 'Accredited Researcher application form' and 'Research proposal', to the UKDS. ii. The UKDS screens the application and either rejects or forwards the application to the CLS at UCL. iii. The CLS checks the organisational Information Governance and security assurance evidence provided and either requests further evidence, if the evidence of provided does not meet the requirements (as outlined in the sub-licence), or submits the application for CLS DAC approval. iv. The CLS DAC assesses both project documents (UKDS project proposal and the “UCL Licence agreement”) and makes a decision to approve it, not approve it, or require further information. CLS DAC considerations include an assessment of the expected benefits to health care, adult social care or the promotion of health. Should an application be rejected, a researcher can apply again with a revised application. v. If the CLS DAC approves the project: a. CLS informs UKDS that the project has been approved. b. The CLS authorised representative signs the “UCL License agreement” and sends it back to the UKDS to be forwarded to the researcher. vi. UKDS informs the researcher that their project was approved; sends them a countersigned copy of the “UCL Licence agreement’ and makes the data available to them via Secure access to linked data at the Safe Centre at the UKDS (hosted at the University of Essex) or via the researcher's own institutional desktop PC, depending on the sensitivity/impact level of the data being requested. The agreement with the UKDS is signed at the point of deposit of the data. The data manager will prepare the data for deposit and as part of the depositing of the data, the Deposit Licence agreement is signed. vii. CLS DAC will publish the information about any data dissemination on the CLS website, including the name of the organisation to which data was provided, purpose (summary of the project) and what data was released. (NB: If CLS DAC does not approve the project, no data will be disseminated). The data will be provided to the researcher via their own project folder, which will contain only the data that the researcher needs to see for their project. The research-linked data provided to researchers are pseudonymised and de-identified, and will never contain identifiable information such as name, address, date of birth, NHS or NI number. [1 paragraph unchanged] The data held at CLS will be deleted if the data sharing agreement between NHS Digital and CLS were to cease. If it were to cease, the license agreement between CLS and the licensee organisation will be terminated. Disclosure control checks are carried before any research publication. UCL legal basis for processing (acquiring, linking and sharing) personal data is for a public task under GDPR (article 6(1)(e)) i.e. processing is necessary for the performance of a task carried out in the public interest (as is made explicit to participants in the information leaflets provided). UCL also process special categories of personal data for research under GDPR (article 9(2)(j)) i.e. processing is necessary for archiving purposes in the public interest, scientific or historical research purposes or statistical purposes. In addition, for ethical reasons and under the Common Law Duty of Confidentiality, CLS sought permission from cohort members to access and link their routine health records to their survey data, and to the onward sharing of this linked data in pseudonymised form (via a secure setting with appropriate safeguards). The data sharing controls in place between NHS England and UCL are replicated between UCL and the other organisations. UCL, which houses CLS at the UCL Institute of Education, is fully accountable for the actions of the parties involved in subsequent data share and use. The UCL Licence agreement mirrors the Data Sharing Framework Contract in place between NHS England and UCL. All data processed under the sub-license will be completed using the same legal basis as mentioned above, namely GDPR (article 6(1)(e))and GDPR (article 9(2)(j)). The CLS Licence agreement will require licencees to provide the Legal Basis of their request to link health data via CLS and therefore CLS Data Access Committee (DAC) will only grant approval to applications from researchers within public bodies who have a legal basis to process data under GDPR. There will be no charge applied to licenses supplied by UCL. The data disseminated to CLS will be accessed by substantive employees of UCL who will work on the data to make it research ready, will pseudonymise the data and deposit it at the UKDS for researchers applying to use for specific projects. The pseudonymised data will also be accessed by CLS employees to conduct methodological and research work via the UCL Data Safe Heaven. NHS England will retain the ability to directly audit UKDS's compliance with the outlined and agreed data access arrangements. Access to the deposited data can be remote access via the secure lab or physically present at UKDS, depending on which environment is more suitable for the researcher. The anticipated volume / number of Licenses is 1-2 sub-licences per month. Sub-licences shall not exceed a term of 12 months at a time and may be extended/renewed if appropriate. The sub-licences remain valid only while UCL retains the right to hold and share the data from NHS England. The territory of use in the sub-licence will be the same or narrower than the territory of use stated in this data sharing agreement, namely the UK. The UKDS (hosted by University of Essex) is a processor acting under the instructions of UCL. UKDS’ role is limited to holding the linked data in a secure environment; screening for completeness of applications for data access; providing training for use of linked data securely; entering into contractual agreements with approved researchers; extraction of approved data and setting up access systems, and approving statistical outputs, following a statistical disclosure control procedure. UCL will maintain an agreement with UKDS which outlines the terms and conditions under which the linked data can be accessed via the UKDS Secure Lab. UCL will not provide data access to commercial organisations for research or for commercial purposes. UCL is the controller as the organisation responsible for ensuring that the data will only be processed for the purpose described above. The lawful basis for processing personal data under the UK GDPR is Article 6(1)(e) - processing is necessary for the performance of a task carried out in the public interest or in the exercise of official authority vested in the controller; The lawful basis for processing special category data under UK GDPR is Article 9(2)(j) processing is necessary for archiving purposes in the public interest, scientific or historical research purposes or statistical purposes. In addition, for ethical reasons and under the Common Law Duty of Confidentiality, UCL sought permission from cohort members to access and link their routine health records to their survey data, and to the onward sharing of this linked data in pseudonymised form (via a secure setting with appropriate safeguards). The funding is provided by the Economic and Social Research Council. The University of Essex is a processor acting under the instructions of UCL. The University of Essex hosts the UKDS and their role is limited to storing the linked pseudonymised data and facilitating access to third-party researchers who have the necessary approvals from the CLS DAC and an active sublicense agreement with UCL. Only staff who are permitted to work at the UKDS (and are substantively employed by the University of Essex) will process the data. Should any substantively employed researchers from the University of Essex wish to use the UKDS data, they will be required to apply via the sub-licence route, the same as other researchers from other organisations. Amazon Web Services (AWS) is a processor acting under the instructions of UCL. AWS’ role is limited to secure back-up of data stored in UCL’s Data Safe Haven. UCL uses offsite data centre services provided by VIRTUS data centre. VIRTUS does not have access to the data. The UKDS is funded by the Economic and Social Research Council (ESRC) with contributions from the University of Essex, the University of Manchester and Jisc (Jisc is a United Kingdom not-for-profit company whose role is to support post-16 and higher education, and research, by providing relevant and useful advice, digital resources and network and technology services, while researching and developing new technologies and ways of working). The UKDS provides access to high quality data to meet the data needs of researchers, students and teachers from all sectors including academia and central and local government.

Processing activities

No further data is being requested and no data is being sent to NHS Digital under this version of the Agreement. The CLS Team is based at UCL. The CLS UCL will transfer data to NHS England. The data will consist of identifying details (specifically NHS Number, Date of Birth, full name, Postcode, Sex and a unique person ID) for the cohort to be linked with NHS England data. 1. CLS team have supplied NHS Digital with identifiers of cohort members who have consented to this data linkage, including full name, sex, postcode, date of birth, NHS number (if known) and study ID (study-specific pseudonymised identifier). NHS England data will provide the relevant records from the HES and ECDS datasets to UCL. The data will contain no direct identifying data items but will contain a unique person ID which can be used to link the data with other record level data already held by the recipient. 2. NHS Digital have linked the identifiable study data to HES data. NHS Digital have removed identifiers from linked dataset and returned the pseudonymised dataset to the CLS team at UCL with the study ID. The CLS will carry out validation of the administrative pseudonymised data received (linked HES/ECDS data) and combined the supplied administrative data with the information collected from the participant as part of the BCS70 study using the study ID. 3. CLS carried out validation of the administrative pseudonymised data received (linked HES data) and combined the supplied administrative data with the information collected from the participant as part of the Next Steps study using the study ID. Once the linked survey-administrative data files have been created, the CLS may perform other activities to prepare the data for use, such as coding and cleaning, derivation of summary variables and compilation of data documentation. Once the linked survey-administrative data files have been created, CLS may perform other activities to prepare the data for use, such as coding and cleaning, derivation of summary variables and compilation of data documentation. The CLS will use these data to create an analysis file which does not contain any identifiable data. 4. CLS researchers used these data to create an analysis file, which do not contain any identifiable data. The CLS creates derived variables that summarise study members’ hospitalisation and health histories (e.g. hospital admissions and re-admissions, incidence of common diseases, children’s ailments etc.) and compare BCS70 survey data with data from hospital statistics in order to compare and validate the data collected in CLS surveys. 5. CLS created derived variables that summarise study members’ hospitalisation and health histories (e.g. hospital admissions and re-admissions, incidence of common diseases, children’s ailments etc.) and compare Next Steps survey data with data from hospital statistics, in order to compare and validate the data collected in CLS surveys. The CLS will securely transfer the analysis file to the UKDS (hosted by University of Essex). Identifiers are held separately from attribute characteristics. HES data is not be relinked to the identifiable data which is held separately from the survey responses. Re-identification will only happen at the occasion of a request, made from a cohort member, for withdrawal from the study, and this includes removal of data. Where a participant wishes to withdraw from the study, the identifiable data is used to locate the study id, and then in turn destroy their data. The data will be stored on servers at both UCL and the UK Data Archive based at the University of Essex. The UK Data Archive will store the pseudonymised analysis file only. Addition of the sub-licence: Amazon Web Services provides cloud hosting services to UCL and will store the data as contracted by UCL. The process of accessing the linked data via the UKDS Service Secure Lab include the following steps: The data will be accessed by authorised personnel via remote access. The data will remain on the servers at UCL, AWS and the University of Essex at all times. • Registration with the UKDS Service. Personnel are prohibited from downloading or copying data to local devices. • Submission of an application, including an ‘Accredited Researcher application form’ and ‘Research proposal’. The data will not leave the UK at any time. • Screening of application by UKDS for completeness. Access is restricted to authorised individuals within the CLS at UCL, individuals employed by the UK Data Archive at the University of Essex and access to appropriately minimised subsets of the pseudonymised analysis file will be granted to authorised third parties under sublicense. Once a researcher has registered and UKDS has screened / approved the application: All personnel accessing the data have been appropriately trained in data protection and confidentiality. 1) UKDS sends project proposal (researcher application forms) to CLS-UCL (for Data Access Committee (DAC) approval). Applicants are required to demonstrate they have security assurance in place (System Level Security Policy/ISO Certificate/DSPT). CLS does not link HES/ECDS data to any other dataset. However, when a researcher accesses the pseudonymised data via the UKDS, they may wish to access this data in combination with other pseudonymised datasets which are also available at the UKDS. If a researcher wishes to use the data in combination with other datasets they may do so by using the two datasets together in a secure environment. However, they will need to explicitly mention this in their application to CLS and will only be permitted if CLS DAC approves the project proposal. 2) CLS-UCL sends the CLS License Agreement for Linked NHS Digital data to researchers to be completed and signed by their organisation (this includes the benefits to health and social care and evidence of organisational security assurances) not covered by UKDS application. At UCL, identifiers will be held separately from attribute characteristics. HES/ECDS data will not be relinked to the identifiable data which is held separately from the survey responses. Re-identification will only happen at the occasion of a request, made from a cohort member, for withdrawal from the study, and this includes removal of data. Where a participant wishes to withdraw from the study, the identifiable data is used to locate the study ID and then in turn destroy their data. 3) Researcher/their organisation representative will send the CLS License Agreement for Linked NHS Digital completed and signed back to CLS-UCL. UCL only request data for those individuals who have given consent to link their health records to their survey data. Before preparing the file to be sent to NHS England, for the matching of consenting participants to the NHS England HES/ECDS datasets, the data manager will check for withdrawals and will remove participants who- 4) CLS-UCL will: a) check the organisational Information Governance and security assurance evidence provided as per Section 15 Organisational Security Assurance of the CLS Licence agreement, b) send the project for CLS DAC approval. · Have asked CLS to withdraw their consent to health data linkage 5) Should evidence of organisational Information Governance and security assurance provided not meet the requirements (as outlined in the sub-license) CLS will request the applicant to provide further evidence, and will only submit the project to CLS DAC for approval when evidence provided is satisfactory. Approval for data access will only be granted to applicant organisations that meet the security assurance requirement. · Have asked CLS to delete their data 6) CLS DAC will assess both documents (UKDS project proposal + CLS Licence agreement) and make a decision to approve it or not approve it or require further information. Should an application be rejected, a researcher can apply again with a revised application. The file will only contain details of those who consented to their health data being linked to BCS70 study data and have not subsequently withdrawn their consent or requested that their data be deleted. 7) In the CLS License agreement, CLS DAC will, among other things assess the benefits for health and social care statement, and decide whether it is satisfied with the answer. The HES/ECDS data provided by NHS England, which are linked to the CLS cohort members, are processed by the CLS data management team to minimise the risk of disclosure when linked to the CLS survey data. This is achieved by removing highly identifiable variables and altering other variables by top-coding or truncating them. 8) Once CLS DAC approves the project : The data provided to the UK Data Archive will be pseudonymised and will be accessed only via the UKDS secure lab. Data accessed in this way cannot be downloaded. This means that researchers will have access to a screen view only and it is not possible to remove data from the environment. Once researchers and their projects are approved, they can analyse the data remotely from their organisational desktop, or by using the UKDS Safe Room. Specialised staff will apply statistical control techniques to ensure the delivery of safe statistical results. a) CLS will inform UKDS that project has been approved. Only staff who are permitted to work at the UKDS (and are substantively employed by University of Essex) will process the data for sub-licensing. Note that any data accessed through the UKDS Secure Lab can only be accessed under secure conditions and cannot be downloaded. The linked data provided to approved researchers may be subject to sub-setting of variables (and, if necessary, cases) to minimize disclosure risks and ensure that no individual or organisation can be identified from the results. In addition, all statistical outputs are subject to statistical disclosure control procedure. Access to the Secure Lab is only available to researchers who are based at a UK academic institution or an ESRC-funded research centre and are an ESRC Accredited Researchers. PhD and research students can request access but must apply jointly with their supervisors from established organisations. b) CLS representative should sign the CLS License agreement noting the DAC reference number on the License document and send it back to the organisation of the applicant (the Principal Investigator for the study requiring access will sign the agreement - they will be an authorised signatory for their organisation). c) CLS DAC will provide information about any data dissemination to NHS Digital, including the name of the organisation to which data was provided, purpose (summary of the project) and what data was released. (NB. If CLS DAC doesn't approve the project, no data will be disseminated). 9) If CLS DAC is not satisfied with the evidence provided by the applicant about the benefits to health and social care, then CLS DAC can ask the applicant to provide additional information and the project can be re-submitted for CLS DAC approval on the next CLS DAC meeting or via Chair approval. 10) UKDS will inform the researcher that their project was approved and make the data available to them via Secure access to linked data at the Safe Centre at the UK Data Service (hosted at the University of Essex) or via the researcher’s own institutional desktop PC, depending on the sensitivity/impact level of the data being requested . Note that any data accessed through the UKDS Secure Lab can only be accessed under secure conditions and cannot be downloaded. The linked data provided to approved researchers may be subject to sub-setting of variables (and if necessary cases) to minimize disclosure risks and ensure that no individual or organisation can be identified from the results. In addition, all statistical outputs are subject to statistical disclosure control procedure. Access to the Secure Lab is only available to researchers who are be based at a UK academic institution or an ESRC-funded research centre and be an ESRC Accredited Researcher. PhD and research students can request access but must apply jointly with their supervisors from established organisations. [1 paragraph unchanged] UKDS SECURE DATA HANDLING PROCEDURES The UKDS home working policy does not involve Bring your own device (BYOD). Researchers applying to use the data (stored at the UKDS Secure lab) remotely from home, will only be given permission to access the data if they agree that they will use their work organisation office computer remotely and from there access to the Secure lab. The UK Data Service has received government technical accreditation and has been certified for its secure data handling procedures under the international standard for information security (ISO 27001). To maintain this certification, regular internal and external audits are undertaken. UKDS also hires a government-approved company to conduct internal and external penetration testing of its Secure Lab systems. The data can be accessed by authorised CLS personnel via remote access on UCL-issued devices from their work organisation office or from home. The data will always remain on the servers at UCL CLS. Personnel are prohibited from downloading or copying data to local devices. More widely, the UKDS employs an Information Security Management System (ISMS), to ensure compliance with the ISO accreditation. The Secure Lab falls into this system, and a number of documented processes are regularly maintained and reviewed to ensure these processes are robust, relevant, and fit-for-purpose. The ISMS is overseen by an Information Security Management Group (ISMG), which regularly meets and approves changes to procedures. UKDS DATA ACCESS MECHANISMS As an ESRC resource centre, CLS shares its survey data with the research community via the UKDS under safeguarded or controlled access mechanisms, dependent on the likelihood and potential impact of disclosure. Data with higher risk of disclosure is treated with an appropriate degree of security and management. CLS data fall into the following categories, which are defined by the likelihood and potential impact of disclosure: • Tier 1: data with low level of disclosure: e.g. participant self-reported survey data. These data are made available through the UKDS End User Licence and have a low impact of disclosure; • Tier 2a: data that is potentially disclosive: e.g. medium level and coarse geographies or sensitive information about cohort members. These data are made available through the UKDS Special Licence and have a medium impact of disclosure; • Tier 2: data that are too detailed, sensitive or confidential to be made available under the standard End User Licence or Special Licence, such as detailed geographical indicators or fine-grained individual level linked data. These data have a high impact of disclosure and are made available through the UKDS Secure Access. Access mechanisms to NHS Digital HES data linked to CLS cohort studies via the UKDS The HES data provided to CLS by NHS Digital, which are linked to the CLS cohort members, have been processed by the CLS data management team to minimise the risk of disclosivity when linked to the CLS survey data. This has been achieved by removing highly identifiable variables and altering other variables by top-coding or truncating them. Following this processing, the final health data sets have been classified under Tier 2. It is therefore CLS’s intention to deposit these Tier 2 linked HES data with the UK Data Service under the UKDS Secure Access, and provide access to this information for approved researchers, following the process and contractual arrangements, outlined above and described in more detail below, following an agreed between NHS Digital, CLS and UKDS onward sharing model. The UKDS’s ‘Controlled access to data’ specification is supplied to NHS Digital as part of this application amendment. The data provided will be pseudonymised and will be accessed only via the UKDS secure lab. Downloading the data is not possible. All organisations party to this agreement must comply with the Data Sharing Framework Contract requirements, including those regarding the use (and purposes of that use) by “Personnel” (as defined within the Data Sharing Framework Contract ie: employees, agents and contractors of the Data Recipient who may have access to that data). No further data is being requested and no data is being sent to NHS Digital under this version of the Agreement. 1. CLS team have supplied NHS Digital with identifiers of cohort members who have consented to this data linkage, including full name, sex, postcode, date of birth, NHS number (if known) and study ID (study-specific pseudonymised identifier). 2. NHS Digital have linked the identifiable study data to HES data. NHS Digital have removed identifiers from linked dataset and returned the pseudonymised dataset to the CLS team at UCL with the study ID. The data disseminated to UCL will be accessed by substantive employees of UCL who have been appropriately trained in data protection and confidentiality. The data will be held at the secure server in the UCL Data Safe Haven (DSH) and accessed remotely by CLS staff. 3. CLS carried out validation of the administrative pseudonymised data received (linked HES data) and combined the supplied administrative data with the information collected from the participant as part of the Next Steps study using the study ID. Once the linked survey-administrative data files have been created, CLS may perform other activities to prepare the data for use, such as coding and cleaning, derivation of summary variables and compilation of data documentation. 4. CLS researchers used these data to create an analysis file, which do not contain any identifiable data. 5. CLS created derived variables that summarise study members’ hospitalisation and health histories (e.g. hospital admissions and re-admissions, incidence of common diseases, children’s ailments etc.) and compare Next Steps survey data with data from hospital statistics, in order to compare and validate the data collected in CLS surveys. Identifiers are held separately from attribute characteristics. HES data is not be relinked to the identifiable data which is held separately from the survey responses. Re-identification will only happen at the occasion of a request, made from a cohort member, for withdrawal from the study, and this includes removal of data. Where a participant wishes to withdraw from the study, the identifiable data is used to locate the study id, and then in turn destroy their data. Addition of the sub-licence: The process of accessing the linked data via the UKDS Service Secure Lab include the following steps: • Registration with the UKDS Service. • Submission of an application, including an ‘Accredited Researcher application form’ and ‘Research proposal’. • Screening of application by UKDS for completeness. Once a researcher has registered and UKDS has screened / approved the application: 1) UKDS sends project proposal (researcher application forms) to CLS-UCL (for Data Access Committee (DAC) approval). Applicants are required to demonstrate they have security assurance in place (System Level Security Policy/ISO Certificate/DSPT). 2) CLS-UCL sends the CLS License Agreement for Linked NHS Digital data to researchers to be completed and signed by their organisation (this includes the benefits to health and social care and evidence of organisational security assurances) not covered by UKDS application. 3) Researcher/their organisation representative will send the CLS License Agreement for Linked NHS Digital completed and signed back to CLS-UCL. 4) CLS-UCL will: a) check the organisational Information Governance and security assurance evidence provided as per Section 15 Organisational Security Assurance of the CLS Licence agreement, b) send the project for CLS DAC approval. 5) Should evidence of organisational Information Governance and security assurance provided not meet the requirements (as outlined in the sub-license) CLS will request the applicant to provide further evidence, and will only submit the project to CLS DAC for approval when evidence provided is satisfactory. Approval for data access will only be granted to applicant organisations that meet the security assurance requirement. 6) CLS DAC will assess both documents (UKDS project proposal + CLS Licence agreement) and make a decision to approve it or not approve it or require further information. Should an application be rejected, a researcher can apply again with a revised application. 7) In the CLS License agreement, CLS DAC will, among other things assess the benefits for health and social care statement, and decide whether it is satisfied with the answer. 8) Once CLS DAC approves the project : a) CLS will inform UKDS that project has been approved. b) CLS representative should sign the CLS License agreement noting the DAC reference number on the License document and send it back to the organisation of the applicant (the Principal Investigator for the study requiring access will sign the agreement - they will be an authorised signatory for their organisation). c) CLS DAC will publish the information about any data dissemination on the NHS Digital release register, including the name of the organisation to which data was provided, purpose (summary of the project) and what data was released. (NB. If CLS DAC doesn't approve the project, no data will be disseminated). 9) If CLS DAC is not satisfied with the evidence provided by the applicant about the benefits to health and social care, then CLS DAC can ask the applicant to provide additional information and the project can be re-submitted for CLS DAC approval on the next CLS DAC meeting or via Chair approval. 10) UKDS will inform the researcher that their project was approved and make the data available to them via Secure access to linked data at the Safe Centre at the UK Data Service (hosted at the University of Essex) or via the researcher’s own institutional desktop PC, depending on the sensitivity/impact level of the data being requested . Note that any data accessed through the UKDS Secure Lab can only be accessed under secure conditions and cannot be downloaded. The linked data provided to approved researchers may be subject to sub-setting of variables (and if necessary cases) to minimize disclosure risks and ensure that no individual or organisation can be identified from the results. In addition, all statistical outputs are subject to statistical disclosure control procedure. Access to the Secure Lab is only available to researchers who are be based at a UK academic institution or an ESRC-funded research centre and be an ESRC Accredited Researcher. PhD and research students can request access but must apply jointly with their supervisors from established organisations. No further onward sharing can occur beyond the sub-licence. UKDS SECURE DATA HANDLING PROCEDURES The UK Data Service has received government technical accreditation and has been certified for its secure data handling procedures under the international standard for information security (ISO 27001). To maintain this certification, regular internal and external audits are undertaken. UKDS also hires a government-approved company to conduct internal and external penetration testing of its Secure Lab systems. More widely, the UKDS employs an Information Security Management System (ISMS), to ensure compliance with the ISO accreditation. The Secure Lab falls into this system, and a number of documented processes are regularly maintained and reviewed to ensure these processes are robust, relevant, and fit-for-purpose. The ISMS is overseen by an Information Security Management Group (ISMG), which regularly meets and approves changes to procedures. UKDS DATA ACCESS MECHANISMS As an ESRC resource centre, CLS shares its survey data with the research community via the UKDS under safeguarded or controlled access mechanisms, dependent on the likelihood and potential impact of disclosure. Data with higher risk of disclosure is treated with an appropriate degree of security and management. CLS data fall into the following categories, which are defined by the likelihood and potential impact of disclosure: • Tier 1: data with low level of disclosure: e.g. participant self-reported survey data. These data are made available through the UKDS End User Licence and have a low impact of disclosure; • Tier 2a: data that is potentially disclosive: e.g. medium level and coarse geographies or sensitive information about cohort members. These data are made available through the UKDS Special Licence and have a medium impact of disclosure; • Tier 2: data that are too detailed, sensitive or confidential to be made available under the standard End User Licence or Special Licence, such as detailed geographical indicators or fine-grained individual level linked data. These data have a high impact of disclosure and are made available through the UKDS Secure Access. Access mechanisms to NHS Digital HES data linked to CLS cohort studies via the UKDS The HES data provided to CLS by NHS Digital, which are linked to the CLS cohort members, have been processed by the CLS data management team to minimise the risk of disclosivity when linked to the CLS survey data. This has been achieved by removing highly identifiable variables and altering other variables by top-coding or truncating them. Following this processing, the final health data sets have been classified under Tier 2. It is therefore CLS’s intention to deposit these Tier 2 linked HES data with the UK Data Service under the UKDS Secure Access, and provide access to this information for approved researchers, following the process and contractual arrangements, outlined above and described in more detail below, following an agreed between NHS Digital, CLS and UKDS onward sharing model. The UKDS’s ‘Controlled access to data’ specification is supplied to NHS Digital as part of this application amendment. The data provided will be pseudonymised and will be accessed only via the UKDS secure lab. Downloading the data is not possible. All organisations party to this agreement must comply with the Data Sharing Framework Contract requirements, including those regarding the use (and purposes of that use) by “Personnel” (as defined within the Data Sharing Framework Contract ie: employees, agents and contractors of the Data Recipient who may have access to that data). CLS researchers who need to access the data to produce methodological papers on the quality of the data (eg around measurement, representativeness) and research papers helping to showcase its benefits for health and social care will need to submit an application to CLS DAC detailing their project proposal. Upon DAC approval, a pseudonymised dataset will be provided to the researcher. The data will be held at the secure server in the UCL Data Safe Haven (DSH). The UCL DSH is certified to ISO 27001:2013 and is compliant with NHS Digital's Data Security and Protection Toolkit. Research teams using the DSH complete annual training and regularly review data access arrangements ensuring data is only limited to those authorised to access it. UCL Computing Regulations are based on the premise that access to resources is generally forbidden unless expressly permitted. All data transfers from the DSH require approval and are carried out through secure portals which are fully audited. Access to the UCL DSH is via remote desktop and requires multi-factor authentication. In addition to a strong password each user has to use a six digit number generated by a smartphone app or physical token at each login. Passwords must be changed at regular intervals, and unused accounts are automatically disabled after a fixed period. Once inside the environment, robust access control ensures that researchers can only examine information that they are approved to use.

Expected output

The Following the data quality and validation work, the first output, output will be the creation addition of the refreshed data to the existing linked BCS70/HES dataset, NCDS/HES dataset which is now available for researchers to apply. The most recent HES data requested in under this application Agreement will refresh this already rich linked dataset. CLS and the UKDS will publicise the data release at both on the CLS and UKDS websites. website. CLS has not yet sub-licenced the available BCS70/HES data as CLS only recently got permission for sub-licensing this data. CLS has recently delivered a webinar to introduce this dataset to researchers and hope to start receiving applications soon. A first application to use the data is currently in progress, details are provided below: The second output will be a methodological paper titled: “Examining the linkage quality and sample representativeness of the linked 1970 British Cohort Study”. This is planned to be published by the end of 2024. The target journals for publication are : Project Title: 'Linkage of National Longitudinal Cohort Studies and Administrative Data: A Mutually Beneficial Arrangement' 1) Journal for Survey Statistics and Methodology special issue on “Recent Advances in Data Integration” This research will be addressing the following three methodological research questions, which will be directly reflected in the project work packages. 2) Public Opinion Quarterly special issue on “Augmenting Surveys with Paradata, Administrative Data, and Contextual Data” 1. How can linked administrative data aid the handling of missing cohort data? 3) International Journal of Population Data Science 2. How can linked cohort data improve our understanding of the quality of administrative data? In this paper, researchers will examine the quality of the linkage in terms of the associations between key cohort member sociodemographic characteristics and successful linkage, and compare the levels of successful linkage within strata of BCS70 variables which may be expected to be associated with hospital attendance, and hence with successful HES linkage (self-reported hospital attendance, self-rated general health, self-reported long-term illness). The researchers will additionally evaluate the population representativeness of the linked sample using external data (hospital admission rates in the general population). The methodological project above mentioned is currently being carried out for CLS’s other study, the 1958 National Child Development Study (NCDS) and it is near completion. The findings suggest that the linkage quality of the NCDS-HES data is high and that the linked sample maintains an excellent level of population representativeness. Researchers hope that these analyses will both improve the quality and transparency of research using this linked data resource and encourage providers and users of other linked data resources to undertake and publish similarly thorough evaluations. This paper is expected to be published during 2023. 3. How can linked cohort data help address residual confounding in analyses of administrative data CLS has not yet published any methodological papers reviewing the linkage. No papers have been published since earlier versions of this Agreement were approved because CLS have a policy of not using data internally for research when not available to external users and the original approval did not allow CLS to share the data with external users. Thus, CLS have focused on getting the necessary permission for sub-licencing the data. The second output will be methodological papers published in peer reviewed journals reviewing the linkage and validating the data from the two data sources. These methodological assessments are expected to finish two years after obtaining the data. Outputs will contain only aggregate level data with small numbers suppressed in line with HES analysis guide. The UKDS will approve statistical outputs, following a statistical disclosure control procedure and HES analysis guide for the data accessed via the UKDS secure lab. The creation of this refreshed HES/ECDS-BCS70 database including this and the methodological papers are the first steps in establishing a robust research database which will be of benefit to health and social care. CLS has not yet published any methodological papers reviewing the linkage. CLS expects to carry out these methodological and research assessments two/three years after the approval of this extension. This is because CLS have a policy of not using data internally for research when not available to external users and the original approval did not allow CLS to share the data with external users. Thus, CLS have focused on getting the necessary permission for sub-licencing the data. CLS actively promotes the use of their data among the research community through publications and briefings, working papers, webinars, social media, public reports, hosted events, as well as providing extensive documentation, guidance, training and workshops on each data set to help researchers better use the data and so ultimately benefit health and social care. The creation of this HES/BCS70 database and the methodological papers are the first steps in establishing a robust research database which will be of benefit to health and social care. CLS actively promotes the use of their data among the research community through publications and briefings , working papers, webinars, social media, public reports, hosted events, as well as providing extensive documentation, guidance, training and workshops on each data set to help researchers better use the data and so ultimately benefit health and social care.

Expected measurable benefits

The BCS70 surveys include questions relating to health outcomes and hospitalisations. CLS [34 words unchanged] the data quality and comparability of two important data sources. This will help both improve the quality and transparency of research using this linked data resource and encourage providers and users of other linked data resources to undertake and publish similarly thorough evaluations. This will also be of benefit to research looking at health and social care issues which in turn, through time and cost savings will be of benefit to patients. issues. This data linkage will also facilitate research that CLS anticipate will be carried out on the effects [34 words unchanged] as those interfacing with schools through informing policy to improve healthy lifestyles. It is difficult to predict in advance the type of research question that might be put forward. Below are four examples of existing publications using BCS70 data benefiting public health. The CLS have already demonstrated yielded measurable benefits within the Health and Social care system with various studies to date. Whilst a single output is not expected to change healthcare policy or practice. The variety of outputs that are expected are planned to add to the existing body of evidence supporting improvements to healthcare policy and practice in the long term. HAMER, M, KIVIMAKI, M and BATTY, G.D. (2020) Blood Pressure Trajectories in Youth and Hypertension Risk in Adulthood: the 1970 British Cohort Study. American Journal of Epidemiology, 189(2), 162-163. Using the Millennium Cohort Study (MCS), another existing study being researched at the CLS, as an example below are examples highlighting each point, which are expected to be replicated: HAMER, M. and DAVID BATTY, G. (2020) Markers of Early Life Infection in Relation to Adult Diabetes: Prospective Evidence From a National Birth Cohort Study Over Four Decades. Diabetes Care, 43(4), dc192471. 1. CLS researchers have already added to the existing body of evidence supporting various scientific publications. Based on ESRC-supported research and using both Millennium Cohort and Understanding Society data, the Department for Work and Pensions (DWP) has launched a policy initiative aimed at supporting parents/carers and families who experience worklessness and economic disadvantage, with the objective of improving educational attainment and mental health outcomes for children and young people. This policy announcement uniquely recognises young peoples educational attainment and mental health as primary pillars of future employability, and the importance of the longitudinal studies employed to support these conclusions and policy investment HAMER, M., O'DONOVAN, G., DAVID BATTY, G. and STAMATAKIS, E. (2020) Estimated cardiorespiratory fitness in childhood and cardiometabolic health in adulthood: 1970 British Cohort Study. Scandinavian Journal of Medicine & Science in Sports, 30(5), 932-938. recommendations. As an example of longitudinal study data use, the DWP describe: This innovative, research-led policy investment is directing support to front-line professionals aimed at improving educational and mental health outcomes for children whose parents/carers experience worklessness. Proposals based on the findings include: Redefining the Troubled Families Programme “to encourage a greater emphasis on tackling worklessness and issues associated with it”. NORRIS, T, BANN, D, HARDY, R and JOHNSON, W. (2020) Socioeconomic inequalities in childhood-to-adulthood BMI tracking in three British birth cohorts. International Journal of Obesity, 44, 388–398. - Strengthening support to help reduce relationship distress between parents/carers, whether together or separated, announcing an innovative new programme, backed initially by £30 million (April 2017), with an additional 30 million added in the November 2017 Budget Statement. HASSIOTIS, A, BROWN, E, HARRIS, J, HELM, D, MUNIR, K, SALVADOR-CARULLA, L, BERTELLIA, M, BAGHDADLI, M, WIELAND, J, NOVELL-ALSINA, R, CID, J, VERGÉS, L, MARTÍNEZ-LEAL, R, MUTLUER, T, ISMAYILOV, F and EMERSON, E. (2019) Using data from the Millennium Cohort Study (MCS), CLS researchers and collaborators have investigated the prevalence of mental ill-health during childhood and adolescence, up to age 14. Their research has aimed to identify the factors associated with mental ill-health and the groups most at risk and in need of support. In addition, their studies have examined the distinction between poor mental health and poor wellbeing. This research has received widespread public attention and achieved a variety of impacts on policy and practice. Following on from this work, CLS researchers are exploring the prevalence of mental ill-health among the cohort in their mid-teens, using MCS data, collected at age 17. Association of Borderline Intellectual Functioning and Adverse Childhood Experience with adult psychiatric morbidity. Findings from a British birth cohort. BMC Psychiatry, 19, 387. 2. Research evidence used for government briefing papers. DOLAN, P and LORDAN, G. (2019) Climbing Up Ladders and Sliding Down Snakes: An Empirical Assessment of the Effect of Social Mobility on Subjective Wellbeing. IZA Discussion Paper 12519, 12 Aug 2019. CLS academics, wrote accessible briefing papers available on the link below, which were shared with government departments. The extensive media coverage about the research drew huge interest from policymakers, practitioners, parents, and educators. The research rapidly became part of the bloodstream of public discussion of young people’s mental health. EINIO, E, GOISIS, A and MYRSKYLA, M. (2019) Is the relationship between men's age at first birth and midlife health changing? Evidence from two British cohorts. SSM - Population Health, 8, 100458. https://cls.ucl.ac.uk/briefings_impact/ HUANG, B-H, HAMER, M, CHASTIN, S, KOSTER, A, PEARSON, N and STAMATAKIS, E. (2019) Independent and Joint Associations of Sedentary Behavior and Physical Activity with Cardiometabolic Health Markers in the 1970 British Birth Cohort. MedRxiv, published online, 22 October 2019. The researchers hosted an ESRC Festival of Social Science event, attended by policymakers and third sector, participated in the Public Health England Special Interest Group on young people's mental health, and presented at a Conservative Party roundtable on youth mental health, and at the Public Health England (PHE) annual conference. To help communicate the distinction between mental health and wellbeing, the researchers translated complex statistical analysis into an infographic showing risk and protective factors at age 11. This was used in several contexts and by practitioners in public health, including PHE, the Department for Education and many local government and child mental health training programmes. GOISIS, A., SCHNEIDER, D. and MYRSKYLÄ, M. (2018) Secular changes in the association between advanced maternal age and the risk of low birth weight: a cross-cohort comparison in the UK. Population Studies, 72(3), 381-397. Concrete policy impacts include decisions to increase children and young peoples (CYP) mental health services capacity and changes to PHE strategies for tackling CYP mental health. For example, due to this work, PHE has expanded its focus from one that had previously been on mental health, to also include mental wellbeing. It also adapted the framework it uses to identify how to best support young people, by extending the range of multi-level and multi-setting risk and protective factors associated with mental health and wellbeing. BANN, D., FLUHARTY, M., HARDY, R. and SCHOLES, S. (2019) Socioeconomic inequalities in blood pressure: co-ordinated analysis of 147,775 participants from repeated birth cohort and cross-sectional datasets, 1989 to 2016. MedRxiv, Posted, 21 December 2019. This work has also framed discussion among policymakers at the Department for Education. BROWN, M, GILBERT, E, CALDERWOOD, L, TAYLOR, K and MORGAN, H. (2019) Collecting biomedical and social data in a longitudinal survey: A comparison of two approaches. Longitudinal and Life Course Studies, 10(4), 453-469(17). The research based on MCS age 14 data highlighted for the first time the extent of mental ill-health among young people across the UK. Through widespread dissemination in the media, it was instrumental in bringing the scale of the issue to public consciousness. Coverage included front-page headlines and follow-up features in a variety of national newspapers, and high-profile interviews in the broadcast media. As NHS England’s National Mental Health Director stated to The Guardian in response to the research: “After decades in the shadows, children’s mental health is finally in the spotlight” 3. Attracting public attention to the wider issues surrounding the research. There was also extensive coverage for the findings on changes in mental health over time, and on the links between parental break-up and children’s mental health. AKASAKI, M, PLOUBIDIS, G.B, DODGEON, B and BONELL, C.P. (2019) The clustering of risk behaviours in adolescence and health consequences in middle age. Journal of Adolescence, 77(Dec 2019), 188-197. For example: BOUNTZIOUKA,V, CUMBERLAND,P.M and RAHI,J.S. (2017) Trends in Visual Health Inequalities in Childhood Through Associations of Visual Function With Sex and Social Position Across 3 UK Birth Cohorts. JAMA Ophthalmology, 135(9), 954-961. The Times -Quarter of girls are depressed at 14 in mental health crisis BBC News - Quarter of 14-year-old girls ‘have signs of depression’ BRIDGER, E and DALY, M. (2017) Does cognitive ability buffer the link between childhood disadvantage and adult health? Health Psychology, 36(10), 966-976 The data linkage in this Agreement is expected to facilitate research that CLS anticipate is expected to be carried out on the effects of social or economic determinations of health, and environmental factors on the evolution of the wellbeing, health, and development of family members. This could be of direct benefit to the NHS and to community services interfacing with schools through informing policy to improve healthy lifestyles HAMER, M., YATES, T., SHERAR, L.B., CLEMES, S.A. and SHANKAR, A. (2016) Association of after school sedentary behaviour in adolescence with mental wellbeing in adulthood. Preventive Medicine, 87, 6-10. GREENE, G, GREGORY, A.M, FONE, D and WHITE, J. (2015) Childhood sleeping difficulties and depression in adulthood: the 1970 British Cohort Study. Journal of Sleep Research, 24(1), 19-23. VINER, R.M. and TAYLOR, B. (2007) Adult outcomes of binge drinking in adolescence: findings from a UK national birth cohort. Journal of Epidemiology and Community Health, 61(10), 902-907. CABLE, N, KELLY, Y, BARTLEY, M, SATO, Y and SACKER, A. (2014) Critical role of smoking and household dampness during childhood for adult phlegm and cough: a research example from a prospective cohort study in Great Britain. BMJ Open, 4(4), e004807. SMITH, L, GARDNER, B, AGGIO, D and HAMER, M. (2015) Association between participation in outdoor play and sport at 10 years old with physical activity in adulthood. Preventive Medicine, 74(May 2015), 31–35. Below expands further on the benefits of some of these examples of existing publications using BCS70 data drawing attention on how early life course experiences/exposures shape health outcomes into adulthood. Greene, Gregory, Fone and White (2015), for example, investigated the relationship between childhood sleeping difficulties (at age 5) and depression in adulthood (age 34), to conclude that severe sleeping problems in childhood may be associated with increased susceptibility to depression in adult life. Adjusting for the potential confounding influences of maternal depression and sleeping difficulties, parental reports of severe sleeping difficulties at 5 years were associated with an increased risk of depression at age 34 years [odds ratio (OR) = 1.9, 95% confidence interval (CI) = 1.2, 3.2] whereas moderate sleeping difficulties were not (OR = 1.1, 95% CI = 0.9, 1.3). Further research, however, is needed to explore whether screening and the treatment of children for poor sleeping patterns might impact upon their mental health in adulthood. Persistent sleep problems are an increasing health concern. In addition, poor sleep in adulthood has been linked with hypertension, diabetes, depression and obesity, as well as from cancer and increased mortality (Colten and Altevogt, 2006). Therefore, successful identification and treatment for children with sleeping difficulties could, if the association identified by the authors is causal, have large dividends across many aspects of health in the future (GREENE, G, GREGORY, A.M, FONE, D and WHITE, J. (2015) Childhood sleeping difficulties and depression in adulthood: the 1970 British Cohort Study. Journal of Sleep Research, 24(1), 19-23.). Viner and Taylor (2007) studied outcomes in adult life (at age 30) of binge drinking in adolescence (at age 16). Adolescent binge drinking predicted an increased risk of adult alcohol dependence (OR 1.6, 95% CI 1.3 to 2.0), excessive regular consumption (OR 1.7, 95% CI 1.4 to 2.1), illicit drug use (OR 1.4, 95% CI 1.1 to 1.8), psychiatric morbidity (OR 1.4, 95% CI 1.1 to 1.9), homelessness (OR 1.6, 95% CI 1.1 to 2.4), convictions (1.9, 95% CI 1.4 to 2.5), school exclusion (OR 3.9, 95% CI 1.9 to 8.2), lack of qualifications (OR 1.3, 95% CI 1.1 to 1.6), accidents (OR 1.4, 95% CI 1.1 to 1.6) and lower adult social class, after adjustment for adolescent socioeconomic status and adolescent baseline status of the outcome under study. The authors draw attention that these associations appear to be distinct from those associated with habitual frequent alcohol use, and binge drinking may contribute to the development of health and social inequalities during the transition from adolescence to adulthood (VINER, R.M. and TAYLOR, B. (2007) Adult outcomes of binge drinking in adolescence: findings from a UK national birth cohort. Journal of Epidemiology and Community Health, 61(10), 902-907.). Cable, Kelly, Bartley, Sato, and Sacker (2014) findings from BCS70 data give support to current public health interventions for adult smoking and raise concerns about the long-term effects of a damp home environment on the respiratory health of children. The authors examined the associations between childhood exposures to smoking and household dampness (at age 10), and phlegm and cough in adulthood (29 years of age), and found that childhood smoking and exposure to marked household dampness at age 10 were associated with phlegm (childhood smoking: relative risk ratio (RRR) =1.45, 95% CI 1.02 to 2.05; dampness: RRR=2.05, 95% CI 1.07 to 3.91) and co-occurring cough and phlegm (childhood smoking: RRR=1.35. 95% CI 1.08 to 1.67; dampness: RRR=2.73, 95% CI 1.88 to 3.99), while exposure to two or more adult smokers in the household was associated with cough-related symptoms (cough only: RRR=1.28, 95% CI 1.04 to 1.58; phlegm and cough: RRR=1.32, 95% CI 1.06 to 1.64). These associations were independent from adult smoking, childhood phlegm and cough, early social background and sex. Smoking at age 29 contributed to all symptom patterns, however, a substantial association between household dampness and co-occurring phlegm and cough suggest long-term detrimental effects of childhood environmental exposures. The authors findings support current public health interventions to reduce adult smoking, but also indicate that the management of childhood risk factors such as exposure to smoke (active or second-hand) and household dampness can be a way to prevent adults experiencing poor respiratory health (CABLE, N, KELLY, Y, BARTLEY, M, SATO, Y and SACKER, A. (2014) Critical role of smoking and household dampness during childhood for adult phlegm and cough: a research example from a prospective cohort study in Great Britain. BMJ Open, 4(4), e004807). Smith, Gardner, Aggio and Hamer (2015) investigated whether active outdoor play and/or sports at age 10 is associated with sport/physical activity at age 42. Final adjusted Cox regression models showed that participants (n=6458) who often participated in sports at age 10 were significantly more likely to participate in sport/physical activity at age 42 (RR 1.10; 95% CI 1.01 to 1.19). Active outdoor play at age 10 was not associated with participation in sport/physical activity at age 42 (RR 0.99; 95% CI 0.91 to 1.07). The finding authors suggest that childhood activity interventions might best achieve lasting change by promoting engagement in sport rather than active outdoor play (Tammelin et al., 2003a, 2003b) (SMITH, L, GARDNER, B, AGGIO, D and HAMER, M. (2015) Association between participation in outdoor play and sport at 10 years old with physical activity in adulthood. Preventive Medicine, 74(May 2015), 31–35.) To provide an example of the sorts of benefits to health that this linkage and use of this data may provide, it may be useful to be aware of the impact and benefit to health the 1958 National Child Development Study (NCDS) cohort has made. This is a similar birth tracking cohort still following it's members today. In it’s nearly sixty years research from this cohort has been responsible for proving beyond doubt that mothers who smoked heavily during pregnancy harmed the health and reduced the weight and height of their children, continuing on to damage English and maths scores at 16 years old. The study also informed the debate about the best place to deliver babies, indicating that mothers should only opt for home births when very early transfer to hospital is possible at the first sign of need and where highly experienced midwives and doctors are available. The study repeatedly demonstrated the need for steps to promote the health of pregnant mothers and facilities for safe childbirth. This led to the modernisation of maternity services with ready availability of high quality obstetrics on the one hand and better and more personal care for all. The case was made for adequate numbers of hospital beds and abolition of the lottery of where to give birth. Research has also made use of the longitudinal nature of the NCDS to examine the long-term effects of breastfeeding. For example, Rudnicka et al (2007) demonstrate that, compared with those who were bottle-fed with formula milk, children who were breastfed for more than a month had a reduced waist circumference and waist/hip ratio, and lower odds of obesity as adults in their mid-forties. Research using this cohort has also shed light on cancer and leukaemia in childhood, behavioural disorder, educational delay and disability. RUDNICKA, A. R, OWEN, C. G and STRACHAN, D. P. (2007) The effect of breast feeding on cardio-respiratory risk factors in adulthood. Pediatrics, 119(5), E1107-15. BCS70 data is a rich and unique resource for the research and policy community, and the information collected on health and its social determinants widens its potential value for health research and policy interventions. Linking health data from Hospital Episodes Statistics (HES) to the BCS70 survey data will greatly increase the potential of the data and future research in the area of health. The validation of self reported and hospital reported outcomes will benefit health research in terms of being able to offer research methodologies that are quicker and more cost effective. This will be of benefit to patients who are the recipients of research such as in public health and medical interventions etc. For example, using health administration data such as HES could make the delivery of research more efficient and potentially more accurate, it may increase the volume of research and it may ensure that research takes place into diseases which are currently difficult to fund.

Benefits reported

There have been hundreds of published journal articles, books, chapters, reports or conference presentations based on data from the 1970 British Cohort Study. It is difficult to predict in advance the type of research question that might be put forward to use the linked BCS70/HES dataset. Below are four examples of existing publications using BCS70 data benefiting public health. Below are some examples of existing publications using BCS70 data benefiting public health: The research papers below have been written using data from the CLS cohorts and COVID19 surveys: AYLOR, B and WADSWORTH, J. (1987) Maternal smoking during pregnancy and lower respiratory tract illness in early life. Archives of Disease in Childhood, 62(8), 786-791. David Bann, Aase Villadsen, Jane Maddock, View ORCID ProfileAlun Hughes, George B. Ploubidis, Richard J. Silverwood, Praveetha Patalay (2020) ‘Changes in the behavioural determinants of health during the coronavirus (COVID-19) pandemic: gender, socioeconomic and ethnic inequalities in 5 British cohort studies’. IMPACT: Research from BCS70 has contributed to the understanding of the effects of maternal smoking on child health. Using data from five nationally representative British cohort studies (born 2000-2, 1989-90, 1970, 1958, and 1946), researchers investigated sleep, physical activity (exercise), diet, and alcohol intake (N=14,297). Using measures of each behaviour reported before and during lockdown, researchers investigated change in each behaviour, and whether such changes differed by age/cohort, gender, ethnicity, and socioeconomic position (SEP; childhood social class, education attainment, and adult reporting of financial difficulties). The results showed changes in these outcomes occurred in both directions, i.e. shifts from the middle part of the distribution to both declines and increases in sleep, exercise, and alcohol use. For all outcomes, older cohorts were less likely to report changes in behaviours compared with younger cohorts. In the youngest cohort (born 2001), the following shifts were more evident: increases in exercise, fruit and vegetable intake, sleep duration, and less frequent alcohol consumption. Widening inequalities in sleep during lockdown were more frequent amongst females, socioeconomically disadvantaged groups, and ethnic minorities. For other outcomes, inequalities were largely similar before and during lockdown, yet ethnic minorities were increasingly likely during lockdown to undertake less exercise and consume lower amounts of fruit and vegetables doi: https://doi.org/10.1101/2020.07.29.20164244 SUMMARY: In a national study of 12,743 children maternal, but not paternal, smoking was confirmed as having a significant influence on the reported incidence of bronchitis and admission to hospital for lower respiratory tract illness during the first five years of life. Reported rates of admissions to hospital for lower respiratory tract diseases were found to be as high in children born to mothers who stopped smoking during pregnancy as in those whose mothers smoked continuously both during and after pregnancy. Rates of admissions to hospital for lower respiratory tract diseases in children whose mothers started smoking only postnatally were no higher than in those whose mothers remained non-smokers. Postnatal smoking seemed to exert a significant influence on the reported incidence of bronchitis, but less than smoking during pregnancy. These findings suggest that maternal smoking influences the incidence of respiratory illnesses in children mainly through a congenital effect, and only to a lesser extent through passive exposure after birth. Constantin-Cristian Topriceanu, Andrew Wong, James C Moon, View ORCID Profile Alun D Hughes, David Bann, Nish Chaturvedi, Praveetha Patalay, Gabriella Conti, Gabriella Captur (2020), ‘Inequality in access to health and care services during lockdown’ – Findings from the COVID-19 survey in five UK national longitudinal studies Researchers studied whether COVID19 further deepened existing health inequalities. Access to health services and adequate care is influenced by sex, ethnicity, socio-economic position (SEP) and burden of co-morbidities. However, it is unknown whether the COVID-19 pandemic further deepened these already existing health inequalities. Participants were from five longitudinal age-homogenous British cohorts (born in 2001, 1990, 1970, 1958 and 1946). A web and telephone-based survey provided data on cancelled surgical or medical appointments, and the number of care hours received during the UK COVID-19 national lockdown. Using binary or ordered logistic regression, researchers evaluated whether these outcomes differed by sex, ethnicity, SEP and having a chronic illness. The findings showed that Females and those with a chronic illness experienced significantly more cancellations during lockdown. Ethnic minorities and those with a chronic illness required a higher number of care hours during the lockdown . Age was not independently associated with either outcome in meta-regression. SEP was not associated with cancellation or care hours. MARMOT, M and BELL, R. (2016) Social inequalities in health: a proper concern of epidemiology. Annals of Epidemiology, 26(4), 238-240. https://doi.org/10.1101/2020.09.12.20191973 IMPACT: Research using BCS70 has highlighted an interrogated socio-economic inequalities in health. CABLE, N, KELLY, Y, BARTLEY, M, SATO, Y and SACKER, A. (2014) Critical role of smoking and household dampness during childhood for adult phlegm and cough: a research example from a prospective cohort study in Great Britain. BMJ Open, 4(4), e004807. Abstract: Social inequalities are a proper concern of epidemiology. Epidemiological thinking and modes of analysis are central, but epidemiological research is one among many areas of study that provide the evidence for understanding the causes of social inequalities in health and what can be done to reduce them. Understanding the causes of health inequalities requires insights from social, behavioural and biological sciences, and a chain of reasoning that examines how the accumulation of positive and negative influences over the life course leads to health inequalities in adult life. Evidence that the social gradient in health can be reduced should make the team optimistic that reducing health inequalities is a realistic goal for all societies. Cable, Kelly, Bartley, Sato, and Sacker (2014) findings from BCS70 data give support to current public health interventions for adult smoking and raise concerns about the long-term effects of a damp home environment on the respiratory health of children. The authors examined the associations between childhood exposures to smoking and household dampness (at age 10), and phlegm and cough in adulthood (29 years of age), and found that childhood smoking and exposure to marked household dampness at age 10 were associated with phlegm (childhood smoking: relative risk ratio (RRR) =1.45, 95% CI 1.02 to 2.05; dampness: RRR=2.05, 95% CI 1.07 to 3.91) and co-occurring cough and phlegm (childhood smoking: RRR=1.35. 95% CI 1.08 to 1.67; dampness: RRR=2.73, 95% CI 1.88 to 3.99), while exposure to two or more adult smokers in the household was associated with cough-related symptoms (cough only: RRR=1.28, 95% CI 1.04 to 1.58; phlegm and cough: RRR=1.32, 95% CI 1.06 to 1.64). PLOUBIDIS, G.B, SULLIVAN, A, BROWN, M and GOODMAN, A. (2017) Psychological Distress in Mid-Life: Evidence from the 1958 and 1970 British Birth Cohorts. Psychological Medicine, 47(2), 291-303. These associations were independent from adult smoking, childhood phlegm and cough, early social background and sex. Smoking at age 29 contributed to all symptom patterns, however, a substantial association between household dampness and co-occurring phlegm and cough suggest long-term detrimental effects of childhood environmental exposures. IMPACT: Research using BCS70 has highlighted the growing problem of depression in the UK. The authors findings support current public health interventions to reduce adult smoking, but also indicate that the management of childhood risk factors such as exposure to smoke (active or second-hand) and household dampness can be a way to prevent adults experiencing poor respiratory health (CABLE, N, KELLY, Y, BARTLEY, M, SATO, Y and SACKER, A. (2014) Critical role of smoking and household dampness during childhood for adult phlegm and cough: a research example from a prospective cohort study in Great Britain. BMJ Open, 4(4), e004807). Abstract: This paper addresses the levels of psychological distress experienced at age 42 years by men and women born in 1958 and 1970. Comparing these cohorts born 12 years apart, the team ask whether psychological distress has increased, and, if so, whether this increase can be explained by differences in their childhood conditions. Data were utilized from two well-known population-based birth cohorts, the National Child Development Study and the 1970 British Cohort Study. Latent variable models and causal mediation methods were employed. After establishing the measurement equivalence of psychological distress in the two cohorts the team found that men and women born in 1970 reported higher levels of psychological distress compared with those born in 1958. These differences were more pronounced in men (b = 0.314, 95% confidence interval 0.2520.375), with the magnitude of the effect being twice as strong compared with women (b = 0.147, 95% confidence interval 0.0760.218). The effect of all hypothesized early-life mediators in explaining these differences was modest. Our findings have implications for public health policy, indicating a higher average level of psychological distress among a cohort born in 1970 compared with a generation born 12 years earlier. Due to increases in life expectancy, more recently born cohorts are expected to live longer, which implies if such differences persist that they are likely to spend more years with mental health-related morbidity compared with earlier-born cohorts. SMITH, L, GARDNER, B, AGGIO, D and HAMER, M. (2015) Association between participation in outdoor play and sport at 10 years old with physical activity in adulthood. Preventive Medicine, 74(May 2015), 31–35. V.P Mateia, A.I. Mihailescub, L.V. Diaconescuc, T. Purnischid, R. Grigorase, O. Popa-Veleac (2018) Depression in young adults diagnosed with cancer -an analysis of the outcomes of 1970 British Cohort Study. GREENE, G, GREGORY, A.M, FONE, D and WHITE, J. (2015) Childhood sleeping difficulties and depression in adulthood: the 1970 British Cohort Study. Journal of Sleep Research, 24(1), 19-23. IMPACT: Research using BCS70 Cohort Study data has contributed to the understanding of the risk of depression inyoung patients diagnosed with cancer. Greene, Gregory, Fone and White (2015), for example, investigated the relationship between childhood sleeping difficulties (at age 5) and depression in adulthood (age 34), to conclude that severe sleeping problems in childhood may be associated with increased susceptibility to depression in adult life. Adjusting for the potential confounding influences of maternal depression and sleeping difficulties, parental reports of severe sleeping difficulties at 5 years were associated with an increased risk of depression at age 34 years [odds ratio (OR) = 1.9, 95% confidence interval (CI) = 1.2, 3.2] whereas moderate sleeping difficulties were not (OR = 1.1, 95% CI = 0.9, 1.3). Further research, however, is needed to explore whether screening and the treatment of children for poor sleeping patterns might impact upon their mental health in adulthood. Summary: The study found that the risk of depression is higher at people with onset of cancer before 30. The study did not identify an increased risk for depression by socioeconomic status. Instead, they suggest the importance of active Persistent sleep problems are an increasing health concern. In addition, poor sleep in adulthood has been linked with hypertension, diabetes, depression and obesity, as well as from cancer and increased mortality (Colten and Altevogt, 2006). Therefore, successful identification and treatment for children with sleeping difficulties could, if the association identified by the authors is causal, have large dividends across many aspects of health in the future (GREENE, G, GREGORY, A.M, FONE, D and WHITE, J. (2015) Childhood sleeping difficulties and depression in adulthood: the 1970 British Cohort Study. Journal of Sleep Research, 24(1), 19-23.). screening and treatment of depression at young patients with cancer. Detailed information about the study can be found here https://www.sciencedirect.com/science/article/pii/S0022399918303088?via%3Dihub BANN, D, JOHNSON, W, LI, L, KUH, D and HARDY, R. (2018) Socioeconomic inequalities in childhood and adolescent body-mass index, weight, and height from 1953 to 2015: an analysis of four longitudinal, observational, British birth cohort studies. Lancet Public Health, 3(4), e194-e203. IMPACT: Research using BCS70 Cohort Study data has contributed to the understanding of how socioeconomic inequalities in childhood body-mass index (BMI) have been documented in high-income countries, how they have changed over time, how inequalities in the composite parts (ie, weight and height) of BMI have changed, and whether inequalities differ in magnitude across the outcome distribution. The study investigated how socioeconomic inequalities in childhood and adolescent weight, height, and BMI have changed over time in Britain. Detailed information about the study can be found here: https://www.sciencedirect.com/science/article/pii/S2468266718300458?via%3Dihub ***Latest update -The first yielded benefit the creation of the linked BCS70/HES dataset. The dataset is now available for researchers to use via the UKDS. A link to the dataset is provided here https://beta.ukdataservice.ac.uk/datacatalogue/studies/study?id=8733 -CLS has also produced the Next Steps/HES user guide. This document provides researchers with complete guide to the linked data and information on the application process - http://doc.ukdataservice.ac.uk/doc/8733/mrdoc/pdf/bcs_hes_user_guide_v1.pdf -Webinar- An introduction to linked health administrative data in four cohort studies. CLS delivered a webinar on the 11th February 2021 to introduce the HES linked datasets and provide information to researchers on how to access them. -Yielded benefits from the survey Yielded benefits from the COVID survey carried out by CLS with participants from CLS' four cohort studies between May 2020 and February 2021. Two research papers have been written using data from the CLS cohorts and COVID19 surveys David Bann, Aase Villadsen, Jane Maddock, View ORCID ProfileAlun Hughes, George B. Ploubidis, Richard J. Silverwood, Praveetha Patalay (2020) Changes in the behavioural determinants of health during the coronavirus (COVID-19) pandemic: gender, socioeconomic and ethnic inequalities in 5 British cohort studies. Using data from five nationally representative British cohort studies (born 2000-2, 1989-90, 1970, 1958, and 1946), researchers investigated sleep, physical activity (exercise), diet, and alcohol intake (N=14,297). More details about this study can be found via this link doi: https://doi.org/10.1101/2020.07.29.20164244 Constantin-Cristian Topriceanu, Andrew Wong, James C Moon, View ORCID ProfileAlun D Hughes, David Bann, Nish Chaturvedi, Praveetha Patalay, Gabriella Conti, Gabriella Captur (2020) Inequality in access to health and care services during lockdown – Findings from the COVID-19 survey in five UK national longitudinal studies. Researchers studied whether COVID19 further deepened existing health inequalities. Access to health services and adequate care is influenced by sex, ethnicity, socio-economic position (SEP) and burden of co-morbidities. However, it is unknown whether the COVID-19 pandemic further deepened these already existing health inequalities. More details about this study can be found via this link - https://doi.org/10.1101/2020.09.12.20191973

Text removed is struck through; text added is underlined. Unchanged paragraphs are summarised rather than repeated.

Datasets: + Emergency Care Data Set (ECDS)

Objective for processing

*** TO CORRECT THE INVOICE Previous iterations of this DSA have covered the dissemination of HES data and its linkage to a subset of the 1970 British Cohort Study (BCS70) survey data as part of the BCS70 longitudinal study. This amendment request (version 1) is for the addition of a sub-licence to allow onward sharing of the linked HES data with the UK Data Services (UKDS) where data can be accessed by accredited researchers. Further detail of this is outlined below: [33 paragraphs unchanged] UCL legal basis for processing (acquiring, linking and sharing) personal data is [97 words unchanged] survey data, and to the onward sharing of this linked data in pseudo-anonymised pseudonymised form (via a secure setting with appropriate safeguards). [1 paragraph unchanged] The data disseminated to CLS will be accessed by substantive employees of UCL who will work on the data to make it research ready, will pseudo-anonymise pseudonymise the data and deposit it at the UKDS for researchers applying to use for specific projects. The pseudo-anonymised pseudonymised data will also be accessed by CLS employees to conduct methodological and research work via the UCL Data Safe Heaven.

Processing activities

[3 paragraphs unchanged] 3. CLS carried out validation of the administrative pseudonymised data received (linked HES data) and combined the supplied administrative data with the information collected from the participant as part of the Next Steps study using the study ID. Once the linked survey-administrative data files have been created, CLS may perform other activities to prepare the data for use, such as coding and cleaning, derivation of summary variables and compilation of data documentation. 4. CLS researchers used these data to create an analysis file, which do not contain any identifiable data. 5. CLS created derived variables that summarise study members’ hospitalisation and health histories (e.g. hospital admissions and re-admissions, incidence of common diseases, children’s ailments etc.) and compare Next Steps survey data with data from hospital statistics, in order to compare and validate the data collected in CLS surveys. Identifiers are held separately from attribute characteristics. HES data is not be relinked to the identifiable data which is held separately from the survey responses. Re-identification will only happen at the occasion of a request, made from a cohort member, for withdrawal from the study, and this includes removal of data. Where a participant wishes to withdraw from the study, the identifiable data is used to locate the study id, and then in turn destroy their data. Addition of the sub-licence: The process of accessing the linked data via the UKDS Service Secure Lab include the following steps: • Registration with the UKDS Service. • Submission of an application, including an ‘Accredited Researcher application form’ and ‘Research proposal’. • Screening of application by UKDS for completeness. Once a researcher has registered and UKDS has screened / approved the application: 1) UKDS sends project proposal (researcher application forms) to CLS-UCL (for Data Access Committee (DAC) approval). Applicants are required to demonstrate they have security assurance in place (System Level Security Policy/ISO Certificate/DSPT). 2) CLS-UCL sends the CLS License Agreement for Linked NHS Digital data to researchers to be completed and signed by their organisation (this includes the benefits to health and social care and evidence of organisational security assurances) not covered by UKDS application. 3) Researcher/their organisation representative will send the CLS License Agreement for Linked NHS Digital completed and signed back to CLS-UCL. 4) CLS-UCL will: a) check the organisational Information Governance and security assurance evidence provided as per Section 15 Organisational Security Assurance of the CLS Licence agreement, b) send the project for CLS DAC approval. 5) Should evidence of organisational Information Governance and security assurance provided not meet the requirements (as outlined in the sub-license) CLS will request the applicant to provide further evidence, and will only submit the project to CLS DAC for approval when evidence provided is satisfactory. Approval for data access will only be granted to applicant organisations that meet the security assurance requirement. 6) CLS DAC will assess both documents (UKDS project proposal + CLS Licence agreement) and make a decision to approve it or not approve it or require further information. Should an application be rejected, a researcher can apply again with a revised application. 7) In the CLS License agreement, CLS DAC will, among other things assess the benefits for health and social care statement, and decide whether it is satisfied with the answer. 8) Once CLS DAC approves the project : a) CLS will inform UKDS that project has been approved. b) CLS representative should sign the CLS License agreement noting the DAC reference number on the License document and send it back to the organisation of the applicant (the Principal Investigator for the study requiring access will sign the agreement - they will be an authorised signatory for their organisation). c) CLS DAC will provide information about any data dissemination to NHS Digital, including the name of the organisation to which data was provided, purpose (summary of the project) and what data was released. (NB. If CLS DAC doesn't approve the project, no data will be disseminated). 9) If CLS DAC is not satisfied with the evidence provided by the applicant about the benefits to health and social care, then CLS DAC can ask the applicant to provide additional information and the project can be re-submitted for CLS DAC approval on the next CLS DAC meeting or via Chair approval. 10) UKDS will inform the researcher that their project was approved and make the data available to them via Secure access to linked data at the Safe Centre at the UK Data Service (hosted at the University of Essex) or via the researcher’s own institutional desktop PC, depending on the sensitivity/impact level of the data being requested . Note that any data accessed through the UKDS Secure Lab can only be accessed under secure conditions and cannot be downloaded. The linked data provided to approved researchers may be subject to sub-setting of variables (and if necessary cases) to minimize disclosure risks and ensure that no individual or organisation can be identified from the results. In addition, all statistical outputs are subject to statistical disclosure control procedure. Access to the Secure Lab is only available to researchers who are be based at a UK academic institution or an ESRC-funded research centre and be an ESRC Accredited Researcher. PhD and research students can request access but must apply jointly with their supervisors from established organisations. No further onward sharing can occur beyond the sub-licence. UKDS SECURE DATA HANDLING PROCEDURES The UK Data Service has received government technical accreditation and has been certified for its secure data handling procedures under the international standard for information security (ISO 27001). To maintain this certification, regular internal and external audits are undertaken. UKDS also hires a government-approved company to conduct internal and external penetration testing of its Secure Lab systems. More widely, the UKDS employs an Information Security Management System (ISMS), to ensure compliance with the ISO accreditation. The Secure Lab falls into this system, and a number of documented processes are regularly maintained and reviewed to ensure these processes are robust, relevant, and fit-for-purpose. The ISMS is overseen by an Information Security Management Group (ISMG), which regularly meets and approves changes to procedures. UKDS DATA ACCESS MECHANISMS As an ESRC resource centre, CLS shares its survey data with the research community via the UKDS under safeguarded or controlled access mechanisms, dependent on the likelihood and potential impact of disclosure. Data with higher risk of disclosure is treated with an appropriate degree of security and management. CLS data fall into the following categories, which are defined by the likelihood and potential impact of disclosure: • Tier 1: data with low level of disclosure: e.g. participant self-reported survey data. These data are made available through the UKDS End User Licence and have a low impact of disclosure; • Tier 2a: data that is potentially disclosive: e.g. medium level and coarse geographies or sensitive information about cohort members. These data are made available through the UKDS Special Licence and have a medium impact of disclosure; • Tier 2: data that are too detailed, sensitive or confidential to be made available under the standard End User Licence or Special Licence, such as detailed geographical indicators or fine-grained individual level linked data. These data have a high impact of disclosure and are made available through the UKDS Secure Access. Access mechanisms to NHS Digital HES data linked to CLS cohort studies via the UKDS The HES data provided to CLS by NHS Digital, which are linked to the CLS cohort members, have been processed by the CLS data management team to minimise the risk of disclosivity when linked to the CLS survey data. This has been achieved by removing highly identifiable variables and altering other variables by top-coding or truncating them. Following this processing, the final health data sets have been classified under Tier 2. It is therefore CLS’s intention to deposit these Tier 2 linked HES data with the UK Data Service under the UKDS Secure Access, and provide access to this information for approved researchers, following the process and contractual arrangements, outlined above and described in more detail below, following an agreed between NHS Digital, CLS and UKDS onward sharing model. The UKDS’s ‘Controlled access to data’ specification is supplied to NHS Digital as part of this application amendment. The data provided will be pseudonymised and will be accessed only via the UKDS secure lab. Downloading the data is not possible. All organisations party to this agreement must comply with the Data Sharing Framework Contract requirements, including those regarding the use (and purposes of that use) by “Personnel” (as defined within the Data Sharing Framework Contract ie: employees, agents and contractors of the Data Recipient who may have access to that data). No further data is being requested and no data is being sent to NHS Digital under this version of the Agreement. 1. CLS team have supplied NHS Digital with identifiers of cohort members who have consented to this data linkage, including full name, sex, postcode, date of birth, NHS number (if known) and study ID (study-specific pseudonymised identifier). 2. NHS Digital have linked the identifiable study data to HES data. NHS Digital have removed identifiers from linked dataset and returned the pseudonymised dataset to the CLS team at UCL with the study ID. The data disseminated to UCL will be accessed by substantive employees of UCL who have been appropriately trained in data protection and confidentiality. The data will be held at the secure server in the UCL Data Safe Haven (DSH) and accessed remotely by CLS staff. [40 paragraphs unchanged] No further data is being requested and no data is being sent to NHS Digital under this version of the Agreement. CLS researchers who need to access the data to produce methodological papers on the quality of the data (eg around measurement, representativeness) and research papers helping to showcase its benefits for health and social care will need to submit an application to CLS DAC detailing their project proposal. Upon DAC approval, a pseudonymised dataset will be provided to the researcher. The data will be held at the secure server in the UCL Data Safe Haven (DSH). 1. CLS team have supplied NHS Digital with identifiers of cohort members who have consented to this data linkage, including full name, sex, postcode, date of birth, NHS number (if known) and study ID (study-specific pseudonymised identifier). The UCL DSH is certified to ISO 27001:2013 and is compliant with NHS Digital's Data Security and Protection Toolkit. Research teams using the DSH complete annual training and regularly review data access arrangements ensuring data is only limited to those authorised to access it. UCL Computing Regulations are based on the premise that access to resources is generally forbidden unless expressly permitted. All data transfers from the DSH require approval and are carried out through secure portals which are fully audited. Access to the UCL DSH is via remote desktop and requires multi-factor authentication. In addition to a strong password each user has to use a six digit number generated by a smartphone app or physical token at each login. Passwords must be changed at regular intervals, and unused accounts are automatically disabled after a fixed period. Once inside the environment, robust access control ensures that researchers can only examine information that they are approved to use. 2. NHS Digital have linked the identifiable study data to HES data. NHS Digital have removed identifiers from linked dataset and returned the pseudonymised dataset to the CLS team at UCL with the study ID. 3. CLS carried out validation of the administrative pseudonymised data received (linked HES data) and combined the supplied administrative data with the information collected from the participant as part of the Next Steps study using the study ID. Once the linked survey-administrative data files have been created, CLS may perform other activities to prepare the data for use, such as coding and cleaning, derivation of summary variables and compilation of data documentation. 4. CLS researchers used these data to create an analysis file, which do not contain any identifiable data. 5. CLS created derived variables that summarise study members’ hospitalisation and health histories (e.g. hospital admissions and re-admissions, incidence of common diseases, children’s ailments etc.) and compare Next Steps survey data with data from hospital statistics, in order to compare and validate the data collected in CLS surveys. Identifiers are held separately from attribute characteristics. HES data is not be relinked to the identifiable data which is held separately from the survey responses. Re-identification will only happen at the occasion of a request, made from a cohort member, for withdrawal from the study, and this includes removal of data. Where a participant wishes to withdraw from the study, the identifiable data is used to locate the study id, and then in turn destroy their data. Addition of the sub-licence: The process of accessing the linked data via the UKDS Service Secure Lab include the following steps: • Registration with the UKDS Service. • Submission of an application, including an ‘Accredited Researcher application form’ and ‘Research proposal’. • Screening of application by UKDS for completeness. Once a researcher has registered and UKDS has screened / approved the application: 1) UKDS sends project proposal (researcher application forms) to CLS-UCL (for Data Access Committee (DAC) approval). Applicants are required to demonstrate they have security assurance in place (System Level Security Policy/ISO Certificate/DSPT). 2) CLS-UCL sends the CLS License Agreement for Linked NHS Digital data to researchers to be completed and signed by their organisation (this includes the benefits to health and social care and evidence of organisational security assurances) not covered by UKDS application. 3) Researcher/their organisation representative will send the CLS License Agreement for Linked NHS Digital completed and signed back to CLS-UCL. 4) CLS-UCL will: a) check the organisational Information Governance and security assurance evidence provided as per Section 15 Organisational Security Assurance of the CLS Licence agreement, b) send the project for CLS DAC approval. 5) Should evidence of organisational Information Governance and security assurance provided not meet the requirements (as outlined in the sub-license) CLS will request the applicant to provide further evidence, and will only submit the project to CLS DAC for approval when evidence provided is satisfactory. Approval for data access will only be granted to applicant organisations that meet the security assurance requirement. 6) CLS DAC will assess both documents (UKDS project proposal + CLS Licence agreement) and make a decision to approve it or not approve it or require further information. Should an application be rejected, a researcher can apply again with a revised application. 7) In the CLS License agreement, CLS DAC will, among other things assess the benefits for health and social care statement, and decide whether it is satisfied with the answer. 8) Once CLS DAC approves the project : a) CLS will inform UKDS that project has been approved. b) CLS representative should sign the CLS License agreement noting the DAC reference number on the License document and send it back to the organisation of the applicant (the Principal Investigator for the study requiring access will sign the agreement - they will be an authorised signatory for their organisation). c) CLS DAC will publish the information about any data dissemination on the NHS Digital release register, including the name of the organisation to which data was provided, purpose (summary of the project) and what data was released. (NB. If CLS DAC doesn't approve the project, no data will be disseminated). 9) If CLS DAC is not satisfied with the evidence provided by the applicant about the benefits to health and social care, then CLS DAC can ask the applicant to provide additional information and the project can be re-submitted for CLS DAC approval on the next CLS DAC meeting or via Chair approval. 10) UKDS will inform the researcher that their project was approved and make the data available to them via Secure access to linked data at the Safe Centre at the UK Data Service (hosted at the University of Essex) or via the researcher’s own institutional desktop PC, depending on the sensitivity/impact level of the data being requested . Note that any data accessed through the UKDS Secure Lab can only be accessed under secure conditions and cannot be downloaded. The linked data provided to approved researchers may be subject to sub-setting of variables (and if necessary cases) to minimize disclosure risks and ensure that no individual or organisation can be identified from the results. In addition, all statistical outputs are subject to statistical disclosure control procedure. Access to the Secure Lab is only available to researchers who are be based at a UK academic institution or an ESRC-funded research centre and be an ESRC Accredited Researcher. PhD and research students can request access but must apply jointly with their supervisors from established organisations. No further onward sharing can occur beyond the sub-licence. UKDS SECURE DATA HANDLING PROCEDURES The UK Data Service has received government technical accreditation and has been certified for its secure data handling procedures under the international standard for information security (ISO 27001). To maintain this certification, regular internal and external audits are undertaken. UKDS also hires a government-approved company to conduct internal and external penetration testing of its Secure Lab systems. More widely, the UKDS employs an Information Security Management System (ISMS), to ensure compliance with the ISO accreditation. The Secure Lab falls into this system, and a number of documented processes are regularly maintained and reviewed to ensure these processes are robust, relevant, and fit-for-purpose. The ISMS is overseen by an Information Security Management Group (ISMG), which regularly meets and approves changes to procedures. UKDS DATA ACCESS MECHANISMS As an ESRC resource centre, CLS shares its survey data with the research community via the UKDS under safeguarded or controlled access mechanisms, dependent on the likelihood and potential impact of disclosure. Data with higher risk of disclosure is treated with an appropriate degree of security and management. CLS data fall into the following categories, which are defined by the likelihood and potential impact of disclosure: • Tier 1: data with low level of disclosure: e.g. participant self-reported survey data. These data are made available through the UKDS End User Licence and have a low impact of disclosure; • Tier 2a: data that is potentially disclosive: e.g. medium level and coarse geographies or sensitive information about cohort members. These data are made available through the UKDS Special Licence and have a medium impact of disclosure; • Tier 2: data that are too detailed, sensitive or confidential to be made available under the standard End User Licence or Special Licence, such as detailed geographical indicators or fine-grained individual level linked data. These data have a high impact of disclosure and are made available through the UKDS Secure Access. Access mechanisms to NHS Digital HES data linked to CLS cohort studies via the UKDS The HES data provided to CLS by NHS Digital, which are linked to the CLS cohort members, have been processed by the CLS data management team to minimise the risk of disclosivity when linked to the CLS survey data. This has been achieved by removing highly identifiable variables and altering other variables by top-coding or truncating them. Following this processing, the final health data sets have been classified under Tier 2. It is therefore CLS’s intention to deposit these Tier 2 linked HES data with the UK Data Service under the UKDS Secure Access, and provide access to this information for approved researchers, following the process and contractual arrangements, outlined above and described in more detail below, following an agreed between NHS Digital, CLS and UKDS onward sharing model. The UKDS’s ‘Controlled access to data’ specification is supplied to NHS Digital as part of this application amendment. The data provided will be pseudonymised and will be accessed only via the UKDS secure lab. Downloading the data is not possible. All organisations party to this agreement must comply with the Data Sharing Framework Contract requirements, including those regarding the use (and purposes of that use) by “Personnel” (as defined within the Data Sharing Framework Contract ie: employees, agents and contractors of the Data Recipient who may have access to that data).

Expected output

Following the data quality and validation work, the The first output will be output, the creation of the linked BCS70 (Age42)/HES data set. The HES data will add an important layer to this already rich data as well as providing the means for data quality checking. CLS BCS70/HES dataset, is currently working on the data to make it ‘research ready’. The HES/NCDS dataset is nearly ready and will be made now available for researchers to apply via the UKDS once sub-licensing is approved. apply. The most recent HES data requested in this application will refresh this already rich linked dataset. CLS and the UKDS will publicise the data release at both the CLS and UKDS websites. CLS has not yet sub-licenced the available BCS70/HES data as CLS only recently got permission for sub-licensing this data. CLS has recently delivered a webinar to introduce this dataset to researchers and hope to start receiving applications soon. A first application to use the data is currently in progress, details are provided below: Project Title: 'Linkage of National Longitudinal Cohort Studies and Administrative Data: A Mutually Beneficial Arrangement' This research will be addressing the following three methodological research questions, which will be directly reflected in the project work packages. 1. How can linked administrative data aid the handling of missing cohort data? 2. How can linked cohort data improve our understanding of the quality of administrative data? 3. How can linked cohort data help address residual confounding in analyses of administrative data [4 paragraphs unchanged]

Benefits reported

[7 paragraphs unchanged] Abstract: Social inequalities are a proper concern of epidemiology. Epidemiological thinking and [76 words unchanged] Evidence that the social gradient in health can be reduced should make us the team optimistic that reducing health inequalities is a realistic goal for all societies. [2 paragraphs unchanged] Abstract: This paper addresses the levels of psychological distress experienced at age [6 words unchanged] born in 1958 and 1970. Comparing these cohorts born 12 years apart, we the team ask whether psychological distress has increased, and, if so, whether this increase [38 words unchanged] After establishing the measurement equivalence of psychological distress in the two cohorts we the team found that men and women born in 1970 reported higher levels of [110 words unchanged] to spend more years with mental health-related morbidity compared with earlier-born cohorts. [8 paragraphs unchanged] CHENG, H and FURNHAM, A. (2018) Teenage locus of control, psychological distress, educational qualifications and occupational prestige as well as sex are independent predictors of adult binge drinking. Alcohol, advance online access, 1 Sept 2018. ***Latest update IMPACT : Research using BCS70 Cohort Study data has contributed to the understanding of how various psychological and socio-demographic factors in childhood and adulthood that relate to alcohol intake and binge drinking at age 42 years. -The first yielded benefit the creation of the linked BCS70/HES dataset. The dataset is now available for researchers to use via the UKDS. A link to the dataset is provided here https://beta.ukdataservice.ac.uk/datacatalogue/studies/study?id=8733 Abstract: Data were drawn from the 1970 British Cohort Study (BCS70), The analytic sample comprised 5267 cohort members with data on parental social class at birth, cognitive ability at age 10, locus of control at age 16, -CLS has also produced the Next Steps/HES user guide. This document provides researchers with complete guide to the linked data and information on the application process - http://doc.ukdataservice.ac.uk/doc/8733/mrdoc/pdf/bcs_hes_user_guide_v1.pdf psychological distress at age 30, educational qualifications at age 34, and current occupation and alcohol consumption at age 42 years. Results showed that sex (male), lower parental social class, adolescent external locus of control, psychological distress, lower scores on childhood intelligence, lower educational qualifications and less professional occupations were all significantly and positively associated with binge drinking in adulthood. Both psychological and social factors influence adult excessive alcohol consumption. Adolescent locus of control beliefs had a modest but significant effect on adult binge drinking 26 years later. Detailed information can be found here: -Webinar- An introduction to linked health administrative data in four cohort studies. https://www.sciencedirect.com/science/article/pii/S0741832916301677?via%3Dihub CLS delivered a webinar on the 11th February 2021 to introduce the HES linked datasets and provide information to researchers on how to access them. -Yielded benefits from the survey Yielded benefits from the COVID survey carried out by CLS with participants from CLS' four cohort studies between May 2020 and February 2021. Two research papers have been written using data from the CLS cohorts and COVID19 surveys David Bann, Aase Villadsen, Jane Maddock, View ORCID ProfileAlun Hughes, George B. Ploubidis, Richard J. Silverwood, Praveetha Patalay (2020) Changes in the behavioural determinants of health during the coronavirus (COVID-19) pandemic: gender, socioeconomic and ethnic inequalities in 5 British cohort studies. Using data from five nationally representative British cohort studies (born 2000-2, 1989-90, 1970, 1958, and 1946), researchers investigated sleep, physical activity (exercise), diet, and alcohol intake (N=14,297). More details about this study can be found via this link doi: https://doi.org/10.1101/2020.07.29.20164244 Constantin-Cristian Topriceanu, Andrew Wong, James C Moon, View ORCID ProfileAlun D Hughes, David Bann, Nish Chaturvedi, Praveetha Patalay, Gabriella Conti, Gabriella Captur (2020) Inequality in access to health and care services during lockdown – Findings from the COVID-19 survey in five UK national longitudinal studies. Researchers studied whether COVID19 further deepened existing health inequalities. Access to health services and adequate care is influenced by sex, ethnicity, socio-economic position (SEP) and burden of co-morbidities. However, it is unknown whether the COVID-19 pandemic further deepened these already existing health inequalities. More details about this study can be found via this link - https://doi.org/10.1101/2020.09.12.20191973

Unchanged: Expected measurable benefits.

Text removed is struck through; text added is underlined. Unchanged paragraphs are summarised rather than repeated.

Objective for processing

*** TO CORRECT THE INVOICE [37 paragraphs unchanged]

Unchanged: Processing activities, Expected output, Expected measurable benefits, Benefits reported.

Text removed is struck through; text added is underlined. Unchanged paragraphs are summarised rather than repeated.

Objective for processing

Previous iterations of this DSA have covered the dissemination of HES data and its linkage to a subset of the 1970 British Cohort Study (BCS70) survey data as part of the BCS70 longitudinal study. This amendment request (version 1) is for the addition of a sub-licence to allow onward sharing of the linked HES data with the UK Data Services (UKDS) where data can be accessed by accredited researchers. Further detail of this is outlined below: The Centre for Longitudinal Studies (CLS) at University College London (UCL) is an academic resource centre responsible for producing and disseminating data resources for the scientific community. CLS manages four world-renowned birth cohort studies; the National Child Development Study 1958, the 1970 British Cohort study and the Millennium Cohort Study 2000 and now have the Next Steps cohort in their portfolio. [1 paragraph unchanged] The 1970 British Cohort Study (BCS70) has its origins originated in the late 1960s, when there was a great deal of concern [6 words unchanged] number of babies born with abnormalities, or dying very early in life. They It was decided to compare those mothers and babies who had problems, with those [39 words unchanged] throughout England, Wales and Scotland, this study was carried out in 1970. Information was collected on the family background of the mother, her the pregnancy and labour, and about her the baby at birth and in the first week of the baby’s life. Almost 17,500 babies were studied. It was not for another 5 years that it was decided that [66 words unchanged] the original 1970 survey – in 1980, 1986, 1996, 1999/2000, 2004/5, 2008 and 2012, 2016. The Age 50 survey commenced in 2012 when January 2020 but is currently paused due to the impact of the COVID-19 pandemic. It is expected to re-commence in early 2021. Subsequent sweeps of the study members were aged 42. will likely take place every five years. During the 2012 survey, CLS obtained informed consent from cohort members for [7 words unchanged] the data collected in the study. In total consent was obtained from 6181 6,181 cohort members who at the time were in England. Linking health data from Hospital Episodes Statistics (HES) to the BCS70 Next Steps survey data will has greatly increase increased the possibilities for using the cohort to study how health outcomes impact [42 words unchanged] documented as part of the study. The successful inclusion of HES data will enrich has enriched these data by revealing which cohort members have been admitted to or [9 words unchanged] and alcohol treatment, accident and emergency, maternity and mental health services which could help improve understanding of have helped CLS better understand how health conditions could be better treated or supported. Data about health behaviours may be are more accurate if when obtained from administrative records as a result because of misreporting of complex health conditions, under-reporting of particular health problems or due to perceived sensitivities around certain behaviours and lifestyle choices. So So, this also offers a valuable an interesting methodological opportunity to validate the data collected in the survey and vice versa. [3 paragraphs unchanged] 3. Develop and create a useful and rich HES linked (Age 42) BCS70 dataset data set UCL will not link the identifiable data they hold with data disseminated from NHS Digital. The only exception would be where a participant wishes to withdraw from the study. 4. Advance learning in the research community by providing access to the linked NHS Digital HES / CLS BCS70 data to the research community via the UK Data Service (UKDS) Secure Lab, through a sub-licensing agreement agreed between CLS and NHS Digital. UCL will not share the linked HES/Age 42 BCS70 dataset with third parties. THE SUB-LICENCE: CLS are permitted to include onward sharing of the linked HES and Next Steps data with the UK Data Service (UKDS), where data can be accessed by accredited researchers in a Secure Research Environment, known as Secure Lab, following a “Sub-licensing model”. The UKDS is funded by the Economic and Social Research Council (ESRC) with contributions from the University of Essex, the University of Manchester and Jisc (Jisc is a United Kingdom not-for-profit company whose role is to support post-16 and higher education, and research, by providing relevant and useful advice, digital resources and network and technology services, while researching and developing new technologies and ways of working). The UKDS provides access to high-quality data to meet the data needs of researchers, students and teachers from all sectors including academia and central and local government. The UKDS is based at, and hosted by, the University of Essex. Although the researchers at the UKDS are substantively employed by the University of Essex, only staff who are permitted to work at the UKDS will access the data. Under the “Sub-licensing model”, NHS Digital shares data with CLS, who are in turn licensed to share these data with other organisations, subject to agreed controls, scoped in this agreement between NHS Digital and UCL. In line with this onward sharing model, the data sharing controls in place between NHS Digital and CLS are replicated between CLS and the other organisations. UCL, which houses CLS at the UCL Institute of Education, is fully accountable for the actions of the parties involved in subsequent data share and use. The agreement mirrors the Data Sharing Framework Contract in place between NHS Digital and UCL. It also requests information about the research proposal, benefits to health and/or social care, organisational security assurance and terms and conditions regarding onward sharing of data, responsibilities and processing activities etc. Under the sub-licensing model CLS will deposit the linked data with UK Data Service, who will serve as a data repository. Access to the deposited data will be granted to approved researchers within a Secure Research Environment on behalf of CLS, as outlined in this document. NHS Digital will retain the ability to directly audit UKDS’s compliance with the outlined and agreed data access arrangements. There will be no charge applied to Licence supplied by CLS. The territory of use in the sub-licence will be the same or narrower than the territory of use stated in this DSA, namely UK. In this sharing model of the linked data, CLS will be a data controller, determining the purposes for which and the manner in which the linked data are processed. The UKDS will be the data processor, as they will be processing the data on behalf of CLS. This includes holding the linked data in a secure environment, screening for completeness of applications for data access, providing training for use of linked data securely, entering into contractual agreements with approved researchers, extraction of approved data and setting up access systems, and approving statistical outputs, following a statistical disclosure control procedure. The approved organisations and researchers, who are granted an access to the linked data via the UKDS Secure Lab, agree to terms and conditions of use, their rights and responsibilities as users of the linked data, as defined by the UKDS. In addition to the agreements signed with the UKDS, the organisation of the researcher applying to use the linked data will enter into a Licence agreement with UCL. ORGANISATIONAL AGREEMENTS CLS will provide a sub-licence to UK organisations undertaking research that will be of benefit to the public (this will be assessed in the project proposal form submitted to the UKDS and to CLS). Applicants (potential licencees) will need to show in Schedule 1 Section 18 (a) and (b) that the provision of the sub licencing will be in the public interest and that that the data will be used either (i) for the provision of health care or adult social care; or (ii) for the promotion of health. CLS will not provide data access to commercial organisations for research for commercial purposes. Additionally, the CLS Licence agreement, Schedule 1 Section 18, will assess the project proposal against its assessment criteria to determine the details of the project, the people who will be accessing the data, and what the data will be requested. Applicants will need to be accredited researchers or agree to undertake training and become accredited, prior to accessing the data. Additionally, applicant’s organisation will need to provide evidence that they have IG and security assurances in place (covered in Schedule 1, Section 15 of the CLS Licence agreement). Members of the CLS Data Access Committee (DAC) will review and decide if the evidence provided satisfy the criteria requirements. Applicants (licencees) and their organisations will have to sign two agreements to obtain a sub-licence, one with the UKDS and another with CLS, in both cases the licencee will agree with the terms stated in the Confidentiality Section of the CLS Licence Agreement and with the Confidentiality Terms stated in the Secure Access Agreement which will be signed with the UKDS. By signing these agreements the licencee agrees to adhere to these terms, including respecting the privacy of health services users data they will receive. Licencees are also be reminded of the penalties they are likely to incur if they do not comply with the terms they have agreed. In addition to the above, the UKDS agreement stipulates that data users must complete mandatory training before they are allowed to access the data. To ensure the security of the linked information, shared with CLS by NHS Digital, and subsequently shared by CLS with the UKDS, where data could be accessed by approved researchers in a Secure Lab, CLS envisage the following controls employed at the different steps of the process of depositing, approving and sharing of the linked information: • An agreement between NHS Digital and CLS to onwardly share linked HES and CLS information under “Sub-licencing model”, which outlines the terms and conditions of use of the linked data via the UKDS Service Secure Lab as the data repository, and the full accountability of UCL (housing CLS at the UCL Institute of Education) to the actions of the parties involved in subsequent access to the linked data. • An agreement between CLS (as a data controller) and UKDS (as a data processor), which outlines the terms and conditions under which the linked data can be accessed via the UKDS Secure Lab. • An agreement between UKDS and the approved researcher, which outlines the terms and conditions of use of the linked data in the UKDS’s Secure Lab. • An Agreement between UCL and the organisation requesting to use the linked data via the UKDS, which outlines the terms and conditions of use of the linked data. The researcher accessing the data via the UKDS Secure Lab will not be able to download any data. Once the researcher has finished their research, the UKDS will delete the data folder with the tailored dataset for the specific project. The data held at CLS will be deleted if the data sharing agreement between NHS Digital and CLS were to cease. If it were to cease, the license agreement between CLS and the licensee organisation will be terminated. UCL legal basis for processing (acquiring, linking and sharing) personal data is for a public task under GDPR (article 6(1)(e)) i.e. processing is necessary for the performance of a task carried out in the public interest (as is made explicit to participants in the information leaflets provided). UCL also process special categories of personal data for research under GDPR (article 9(2)(j)) i.e. processing is necessary for archiving purposes in the public interest, scientific or historical research purposes or statistical purposes. In addition, for ethical reasons and under the Common Law Duty of Confidentiality, CLS sought permission from cohort members to access and link their routine health records to their survey data, and to the onward sharing of this linked data in pseudo-anonymised form (via a secure setting with appropriate safeguards). All data processed under the sub-license will be completed using the same legal basis as mentioned above, namely GDPR (article 6(1)(e))and GDPR (article 9(2)(j)). The CLS Licence agreement will require licencees to provide the Legal Basis of their request to link health data via CLS and therefore CLS Data Access Committee (DAC) will only grant approval to applications from researchers within public bodies who have a legal basis to process data under GDPR. The data disseminated to CLS will be accessed by substantive employees of UCL who will work on the data to make it research ready, will pseudo-anonymise the data and deposit it at the UKDS for researchers applying to use for specific projects. The pseudo-anonymised data will also be accessed by CLS employees to conduct methodological and research work via the UCL Data Safe Heaven.

Processing activities

Data disseminated from NHSD to UCL will only be accessed by substantive employees of UCL and only for the purposes described in this document. No further data is being requested and no data is being sent to NHS Digital under this version of the Agreement. The CLS Team is based at UCL. HES data will not be relinked to the identifiable data which is held separately from the survey response data. Re-identification will only happen at the occasion of a request, made from a cohort member, for withdrawal from the study, and this includes removal of data. Where a participant wishes to withdraw from the study, the identifiable data is used to locate the study id, and then in turn destroy their data. 1. CLS team have supplied NHS Digital with identifiers of cohort members who have consented to this data linkage, including full name, sex, postcode, date of birth, NHS number (if known) and study ID (study-specific pseudonymised identifier). 1. CLS team will supply NHS Digital with the following identifiers of cohort members who have consented to this data sharing; sex, postcode, date of birth, NHS number (if known) and unique ID (study-specific pseudonymised identifier). 2. NHS Digital have linked the identifiable study data to HES data. NHS Digital have removed identifiers from linked dataset and returned the pseudonymised dataset to the CLS team at UCL with the study ID. 2. NHS Digital will link the identifiable study data to HES data. NHS Digital will then remove identifiers from linked dataset and return the dataset to the CLS team at UCL with the study ID. 3. CLS carried out validation of the administrative pseudonymised data received (linked HES data) and combined the supplied administrative data with the information collected from the participant as part of the Next Steps study using the study ID. 3. CLS will carry out validation of the linked HES data and will combine the supplied HES data with the information collected from the participant as part of the BCS70 study. Once the linked survey-administrative data files have been created, CLS may perform other activities to prepare the data for use, such as coding and cleaning, derivation of summary variables and compilation of data documentation. Once the linked survey-HES data files have been created, CLS may perform other activities to prepare the data for use in research, such as coding and cleaning, derivation of summary variables and compilation of data documentation. 4. CLS researchers used these data to create an analysis file, which do not contain any identifiable data. 4. CLS researchers will use these data to create an analysis file that will not contain any identifiable data. 5. CLS created derived variables that summarise study members’ hospitalisation and health histories (e.g. hospital admissions and re-admissions, incidence of common diseases, children’s ailments etc.) and compare Next Steps survey data with data from hospital statistics, in order to compare and validate the data collected in CLS surveys. 5. CLS will create derived variables that summarise study members’ hospitalisation and health histories (e.g. hospital admissions and re-admissions, incidence of common diseases, children’s ailments etc.), and will compare BCS70 survey data with data from hospital statistics, in order to compare and validate the data collected in CLS surveys. Identifiers are held separately from attribute characteristics. HES data is not be relinked to the identifiable data which is held separately from the survey responses. Re-identification will only happen at the occasion of a request, made from a cohort member, for withdrawal from the study, and this includes removal of data. Where a participant wishes to withdraw from the study, the identifiable data is used to locate the study id, and then in turn destroy their data. Addition of the sub-licence: The process of accessing the linked data via the UKDS Service Secure Lab include the following steps: • Registration with the UKDS Service. • Submission of an application, including an ‘Accredited Researcher application form’ and ‘Research proposal’. • Screening of application by UKDS for completeness. Once a researcher has registered and UKDS has screened / approved the application: 1) UKDS sends project proposal (researcher application forms) to CLS-UCL (for Data Access Committee (DAC) approval). Applicants are required to demonstrate they have security assurance in place (System Level Security Policy/ISO Certificate/DSPT). 2) CLS-UCL sends the CLS License Agreement for Linked NHS Digital data to researchers to be completed and signed by their organisation (this includes the benefits to health and social care and evidence of organisational security assurances) not covered by UKDS application. 3) Researcher/their organisation representative will send the CLS License Agreement for Linked NHS Digital completed and signed back to CLS-UCL. 4) CLS-UCL will: a) check the organisational Information Governance and security assurance evidence provided as per Section 15 Organisational Security Assurance of the CLS Licence agreement, b) send the project for CLS DAC approval. 5) Should evidence of organisational Information Governance and security assurance provided not meet the requirements (as outlined in the sub-license) CLS will request the applicant to provide further evidence, and will only submit the project to CLS DAC for approval when evidence provided is satisfactory. Approval for data access will only be granted to applicant organisations that meet the security assurance requirement. 6) CLS DAC will assess both documents (UKDS project proposal + CLS Licence agreement) and make a decision to approve it or not approve it or require further information. Should an application be rejected, a researcher can apply again with a revised application. 7) In the CLS License agreement, CLS DAC will, among other things assess the benefits for health and social care statement, and decide whether it is satisfied with the answer. 8) Once CLS DAC approves the project : a) CLS will inform UKDS that project has been approved. b) CLS representative should sign the CLS License agreement noting the DAC reference number on the License document and send it back to the organisation of the applicant (the Principal Investigator for the study requiring access will sign the agreement - they will be an authorised signatory for their organisation). c) CLS DAC will publish the information about any data dissemination on the NHS Digital release register, including the name of the organisation to which data was provided, purpose (summary of the project) and what data was released. (NB. If CLS DAC doesn't approve the project, no data will be disseminated). 9) If CLS DAC is not satisfied with the evidence provided by the applicant about the benefits to health and social care, then CLS DAC can ask the applicant to provide additional information and the project can be re-submitted for CLS DAC approval on the next CLS DAC meeting or via Chair approval. 10) UKDS will inform the researcher that their project was approved and make the data available to them via Secure access to linked data at the Safe Centre at the UK Data Service (hosted at the University of Essex) or via the researcher’s own institutional desktop PC, depending on the sensitivity/impact level of the data being requested . Note that any data accessed through the UKDS Secure Lab can only be accessed under secure conditions and cannot be downloaded. The linked data provided to approved researchers may be subject to sub-setting of variables (and if necessary cases) to minimize disclosure risks and ensure that no individual or organisation can be identified from the results. In addition, all statistical outputs are subject to statistical disclosure control procedure. Access to the Secure Lab is only available to researchers who are be based at a UK academic institution or an ESRC-funded research centre and be an ESRC Accredited Researcher. PhD and research students can request access but must apply jointly with their supervisors from established organisations. No further onward sharing can occur beyond the sub-licence. UKDS SECURE DATA HANDLING PROCEDURES The UK Data Service has received government technical accreditation and has been certified for its secure data handling procedures under the international standard for information security (ISO 27001). To maintain this certification, regular internal and external audits are undertaken. UKDS also hires a government-approved company to conduct internal and external penetration testing of its Secure Lab systems. More widely, the UKDS employs an Information Security Management System (ISMS), to ensure compliance with the ISO accreditation. The Secure Lab falls into this system, and a number of documented processes are regularly maintained and reviewed to ensure these processes are robust, relevant, and fit-for-purpose. The ISMS is overseen by an Information Security Management Group (ISMG), which regularly meets and approves changes to procedures. UKDS DATA ACCESS MECHANISMS As an ESRC resource centre, CLS shares its survey data with the research community via the UKDS under safeguarded or controlled access mechanisms, dependent on the likelihood and potential impact of disclosure. Data with higher risk of disclosure is treated with an appropriate degree of security and management. CLS data fall into the following categories, which are defined by the likelihood and potential impact of disclosure: • Tier 1: data with low level of disclosure: e.g. participant self-reported survey data. These data are made available through the UKDS End User Licence and have a low impact of disclosure; • Tier 2a: data that is potentially disclosive: e.g. medium level and coarse geographies or sensitive information about cohort members. These data are made available through the UKDS Special Licence and have a medium impact of disclosure; • Tier 2: data that are too detailed, sensitive or confidential to be made available under the standard End User Licence or Special Licence, such as detailed geographical indicators or fine-grained individual level linked data. These data have a high impact of disclosure and are made available through the UKDS Secure Access. Access mechanisms to NHS Digital HES data linked to CLS cohort studies via the UKDS The HES data provided to CLS by NHS Digital, which are linked to the CLS cohort members, have been processed by the CLS data management team to minimise the risk of disclosivity when linked to the CLS survey data. This has been achieved by removing highly identifiable variables and altering other variables by top-coding or truncating them. Following this processing, the final health data sets have been classified under Tier 2. It is therefore CLS’s intention to deposit these Tier 2 linked HES data with the UK Data Service under the UKDS Secure Access, and provide access to this information for approved researchers, following the process and contractual arrangements, outlined above and described in more detail below, following an agreed between NHS Digital, CLS and UKDS onward sharing model. The UKDS’s ‘Controlled access to data’ specification is supplied to NHS Digital as part of this application amendment. The data provided will be pseudonymised and will be accessed only via the UKDS secure lab. Downloading the data is not possible. All organisations party to this agreement must comply with the Data Sharing Framework Contract requirements, including those regarding the use (and purposes of that use) by “Personnel” (as defined within the Data Sharing Framework Contract ie: employees, agents and contractors of the Data Recipient who may have access to that data). No further data is being requested and no data is being sent to NHS Digital under this version of the Agreement. 1. CLS team have supplied NHS Digital with identifiers of cohort members who have consented to this data linkage, including full name, sex, postcode, date of birth, NHS number (if known) and study ID (study-specific pseudonymised identifier). 2. NHS Digital have linked the identifiable study data to HES data. NHS Digital have removed identifiers from linked dataset and returned the pseudonymised dataset to the CLS team at UCL with the study ID. 3. CLS carried out validation of the administrative pseudonymised data received (linked HES data) and combined the supplied administrative data with the information collected from the participant as part of the Next Steps study using the study ID. Once the linked survey-administrative data files have been created, CLS may perform other activities to prepare the data for use, such as coding and cleaning, derivation of summary variables and compilation of data documentation. 4. CLS researchers used these data to create an analysis file, which do not contain any identifiable data. 5. CLS created derived variables that summarise study members’ hospitalisation and health histories (e.g. hospital admissions and re-admissions, incidence of common diseases, children’s ailments etc.) and compare Next Steps survey data with data from hospital statistics, in order to compare and validate the data collected in CLS surveys. Identifiers are held separately from attribute characteristics. HES data is not be relinked to the identifiable data which is held separately from the survey responses. Re-identification will only happen at the occasion of a request, made from a cohort member, for withdrawal from the study, and this includes removal of data. Where a participant wishes to withdraw from the study, the identifiable data is used to locate the study id, and then in turn destroy their data. Addition of the sub-licence: The process of accessing the linked data via the UKDS Service Secure Lab include the following steps: • Registration with the UKDS Service. • Submission of an application, including an ‘Accredited Researcher application form’ and ‘Research proposal’. • Screening of application by UKDS for completeness. Once a researcher has registered and UKDS has screened / approved the application: 1) UKDS sends project proposal (researcher application forms) to CLS-UCL (for Data Access Committee (DAC) approval). Applicants are required to demonstrate they have security assurance in place (System Level Security Policy/ISO Certificate/DSPT). 2) CLS-UCL sends the CLS License Agreement for Linked NHS Digital data to researchers to be completed and signed by their organisation (this includes the benefits to health and social care and evidence of organisational security assurances) not covered by UKDS application. 3) Researcher/their organisation representative will send the CLS License Agreement for Linked NHS Digital completed and signed back to CLS-UCL. 4) CLS-UCL will: a) check the organisational Information Governance and security assurance evidence provided as per Section 15 Organisational Security Assurance of the CLS Licence agreement, b) send the project for CLS DAC approval. 5) Should evidence of organisational Information Governance and security assurance provided not meet the requirements (as outlined in the sub-license) CLS will request the applicant to provide further evidence, and will only submit the project to CLS DAC for approval when evidence provided is satisfactory. Approval for data access will only be granted to applicant organisations that meet the security assurance requirement. 6) CLS DAC will assess both documents (UKDS project proposal + CLS Licence agreement) and make a decision to approve it or not approve it or require further information. Should an application be rejected, a researcher can apply again with a revised application. 7) In the CLS License agreement, CLS DAC will, among other things assess the benefits for health and social care statement, and decide whether it is satisfied with the answer. 8) Once CLS DAC approves the project : a) CLS will inform UKDS that project has been approved. b) CLS representative should sign the CLS License agreement noting the DAC reference number on the License document and send it back to the organisation of the applicant (the Principal Investigator for the study requiring access will sign the agreement - they will be an authorised signatory for their organisation). c) CLS DAC will publish the information about any data dissemination on the NHS Digital release register, including the name of the organisation to which data was provided, purpose (summary of the project) and what data was released. (NB. If CLS DAC doesn't approve the project, no data will be disseminated). 9) If CLS DAC is not satisfied with the evidence provided by the applicant about the benefits to health and social care, then CLS DAC can ask the applicant to provide additional information and the project can be re-submitted for CLS DAC approval on the next CLS DAC meeting or via Chair approval. 10) UKDS will inform the researcher that their project was approved and make the data available to them via Secure access to linked data at the Safe Centre at the UK Data Service (hosted at the University of Essex) or via the researcher’s own institutional desktop PC, depending on the sensitivity/impact level of the data being requested . Note that any data accessed through the UKDS Secure Lab can only be accessed under secure conditions and cannot be downloaded. The linked data provided to approved researchers may be subject to sub-setting of variables (and if necessary cases) to minimize disclosure risks and ensure that no individual or organisation can be identified from the results. In addition, all statistical outputs are subject to statistical disclosure control procedure. Access to the Secure Lab is only available to researchers who are be based at a UK academic institution or an ESRC-funded research centre and be an ESRC Accredited Researcher. PhD and research students can request access but must apply jointly with their supervisors from established organisations. No further onward sharing can occur beyond the sub-licence. UKDS SECURE DATA HANDLING PROCEDURES The UK Data Service has received government technical accreditation and has been certified for its secure data handling procedures under the international standard for information security (ISO 27001). To maintain this certification, regular internal and external audits are undertaken. UKDS also hires a government-approved company to conduct internal and external penetration testing of its Secure Lab systems. More widely, the UKDS employs an Information Security Management System (ISMS), to ensure compliance with the ISO accreditation. The Secure Lab falls into this system, and a number of documented processes are regularly maintained and reviewed to ensure these processes are robust, relevant, and fit-for-purpose. The ISMS is overseen by an Information Security Management Group (ISMG), which regularly meets and approves changes to procedures. UKDS DATA ACCESS MECHANISMS As an ESRC resource centre, CLS shares its survey data with the research community via the UKDS under safeguarded or controlled access mechanisms, dependent on the likelihood and potential impact of disclosure. Data with higher risk of disclosure is treated with an appropriate degree of security and management. CLS data fall into the following categories, which are defined by the likelihood and potential impact of disclosure: • Tier 1: data with low level of disclosure: e.g. participant self-reported survey data. These data are made available through the UKDS End User Licence and have a low impact of disclosure; • Tier 2a: data that is potentially disclosive: e.g. medium level and coarse geographies or sensitive information about cohort members. These data are made available through the UKDS Special Licence and have a medium impact of disclosure; • Tier 2: data that are too detailed, sensitive or confidential to be made available under the standard End User Licence or Special Licence, such as detailed geographical indicators or fine-grained individual level linked data. These data have a high impact of disclosure and are made available through the UKDS Secure Access. Access mechanisms to NHS Digital HES data linked to CLS cohort studies via the UKDS The HES data provided to CLS by NHS Digital, which are linked to the CLS cohort members, have been processed by the CLS data management team to minimise the risk of disclosivity when linked to the CLS survey data. This has been achieved by removing highly identifiable variables and altering other variables by top-coding or truncating them. Following this processing, the final health data sets have been classified under Tier 2. It is therefore CLS’s intention to deposit these Tier 2 linked HES data with the UK Data Service under the UKDS Secure Access, and provide access to this information for approved researchers, following the process and contractual arrangements, outlined above and described in more detail below, following an agreed between NHS Digital, CLS and UKDS onward sharing model. The UKDS’s ‘Controlled access to data’ specification is supplied to NHS Digital as part of this application amendment. The data provided will be pseudonymised and will be accessed only via the UKDS secure lab. Downloading the data is not possible. All organisations party to this agreement must comply with the Data Sharing Framework Contract requirements, including those regarding the use (and purposes of that use) by “Personnel” (as defined within the Data Sharing Framework Contract ie: employees, agents and contractors of the Data Recipient who may have access to that data).

Expected output

Following the data quality and validation work, the first output will be the creation of the linked BCS70 (Age42)/HES dataset. data set. The HES data will add an important layer to this already rich data as well as providing the means for data quality checking. CLS is currently working on the data to make it ‘research ready’. The HES/NCDS dataset is nearly ready and will be made available for researchers to apply via the UKDS once sub-licensing is approved. CLS and the UKDS will publicise the data release at both the CLS and UKDS websites. The second output will be methodological papers published in peer reviewed journals [30 words unchanged] level data with small numbers suppressed in line with HES analysis guide. The UKDS will approve statistical outputs, following a statistical disclosure control procedure and HES analysis guide for the data accessed via the UKDS secure lab. The creation of this database and the methodological papers are the first steps in establishing a robust research database which will be of benefit to health and social care. No onward sharing to researchers will take place. Any onward sharing will be subject to a further application to NHS Digital. CLS has not yet published any methodological papers reviewing the linkage. CLS expects to carry out these methodological and research assessments two/three years after the approval of this extension. This is because CLS have a policy of not using data internally for research when not available to external users and the original approval did not allow CLS to share the data with external users. Thus, CLS have focused on getting the necessary permission for sub-licencing the data. The outputs in the long term from this dataset are difficult to quantify, but the CLS currently has a searchable bibliography on it's website with over 3,600 publications based on data from the 1958, 1970 and millennium cohort studies. The creation of this HES/BCS70 database and the methodological papers are the first steps in establishing a robust research database which will be of benefit to health and social care. CLS actively promotes the use of their data among the research community through publications and briefings , working papers, webinars, social media, public reports, hosted events, as well as providing extensive documentation, guidance, training and workshops on each data set to help researchers better use the data and so ultimately benefit health and social care.

Expected measurable benefits

[3 paragraphs unchanged] HAMER, M, KIVIMAKI, M and BATTY, G.D. (2020) Blood Pressure Trajectories in Youth and Hypertension Risk in Adulthood: the 1970 British Cohort Study. American Journal of Epidemiology, 189(2), 162-163. HAMER, M. and DAVID BATTY, G. (2020) Markers of Early Life Infection in Relation to Adult Diabetes: Prospective Evidence From a National Birth Cohort Study Over Four Decades. Diabetes Care, 43(4), dc192471. HAMER, M., O'DONOVAN, G., DAVID BATTY, G. and STAMATAKIS, E. (2020) Estimated cardiorespiratory fitness in childhood and cardiometabolic health in adulthood: 1970 British Cohort Study. Scandinavian Journal of Medicine & Science in Sports, 30(5), 932-938. NORRIS, T, BANN, D, HARDY, R and JOHNSON, W. (2020) Socioeconomic inequalities in childhood-to-adulthood BMI tracking in three British birth cohorts. International Journal of Obesity, 44, 388–398. HASSIOTIS, A, BROWN, E, HARRIS, J, HELM, D, MUNIR, K, SALVADOR-CARULLA, L, BERTELLIA, M, BAGHDADLI, M, WIELAND, J, NOVELL-ALSINA, R, CID, J, VERGÉS, L, MARTÍNEZ-LEAL, R, MUTLUER, T, ISMAYILOV, F and EMERSON, E. (2019) Association of Borderline Intellectual Functioning and Adverse Childhood Experience with adult psychiatric morbidity. Findings from a British birth cohort. BMC Psychiatry, 19, 387. DOLAN, P and LORDAN, G. (2019) Climbing Up Ladders and Sliding Down Snakes: An Empirical Assessment of the Effect of Social Mobility on Subjective Wellbeing. IZA Discussion Paper 12519, 12 Aug 2019. EINIO, E, GOISIS, A and MYRSKYLA, M. (2019) Is the relationship between men's age at first birth and midlife health changing? Evidence from two British cohorts. SSM - Population Health, 8, 100458. HUANG, B-H, HAMER, M, CHASTIN, S, KOSTER, A, PEARSON, N and STAMATAKIS, E. (2019) Independent and Joint Associations of Sedentary Behavior and Physical Activity with Cardiometabolic Health Markers in the 1970 British Birth Cohort. MedRxiv, published online, 22 October 2019. GOISIS, A., SCHNEIDER, D. and MYRSKYLÄ, M. (2018) Secular changes in the association between advanced maternal age and the risk of low birth weight: a cross-cohort comparison in the UK. Population Studies, 72(3), 381-397. BANN, D., FLUHARTY, M., HARDY, R. and SCHOLES, S. (2019) Socioeconomic inequalities in blood pressure: co-ordinated analysis of 147,775 participants from repeated birth cohort and cross-sectional datasets, 1989 to 2016. MedRxiv, Posted, 21 December 2019. BROWN, M, GILBERT, E, CALDERWOOD, L, TAYLOR, K and MORGAN, H. (2019) Collecting biomedical and social data in a longitudinal survey: A comparison of two approaches. Longitudinal and Life Course Studies, 10(4), 453-469(17). AKASAKI, M, PLOUBIDIS, G.B, DODGEON, B and BONELL, C.P. (2019) The clustering of risk behaviours in adolescence and health consequences in middle age. Journal of Adolescence, 77(Dec 2019), 188-197. BOUNTZIOUKA,V, CUMBERLAND,P.M and RAHI,J.S. (2017) Trends in Visual Health Inequalities in Childhood Through Associations of Visual Function With Sex and Social Position Across 3 UK Birth Cohorts. JAMA Ophthalmology, 135(9), 954-961. BRIDGER, E and DALY, M. (2017) Does cognitive ability buffer the link between childhood disadvantage and adult health? Health Psychology, 36(10), 966-976 HAMER, M., YATES, T., SHERAR, L.B., CLEMES, S.A. and SHANKAR, A. (2016) Association of after school sedentary behaviour in adolescence with mental wellbeing in adulthood. Preventive Medicine, 87, 6-10. [4 paragraphs unchanged] Below expands further on the benefits of some of these examples of existing publications using BCS70 data drawing attention on how early life course experiences/exposures shape health outcomes into adulthood. [12 paragraphs unchanged]

Benefits reported

Yielded Benefits is not a requirement for new applications. There have been hundreds of published journal articles, books, chapters, reports or conference presentations based on data from the 1970 British Cohort Study. Below are some examples of existing publications using BCS70 data benefiting public health: AYLOR, B and WADSWORTH, J. (1987) Maternal smoking during pregnancy and lower respiratory tract illness in early life. Archives of Disease in Childhood, 62(8), 786-791. IMPACT: Research from BCS70 has contributed to the understanding of the effects of maternal smoking on child health. SUMMARY: In a national study of 12,743 children maternal, but not paternal, smoking was confirmed as having a significant influence on the reported incidence of bronchitis and admission to hospital for lower respiratory tract illness during the first five years of life. Reported rates of admissions to hospital for lower respiratory tract diseases were found to be as high in children born to mothers who stopped smoking during pregnancy as in those whose mothers smoked continuously both during and after pregnancy. Rates of admissions to hospital for lower respiratory tract diseases in children whose mothers started smoking only postnatally were no higher than in those whose mothers remained non-smokers. Postnatal smoking seemed to exert a significant influence on the reported incidence of bronchitis, but less than smoking during pregnancy. These findings suggest that maternal smoking influences the incidence of respiratory illnesses in children mainly through a congenital effect, and only to a lesser extent through passive exposure after birth. MARMOT, M and BELL, R. (2016) Social inequalities in health: a proper concern of epidemiology. Annals of Epidemiology, 26(4), 238-240. IMPACT: Research using BCS70 has highlighted an interrogated socio-economic inequalities in health. Abstract: Social inequalities are a proper concern of epidemiology. Epidemiological thinking and modes of analysis are central, but epidemiological research is one among many areas of study that provide the evidence for understanding the causes of social inequalities in health and what can be done to reduce them. Understanding the causes of health inequalities requires insights from social, behavioural and biological sciences, and a chain of reasoning that examines how the accumulation of positive and negative influences over the life course leads to health inequalities in adult life. Evidence that the social gradient in health can be reduced should make us optimistic that reducing health inequalities is a realistic goal for all societies. PLOUBIDIS, G.B, SULLIVAN, A, BROWN, M and GOODMAN, A. (2017) Psychological Distress in Mid-Life: Evidence from the 1958 and 1970 British Birth Cohorts. Psychological Medicine, 47(2), 291-303. IMPACT: Research using BCS70 has highlighted the growing problem of depression in the UK. Abstract: This paper addresses the levels of psychological distress experienced at age 42 years by men and women born in 1958 and 1970. Comparing these cohorts born 12 years apart, we ask whether psychological distress has increased, and, if so, whether this increase can be explained by differences in their childhood conditions. Data were utilized from two well-known population-based birth cohorts, the National Child Development Study and the 1970 British Cohort Study. Latent variable models and causal mediation methods were employed. After establishing the measurement equivalence of psychological distress in the two cohorts we found that men and women born in 1970 reported higher levels of psychological distress compared with those born in 1958. These differences were more pronounced in men (b = 0.314, 95% confidence interval 0.2520.375), with the magnitude of the effect being twice as strong compared with women (b = 0.147, 95% confidence interval 0.0760.218). The effect of all hypothesized early-life mediators in explaining these differences was modest. Our findings have implications for public health policy, indicating a higher average level of psychological distress among a cohort born in 1970 compared with a generation born 12 years earlier. Due to increases in life expectancy, more recently born cohorts are expected to live longer, which implies if such differences persist that they are likely to spend more years with mental health-related morbidity compared with earlier-born cohorts. V.P Mateia, A.I. Mihailescub, L.V. Diaconescuc, T. Purnischid, R. Grigorase, O. Popa-Veleac (2018) Depression in young adults diagnosed with cancer -an analysis of the outcomes of 1970 British Cohort Study. IMPACT: Research using BCS70 Cohort Study data has contributed to the understanding of the risk of depression inyoung patients diagnosed with cancer. Summary: The study found that the risk of depression is higher at people with onset of cancer before 30. The study did not identify an increased risk for depression by socioeconomic status. Instead, they suggest the importance of active screening and treatment of depression at young patients with cancer. Detailed information about the study can be found here https://www.sciencedirect.com/science/article/pii/S0022399918303088?via%3Dihub BANN, D, JOHNSON, W, LI, L, KUH, D and HARDY, R. (2018) Socioeconomic inequalities in childhood and adolescent body-mass index, weight, and height from 1953 to 2015: an analysis of four longitudinal, observational, British birth cohort studies. Lancet Public Health, 3(4), e194-e203. IMPACT: Research using BCS70 Cohort Study data has contributed to the understanding of how socioeconomic inequalities in childhood body-mass index (BMI) have been documented in high-income countries, how they have changed over time, how inequalities in the composite parts (ie, weight and height) of BMI have changed, and whether inequalities differ in magnitude across the outcome distribution. The study investigated how socioeconomic inequalities in childhood and adolescent weight, height, and BMI have changed over time in Britain. Detailed information about the study can be found here: https://www.sciencedirect.com/science/article/pii/S2468266718300458?via%3Dihub CHENG, H and FURNHAM, A. (2018) Teenage locus of control, psychological distress, educational qualifications and occupational prestige as well as sex are independent predictors of adult binge drinking. Alcohol, advance online access, 1 Sept 2018. IMPACT : Research using BCS70 Cohort Study data has contributed to the understanding of how various psychological and socio-demographic factors in childhood and adulthood that relate to alcohol intake and binge drinking at age 42 years. Abstract: Data were drawn from the 1970 British Cohort Study (BCS70), The analytic sample comprised 5267 cohort members with data on parental social class at birth, cognitive ability at age 10, locus of control at age 16, psychological distress at age 30, educational qualifications at age 34, and current occupation and alcohol consumption at age 42 years. Results showed that sex (male), lower parental social class, adolescent external locus of control, psychological distress, lower scores on childhood intelligence, lower educational qualifications and less professional occupations were all significantly and positively associated with binge drinking in adulthood. Both psychological and social factors influence adult excessive alcohol consumption. Adolescent locus of control beliefs had a modest but significant effect on adult binge drinking 26 years later. Detailed information can be found here: https://www.sciencedirect.com/science/article/pii/S0741832916301677?via%3Dihub