Skip to main page content
U.S. flag

An official website of the United States government

Dot gov

The .gov means it’s official.
Federal government websites often end in .gov or .mil. Before sharing sensitive information, make sure you’re on a federal government site.

Https

The site is secure.
The https:// ensures that you are connecting to the official website and that any information you provide is encrypted and transmitted securely.

Access keys NCBI Homepage MyNCBI Homepage Main Content Main Navigation
. 2025 Jan 7;15(1):e087946.
doi: 10.1136/bmjopen-2024-087946.

Cohort profile: creation of the SAIL MELD-B e-cohort (SMC) and SAIL MELD-B children and young adult e-cohort (SMYC) to investigate the lived experience of the 'burdensomeness' of multimorbidity

Roberta Chiovoloni  1 , Jakub J Dylag  2 , Nisreen A Alwan  3   4 , Ann Berrington  5 , Michael Boniface  2 , Nic Fair  2 , Emilia Holland  3 , Rebecca Hoyle  6 , Mozhdeh Shiranirad  6 , Sebastian Stannard  3 , Zlatko Zlatev  2 , Rhiannon K Owen  7 , Simon Fraser  3 , Ashley Akbari  7
Affiliations

Cohort profile: creation of the SAIL MELD-B e-cohort (SMC) and SAIL MELD-B children and young adult e-cohort (SMYC) to investigate the lived experience of the 'burdensomeness' of multimorbidity

Roberta Chiovoloni et al. BMJ Open. .

Abstract

Purpose: We have established the SAIL MELD-B electronic cohort (e-cohort SMC) and the SAIL MELD-B children and Young adults e-cohort (SMYC) as a part of the Multidisciplinary Ecosystem to study Lifecourse Determinants and Prevention of Early-onset Burdensome Multimorbidity (MELD-B) project. Each cohort has been created to investigate and develop a deeper understanding of the lived experience of the 'burdensomeness' of multimorbidity by identifying new clusters of burdensomeness concepts, exploring early life risk factors of multimorbidity and modelling hypothetical prevention scenarios.

Participants: The SMC and SMYC are longitudinal e-cohorts created from routinely collected individual-level population-scale anonymised data sources available within the Secure Anonymised Information Linkage (SAIL) Databank. They include individuals with available records from linked health and demographic data sources in SAIL at any time between 1 January 2000 and 31 December 2022. The SMYC e-cohort is a subset of the SMC, including only individuals born on or after the cohort start date.

Findings to date: The SMC and SMYC cohorts include 5 180 602 (50.3% female and 49.7% male) and 896 155 (48.7% female and 51.3% male) individuals, respectively. Considering both primary and secondary care health data, the five most common long-term conditions for individuals in SMC are 'Depression', affecting 21.6% of the cohort, 'Anxiety' (21.1%), 'Asthma' (17.5%), 'Hypertension' (16.2%) and 'Atopic Eczema' (14.1%) and the five most common conditions for individuals in SMYC are 'Atopic Eczema' (21.2%), 'Asthma' (11.6%), 'Anxiety' (6.0%), 'Deafness' (4.6%) and 'Depression' (4.3%).

Future plans: The SMC and SMYC e-cohorts have been developed using a reproducible, maintainable concept curation pipeline, which allows for the cohorts to be updated dynamically over time and manages for the request and processing of further approved long-term conditions and burdensomeness concepts extraction. Best practices from the MELD-B project can be utilised across other projects, accessing similar data with population-scale data sources and trusted research environments.

Keywords: Chronic Disease; Electronic Health Records; Multimorbidity; STATISTICS & RESEARCH METHODS.

PubMed Disclaimer

Conflict of interest statement

Competing interests: The author(s) declared the following potential conflicts of interest with respect to the research, authorship and/or publication of this article: RKO is a member of the National Institute for Health and Care Excellence (NICE) Technology Appraisal Committee, member of the NICE Decision Support Unit (DSU)and associate member of the NICE Technical Support Unit (TSU). She has served as a paid consultant providing unrelated methodological advice to AstraZeneca, Cogentia Healthcare Ltd, Daiichi Sankyo, NICE, the Norwegian Institute of Public Health, Roche and Vifor Pharma. She reports teaching fees from the Association of British Pharmaceutical Industry (ABPI) and the University of Bristol. RH is a member of the Scientific Board of the Smith Institute for Industrial Mathematics and System Engineering. All other authors declare that there are no further conflicts of interest.

Figures

Figure 1
Figure 1. SAIL MELD-B consort diagram based on inclusion criteria. DOD, Date of Death; GP, general practise; SMC, SAIL MELD-B e-cohort; SMYC, SAIL MELD-B Young cohort; WDSD, Welsh Demographic Service Data set; WOB, Week of Birth.
Figure 2
Figure 2. Concept curation pipeline to extract relevant data for SMC and SMYC. SMC, SAIL MELD-B e-cohort; SMYC, SAIL MELD-B children and Young adult e-cohort.
Figure 3
Figure 3. Pyramid plot of SMC at cohort start date. SMC, SAIL MELD-B e-cohort.
Figure 4
Figure 4. Individuals leaving and joining SMC and SMYC each year. Note that in the SMYC plot, the ‘Lost to follow-up’ line almost coincides with the ‘total individuals leaving the cohort’ line. SMC, SAIL MELD-B e-cohort; SMYC, SAIL MELD-B children and Young adult e-cohort.
Figure 5
Figure 5. Percentages of individuals residing in LSOA with WIMD=1,2,3,4 or 5 on 1 January of every year during the cohort study period. LSOA, Lower-layer Super Output Area; SMC, SAIL MELD-B e-cohort; SMYC, SAIL MELD-B children and Young adult e-cohort; WIMD, Welsh Index of Multiple Deprivation.
Figure 6
Figure 6. 20 most common concepts for SMC and SMYC. The number on the bars represents the % of individuals for each sex with records of each concept compared with the complete SMC. SMC, SAIL MELD-B e-cohort; SMYC, SAIL MELD-B children and Young adult e-cohort.
See this image and copyright information in PMC

Similar articles

See all similar articles

Cited by

References

    1. Fortin M, Haggerty J, Almirall J, et al. Lifestyle factors and multimorbidity: a cross sectional study. BMC Public Health. 2014;14:686. doi: 10.1186/1471-2458-14-686. - DOI - PMC - PubMed
    1. Kingston A, Robinson L, Booth H, et al. Projections of multi-morbidity in the older population in England to 2035: estimates from the Population Ageing and Care Simulation (PACSim) model. Age Ageing. 2018;47:374–80. doi: 10.1093/ageing/afx201. - DOI - PMC - PubMed
    1. Lawson KD, Mercer SW, Wyke S, et al. Double trouble: the impact of multimorbidity and deprivation on preference-weighted health related quality of life a cross sectional analysis of the Scottish Health Survey. Int J Equity Health. 2013;12:67. doi: 10.1186/1475-9276-12-67. - DOI - PMC - PubMed
    1. Berntsen G, Høyem A, Lettrem I, et al. A person-centered integrated care quality framework, based on a qualitative study of patients’ evaluation of care in light of chronic care ideals. BMC Health Serv Res. 2018;18:1–15. doi: 10.1186/S12913-018-3246-Z/TABLES/2. - DOI - PMC - PubMed
    1. Salisbury C, Johnson L, Purdy S, et al. Epidemiology and impact of multimorbidity in primary care: a retrospective cohort study. Br J Gen Pract. 2011;61:e12–21. doi: 10.3399/bjgp11X548929. - DOI - PMC - PubMed

LinkOut - more resources