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Robustly measuring multimorbidity using disparate linked datasets.

Regina Prigge1, Kelly J Fleetwood2, Caroline A Jackson2

  • 1Usher Institute, University of Edinburgh, Edinburgh, UK. regina.prigge@ed.ac.uk.

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|July 8, 2025
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Summary
This summary is machine-generated.

Research on multimorbidity, the presence of multiple long-term conditions (LTCs), is inconsistent. This study shows that the data source significantly impacts prevalence estimates for LTCs and multimorbidity, affecting research reproducibility.

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Area of Science:

  • Biomedical Informatics
  • Public Health Research
  • Epidemiology

Background:

  • Measuring multimorbidity (multiple long-term conditions) is inconsistent, hindering research reproducibility.
  • The co-occurrence of two or more conditions in an individual is termed multimorbidity.

Purpose of the Study:

  • To assess how different data sources influence the estimated prevalence of 80 long-term conditions (LTCs) and multimorbidity.
  • To compare prevalence estimates derived from primary care records, UK Biobank baseline assessments, and hospital/cancer registry data.

Main Methods:

  • Utilized a cross-sectional approach with data from 172,563 UK Biobank participants.
  • Developed code-list-based algorithms to ascertain LTC prevalence across three distinct data sources.
  • Analyzed prevalence using primary care records, UK Biobank baseline data, hospital/cancer registry records, and a combination of all three.

Main Results:

  • When combining all data sources, 85.1% of participants had at least one LTC and 63.5% had at least two.
  • Data source choice significantly impacts prevalence estimates, with low agreement (median 4.7%) across all three sources for identifying individuals with a condition.
  • Agreement was highest for endocrine disorders and lowest for genitourinary and mental/behavioural disorders, with primary care data often identifying unique cases.

Conclusions:

  • The selection of data sources critically affects research findings on individual LTCs and multimorbidity.
  • Researchers must clearly justify their chosen data sources to ensure transparency and reproducibility in multimorbidity studies.