Abstract
Objective
To assess the prevalence, disease clusters, and patterns of multimorbidity using a
novel 2-stage approach in middle-aged and older adults from the United Kingdom.
Patients and Methods
Data on 36 chronic conditions from 502,643 participants aged 40 to 69 years with baseline
measurements between March 13, 2006, and October 1, 2010, from the UK Biobank were
extracted. We combined cluster analysis and association rule mining to assess patterns
of multimorbidity overall and by age, sex, and ethnicity. A maximum of 3 clusters
and 30 disease patterns were mined. Comparisons were made using lift as the main measure
of association.
Results
Ninety-five thousand seven hundred-ten participants (19%) had 2 or more chronic conditions.
The first cluster included only myocardial infarction and angina (lift=13.3), indicating
that the likelihood of co-occurrence of these conditions is 13 times higher than in
isolation. The second cluster consisted of 26 conditions, including cardiovascular,
musculoskeletal, respiratory, and neurodegenerative diseases. The strongest association
was found between heart failure and atrial fibrillation (lift=23.6). Diabetes was
at the center of this cluster with strong associations with heart failure, chronic
kidney disease, liver failure, and stroke (lift>2). The third cluster contained 8
highly prevalent conditions, including cancer, hypertension, asthma, and depression,
and the strongest association was observed between anxiety and depression (lift=5.0).
Conclusion
Conditions such as diabetes, hypertension, and asthma are the epicenter of disease
clusters for multimorbidity. A more integrative multidisciplinary approach focusing
on better management and prevention of these conditions may help prevent other conditions
in the clusters.
Abbreviations and Acronyms:
ARM (association rule mining), CKD (chronic kidney disese), COPD (chronic obstructive pulmonary disease), CV (cardiovascular), IBD (irritable bowel disease), IBS (irritable bowel syndrome), IQR (interquartile range), MI (myocardial infarction), PVD (peripheral vascular disease)To read this article in full you will need to make a payment
Purchase one-time access:
Academic & Personal: 24 hour online accessCorporate R&D Professionals: 24 hour online accessOne-time access price info
- For academic or personal research use, select 'Academic and Personal'
- For corporate R&D use, select 'Corporate R&D Professionals'
Subscribe:
Subscribe to Mayo Clinic ProceedingsAlready a print subscriber? Claim online access
Already an online subscriber? Sign in
Register: Create an account
Institutional Access: Sign in to ScienceDirect
References
- Long Term Conditions Compendium of Information.3rd ed. Department of Health, London, UK2012
- Burden of multimorbidity, socioeconomic status and use of health services across stages of life in urban areas: a cross-sectional study.BMC Public Health. 2014; 14: 530
- Prevalence and patterns of multimorbidity among elderly people in rural Bangladesh: a cross-sectional study.J Health Popul Nutr. 2011; 29: 406
- Prevalence of chronic diseases and multimorbidity among the elderly population in Sweden.Am J Public Health. 2008; 98: 1198
- Patterns and impact of comorbidity and multimorbidity among community-resident American Indian elders.Gerontologist. 2003; 43: 649-660
- Multimorbidity and quality of life: a closer look.Health Qual Life Outcomes. 2007; 5: 52
- Multimorbidity redefined: prospective health outcomes and the cumulative effect of co-occurring conditions.Prev Chronic Dis. 2015; 12: E55
- The impact of multimorbidity on adult physical and mental health in low-and middle-income countries: what does the study on global ageing and adult health (SAGE) reveal?.BMC Med. 2015; 13: 178
- Multimorbidity, health care utilization and costs in an elderly community-dwelling population: a claims data based observational study.BMC Health Serv Res. 2015; 15: 23
- Multimorbidity patterns: a systematic review.J Clin Epidemiol. 2014; 67: 254-266
- Prevalence, determinants and patterns of multimorbidity in primary care: a systematic review of observational studies.PLoS One. 2014; 9: e102149
- The influence of age, gender and socio-economic status on multimorbidity patterns in primary care. First results from the multicare cohort study.BMC Health Serv Res. 2012; 12: 89
- Similar multimorbidity patterns in primary care patients from two European regions: results of a factor analysis.PLoS One. 2014; 9: e100375
- Lifestyle and socioeconomic determinants of multimorbidity patterns among mid-aged women: a longitudinal study.PLoS One. 2016; 11: e0156804
- Multimorbidity and its patterns according to immigrant origin: a Nationwide Register-Based Study in Norway.PLoS One. 2015; 10: e0145233
- Global multimorbidity patterns: a cross-sectional, population-based, multi-country study.J Gerontol A Biol Sci Med Sci. 2016; 71: 205-214
- Prevalence and patterns of chronic disease pairs and multimorbidity among older Chinese adults living in a rural area.PLoS One. 2015; 10: e0138521
- Multimorbidity patterns in primary care: interactions among chronic diseases using factor analysis.PLoS One. 2012; 7: e32190
- Patterns and consequences of multimorbidity in the general population: there is no chronic disease management without rheumatic disease management.Arthritis Care Res. 2016; 69: 12-20
- Identifying patterns of multimorbidity in older Americans: application of latent class analysis.J Am Geriatr Soc. 2016; 64: 1668-1673
- Multimorbidity patterns in elderly primary health care patients in a South Mediterranean European region: a cluster analysis.PLoS One. 2015; 10: e0141155
- Patterns of multimorbidity in the aged population: results from the KORA-Age study.PLoS One. 2012; 7: e30556
- Multimorbidity patterns in hospitalized older patients: associations among chronic diseases and geriatric syndromes.PLoS One. 2015; 10: e0132909
- Multimorbidity: Clinical Assessment and Management.National Institute for Health and Care Excellence, London, UKSeptember 2016 (NICE guideline NG56)
- Managing patients with multimorbidity: systematic review of interventions in primary care and community settings.BMJ. 2012; 345: e5205
- UK Biobank: from concept to reality.Pharmacogenomics. 2005; 6: 639-646
- UK Biobank Assessment Centres: operational durations.
- UK Biobank: an open access resource for identifying the causes of a wide range of complex diseases of middle and old age.PLoS Med. 2015; 12: 3
- Epidemiology of multimorbidity and implications for health care, research, and medical education: a cross-sectional study.Lancet. 2012; 380: 37-43
- Aging with multimorbidity: a systematic review of the literature.Ageing Res Rev. 2011; 10: 430-439
- The measurement of multiple chronic diseases: a systematic review on existing multimorbidity indices.J Gerontol A Biol Sci Med Sci. 2011; 66: 301-311
- Setting performance targets in pay for performance programmes: what can we learn from QOF?.BMJ. 2014; 348: g1595
- Deprivation data.https://census.ukdataservice.ac.uk/get-data/related/deprivationDate accessed: March 15, 2017
- Health and Deprivation: Inequality and the North.Croom Helm, London, UK1988
- Identifying change over time in small area socio-economic deprivation.Appl Spatial Anal Policy. 2010; 3: 107-138
- Townsend deprivation index.http://www.restore.ac.uk/geo-refer/36229dtuks00y19810000.phpDate: 2007Date accessed: December 23, 2016
- The New S Language.Wadsworth & Brooks, Pacific Grove, CA1988
- Association rules analysis of comorbidity and multimorbidity: the Concord Health and Aging in Men Project.J Gerontol A Biol Sci Med Sci. 2016; 71: 625-631
- Multimorbidity in General Practice: Adverse Health Effects and Innovative Research Strategies.Universitaire Pers Pers, 2012 (Maastricht University, The Netherlands)
- General Lifestyle Survey. Vol 2013. Office for National Statistics, Wales, UK2011
- Accuracy of self-reported diabetes, hypertension and hyperlipidemia in the adult Spanish population: DINO Study findings.Rev Esp Cardiol. 2009; 62: 143-152
- Ascertainment of chronic diseases using population health data: a comparison of health administrative data and patient self-report.BMC Public Health. 2013; 13: 16
- Prevalence of measured and reported multimorbidity in a representative sample of the Swiss population.BMC Public Health. 2015; 15: 164
- Do race, ethnicity, and psychiatric diagnoses matter in the prevalence of multiple chronic medical conditions?.Med Care. 2013; 51: 540
- How does the trajectory of multimorbidity vary across Black, White, and Mexican Americans in middle and old age?.J Gerontol B Psychol Sci Soc Sci. 2011; 66: 739-749
- Patients with epilepsy are at an increased risk of subsequent stroke: a population-based cohort study.Seizure. 2014; 23: 377-381
- Exploring the pathogenetic association between schizophrenia and type 2 diabetes mellitus diseases based on pathway analysis.BMC Med Genomics. 2013; 6: S17
- Psychiatric co-morbidity with type 1 and type 2 diabetes mellitus/Comorbidite psychiatrique et diabete de type 1 et de type 2.East Mediterr Health J. 2011; 17: 777-783
- Prevalence of cardiovascular risk factors and disease in people with schizophrenia: a population-based study.Schizophr Res. 2010; 117: 75-82
- Higher comorbidity of depression and cardiovascular disease in women: a biopsychosocial perspective.World J Biol Psychiatry. 2010; 11: 922-933
- Depression and risk of heart failure among the elderly: a prospective community-based study.Psychosom Med. 2002; 64: 6-12
- Prevalence of multimorbidity in a geographically defined American population: patterns by age, sex, and race/ethnicity.Mayo Clin Proc. 2014; 89: 1336-1349
- Prevalence of combined somatic and mental health multimorbidity: patterns by age, sex, and race/ethnicity.J Gerontol A Biol Sci Med Sci. 2016; 71: 1483-1491
Article Info
Publication History
Published online: May 22, 2018
Footnotes
For editorial comment, see page 824
Grant Support: This study was supported by the National Institute for Health Research (NIHR) Collaboration for Leadership in Applied Health Research and Care–East Midlands, the Leicester Clinical Trials Unit, and the NIHR Leicester–Loughborough Diet, Lifestyle, and Physical Activity Biomedical Research Unit, which is a partnership between University Hospitals of Leicester National Health Service Trust, Loughborough University, and the University of Leicester.
Potential Competing Interests: Professor Davies has acted as a consultant, advisory board member, and speaker for Novo Nordisk, Sanofi-Aventis, Lilly, Merck Sharp & Dohme, Boehringer Ingelheim, AstraZeneca, and Janssen; has served as a speaker for Mitsubishi Tanabe Pharma Corp; and has received grants in support of investigator and investigator-initiated trials from Novo Nordisk, Sanofi-Aventis, and Lilly. Professor Khunti has acted as a consultant and speaker for Novartis, Novo Nordisk, Sanofi-Aventis, Lilly, Servier, and Merck Sharp & Dohme; has received grants in support of investigator and investigator-initiated trials from Novartis, Novo Nordisk, Sanofi-Aventis, Lilly, Pfizer, Boehringer Ingelheim, and Merck Sharp & Dohme; and has received funds for research, has received honoraria for speaking at meetings, and has served on advisory boards for Lilly, Sanofi-Aventis, Merck Sharp & Dohme, and Novo Nordisk. The rest of the authors report no competing interests.
Identification
Copyright
© 2018 Mayo Foundation for Medical Education and Research
