Fabian P Held1, Fiona Blyth2, Danijela Gnjidic3, Vasant Hirani4, Vasikaran Naganathan5, Louise M Waite5, Markus J Seibel6, Jennifer Rollo1, David J Handelsman6, Robert G Cumming7, David G Le Couteur8. 1. Charles Perkins Centre, University of Sydney, New South Wales, Australia. 2. Centre for Education and Research on Ageing and the Ageing and Alzheimers Institute, University of Sydney and Concord Hospital, New South Wales, Australia. 3. Centre for Education and Research on Ageing and the Ageing and Alzheimers Institute, University of Sydney and Concord Hospital, New South Wales, Australia. Faculty of Pharmacy. 4. Centre for Education and Research on Ageing and the Ageing and Alzheimers Institute, University of Sydney and Concord Hospital, New South Wales, Australia. School of Public Health, ARC Centre of Excellence in Population Ageing Research. 5. Centre for Education and Research on Ageing and the Ageing and Alzheimers Institute, University of Sydney and Concord Hospital, New South Wales, Australia. ANZAC Research Institute, University of Sydney, New South Wales, Australia. 6. ANZAC Research Institute, University of Sydney, New South Wales, Australia. 7. Centre for Education and Research on Ageing and the Ageing and Alzheimers Institute, University of Sydney and Concord Hospital, New South Wales, Australia. School of Public Health, ARC Centre of Excellence in Population Ageing Research, ANZAC Research Institute, University of Sydney, New South Wales, Australia. 8. Charles Perkins Centre, University of Sydney, New South Wales, Australia. Centre for Education and Research on Ageing and the Ageing and Alzheimers Institute, University of Sydney and Concord Hospital, New South Wales, Australia. ANZAC Research Institute, University of Sydney, New South Wales, Australia. david.lecouteur@sydney.edu.au.
Abstract
BACKGROUND: Comorbidity and multimorbidity are common in older people. Here we used a novel analytic approach called Association Rules together with network analysis to evaluate multimorbidity (two or more disorders) and comorbidity in old age. METHODS: A population-based cross-sectional study was undertaken where 17 morbidities were analyzed using network analysis, cluster analysis, and Association Rules methodology. A comorbidity interestingness score was developed to quantify the richness and variability of comorbidities associated with an index condition. The participants were community-dwelling men aged 70 years or older from the Concord Health and Ageing in Men Project, Sydney, Australia, with complete data (n = 1,464). RESULTS: The vast majority (75%) of participants had multimorbidity. Several morbidity clusters were apparent (vascular cluster, metabolic cluster, neurodegenerative cluster, mental health and other cluster, and a musculoskeletal and other cluster). Association Rules revealed unexpected comorbidities with high lift and confidence linked to index diseases. Anxiety and heart failure had the highest comorbidity interestingness scores while obesity, hearing impairment, and arthritis had the lowest (zero) scores. We also performed Association Rules analysis for the geriatric syndromes of frailty and falls to determine their association with multimorbidity. Frailty had a very complex and rich set of frequent and interesting comorbidities, while there were no frequent and interesting sets associated with falls. CONCLUSIONS: Old age is characterized by a complex pattern of multimorbidity and comorbidity. Single disease definitions do not account for the prevalence and complexity of multimorbidity in older people and a new lexicon may be needed to underpin research and health care interventions for older people.
BACKGROUND: Comorbidity and multimorbidity are common in older people. Here we used a novel analytic approach called Association Rules together with network analysis to evaluate multimorbidity (two or more disorders) and comorbidity in old age. METHODS: A population-based cross-sectional study was undertaken where 17 morbidities were analyzed using network analysis, cluster analysis, and Association Rules methodology. A comorbidity interestingness score was developed to quantify the richness and variability of comorbidities associated with an index condition. The participants were community-dwelling men aged 70 years or older from the Concord Health and Ageing in Men Project, Sydney, Australia, with complete data (n = 1,464). RESULTS: The vast majority (75%) of participants had multimorbidity. Several morbidity clusters were apparent (vascular cluster, metabolic cluster, neurodegenerative cluster, mental health and other cluster, and a musculoskeletal and other cluster). Association Rules revealed unexpected comorbidities with high lift and confidence linked to index diseases. Anxiety and heart failure had the highest comorbidity interestingness scores while obesity, hearing impairment, and arthritis had the lowest (zero) scores. We also performed Association Rules analysis for the geriatric syndromes of frailty and falls to determine their association with multimorbidity. Frailty had a very complex and rich set of frequent and interesting comorbidities, while there were no frequent and interesting sets associated with falls. CONCLUSIONS: Old age is characterized by a complex pattern of multimorbidity and comorbidity. Single disease definitions do not account for the prevalence and complexity of multimorbidity in older people and a new lexicon may be needed to underpin research and health care interventions for older people.
Authors: Vanessa P Ho; Nicholas K Schiltz; Andrew P Reimer; Elizabeth A Madigan; Siran M Koroukian Journal: J Am Geriatr Soc Date: 2018-12-02 Impact factor: 5.562
Authors: Shajjia Razi; Victoria C Cogger; Marina Kennerson; Vicky L Benson; Aisling C McMahon; Fiona M Blyth; David J Handelsman; Markus J Seibel; Vasant Hirani; Vasikaran Naganathan; Louise Waite; Rafael de Cabo; Robert G Cumming; David G Le Couteur Journal: J Gerontol A Biol Sci Med Sci Date: 2017-07-01 Impact factor: 6.053
Authors: Claire B Rosen; Chris Wirtalla; Luke J Keele; Sanford E Roberts; Elinore J Kaufman; Daniel N Holena; Scott D Halpern; Rachel R Kelz Journal: Med Care Date: 2022-05-30 Impact factor: 3.178