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Distinct trajectories of multimorbidity in primary care were identified using latent class growth analysis.

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journal contribution
posted on 2019-10-23, 14:21 authored by Vicky Y. Strauss, Peter W. Jones, Umesh T. Kadam, Kelvin P. Jordan
OBJECTIVES: To investigate the use of latent class growth analysis (LCGA) in understanding onset and changes in multimorbidity over time in older adults. STUDY DESIGN AND SETTING: This study used primary care consultations for 42 consensus-defined chronic morbidities over 3 years (2003-2005) by 24,615 people aged >50 years at 10 UK general practices, which contribute to the Consultations in Primary Care Archive database. Distinct groups of people who had similar progression of multimorbidity over time were identified using LCGA. These derived trajectories were tested in another primary care consultation data set with linked self-reported health status. RESULTS: Five clusters of people representing different trajectories were identified: those who had no recorded chronic problems (40%), those who developed a first chronic morbidity over 3 years (10%), a developing multimorbidity group (37%), a group with increasing number of chronic morbidities (12%), and a multi-chronic group with many chronic morbidities (1%). These trajectories were also identified using another consultation database and associated with self-reported physical and mental health. CONCLUSION: There are distinct trajectories in the development of multimorbidity in primary care populations, which are associated with poor health. Future research needs to incorporate such trajectories when assessing progression of disease and deterioration of health.


: Consultations in Primary Care Archive was funded by the North Staffordshire Primary Care Research Consortium and Keele University Institute for Primary Care and Health Sciences. The North Staffordshire Osteoarthritis Project study was supported by the Medical Research Council, UK program grant (grant code: G9900220) and the North Staffordshire Primary Care R&D Consortium for National Health Service service support costs.



Journal of Clinical Epidemiology, 2014, 67 (10), pp. 1163-1171

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