Distinct trajectories of multimorbidity in primary care were identified using latent class growth analysis
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...
| Hlavní autoři: | , , , |
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| Médium: | Journal article |
| Jazyk: | English |
| Vydáno: |
Elsevier
2014
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| _version_ | 1826300101737316352 |
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| author | Strauss, V Jones, P Kadam, U Jordan, K |
| author_facet | Strauss, V Jones, P Kadam, U Jordan, K |
| author_sort | Strauss, V |
| collection | OXFORD |
| description | 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. |
| first_indexed | 2024-03-07T05:12:02Z |
| format | Journal article |
| id | oxford-uuid:dbe40539-c0bd-4fc6-992f-ad6b51a48c6d |
| institution | University of Oxford |
| language | English |
| last_indexed | 2024-03-07T05:12:02Z |
| publishDate | 2014 |
| publisher | Elsevier |
| record_format | dspace |
| spelling | oxford-uuid:dbe40539-c0bd-4fc6-992f-ad6b51a48c6d2022-03-27T09:13:51ZDistinct trajectories of multimorbidity in primary care were identified using latent class growth analysisJournal articlehttp://purl.org/coar/resource_type/c_dcae04bcuuid:dbe40539-c0bd-4fc6-992f-ad6b51a48c6dEnglishSymplectic Elements at OxfordElsevier2014Strauss, VJones, PKadam, UJordan, KObjectives 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. |
| spellingShingle | Strauss, V Jones, P Kadam, U Jordan, K Distinct trajectories of multimorbidity in primary care were identified using latent class growth analysis |
| title | Distinct trajectories of multimorbidity in primary care were identified using latent class growth analysis |
| title_full | Distinct trajectories of multimorbidity in primary care were identified using latent class growth analysis |
| title_fullStr | Distinct trajectories of multimorbidity in primary care were identified using latent class growth analysis |
| title_full_unstemmed | Distinct trajectories of multimorbidity in primary care were identified using latent class growth analysis |
| title_short | Distinct trajectories of multimorbidity in primary care were identified using latent class growth analysis |
| title_sort | distinct trajectories of multimorbidity in primary care were identified using latent class growth analysis |
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