Trajectories of multiple long-term conditions and mortality in older adults: A retrospective cohort study using English Longitudinal Study of Ageing (ELSA)
Trajectories of multiple long-term conditions and mortality in older adults: A retrospective cohort study using English Longitudinal Study of Ageing (ELSA)
OBJECTIVES: To classify older adults with MLTC into clusters based on accumulating conditions as trajectories over time, characterise clusters and quantify associations between derived clusters and all-cause mortality.
DESIGN: We conducted a retrospective cohort study using the English Longitudinal Study of Ageing (ELSA) over nine years (n=15,091 aged 50 years and older). Group-based trajectory modelling was used to classify people into MLTC clusters based on accumulating conditions over time. Derived clusters were used to quantify the associations between MLTC trajectory memberships, sociodemographic characteristics, and all-cause mortality.
RESULTS: Five distinct clusters of MLTC trajectories were identified and characterised as: "no-LTC" (18.57%), "single-LTC" (31.21%), "evolving MLTC" (25.82%), "moderate MLTC" (17.12%), and "high MLTC" (7.27%). Increasing age was consistently associated with an increased number of MLTC. Female sex (aOR = 1.13; 95%CI 1.01 to 1.27) and ethnic minority (aOR = 2.04; 95%CI 1.40 to 3.00) were associated with the "moderate MLTC" and "high MLTC" clusters, respectively. Higher education and paid employment were associated with a lower likelihood of progression over time towards an increased number of MLTC. All the clusters had higher all-cause mortality than the "no-LTC" cluster.
CONCLUSIONS: The development of MLTC and the increase in the number of conditions over time follow distinct trajectories. These are determined by non-modifiable (age, sex, ethnicity) and modifiable factors (education and employment). Stratifying risk through clustering will enable practitioners to identify older adults with a higher likelihood of worsening MLTC over time to tailor effective interventions.
Chalitsios, Christos V
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Santoso, Cornelia
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Nartey, Yvonne
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Khan, Nusrat
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Simpson, Glenn
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Islam, Nazrul
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Stuart, Beth
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Farmer, Andrew
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Dambha-Miller, Hajira
58961db5-31aa-460e-9394-08590c4b7ba1
19 May 2023
Chalitsios, Christos V
a96ff8c1-a547-46a5-b254-224a1764f3d5
Santoso, Cornelia
a10d071e-662f-4324-b84c-fde52f6c5153
Nartey, Yvonne
18b02d48-c668-497a-a1ee-8695b013960a
Khan, Nusrat
0da3cc33-cd6e-4846-a790-ffc05f53d5d1
Simpson, Glenn
802b50d9-aa00-4cca-9eaf-238385f8481c
Islam, Nazrul
e5345196-7479-438f-b4f6-c372d2135586
Stuart, Beth
626862fc-892b-4f6d-9cbb-7a8d7172b209
Farmer, Andrew
c384123c-1276-4d06-a2b5-d5419bd83b1d
Dambha-Miller, Hajira
58961db5-31aa-460e-9394-08590c4b7ba1
Chalitsios, Christos V, Santoso, Cornelia, Nartey, Yvonne, Khan, Nusrat, Simpson, Glenn, Islam, Nazrul, Stuart, Beth, Farmer, Andrew and Dambha-Miller, Hajira
(2023)
Trajectories of multiple long-term conditions and mortality in older adults: A retrospective cohort study using English Longitudinal Study of Ageing (ELSA).
(doi:10.1101/2023.05.18.23290151).
Abstract
OBJECTIVES: To classify older adults with MLTC into clusters based on accumulating conditions as trajectories over time, characterise clusters and quantify associations between derived clusters and all-cause mortality.
DESIGN: We conducted a retrospective cohort study using the English Longitudinal Study of Ageing (ELSA) over nine years (n=15,091 aged 50 years and older). Group-based trajectory modelling was used to classify people into MLTC clusters based on accumulating conditions over time. Derived clusters were used to quantify the associations between MLTC trajectory memberships, sociodemographic characteristics, and all-cause mortality.
RESULTS: Five distinct clusters of MLTC trajectories were identified and characterised as: "no-LTC" (18.57%), "single-LTC" (31.21%), "evolving MLTC" (25.82%), "moderate MLTC" (17.12%), and "high MLTC" (7.27%). Increasing age was consistently associated with an increased number of MLTC. Female sex (aOR = 1.13; 95%CI 1.01 to 1.27) and ethnic minority (aOR = 2.04; 95%CI 1.40 to 3.00) were associated with the "moderate MLTC" and "high MLTC" clusters, respectively. Higher education and paid employment were associated with a lower likelihood of progression over time towards an increased number of MLTC. All the clusters had higher all-cause mortality than the "no-LTC" cluster.
CONCLUSIONS: The development of MLTC and the increase in the number of conditions over time follow distinct trajectories. These are determined by non-modifiable (age, sex, ethnicity) and modifiable factors (education and employment). Stratifying risk through clustering will enable practitioners to identify older adults with a higher likelihood of worsening MLTC over time to tailor effective interventions.
Text
2023.05.18.23290151v1.full
- Author's Original
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Published date: 19 May 2023
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Local EPrints ID: 477952
URI: http://eprints.soton.ac.uk/id/eprint/477952
PURE UUID: b5e4a23c-abc4-4779-ba60-9cd55b91ea84
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Date deposited: 16 Jun 2023 16:52
Last modified: 17 Mar 2024 04:15
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Author:
Christos V Chalitsios
Author:
Cornelia Santoso
Author:
Yvonne Nartey
Author:
Nusrat Khan
Author:
Nazrul Islam
Author:
Andrew Farmer
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