Dataset Information

Simple approaches to characterising multiple long-term conditions (multimorbidity) and rates of emergency hospital admission: Findings from 495,465 UK Biobank participants.

ABSTRACT:

Background

Numerous approaches are used to characterise multiple long-term conditions (MLTC), including counts and indices. Few studies have compared approaches within the same dataset. We aimed to characterise MLTC using simple approaches, and compare their prevalence estimates of MLTC and associations with emergency hospital admission in the UK Biobank.

Methods

We used baseline data from 495,465 participants (age 38-73 years) to characterise MLTC using four approaches: Charlson index (CI), Byles index (BI), count of 43 conditions (CC) and count of body systems affected (BC). We defined MLTC as more than two conditions using CI, BI and CC, and more than two body systems using BC. We categorised scores (incorporating weightings for the indices) from each approach as 0, 1, 2 and 3+. We used linked hospital episode statistics and performed survival analyses to test associations with an endpoint of emergency hospital admission or death over 5 years.

Results

The prevalence of MLTC was 44% (BC), 33% (CC), 6% (BI) and 2% (CI). Higher scores using all approaches were associated with greater outcome rates independent of sex and age group. For example, using CC, compared with score 0, score 2 had 1.95 (95% CI: 1.91, 1.99) and a score of 3+ had 3.12 (95% CI: 3.06, 3.18) times greater outcome rates. The discriminant value of all approaches was modest (C-statistics 0.60-0.63).

Conclusions

The counts classified a greater proportion as having MLTC than the indices, highlighting that prevalence estimates of MLTC vary depending on the approach. All approaches had strong statistical associations with emergency hospital admission but a modest ability to identify individuals at risk.

SUBMITTER: Dodds RM

PROVIDER: S-EPMC10086957 | biostudies-literature | 2023 Jan

REPOSITORIES: biostudies-literature

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Publications

Simple approaches to characterising multiple long-term conditions (multimorbidity) and rates of emergency hospital admission: Findings from 495,465 UK Biobank participants.

Dodds Richard M RM Bunn Jonathan G JG Hillman Susan J SJ Granic Antoneta A Murray James J Witham Miles D MD Robinson Sian M SM Cooper Rachel R Sayer Avan A AA

Journal of internal medicine 20220921 1

<h4>Background</h4>Numerous approaches are used to characterise multiple long-term conditions (MLTC), including counts and indices. Few studies have compared approaches within the same dataset. We aimed to characterise MLTC using simple approaches, and compare their prevalence estimates of MLTC and associations with emergency hospital admission in the UK Biobank.<h4>Methods</h4>We used baseline data from 495,465 participants (age 38-73 years) to characterise MLTC using four approaches: Charlson ...[more]

PMID: 36131375

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Dataset Information

Simple approaches to characterising multiple long-term conditions (multimorbidity) and rates of emergency hospital admission: Findings from 495,465 UK Biobank participants.

Background

Methods

Results

Conclusions

Publications

Simple approaches to characterising multiple long-term conditions (multimorbidity) and rates of emergency hospital admission: Findings from 495,465 UK Biobank participants.

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