The comorbidity burden of type 2 diabetes mellitus: patterns, clusters and predictions from a large English primary care cohort.


Journal

BMC medicine
ISSN: 1741-7015
Titre abrégé: BMC Med
Pays: England
ID NLM: 101190723

Informations de publication

Date de publication:
25 07 2019
Historique:
received: 08 04 2019
accepted: 20 06 2019
entrez: 27 7 2019
pubmed: 28 7 2019
medline: 15 1 2020
Statut: epublish

Résumé

The presence of additional chronic conditions has a significant impact on the treatment and management of type 2 diabetes (T2DM). Little is known about the patterns of comorbidities in this population. The aims of this study are to quantify comorbidity patterns in people with T2DM, to estimate the prevalence of six chronic conditions in 2027 and to identify clusters of similar conditions. We used the Clinical Practice Research Datalink (CPRD) linked with the Index of Multiple Deprivation (IMD) data to identify patients diagnosed with T2DM between 2007 and 2017. 102,394 people met the study inclusion criteria. We calculated the crude and age-standardised prevalence of 18 chronic conditions present at and after the T2DM diagnosis. We analysed longitudinally the 6 most common conditions and forecasted their prevalence in 2027 using linear regression. We used agglomerative hierarchical clustering to identify comorbidity clusters. These analyses were repeated on subgroups stratified by gender and deprivation. More people living in the most deprived areas had ≥ 1 comorbidities present at the time of diagnosis (72% of females; 64% of males) compared to the most affluent areas (67% of females; 59% of males). Depression prevalence increased in all strata and was more common in the most deprived areas. Depression was predicted to affect 33% of females and 15% of males diagnosed with T2DM in 2027. Moderate clustering tendencies were observed, with concordant conditions grouped together and some variations between groups of different demographics. Comorbidities are common in this population, and high between-patient variability in comorbidity patterns emphasises the need for patient-centred healthcare. Mental health is a growing concern, and there is a need for interventions that target both physical and mental health in this population.

Sections du résumé

BACKGROUND
The presence of additional chronic conditions has a significant impact on the treatment and management of type 2 diabetes (T2DM). Little is known about the patterns of comorbidities in this population. The aims of this study are to quantify comorbidity patterns in people with T2DM, to estimate the prevalence of six chronic conditions in 2027 and to identify clusters of similar conditions.
METHODS
We used the Clinical Practice Research Datalink (CPRD) linked with the Index of Multiple Deprivation (IMD) data to identify patients diagnosed with T2DM between 2007 and 2017. 102,394 people met the study inclusion criteria. We calculated the crude and age-standardised prevalence of 18 chronic conditions present at and after the T2DM diagnosis. We analysed longitudinally the 6 most common conditions and forecasted their prevalence in 2027 using linear regression. We used agglomerative hierarchical clustering to identify comorbidity clusters. These analyses were repeated on subgroups stratified by gender and deprivation.
RESULTS
More people living in the most deprived areas had ≥ 1 comorbidities present at the time of diagnosis (72% of females; 64% of males) compared to the most affluent areas (67% of females; 59% of males). Depression prevalence increased in all strata and was more common in the most deprived areas. Depression was predicted to affect 33% of females and 15% of males diagnosed with T2DM in 2027. Moderate clustering tendencies were observed, with concordant conditions grouped together and some variations between groups of different demographics.
CONCLUSIONS
Comorbidities are common in this population, and high between-patient variability in comorbidity patterns emphasises the need for patient-centred healthcare. Mental health is a growing concern, and there is a need for interventions that target both physical and mental health in this population.

Identifiants

pubmed: 31345214
doi: 10.1186/s12916-019-1373-y
pii: 10.1186/s12916-019-1373-y
pmc: PMC6659216
doi:

Types de publication

Journal Article Research Support, Non-U.S. Gov't

Langues

eng

Sous-ensembles de citation

IM

Pagination

145

Subventions

Organisme : Medical Research Council
ID : MC_PC_13042
Pays : United Kingdom
Organisme : Medical Research Council
ID : MR/K006665/1
Pays : United Kingdom
Organisme : Department of Health
ID : RP-PG-0617-20005
Pays : United Kingdom
Organisme : Department of Health
ID : RP_2014-04-026
Pays : United Kingdom

Commentaires et corrections

Type : ErratumIn

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Auteurs

Magdalena Nowakowska (M)

NIHR School for Primary Care Research, Centre for Primary Care and Health Services Research, Manchester Academic Health Science Centre (MAHSC), University of Manchester, 5th floor Williamson Building, Manchester, M13 9PL, UK. magdalena.nowakowska@manchester.ac.uk.
Division of Population Health, Health Services Research & Primary Care, School of Health Sciences, Faculty of Biology, Medicine and Health, Manchester Academic Health Science Centre (MAHSC), University of Manchester, 5th floor Williamson Building, Manchester, M13 9PL, UK. magdalena.nowakowska@manchester.ac.uk.

Salwa S Zghebi (SS)

NIHR School for Primary Care Research, Centre for Primary Care and Health Services Research, Manchester Academic Health Science Centre (MAHSC), University of Manchester, 5th floor Williamson Building, Manchester, M13 9PL, UK.
Division of Population Health, Health Services Research & Primary Care, School of Health Sciences, Faculty of Biology, Medicine and Health, Manchester Academic Health Science Centre (MAHSC), University of Manchester, 5th floor Williamson Building, Manchester, M13 9PL, UK.

Darren M Ashcroft (DM)

NIHR School for Primary Care Research, Centre for Primary Care and Health Services Research, Manchester Academic Health Science Centre (MAHSC), University of Manchester, 5th floor Williamson Building, Manchester, M13 9PL, UK.
Division of Pharmacy and Optometry, School of Health Sciences, Faculty of Biology, Medicine and Health, Manchester Academic Health Science Centre (MAHSC), University of Manchester, Manchester, M13 9PL, UK.
NIHR Greater Manchester Patient Safety Translational Research Centre, University of Manchester, Manchester, M13 9PL, UK.

Iain Buchan (I)

Division of Informatics, Imaging, and Data Science, School of Health Sciences, Faculty of Biology, Medicine and Health, Manchester Academic Health Science Centre (MAHSC), University of Manchester, Manchester, M13 9PL, UK.
Department of Public Health and Policy, Institute of Population Health Sciences, University of Liverpool, Liverpool, L69 3BX, UK.

Carolyn Chew-Graham (C)

Research Institute for Primary Care and Health Sciences, Faculty of Medicine and Health Sciences, Keele University, DJW 1.54a, Staffordshire, ST5 5BJ, UK.

Tim Holt (T)

Nuffield Department of Primary Care Health Sciences, University of Oxford, Oxford, OX2 6GG, UK.

Christian Mallen (C)

Research Institute for Primary Care and Health Sciences, Faculty of Medicine and Health Sciences, Keele University, DJW 1.54a, Staffordshire, ST5 5BJ, UK.

Harm Van Marwijk (H)

Division of Primary Care and Public Health, Brighton and Sussex Medical School, University of Sussex, Brighton, BN1 9PH, UK.

Niels Peek (N)

NIHR Greater Manchester Patient Safety Translational Research Centre, University of Manchester, Manchester, M13 9PL, UK.
Division of Informatics, Imaging, and Data Science, School of Health Sciences, Faculty of Biology, Medicine and Health, Manchester Academic Health Science Centre (MAHSC), University of Manchester, Manchester, M13 9PL, UK.
NIHR Manchester Biomedical Research Centre, Manchester Academic Health Science Centre (MAHSC), University of Manchester, Manchester, M13 9PL, UK.

Rafael Perera-Salazar (R)

Nuffield Department of Primary Care Health Sciences, University of Oxford, Oxford, OX2 6GG, UK.

David Reeves (D)

NIHR School for Primary Care Research, Centre for Primary Care and Health Services Research, Manchester Academic Health Science Centre (MAHSC), University of Manchester, 5th floor Williamson Building, Manchester, M13 9PL, UK.
Division of Population Health, Health Services Research & Primary Care, School of Health Sciences, Faculty of Biology, Medicine and Health, Manchester Academic Health Science Centre (MAHSC), University of Manchester, 5th floor Williamson Building, Manchester, M13 9PL, UK.
Centre for Biostatistics, Division of Population Health, Health Services Research and Primary Care, School of Health Sciences, Faculty of Biology, Medicine and Health, University of Manchester, Manchester, M13 9PL, UK.

Martin K Rutter (MK)

Division of Diabetes, Endocrinology and Gastroenterology, Faculty of Medicine, Biology and Health, University of Manchester, Manchester, M13 9PL, UK.
Manchester Diabetes Centre, Manchester Academic Health Science Centre, Manchester University NHS Foundation Trust, Manchester, M13 0JE, UK.

Stephen F Weng (SF)

Primary Care Stratified Medicine (PRISM), Division of Primary Care, School of Medicine, University of Nottingham, Nottingham, NG7 2RD, UK.

Nadeem Qureshi (N)

Primary Care Stratified Medicine (PRISM), Division of Primary Care, School of Medicine, University of Nottingham, Nottingham, NG7 2RD, UK.

Mamas A Mamas (MA)

Keele Cardiovascular Research Group, Centre for Prognosis Research, Institute for Primary Care and Health Sciences, Keele University, Stoke-on-Trent, ST4 7QB, UK.

Evangelos Kontopantelis (E)

NIHR School for Primary Care Research, Centre for Primary Care and Health Services Research, Manchester Academic Health Science Centre (MAHSC), University of Manchester, 5th floor Williamson Building, Manchester, M13 9PL, UK.
Division of Population Health, Health Services Research & Primary Care, School of Health Sciences, Faculty of Biology, Medicine and Health, Manchester Academic Health Science Centre (MAHSC), University of Manchester, 5th floor Williamson Building, Manchester, M13 9PL, UK.
Division of Informatics, Imaging, and Data Science, School of Health Sciences, Faculty of Biology, Medicine and Health, Manchester Academic Health Science Centre (MAHSC), University of Manchester, Manchester, M13 9PL, UK.

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