Clinical utility of self-reported sleep duration and insomnia symptoms in type 2 diabetes prediction

Alison K Wright; Tianyi Huang; Matthew J Carr; Arjun D Premdayal; Sushant Saluja; Hassan S Dashti; Simon G Anderson; David W Ray; Samuel E Jones; Andrew R Wood; Timothy M Frayling; Michael N Weedon; Jacqueline M Lane; Richa Saxena; Junxi Liu; Jack Bowden; Deborah A Lawlor; Susan Redline; Martin K Rutter

doi:10.1007/s00125-025-06503-6

Clinical utility of self-reported sleep duration and insomnia symptoms in type 2 diabetes prediction

Diabetologia. 2025 Nov;68(11):2523-2534. doi: 10.1007/s00125-025-06503-6. Epub 2025 Aug 2.

Authors

Alison K Wright^{1

2}, Tianyi Huang^{3

4}, Matthew J Carr⁵, Arjun D Premdayal⁶, Sushant Saluja⁷, Hassan S Dashti^{4

8}, Simon G Anderson^{7

9}, David W Ray^{10

11

12}, Samuel E Jones¹³, Andrew R Wood¹⁴, Timothy M Frayling¹⁵, Michael N Weedon¹⁴, Jacqueline M Lane^{8

16

17}, Richa Saxena^{8

16

17}, Junxi Liu^{18

19

20}, Jack Bowden²¹, Deborah A Lawlor^{19

20}, Susan Redline^{4

16

22}, Martin K Rutter^{23

24}

Affiliations

¹ Division of Diabetes, Endocrinology and Gastroenterology, School of Medical Sciences, University of Manchester, Manchester, UK. alison.wright@manchester.ac.uk.
² Centre for Pharmacoepidemiology and Drug Safety, Division of Pharmacy and Optometry, School of Health Sciences, University of Manchester, Manchester Academic Health Sciences Centre, Manchester, UK. alison.wright@manchester.ac.uk.
³ Channing Division of Network Medicine, Brigham and Women's Hospital, Boston, MA, USA.
⁴ Harvard Medical School, Boston, MA, USA.
⁵ Centre for Pharmacoepidemiology and Drug Safety, Division of Pharmacy and Optometry, School of Health Sciences, University of Manchester, Manchester Academic Health Sciences Centre, Manchester, UK.
⁶ Royal Liverpool University Hospital, Liverpool, UK.
⁷ Division of Cardiovascular Sciences, University of Manchester, Manchester, UK.
⁸ Department of Anesthesia, Critical Care and Pain Medicine, Massachusetts General Hospital and Harvard Medical School, Boston, MA, USA.
⁹ Chronic Disease Research Centre of CAIHR, The University of the West Indies, Bridgetown, Barbados.
¹⁰ NIHR Oxford Health Biomedical Research Centre, John Radcliffe Hospital, Oxford, UK.
¹¹ Oxford Centre for Diabetes, Endocrinology and Metabolism, University of Oxford, Oxford, UK.
¹² Oxford Kavli Centre for Nanoscience Discovery, University of Oxford, Oxford, UK.
¹³ Institute for Molecular Medicine, HiLIFE, University of Helsinki, Helsinki, Finland.
¹⁴ Genetics of Complex Traits, College of Medicine and Health, University of Exeter, Exeter, UK.
¹⁵ Department of Genetic Medicine and Development, CMU, University of Geneva, Geneva, Switzerland.
¹⁶ Division of Sleep and Circadian Disorders, Brigham and Women's Hospital, Boston, MA, USA.
¹⁷ Center for Genomic Medicine, Massachusetts General Hospital, Boston, MA, USA.
¹⁸ Nuffield Department of Population Health, Oxford Population Health, University of Oxford, Oxford, UK.
¹⁹ MRC Integrative Epidemiology Unit, University of Bristol, Bristol, UK.
²⁰ Population Health Sciences, Bristol Medical School, University of Bristol, Bristol, UK.
²¹ College of Medicine & Health, University of Exeter, Exeter, UK.
²² Beth Israel Deaconess Medical Center, Boston, MA, USA.
²³ Division of Diabetes, Endocrinology and Gastroenterology, School of Medical Sciences, University of Manchester, Manchester, UK.
²⁴ Diabetes, Endocrinology and Metabolism Centre, Manchester University NHS Foundation Trust, NIHR Manchester Biomedical Research Centre, Manchester Academic Health Sciences Centre, Manchester, UK.

Abstract

Aims/hypothesis: Suboptimal sleep health is linked to higher risks for incident type 2 diabetes. We aimed to assess the clinical utility of adding self-reported sleep traits to a type 2 diabetes prediction model.

Methods: In this cohort study, we used UK Biobank data and Cox proportional hazards models to examine how self-reported sleep duration and insomnia symptoms were associated with incident type 2 diabetes risk. Harrell's C statistic and net reclassification improvement (NRI) were used to assess whether sleep traits improved the incident type 2 diabetes discrimination and predictive utility achieved using QDiabetes variables, with and without including a type 2 diabetes polygenic risk score (PGS). Independent replication was explored in the Nurses' Health Study, the Nurses' Health Study II and the Health Professionals Follow-up Study.

Results: Extremes of sleep duration and occasional or frequent insomnia symptoms were associated with higher risks for incident type 2 diabetes. In the UK Biobank and replication cohorts, adding sleep traits to the QDiabetes risk score did not improve type 2 diabetes prediction (C statistic: QDiabetes alone 0.8933; QDiabetes + sleep duration 0.8939; QDiabetes + insomnia 0.8931; QDiabetes + sleep traits 0.8935). The corresponding total NRI values were: 0.08 (95% CI -0.18, 0.33), 0.04 (95% CI -0.08, 0.16) and 0.04 (95% CI -0.10, 0.18). Inclusion of PGS data marginally improved the type 2 diabetes risk prediction achieved using The QDiabetes calculator, with or without the inclusion of sleep traits in the model (QDiabetes + PGS: C statistic 0.8945; total NRI 0.20 [95% CI 0.12, 0.28]; QDiabetes + PGS + sleep traits: C statistic 0.8946; total NRI 0.18 [95% CI 0.09, 0.27]).

Conclusions/interpretation: While sleep duration and insomnia symptoms were associated with type 2 diabetes risk, they are not useful for improving type 2 diabetes prediction beyond QDiabetes model performance. Inclusion of a type 2 diabetes PGS marginally improved prediction but lacked clear clinical utility.

Keywords: Insomnia; Prediction; Risk assessment; Sleep deprivation; Type 2 diabetes.

MeSH terms

Adult
Aged
Cohort Studies
Diabetes Mellitus, Type 2* / diagnosis
Diabetes Mellitus, Type 2* / epidemiology
Female
Humans
Male
Middle Aged
Proportional Hazards Models
Risk Factors
Self Report
Sleep Duration
Sleep Initiation and Maintenance Disorders* / complications
Sleep Initiation and Maintenance Disorders* / epidemiology
Sleep Initiation and Maintenance Disorders* / physiopathology
Sleep* / physiology
United Kingdom / epidemiology

Abstract

MeSH terms

Grants and funding