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

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

^*Corresponding author for this work

Research output: Contribution to journal › Article (Academic Journal) › peer-review

4 Citations (Scopus)

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.

[ See paper for graphical abstract ]

Original language	English
Pages (from-to)	2523-2534
Number of pages	12
Journal	Diabetologia
Volume	68
Issue number	11
Early online date	2 Aug 2025
DOIs	https://doi.org/10.1007/s00125-025-06503-6
Publication status	Published - 1 Nov 2025

Bibliographical note

Publisher Copyright:
© The Author(s) 2025.

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

SDG 3 Good Health and Well-being

Keywords

Sleep deprivation
Risk assessment
Prediction
Type 2 diabetes
Insomnia

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Wright, A. K., Huang, T., Carr, M. J., Premdayal, A. D., Saluja, S., Dashti, H. S., Anderson, S. G., Ray, D. W., Jones, S. E., Wood, A. R., Frayling, T. M., Weedon, M. N., Lane, J. M., Saxena, R., Liu, J., Bowden, J., Lawlor, D. A., Redline, S., & Rutter, M. K. (2025). Clinical utility of self-reported sleep duration and insomnia symptoms in type 2 diabetes prediction. Diabetologia, 68(11), 2523-2534. https://doi.org/10.1007/s00125-025-06503-6

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

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{\textquoteright}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{\textquoteright} Health Study, the Nurses{\textquoteright} 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. [ See paper for graphical abstract ] ",

keywords = "Sleep deprivation, Risk assessment, Prediction, Type 2 diabetes, Insomnia",

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

note = "Publisher Copyright: {\textcopyright} The Author(s) 2025.",

year = "2025",

month = nov,

day = "1",

doi = "10.1007/s00125-025-06503-6",

language = "English",

volume = "68",

pages = "2523--2534",

journal = "Diabetologia",

issn = "0012-186X",

publisher = "Springer Science and Business Media Deutschland GmbH",

number = "11",

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Wright, AK, Huang, T, Carr, MJ, Premdayal, AD, Saluja, S, Dashti, HS, Anderson, SG, Ray, DW, Jones, SE, Wood, AR, Frayling, TM, Weedon, MN, Lane, JM, Saxena, R, Liu, J, Bowden, J, Lawlor, DA, Redline, S & Rutter, MK 2025, 'Clinical utility of self-reported sleep duration and insomnia symptoms in type 2 diabetes prediction', Diabetologia, vol. 68, no. 11, pp. 2523-2534. https://doi.org/10.1007/s00125-025-06503-6

TY - JOUR

T1 - Clinical utility of self-reported sleep duration and insomnia symptoms in type 2 diabetes prediction

AU - Wright, Alison K.

AU - Huang, Tianyi

AU - Carr, Matthew J.

AU - Premdayal, Arjun D.

AU - Saluja, Sushant

AU - Dashti, Hassan S.

AU - Anderson, Simon G.

AU - Ray, David W.

AU - Jones, Samuel E.

AU - Wood, Andrew R.

AU - Frayling, Timothy M.

AU - Weedon, Michael N.

AU - Lane, Jacqueline M.

AU - Saxena, Richa

AU - Liu, Junxi

AU - Bowden, Jack

AU - Lawlor, Deborah A.

AU - Redline, Susan

AU - Rutter, Martin K.

PY - 2025/11/1

Y1 - 2025/11/1

N2 - 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. [ See paper for graphical abstract ]

AB - 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. [ See paper for graphical abstract ]

KW - Sleep deprivation

KW - Risk assessment

KW - Prediction

KW - Type 2 diabetes

KW - Insomnia

U2 - 10.1007/s00125-025-06503-6

DO - 10.1007/s00125-025-06503-6

M3 - Article (Academic Journal)

C2 - 40753283

SN - 0012-186X

VL - 68

SP - 2523

EP - 2534

JO - Diabetologia

JF - Diabetologia

IS - 11

ER -

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

Abstract

Bibliographical note

UN SDGs

Keywords

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