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GMDS 2015: 60. Jahrestagung der Deutschen Gesellschaft für Medizinische Informatik, Biometrie und Epidemiologie e. V. (GMDS)

Deutsche Gesellschaft für Medizinische Informatik, Biometrie und Epidemiologie

06.09. - 09.09.2015, Krefeld

Associations between sleep disturbances, nocturnal sleep duration, daytime napping, and incident prediabetes and type 2 diabetes: the Heinz Nixdorf Recall Study

Meeting Abstract

  • Bernd Kowall - Institut für Medizinische Informatik, Biometrie und Epidemiologie; Universitätsklinikum Essen, Essen, Deutschland
  • Anna-Therese Lehnich - Institut für Medizinische Informatik, Biometrie und Epidemiologie; Universitätsklinikum Essen, Essen, Deutschland
  • Nicole Jankovic - Institut für Medizinische Informatik, Biometrie und Epidemiologie; Universitätsklinikum Essen, Essen, Deutschland
  • Susanne Moebus - Institut für Medizinische Informatik, Biometrie und Epidemiologie; Universitätsklinikum Essen, Essen, Deutschland
  • Karl-Heinz Strucksberg - Klinik für Endokrinologie & Stoffwechselerkrankungen/Zentrallabor; Universitätsklinik Essen, Essen, Deutschland
  • Dagmar Führer - Klinik für Endokrinologie & Stoffwechselerkrankungen/Zentrallabor; Universitätsklinik Essen, Essen, Deutschland
  • Raimund Erbel - Universitätsklinikum Essen, Westdeutsches Herzzentrum, Klinik für Kardiologie, Essen, Deutschland
  • Karl-Heinz Jöckel - Institut für Medizinische Informatik, Biometrie und Epidemiologie; Universitätsklinikum Essen, Essen, Deutschland
  • Andreas Stang - Institut für Medizinische Informatik, Biometrie und Epidemiologie; Universitätsklinikum Essen, Essen, Deutschland

GMDS 2015. 60. Jahrestagung der Deutschen Gesellschaft für Medizinische Informatik, Biometrie und Epidemiologie e.V. (GMDS). Krefeld, 06.-09.09.2015. Düsseldorf: German Medical Science GMS Publishing House; 2015. DocAbstr. 135

doi: 10.3205/15gmds153, urn:nbn:de:0183-15gmds1531

Veröffentlicht: 27. August 2015

© 2015 Kowall et al.
Dieser Artikel ist ein Open-Access-Artikel und steht unter den Lizenzbedingungen der Creative Commons Attribution 4.0 License (Namensnennung). Lizenz-Angaben siehe http://creativecommons.org/licenses/by/4.0/.


Gliederung

Text

Introduction: Sleep disturbances, and short and long duration of nocturnal sleep have been reported as risk factors for type 2 diabetes [1], [2], [3]. Our aim was to assess whether these sleep characteristics are also associated with incident prediabetes. Furthermore, we studied the association of other rarely investigated sleep characteristics (daytime napping; habitual versus transient sleep disorders) with incident diabetes.

Methods: In the Heinz Nixdorf Recall Study, a population-based cohort study in Germany (N=4,814; age 45-75 years), diabetes at baseline and at 5-year follow-up was assessed by self-report and measurement of glucose levels. Prediabetes was defined as impaired fasting glucose (6.1 - <7.0 mmol/l) [4]. For analyses of incident prediabetes, the effective sample size was 1,156: we excluded 2,057 subjects with missing baseline data of glucose regulation (mainly because subjects had not been fasting for at least 8 hours overnight), 1,117 subjects with prediabetes or diabetes at baseline, and 484 subjects with missing follow-up data. For the analyses of incident type 2 diabetes, the effective sample size was 3,338 participants: we excluded 304 subjects with missing baseline data of diabetes, 656 subjects with known diabetes at baseline, 516 subjects with missing follow-up data.

A sleep questionnaire was used to assess difficulties falling asleep, difficulties maintaining sleep, early morning arousal, and duration of nocturnal and daytime sleep. Robust Poisson regression models were fitted to estimate relative risks (RRs) with 95% confidence intervals (CIs) for the association between sleep characteristics and incidence of prediabetes and type 2 diabetes. Directed acyclic graphs were drawn to find a minimally sufficient adjustment set which included age, sex, smoking, alcohol and coffee consumption, metabolic equivalents per week, school education, subjective health status, depression, and stress. BMI and hypertension as putative mediators of associations between sleep characteristics and incident (pre)diabetes were included in additional analyses.

Results: Among 1,156 subjects without prediabetes / diabetes at baseline, 224 (19.4%) developed prediabetes, and 40 (3.5%) developed type 2 diabetes. Age-sex adjusted RRs for the adjustment between sleep characteristics and incidence of prediabetes hardly changed after adjustment for the minimally sufficient adjustment set. In the latter models, sleep disorders were associated with greater risks of prediabetes (RR=1.32 (95% CI 0.93 – 1.90) for regular early morning arousal, 1.25 (95% CI 0.97 – 1.61) for regular difficulties maintaining sleep, and 1.32 (95% CI 1.03 – 1.69) for any regular sleep disorder). Short (< 6 hours), but not long duration of nocturnal sleep (> 8 hours) was associated with incident prediabetes (RR=1.33 (95% CI 0.95 – 1.86), and RR=0.97 (95% CI 0.58 – 1.63), respectively).

Among 3,338 subjects without diabetes at baseline, 298 (9.0%) developed diabetes during follow-up. RRs for incident diabetes showed hardly any effect for daytime napping. Neither regular long (> 60 minutes, at least 5 times per week) nor regular short nappers (> 0, ≤ 60 minutes, at least 5 times per week) had a larger risk of type 2 diabetes compared to persons napping never or irregularly (RR=0.85 (95% CI 0.36 – 2.02), and RR=0.95 (95% CI 0.68 – 1.33), respectively).

Compared to subjects who never reported any regular sleep disorders, the risk of diabetes was increased by 48% in subjects reporting them at baseline and at follow-up, but only by 12 and 15%, respectively, in those reporting them only at baseline and only at follow-up.

Conclusion: In the present study, we showed that sleep disorders are associated with prediabetes, and that adults with repeatedly reported sleep disorders may be at a particular risk of type 2 diabetes. We found no association between daytime napping and incident type 2 diabetes. More studies on the relationship between sleep and glucose regulation are needed with objective measurements of sleep characteristics, with assessment of sleep characteristics at more than one point in time, and with glucose regulation assessed by oral glucose tolerance test, HOMA and/or HbA1c.


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