gms | German Medical Science

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

Do patients with intake of drugs labeled as sleep disturbing really sleep worse? A population based assessment from the Heinz Nixdorf Recall Study

Meeting Abstract

  • Anna-Therese Lehnich - Universitätsklinikum Essen, Deutschland
  • Bernd Kowall - Institut für Medizinische Informatik, Biometrie und Epidemiologie; Universitätsklinikum Essen, Essen, Deutschland
  • Oliver Kuß - Deutsches Diabetes-Zentrum (DDZ), Leibniz-Zentrum für Diabetes Forschung an der Heinrich-Heine-Universität Düsseldorf, Institut für Biometrie und Epidemiologie, Düsseldorf, Deutschland
  • Andrea Schmidt-Pokrzywniak - Institut für Medizinische Epidemiologie, Biometrie und Informatik; Universitätsklinikum Halle, Deutschland
  • Gerhard Weinreich - Ruhrlandklinik; Universitätsklinikum Essen, Deutschland
  • Nico Dragano - Institut für Medizinische Soziologie; Universitätsklinikum Düsseldorf, Deutschland
  • Susanne Moebus - Institut für Medizinische Informatik, Biometrie und Epidemiologie, Essen, Deutschland
  • Raimund Erbel - Universitätsklinikum Essen, Essen, Deutschland
  • Karl-Heinz Jöckel - Universitätsklinikum Essen, Essen, Deutschland
  • Andreas Stang - 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. 191

doi: 10.3205/15gmds190, urn:nbn:de:0183-15gmds1905

Veröffentlicht: 27. August 2015

© 2015 Lehnich 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: There is only limited quantitative information on the association between intake of sleep disturbing drugs and nocturnal sleep disturbances. Information on sleep disturbing effects of drugs mostly derives from clinical trials with highly selected patient collectives. As these patient collectives do not reflect the general population, the trial results concerning sleep disturbing effects of drugs may not be generalizable to the general population. Our aim was to assess the association between intake of drugs labeled as sleep disturbing and self-reported nocturnal sleep disturbances in a population-based study.

Methods: For this analysis we used data of 4500 participants (49.8% male) aged 45 to 75 years from the baseline examination of the Heinz Nixdorf Recall Study in Germany. From a standardized interview we gained information on difficulties falling asleep (DFA), difficulties maintaining sleep (DMS) and early morning arousal (EMA). Participants had to quantify the average frequency of nocturnal sleep disturbances per week during the most recent four weeks before interview. Frequency categories were never, sometimes (≤ once a week), frequently (≥ 2 times a week) and nearly every night. Any regular nocturnal sleep disorder was defined as at least one type of nocturnal sleep disturbance reported nearly every night.

For the assessment of medication history, participants had been asked to bring all drugs that had been taken the last 7 days. To make sure drug intake was prior to the time window of self-reported nocturnal sleep disturbances, we restricted drug intake to drugs taken at least 4 weeks before the interview. The medical staff assessed medication data online using the IDOM software that automatically assigned the Anatomical Therapeutical Chemical (ATC) code (as of 2003) [1], [2]. We derived probability categories of sleep disturbances relating to drugs from monographs of the German ABDA-database (Federal Union of German Associations of Pharmacists) [3]. This database contains information deriving mainly from summary of product characteristics (SPC). The SPC-based probability of sleep disturbances (pSPC) is qualitatively described by standardized MedDRA-terminology (Medical Dictionary for Regulatory Activities). This terminology corresponds with predefined probability ranges including “very rare” (pSPC < 0.01%), “rare” (0.01% ≤ pSPC < 0.1%), “uncommon” (0.1% ≤ pSPC < 1%), “common” (1% ≤ pSPC < 10%) and “very common” (pSPC ≥ 10%).

We fitted separate relative risk regression models for each of the response categories “sometimes”, “frequently”, “nearly every night” using the reference category „never“ in each of the models. Standard errors for the resulting prevalence ratios (PRs) were estimated by the robust Poisson method [4]. Self-reported sleep disturbances served as outcome variables. In our first analysis, we classified drugs with pSPC ≤ 0.1% as sleep disturbing drugs. In a second analysis we used the SPC-based probability of every drug taken by a participant to derive an estimated cumulative probability for sleep disturbances. For this calculation we assumed that sleep disturbances relating to drugs are independent from other drug intake.

To address confounding, we set up a directed acyclic graph. We used the minimally sufficient adjustment set containing the covariates age, sex, diseases, alcohol consumption and social status to adjust our measures of association.

Results: The prevalence for the intake of sleep disturbing drugs was 44% for men and 52% for women. The most frequently reported sleep disturbance was DMS (36.7%) followed by EMA (10.1%) and DFA (9.6%). We barely found any association between the number of sleep disturbing drugs and self-reported nocturnal sleep disturbances. The crude PRs of any regular nocturnal sleep disorder per additional sleep disturbing drug were 0.96 (95% Confidence Interval (CI): 0.88-1.05) and 0.96 (95% CI: 0.91-1.02) for men and women, respectively. After adjustment, the estimates barely changed (0.95 (95% CI: 0.85-1.06) for men and 0.98 (95% CI: 0.91-1.05) for women). Estimates for DFA, DMS and EMA were close to 1 or lower than 1. PRs for nocturnal sleep disturbances did not increase with rising cumulative probability for sleep disturbances relating to drugs.

Conclusion: SPC-based probabilities of sleep disturbances relating to drugs showed no association with self-reported nocturnal sleep disturbances. Our null result finding suggests that SPC-based probability information may be of limited data quality and may lack generalizability to the general population.


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