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Endocrine

, Volume 53, Issue 1, pp 227–239 | Cite as

Lack of significant association between type 2 diabetes mellitus with longitudinal change in diurnal salivary cortisol: the multiethnic study of atherosclerosis

  • Elias K. Spanakis
  • Xu Wang
  • Brisa N. Sánchez
  • Ana V. Diez Roux
  • Belinda L. Needham
  • Gary S. Wand
  • Teresa Seeman
  • Sherita Hill GoldenEmail author
Original Article

Abstract

Cross-sectional association has been shown between type 2 diabetes and hypothalamic–pituitary–adrenal (HPA) axis dysregulation; however, the temporality of this association is unknown. Our aim was to determine if type 2 diabetes is associated with longitudinal change in daily cortisol curve features. We hypothesized that the presence of type 2 diabetes may lead to a more blunted and abnormal HPA axis profile over time, suggestive of increased HPA axis dysregulation. This was a longitudinal cohort study, including 580 community-dwelling individuals (mean age 63.7 ± 9.1 years; 52.8 % women) with (n = 90) and without (n = 490) type 2 diabetes who attended two MultiEthnic Study of Atherosclerosis Stress ancillary study exams separated by 6 years. Outcome measures that were collected were wake-up and bedtime cortisol, cortisol awakening response (CAR), total area under the curve (AUC), and early, late, and overall decline slopes. In univariate analyses, wake-up and AUC increased over 6 years more in persons with as compared to those without type 2 diabetes (11 vs. 7 % increase for wake-up and 17 vs. 11 % for AUC). The early decline slope became flatter over time with a greater flattening observed in diabetic compared to non-diabetic individuals (23 vs. 9 % flatter); however, the change was only statistically significant for wake-up cortisol (p-value: 0.03). Over time, while CAR was reduced more, late decline and overall decline became flatter, and bedtime cortisol increased less in those with as compared to those without type 2 diabetes, none of these changes were statistically significant in adjusted models. We did not identify any statistically significant change in cortisol curve features over 6 years by type 2 diabetes status.

Keywords

Diabetes Stress Cortisol HPA axis Epidemiology 

Notes

Acknowledgments

The authors thank the other investigators, the staff, and the participants of the MESA study for their valuable contributions. A full list of participating MESA investigators and institutions can be found at http://www.mesa-nhlbi.org.

Funding

MESA was supported by contracts NO1-HC-95159 through NO1-HC-95165 and NO1-HC-95169 from the National Heart, Lung, and Blood Institute (PI: ADR). MESA Stress Study was supported by RO1 HL10161-01A1 and R21 DA024273 (PI: ADR). EKS was supported by an institutional training grant from the National Institute of Diabetes, Digestive, and Kidney Diseases (T32DK062707).

Compliance with ethical standards

Conflict of Interest

The authors have no relevant conflict of interest to disclose.

Ethical Standards

All procedures performed in the study were in accordance with the ethical standards of the institutional and/or national committees and have been performed in accordance with the ethical standards as laid down in the 1964 Helsinki declaration and its latter amendments or comparable ethical standards.

Informed Consent

All participants provided informed consent and the above studies were approved by the Institutional Review Boards of each institution.

Supplementary material

12020_2016_887_MOESM1_ESM.docx (15 kb)
Supplementary material 1 (DOCX 14 kb)
12020_2016_887_MOESM2_ESM.docx (18 kb)
Supplementary material 2 (DOCX 18 kb)

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Copyright information

© Springer Science+Business Media New York 2016

Authors and Affiliations

  • Elias K. Spanakis
    • 1
  • Xu Wang
    • 3
  • Brisa N. Sánchez
    • 4
  • Ana V. Diez Roux
    • 3
  • Belinda L. Needham
    • 5
  • Gary S. Wand
    • 1
  • Teresa Seeman
    • 6
  • Sherita Hill Golden
    • 1
    • 2
    Email author
  1. 1.Division of Endocrinology, Diabetes and Metabolism, Department of MedicineJohns Hopkins University School of MedicineBaltimoreUSA
  2. 2.Department of EpidemiologyJohns Hopkins Bloomberg School of Public HealthBaltimoreUSA
  3. 3.Department of EpidemiologyDrexel University School of Public HealthPhiladelphiaUSA
  4. 4.Department of BiostatisticsUniversity of MichiganAnn ArborUSA
  5. 5.Department of EpidemiologyUniversity of MichiganAnn ArborUSA
  6. 6.Division of Geriatrics, David Geffen School of MedicineUniversity of CaliforniaLos AngelesUSA

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