Obstructive Sleep Apnea Among Obese Patients With Type 2 Diabetes

  1. Gary D. Foster, PHD1,
  2. Mark H. Sanders, MD2,
  3. Richard Millman, MD3,
  4. Gary Zammit, PHD4,
  5. Kelley E. Borradaile, PHD1,
  6. Anne B. Newman, MD2,
  7. Thomas A. Wadden, PHD5,
  8. David Kelley, MD2,
  9. Rena R. Wing, PHD3,
  10. F. Xavier Pi Sunyer, MD6,
  11. Valerie Darcey, MS5,
  12. Samuel T. Kuna, MD5 and
  13. for the Sleep AHEAD Research Group*
  1. 1Temple University, Philadelphia, Pennsylvania;
  2. 2University of Pittsburgh, Pittsburgh, Pennsylvania;
  3. 3Brown University, Providence, Rhode Island;
  4. 4Clinilabs, New York, New York;
  5. 5University of Pennsylvania, Philadelphia, Pennsylvania;
  6. 6Columbia University, New York, New York.
  1. Corresponding author: Gary D. Foster, gfoster{at}temple.edu.

Abstract

OBJECTIVE To assess the risk factors for the presence and severity of obstructive sleep apnea (OSA) among obese patients with type 2 diabetes.

RESEARCH DESIGN AND METHODS Unattended polysomnography was performed in 306 participants.

RESULTS Over 86% of participants had OSA with an apnea-hypopnea index (AHI) ≥5 events/h. The mean AHI was 20.5 ± 16.8 events/h. A total of 30.5% of the participants had moderate OSA (15 ≤ AHI <30), and 22.6% had severe OSA (AHI ≥30). Waist circumference (odds ratio 1.1; 95% CI 1.0–1.1; P = 0.03) was significantly related to the presence of OSA. Severe OSA was most likely in individuals with a higher BMI (odds ratio 1.1; 95% CI 1.0–1.2; P = 0.03).

CONCLUSIONS Physicians should be particularly cognizant of the likelihood of OSA in obese patients with type 2 diabetes, especially among individuals with higher waist circumference and BMI.

We report the prevalence of obstructive sleep apnea (OSA) and the factors that increase the risk and severity of OSA among 306 obese patients with type 2 diabetes enrolled in Sleep AHEAD, a four-site ancillary study of the Look AHEAD Trial (Action for Health in Diabetes).

RESEARCH DESIGN AND METHODS

Look AHEAD (1,2) is a 16-center trial investigating the long-term health impact of an intensive lifestyle intervention in 5,145 overweight and obese adults with type 2 diabetes. Exclusion criteria for Sleep AHEAD were previous treatment for OSA.

The protocol was approved by each site's Institutional Review Board. Participants interested in Sleep AHEAD were consented at a Look AHEAD screening visit. Efforts were made to enroll individuals with undiagnosed OSA using a symptom questionnaire (3). Because almost all of the first 80 participants had OSA upon polysomnography, the symptom screen was dropped as an eligibility criteria.

Polysomnography

A home unattended overnight polysomnogram (Compumedics, Abbotsville, Australia) was performed using techniques developed for the Sleep Heart Health Study except that airflow was measured by nasal pressure cannula and oro-nasal thermistor (4). Polysomnograms were scored using recommended criteria (5). Hypopneas had to be associated with a ≥4% oxygen desaturation (5). The overall failure rate for the home polysomnography recordings was 8%; >90% were due to equipment breakdown.

Weight, height, waist (2), and neck (6) circumferences and the Epworth Sleepiness Scale (7) were assessed within 1 week of the polysomnogram without knowledge of its results.

Statistical analysis

Participants were categorized by apnea-hypopnea index (AHI) into mild (5–14.9), moderate (15–29.9), and severe (≥30) OSA. Group differences were assessed using χ2 and t tests. Variables that were correlated with AHI were included in logistic regressions to predict the presence of OSA (AHI ≥5) and, after removing participants with no OSA (n = 40), severity of OSA. The same variables were used to predict AHI as a continuous (log-transformed) variable. Interactions were included to assess sex differences. Research site was included in all models.

RESULTS

Participant characteristics

One participant with central sleep apnea was removed from all analyses. Participant characteristics are in Table 1. A total of 60% were women. Of the females, 90% were postmenopausal. Nearly three-quarters (72.0%) had dyslipidemia, 82.6% had hypertension, and 93.4% had the metabolic syndrome.

Table 1

Sleep AHEAD participant characteristics at baseline

There were no differences between individuals who were enrolled in Sleep AHEAD (n = 305) and those enrolled in Look AHEAD but not in Sleep AHEAD at the four Sleep AHEAD sites (n = 1,012) in weight, BMI, sex, race/ethnicity, or waist circumference. Sleep AHEAD participants were slightly older (61.3 ± 6.5 vs. 58.7 ± 6.9 years; P < 0.0001) and had lower A1C values (7.2 ± 1.1 vs. 7.4 ± 1.2%; P = 0.03) than Look AHEAD participants who were not enrolled in Sleep AHEAD. There were small but significant differences in the frequency of snoring (3.1 ± 1.0 Sleep AHEAD; 2.8 ± 1.1 Look AHEAD, P < 0.01) (1 = do not snore anymore, to 4 = 6–7 nights per week) and in those already diagnosed with OSA (7.6% Sleep AHEAD; 13.4% Look AHEAD, P < 0.01). There were no differences in the presence or loudness of snoring or excessive daytime sleepiness. No symptoms assessed in this study predicted the presence or severity of OSA.

Sleep-disordered breathing

Only 13.4% of participants did not have OSA, whereas 33.4% had mild OSA, 30.5% moderate OSA, and 22.6% severe OSA. Similar findings were obtained in participants who did not have a previous diagnosis of OSA and had not been prescreened based on symptoms (n = 202). Males had a higher AHI than females. BMI, sex, and waist and neck circumference were related to AHI. Waist circumference was the only significant predictor (odds ratio [OR] 1.1; 95% CI 1.0–1.1; P = 0.03) of the presence of OSA (AHI ≥5). Independent of other variables, a 1-cm increase in waist circumference was associated with a 10% increase in the predicted odds of the presence of OSA (AHI ≥5).

In participants with AHI ≥5 (n = 264), BMI was the only significant predictor of severe OSA (OR 1.1; 95% CI 1.0–1.2; P = 0.03). Independent of other variables, a 1-unit increase in BMI was associated with a 10% increase in the predicted odds of severe OSA. Sex approached significance. Males were 2.2 times more likely to have severe OSA than females (OR 2.2; 95% CI 0.9–5.3; P = 0.08). In the full sample (n = 305), waist circumference was the only statistically significant predictor of continuous AHI (β = 0.02, 95% CI 0.01–0.03; P = 0.04). None of the interaction terms was statistically significant.

CONCLUSIONS

The most remarkable finding of this study is the exceedingly high prevalence of undiagnosed OSA (86.6%) among obese patients with type 2 diabetes. These data were suggested by earlier studies of smaller samples and/or that used less than full polysomnography to assess AHI (810). Equally alarming is the unequivocally elevated mean AHI (20.5 ± 16.8) of this group and that 22.6% of participants had severe OSA. Even though obesity, age, and menopause are known risk factors for OSA (1113), the extraordinarily high rates of undiagnosed and severe OSA in this cohort are remarkable. Given the similarities between the participants in Sleep AHEAD versus Look AHEAD (but not in Sleep AHEAD), our results do not appear to be secondary to a selection bias. Potential links between OSA and type 2 diabetes have been recently reviewed (14). Definitive conclusions about the prevalence of OSA among individuals with type 2 diabetes require a control group without diabetes.

The second major finding was that waist circumference was the only significant predictor of the presence of OSA (AHI ≥5) (15). The failure of neck circumference and BMI to contribute to the model is likely due to the restricted upper range of these variables in this sample compared with a community sample. Having a higher BMI, however, did increase the risk of severe OSA (AHI ≥30).

CONCLUSIONS

Physicians treating obese patients with type 2 diabetes should consider the possibility of OSA, even in the absence of symptoms, especially in individuals with higher waist circumference and BMI. The high prevalence of OSA in obese patients with type 2 diabetes represents a serious public health problem and raises the possibility that some of the morbidity and mortality associated with type 2 diabetes may be attributable to undiagnosed OSA.

Acknowledgments

This work was supported by the National Institutes of Health National Heart, Lung, and Blood Institute Grant HL070301 and National Institute of Diabetes and Digestive and Kidney Diseases grants DK60426, DK56992, and DK057135.

The authors received grant/research support from the following: Andle, Arena, Aventis, Cephalon, Elan, Epix, Evotec, Forest, GlaxoSmithKline, H. Lundbeck, King, Merck, Neurim, Neurocrine Biosciences, Neutrogen, Organon, Orphan Medical, Pfizer, Respironics, sanofi-aventis, sanfo-synthe, Schering-Plough, Sepracor, Somaxon, Takeda Pharmaceuticals North America, Transcept, UCB Pharma, Predix, Vanda, and Whyeth-Ayerst Research. The authors received consulting fees from the following: Alexza, Arena, Aventis, Viovail, Boehringer-Ingelheim, Cephalon, Elan, Eli Lilly, Evotec, Forest, Glaxo Smith Kline, Jazz, King Pharmaceuticals, Ligand McNeil, Merck, Neurocrina Biosciences, Organon, Pfizer, Renovis, sanofi-aventis, select comfort, spracor, shire, somnus, takeda pharmaceuticals, Vels, and Wyeth. Honoraria was received from the following: Neurocrine Biosciences, King Pharmaceuticals, McNeil, sanofi-aventis, sanofi-synthelabo, Sepracor, Takeda Pharmaceuticals, Vela Pharmaceuticals, and Wyeth-Ayerst Research. Ownership, Directorship: Clin Labs, Clinilabs IPA, and Clinilabe Physician Services. M.H.S. is a scientific consultant to Philips-Respironics, which manufactures and distributes devices used to monitor sleep and diagnose and treat sleep disordered breathing, and is coinventor of BiPAP and has a financial interest in this brand and related technologies by Philips-Respironics. No other potential conflicts of interest relevant to this article were reported.

Footnotes

  • *A full list of the members of the Sleep AHEAD Research Group is available in an online appendix at http://care.diabetesjournals.org/cgi/content/full/dc08-1776/DC1.

  • Clinical trial reg. no. NCT00194259, www.clinicaltrials.gov.

  • The costs of publication of this article were defrayed in part by the payment of page charges. This article must therefore be hereby marked “advertisement” in accordance with 18 U.S.C. Section 1734 solely to indicate this fact.

    • Received September 26, 2008.
    • Accepted February 28, 2009.
  • Readers may use this article as long as the work is properly cited, the use is educational and not for profit, and the work is not altered. See http://creativecommons.org/licenses/by-nc-nd/3.0/ for details.

References

| Table of Contents

This Article

  1. Diabetes Care vol. 32 no. 6 1017-1019
  1. Online-Only Appendix
  2. All Versions of this Article:
    1. dc08-1776v1
    2. 32/6/1017 most recent