The Effects of Obstructive Sleep Apnea and Visceral Fat on Insulin Resistance

The Effects of Obstructive Sleep Apnea and Visceral Faton Insulin Resistance:

The Icelandic Sleep Apnea Cohort

Greg Maislin Director, Biostatistics Core

Adjunct Associate Professorof Biostatistics in MedicineDivision of Sleep Medicine

University of Pennsylvania School of Medicine

Dept. of Respiratory Medicine and Sleep

Landspitali University Hospital

Reykjavik Iceland

Bryndis Benediktsdottir

Erna Sif Arnardóttir

Isleifur Olafsson

Thorarinn Gislason

Center for Sleep and Respiratory NeurobiologyDivision of Sleep MedicineUniversity of Pennsylvania

School of MedicinePhiladelphia PA

Richard J. Schwab

Allan I. Pack

Co-Authors

Quick Background I

Mary Ip et al AJRCCM 2002, 165:670“OSA is Independently Associated with Insulin

Resistance”

Hong Kong sleep center population, N=270, excluded

known diabetes, homeostasis model assessment method

(HOMA).

“Stepwise multiple linear regression analyses showed that

obesity was the major determinant of insulin resistance but

sleep disordered breathing parameters were also

independent predictors of insulin resistance.”

Quick Background II

Naresh Punjabi et al AJRCCM 2002 165:677 “Sleep-disorded Breathing and Insulin Resistance in

Middle-aged and Overweight Men”

Community population, N=150 without diabetes or

cardiopulmonary disease, PSG, MSLT, OGGT and

fasting insulin and lipids

“Multivariable linear regression analyses revealed that

increasing AHI was associated with worsening insulin

resistance independent of obesity”

Quick Background III

Naresh Punjabi et al Am J Epid 2004, 160:521.”Sleep-Disordered Breathing, Glucose Intolerence,

and Insulin Resistance: The Sleep Heart Health Study”

Community dwelling, N=2656, RDI and O2 sat., fasting

and glucose 2-hour glocuse (OGTT) within 1 year of PSG.

“The results from this study suggest that SDB in

independently associated with glucose intolerance and

insulin resistance and may lead to type 2 diabetes

mellitus.”

Quick Background IV

Igor Harsch et al AJRCCM 2004, 169:156.“CPAP Treatment Rapidly Improves Insulin

Sensitivity in Patients with OSA”

N=40, euglycemic clamp (invasive)

“The effect of CPAP on insulin sensitivity is smaller in non

obese individuals suggesting that in obese patients

insulin sensivity is mainly determined by obesity, and to a

smaller extent, by sleep apnea.”

Potential Mechanisms

Elevated sympathetic nervous system activity

Alterations in glucocorticoid regulation induced

by sleep loss

Recurrent intermittant hypoxemia associated with

sleep-disorded breather

Aim of Study To compare the relative importance of OSA

and obesity on insulin resistance (IR)

To assess if the effect of OSA on IR varies

among non-obese, mildly obese, and severely

obese

To use MR imaging volumetric determinations

of abdominal fat

Icelandic Sleep Cohort

Patients diagnosed with OSA at one of five health

clinics within Iceland and referred for CPAP to the

Landspitali University Hospital in Reykjavik from Sept

2005 - Dec 2009. >90% agreed to participate in the

study.

Subjects were initially diagnosed as having OSA by

sleep studies. Anthropometric measurements,

medical history, health related quality of life and other

questionnaires, MR imaging, and fasting insulin and

glucose (to determine HOMA) were obtained at

baseline.

Iceland Sleep Apnea Cohort (ISAC)Overall and by Obesity Category

Demographics

Icelandic Sleep Apnea Cohort

BMI < 30 kg/m2

BMI 30 -< 35 kg/m2

BMI ≥ 35 kg/m2

p-value

for comparison

between groups

(Ranks or χ2) n = 826 n = 180 n = 192 n = 126

Age (years) 54.4 ± 10.7 55.8 ± 9.7 55.2 ± 10.6 52.5 ± 11.2 0.001

% of males 81.0 82.9 82.39 78.1 0.28

Body mass index (kg/m2) 33.5 ± 5.7 27.4 ± 2.0 32.4 ± 1.5 39.7 ± 4.0 N/A

Abdominal fat vol. (MRI times 103) (N=665)

4.34 (1.83) 3.21 (1.37) 4.61 (1.54) 5.29 (1.93) <0.0001

Current smokers (%) 21.1 24.2 19.5 20.0 0.37

Epworth Sleepiness Score 11.6 ±5.1 11.5 ± 4.9 11.3 ± 5.2 12.1 ± 5.1 0.20

Why restrict analysis cohort byAHI 14-80 and ODI 10-65?

AHI

1501209060300

BM

I

60

50

40

30

20

BMI tertiles

BMI above 35

BMI 30-35

BMI below 30

To simultaneously estimate the effects of BMI category and OSA severity, the range of the OSA severity must be restricted to be the same across the BMI tertiles for both AHI and ODI (called ‘double overlap cohort’) in order to avoid extrapolation.

All subjects Overlap cohort

Description of Overlap CohortOverall and by Obesity Category

Demographics

All

BMI < 30 kg/m2

BMI 30 -< 35 kg/m2

BMI ≥ 35 kg/m2

p-value

for comparison

between groups

(Ranks or χ2) N = 498 n = 180 n = 192 n = 126

Age (years) 54.5 ± 10.4 55.4 ± 9.5 54.8 ± 10.9 52.8 ± 10.8 0.09

% of males 82.1 86.7 83.9 73.0 0.007

Body mass index (kg/m2) 32.1 ± 4.7 27.5 ± 2.0 32.3 ± 1.4 38.32 ± 2.9 N/A

Abdominal fat vol. (MRI times 103)

4.25 (1.75) 3.26 (1.37) 4.61 (1.54) 5.11 (1.87) <0.0001

Current smokers %) 20.5 23.3 19.8 17.4 0.45

Epworth Sleepiness Score 11.6 ±4.9 11.9 ± 5.0 11.1 ± 4.7 12.1 ± 5.1 0.17


Sleep disordered breathing

All BMI < 30

kg/m2 BMI 30 -< 35

kg/m2 BMI ≥ 35

kg/m2

p-value

for comparison

between groups

(Wilcoxon or χ2)

Apnea-hypopnea index (events/hour)

40.7 ± 15.4 (14.8-79.6)

39.2 ± 14.2 (15.3-79.4)

42.6 ± 16.0 (14.8-79.6)

40.0 ± 15.7 (14.8-75.7)

0.14

Oxygen desaturation index (events/hour)

31.2 ± 13.7 (10.3-65)

28.5 ± 12.4 (10.3-63.7)

33.2 ± 14.8 (10.3-65.0)

31.9 ± 13.3 (10.8-61.2)

0.008

Minimum SaO2 (%) 77.4 ± 6.8 78.7 ± 5.9 77.4 ± 7.2 75.5 ± 7.0 <0.0001

Hypoxia time (minutes) 42.5 ± 60.0 30.4 ± 42.8 45.7 ± 63.7 55.0 ± 71.5

<0.0001

Summary of Insulin Resistance Measures

Measure

All

(N=498)

BMI<30

(N=180)

BMI 30-35

(N=192)

BMI>35

(N=126) P-value

Glucose 5.60 (0.63) 5.43 (0.50) 5.61 (0.61) 5.83 (0.75) <0.0001

Insulin 17.60 (14.24) 11.29 (8.77) 17.17 (11.75) 27.26 (18.25) <0.0001

HOMA 4.52 (4.06) 2.75 (2.09) 4.38 (3.23) 7.27 (5.58) <0.0001

Log(HOMA) 1.26 (0.68) 0.86 (0.54) 1.29 (0.59) 1.78 (0.62) <0.0001

HOMA>3.99 40.4% 12.2% 42.2% 77.8% <0.0001

SAT: 3568 cm3

VAT: 2556 cm3

SAT: 5926 cm3

VAT: 4318 cm3SAT: 9153 cm3

VAT: 5902 cm3

BMI: 27.7 kg/m2 BMI: 32.3 kg/m2

= Subcutaneous Adipose Tissue (SAT) = Visceral Adipose Tissue (VAT) = Liver = Kidneys = Spine

BMI: 39.0 kg/m2

MRI Imaging of the Abdominal Region

Correlations between log(HOMA) andObesity Measures

Obesity Measures Log(HOMA)

r p

Total abdominal fat volume (cm3) 0.56 <0.0001

Body mass index (kg/m2) 0.55 <0.0001

Waist circumference (cm) 0.54 <0.0001

Subcutaneous fat volume (cm3) 0.47 <0.0001

Visceral fat volume (cm3) 0.44 <0.0001

Waist-to-hip ratio (cm/cm) 0.29 <0.0001

Note: Similar correlations were obtained when assessed using Spearman correlation

Bootstrap Tests for Differences between Correlations with log(HOMA)

Measure 1 Measure 2 Mean difference

95% non-parametric CI

P-value

Total abdominal fat Visceral fat 0.123 (.073 – 0.173) <0.001

BMI Visceral fat 0.110 (.043 - .186) <0.001

Waist circumference Visceral fat 0.102 (.046 - .162) <0.001

Subcutaneous fat Visceral fat 0.036 (-.043 – .128) 0.16

Waist to hip ratio Visceral fat -0.144 (-.212 - -.081) <0.001

Correlations between log(HOMA)and Apnea Severity Measures

Overall and by Obesity Category

Measure All

(N=498)

BMI < 30 kg/m2

(N=180)

BMI ≥30 and <35 kg/m2

(N=192)

BMI ≥35 kg/m2

(N=126)

r p r p r p r p

Apnea-hypopnea index 0.05 0.26 0.08 0.27 -0.04 0.55 0.13 0.16

Oxygen desaturation index 0.14 0.002 0.21 0.005 -0.01 0.84 0.16 0.07

Minimum SaO2 (%) -0.18 <0.001 -0.07 0.37 -0.10 0.16 -0.16 0.07

Hypoxia time (minutes) 0.18 <0.001 0.24 0.0009 0.11 0.13 0.03 0.78

Correlations between log(IL-6) andApnea Severity Measures

Measure All

(N=347)

BMI < 30 kg/m2

(N=142)

BMI ≥30 and <35 kg/m2

(N=131)

BMI ≥35 kg/m2 (N=74)

r p r p r p r p

Apnea-hypopnea index -0.02 0.70 -0.23 0.005 0.12 0.16 0.02 0.87

Oxygen desaturation index 0.08 0.12 -0.09 0.30 0.16 0.07 0.07 0.57

Minimum SaO2 (%) -0.13 0.01 0.12 0.17 -0.24 0.005 -0.16 0.18

Hypoxia time (minutes) 0.18 0.001 -0.06 0.45 0.36 <0.0001 0.09 0.43

Response Surface Methodology

Y=f(X1, X2, X3,) + , ~N(0, 2)

E[log(HOMA)] was modeled as a third order

linear model with terms defined by apnea (A)

and obesity severity (O)

Normal and constant variance assumptions

verified for log transformed outcomes


The specific model used was:

E[log(HOMA] =

0 +

1*A + 2*(A)2 +

3*O + 4*(O)2 +

5*(A*O) +

6*A*(O)2 +7*O*(A)2

A = apnea severity measure; O = obesity severity

measure

RSM: log(HOMA)=f(ODI, BMI)

0.0

0.5

1.0

1.5

2.0

2.5

3.0

3.5

4.0

25

30

35

40

45

101520

253035

4045505560

log

(HO

MA

)

BMI

ODI

R2=33.3%(p<0.0001)

Partial R2’sObesity = 32.6%

(p<0.0001)

Apnea = 3.1%(p=0.01)

O x A = 2.2%(p=0.01)

Non-linear = 5%(p=0.0005)


0

1

2

3

4

25

30

35

40

45

1520

2530

3540

4550

5560

6570

7580

log

(HO

MA

)

BMI

AHI

0.0

0.5

1.0

1.5

2.0

2.5

3.0

3.5

4.0

25

30

35

40

45

1015202530354045

505560

log

(HO

MA

)

BMI

ODI

0.0

0.5

1.0

1.5

2.0

2.5

3.0

3.5

4.0

25

30

35

40

45

7274

7678

8082

8486

88

log

(HO

MA

)

BMIMinimum SAO

2

0.0

0.5

1.0

1.5

2.0

2.5

3.0

3.5

4.0

25

30

35

40

45

025

5075

100125

log

(HO

MA

)

BMI

Minutes O2 <90%

RSM: log(HOMA)=f(ODI, Total Abd. Fat)

R2=34.1%(p<0.0001)

Partial R2’sObesity = 32.8%

(p<0.0001)

Apnea = 1.4%(p=0.20)

O x A = 0.9%(p=0.21)

Non-linear = 3.4%(p=0.002)

0.0

0.5

1.0

1.5

2.0

2.5

3.0

6

8

10

12

14

1020

3040

5060

log

(HO

MA

)

Abdominal Fat V

olume (MRI)

(x 1000)ODI


0.0

0.5

1.0

1.5

2.0

2.5

3.0

0.01.5

3.04.5

6.07.5

9.0

15202530

3540

455055

606570

75

log

(HO

MA

)

Visceral Fat V

olume (MRI)

(x 1000)AHI

0.0

0.5

1.0

1.5

2.0

2.5

3.0

0.01.5

3.04.5

6.07.5

9.0

1020

3040

5060

log

(HO

MA

)

Visceral Fat V

olume (MRI)

(x 1000)ODI

0.0

0.5

1.0

1.5

2.0

2.5

3.0

0.01.5

3.04.5

6.07.5

9.0

7274

7678

8082

8486

88

log

(HO

MA

)

Visceral Fat V

olume (MRI)

(x 1000)

Minimum SAO2

0.0

0.5

1.0

1.5

2.0

2.5

3.0

0.01.5

3.04.5

6.07.5

9.0

025

5075

100125

log

(HO

MA

)

Visceral Fat V

olume (MRI)

(x 1000)

Minutes O2 <90%

Conclusions

Obesity is a much more important determinant of insulin

resistance than obstructive sleep apnea.

There is a complex interaction between obesity and OSA and

insulin resistance.

Different metrics produce different results which may be

related to differences in what these metrics actually measure.

Depending upon which metrics are examined, our study

provides additional confirmation that among non-obese, OSA

increases insulin resistance.

There may also be differentially important amplification of

OSA effects among the most obese.

BMI, Total Fat, and Visceral Fat by BMI Category

N Std

BMI3GRP Obs Variable Label N Mean Dev Min Max

---------------------------------------------------------------------------------------------

<30 180 BMI Body Mass Index (k/m-sq) 180 27.5 2.0 20.0 29.9

MR54 ab total fat vol. 180 7.2 2.1 1.2 12.4

MR56 ab visc fat vol. 180 3.3 1.4 0.2 8.0

30-<35 192 BMI Body Mass Index (k/m-sq) 192 32.3 1.4 30.0 35.0


MR56 ab visc fat vol. 192 4.6 1.5 0.7 10.1

>=35 126 BMI Body Mass Index (k/m-sq) 126 38.3 2.9 35.1 51.2


MR56 ab visc fat vol. 126 5.1 1.9 1.4 11.2

---------------------------------------------------------------------------------------------

Response Surface Methodologyusing BMI as Measure of Obesity

Null hypothesis tested

No BMI or OSA

effects (df=7)

No BMI Effect (df=5)

No OSA Effect (df=5)

No BMI*OSA

interaction (df=3)

No Non-

linearity (df=4)

AHI p-value for rejecting Ho: <0.0001 <0.0001 0.01 0.02 <0.0001

R2 or Partial R2 33.9% 32.8% 3.0% 1.9% 4.7%

ODI p-value for rejecting Ho: <0.0001 <0.0001 0.01 0.01 0.0003

R2 or Partial R2 33.9% 32.6% 3.1% 2.2% 5.0%

Min SAO2 p-value for rejecting Ho: <0.0001 <0.0001 0.10 0.11 0.001

R2 or Partial R2 33.1% 30.7% 1.9% 1.2% 3.7%

Minutes O2 p-value for rejecting Ho: <0.0001 <0.0001 <0.0001 0.001 0.0003

< 90% R2 or Partial R2 33.8% 31.3% 2.9% 2.1% 3.6%

Response Surface MethodologyUsing Abdominal Visceral Fat Volume

Null hypothesis tested

No VisFAT or OSA effects (df=7)

No VISFAT Effect (df=5)

No OSA Effect (df=5)

No VISFAT*OSA interaction

(df=3)

No Non-

linearity (df=4)

AHI p-value for rejecting Ho: <0.0001 <0.0001 0.25 0.77 0.003

R2 or Partial R2 21.9% 26.0% 1.2% 0.1% 3.2%

ODI p-value for rejecting Ho: <0.0001 <0.0001 0.36 0.73 0.02

R2 or Partial R2 21.7% 25.3% 1.1% 0.3% 2.4%

Min SAO2 p-value for rejecting Ho: <0.0001 <0.0001 0.01 0.62 0.02

R2 or Partial R2 23.2% 20.5% 1.9% 1.2% 3.7%

Minutes p-value for rejecting Ho: <0.0001 <0.0001 0.06 0.12 0.07

O2< 90% R2 or Partial R2 22.5% 20.6% 2.1% 1.1% 1.8%


Medical history

All

(N=498) BMI < 30

kg/m2 BMI 30 -< 35

kg/m2 BMI ≥ 35

kg/m2

p-value

for comparison

between groups

(Wilcoxon or χ2)

Hypertension (%) 41.0 31.3 42.6 52.4 <0.001

Cardiovascular disease (%) 16.0 17.4 16.3 13.5 0.65

Obstructive lung disease (%) 18.2 16.2 16.8 23.2 0.25 Diabetes (%) (current users of diabetes medication excluded from cohort)

1.4 0.6 1.1 3.2 0.14

Statin use (%) 19.5 18.3 19.8 20.6 0.87

Participate in exercise (%) 65.5 76.3 63.0 54.4 <0.001

Construction of the ‘Double Overlap Cohort’ AHI 14-80 and ODI 10-65

The Effects of Obstructive Sleep Apnea and Visceral Fat on Insulin Resistance

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