What is the Incidence of Sleep Apnea in Type 2 Diabetics in Japan?
－JEDAS Study Report－（JEDAS：Japanese Epidemiology DM and SAS）
Shunichi Tanaka, Yasuo Akanuma, Yasuo Ohashi, JEDAS Study Group
Materials & MethodBackground
1. Stress associated with sleep apnea
syndrome (SAS) has recently beenbrought to attention as a risk factor for
abnormal glucose metabolism andinsulin resistance. (Naresh et al. Am JEpidemiol, 2004)
2. Compared with non-diabetics,
prevalence of SAS is known to behigher in diabetics in the U.S.A. andEurope (15.6% vs 23.8%). (Resnick etal. Diabetes Care, 2003) In contrast,
SAS prevalence among Japanesediabetics is unknown.
3. SAS is strongly associated with obesity.
A large percentage of Japanese type 2
diabetics is leptosomatic comparedwith their counterparts in the U.S.A.
and Europe
4. We conducted a multicenter crosssectional epidemiological study inoutpatients with type II DM to estimate
the prevalence of SAS among DM.

Objective
1.

2.

To estimate prevalence of SAS
among type 2 diabetics
To explore association between SAS
and diabetic pathology such as insulin
resistance in type 2 diabetics

ResultSubjects• Inclusion criteria: outpatients with type 2 diabetes(according to the diagnostic criteria of Japan DiabetesSociety)• Exclusion criteria: patients without diabetes treatment
information for the last 3 months• Number of patients analyzed: consecutive 904 patients
Study design• Multicenter prospective cross-sectional observational
study (epidemiological study)
Measurements/data investigated• Demographic data, history of diabetes, physicalmeasurements, vital signs, blood biochemical test (ex.
FBG, fasting insulin, HbA1c), urine test, lifestyle,past/current disorders and complications• Nocturnal pulse oximetry to estimate presence of SAS• Patient questionnaire (SF-36, Beck Depression Inventory,
stress check list, Pittsburgh sleep quality index)
Statistical analysis• Ratio estimation (95% CI), correlation analysis,multivariate analysis (ex. logistic regression)
Characteristics of the patients
Ite mM al eN
6 02
5 52
5 72
5 99
5 72
5 96
5 97
5 02
5 58
3 14
1 36
5 93
1 15
5 83
6 02

A g e ( ye ar)
D u ra ti on o f di ab et es (m o nt h)
H e ig ht (㎝ )W ei gh t (㎏ )B M I (㎏ /㎡ )S ys to li c B P (m m H g )D ia st ol ic B P (m m H g )H e art rate (b p m )A bd o m i n al c ircu m fe re n ce (㎝ )F as tin g b lo o d gl uc o se (㎎ / dL )Fa st in g in su l in (µ U / m L)
H bA 1c ( % )H O M A -IR (I U /L )*C re at in in e (㎎ /d L )3% O D I (/ ho u r)
N u m b er of d ia be ti c c o m p li ca ti on **02 471
1 23257344

6 0. 612 8
1 67 .4
7 0. 32 5. 013 27777
8 8. 813 986. 9
2. 80 .8 3
11

*Data of patients without previous insulin therapy

Fe m al e±±±±±±±±±±±±±±±

1 2 .310 7
6. 4
1 3 .6
4. 3171112
1 0 .2
476
1. 2
2. 1
0 .2 211N
302
262277
301
277
300
300
236280151
5429248291
302

6 2 .711 9
1 54 .0
6 1 .02 5 .613 174788 6 .413 496. 9
2. 90 .6 69±±±±±±±±±±±±±±±11 .598
5. 712 .3
4. 716111212 .6404
1. 1
1. 6
0. 39
8102533816(Mean ± SD)**Three major complications (diabetic retinopathy, diabetic nephropathy, diabetic neuropathy)

Estimated SAS Prevalence

Item

Cut-off value: 3% ODI > 10Height
WeightBMI
Abdominal circumference
Hip circumference
Neck circumference
Number of years drinking
Number of complication
Fasting insulin

Error bar: 95% CI>25Male

Summary

Simple Correlation with 3％ ODI

Female<25HOMA-IR(without previous insulin therapy)

Uric acid
Creatinine
Systolic BP
Diastolic BP
Heart rate
Physical function

Correlation
P valuecoefficient
0.07
0.05
0.23
<0.01
0.24
<0.01
0.30
<0.01
0.24
<0.01
0.25
<0.01
0.08
0.04
0.11
<0.01
0.18
0.01

N
849
900
849
818
818
818
627
678
190

0.17

0.03

163

0.13
0.07
0.12
0.13
0.09
-0.12

<0.01
0.03
<0.01
<0.01
0.01
<0.01

739
874896897
738899Multivariate Analysis Model (proportional odds model)
Statistically significant explanatory variables (statistical significance based on outcome
variables categorized by SAS severity [3% ODI of < 5, 5 < and < 15 or 15 <])Explanatory
variable
Age
SexBMIHeart rate
Creatinine
Hypertension

EstimateSE

P value

Odds ratio

0.02
-0.44
0.14
0.01
0.86
0.42

0.01
0.17
0.02
0.01
0.34
0.15

<0.01
0.01
<0.01
0.03
0.01
0.01

1.02
0.64
1.15
1.01
2.37
1.52

95% CI
1.01
0.46
1.11
1.00
1.21
1.13

1.04
0.90
1.20
1.03
4.65
2.03

Odds ratio per explanatory variable unit

E xplanatory
variableAgeSex
B MIHeart rate
C reatinine
Hypertension

U nit
10Male vs Female
5100.5
Yes vs N OOddsratio
1.27
0.64
2.01
1.14
1.54
1.52

95% CI
1.12
0.46
1.65
1.01
1.10
1.13

1.45
0.90
2.46
1.28
2.16
2.03

1. Estimated SAS prevalence among diabetics was 37.3% (95% CI, 0.34to 0.41) with a cut-off value of 3% ODI > 10.
2. Estimated SAS prevalence among diabetics with BMI < 25 was 30.2%(95% CI, 0.26 to 0.34) with a cut-off value of 3% ODI > 10.
3. Correlation with SAS severity (3% ODI) was seen in (1) physique data
(height, weight, BMI, abdominal circumference, hip circumference,neck circumference, number of years drinking), (2) diabetes-related
data (number of complication, fasting insulin, HOMA-IR), (3) renalfunction (creatinine, uric acid), (4) circulatory dynamics (bloodpressure, heart rate) and (5) questionnaire result (PhysicalFunctioning in SF-36).
4. The multivariate analysis using a proportional odds model showed
SAS severity (3% ODI) was related with age, sex, BMI, heart rate,creatinine and hypertension.

Discussion
1. As in the U.S.A. and Europe, SAS prevalence among Japanesediabetics is higher compared with general population (1.7%; Kayukawa
et al. Biomedicine and Therapeutics, 1996).
2. The estimated SAS prevalence among diabetics with BMI < 25suggests obesity is not the sole factor for SAS in diabetics.
3. ODI was correlated with number of diabetic complication, fasting insulinand HOMA-IR, suggesting a potential association between SAS anddiabetic pathologies.
4. Lack of correlation between QOL questionnaire survey results and ODI
shows diabetics are unaware of their symptoms even if they haveconcurrent SAS.
5. SAS affects blood glucose control in type 2 diabetics (Gottlieb et al.
Arch Intern Med, 2005) and is anReferences
independent risk factor for
cardiovascular disease (macrovascular disease) (Somers et al.
Circulation, 2008).
6. Based on the results of this study, we propose to implement it actively
screening for SAS in patients with diabetes.
7. The significant factors shown in the multivariate analysis, age, male,BMI, heart rate, hypertension and creatinine, are important
determinants of candidate diabetics for SAS screening.
8. It remains uncertain relationship between diabetes and SAS, therefore
we are planning the longitudinal study to reveal it for Japanese patients.
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