□ ORIGINAL ARTICLE □Investigating the Relationship between Morning Glycemic
Variability and Patient Characteristics Using Continuous
Glucose Monitoring Data in Patients with Type 2 Diabetes
Soichi Takeishi, Akihiro Mori, Miyuka Kawai, Yohei Yoshida, Hiroki Hachiya,
Takayuki Yumura, Shun Ito, Takashi Shibuya, Nobutoshi Fushimi,
Noritsugu Ohashi and Hiromi Kawai

Abstract
Objective To investigate the relationship between patient characteristics and morning glycemic variability.
Methods We retrospectively evaluated 106 patients with type 2 diabetes who underwent continuous glucose
monitoring during admission. The highest postprandial glucose level (within 3 hours after breakfast; ‘highest
level’), the time from the start of breakfast to the highest postprandial glucose level (‘highest time’), the difference between the pre-breakfast and highest postprandial breakfast glucose level (‘increase’), the area under
the curve (AUC; !180 mg/dL) for the glycemic variability within 3 hours after breakfast (‘morning AUC’),and the post-breakfast glucose gradient (‘gradient’) were calculated. We analyzed the associations between
these factors and nocturnal hypoglycemia and the patients’ characteristics by using a regression analysis.
Results After stepwise multivariate adjustment, significant independent associations were found between‘highest level’ and high age, low BMI, and high HbA1c; ‘highest time’ and high HbA1c, low C-peptide immunoreactivity (CPR), and low fasting plasma glucose (FPG); the ‘increase’ and high age, low BMI, highHbA1c, low FPG and hypoglycemia; ‘morning AUC’ and high age, high HbA1c and hypoglycemia; and ‘gradient’ and long duration of diabetes and low BMI.
Conclusion Higher age and lower BMI are associated with higher ‘highest’ and ‘increase’ levels. Higher
HbA1c levels were linked to a longer ‘highest time’, and longer durations of the diabetes, while lower BMI
values were related to a higher ‘gradient’.
Key words: morning glycemic variability, patient characteristics, Continuous Glucose Monitoring (CGM)(Intern Med 56: 1467-1473, 2017)(DOI: 10.2169/internalmedicine.56.7971)

Introduction
The post-breakfast glucose levels are often increased to agreater extent than post-lunch or post-supper glucose levels,and may cause increased glycemic variability over 24hours (1). The glucose level after the first meal (breakfast) (2), and sometimes the Somogyi phenomenon (3) andthe dawn phenomenon (4) are the main causes of increased
morning glucose levels. In the case of the Somogyi phenomenon, the cause is nocturnal hypoglycemia. Thus, (i) ad-

justing treatment to avoid nocturnal hypoglycemia when
nocturnal hypoglycemia causes increased morning glucose
levels and (ii) decreasing the post-breakfast glucose levels
directly by adjusting treatment, are necessary in order to improve increased post-breakfast glucose levels.
Large clinical studies have shown that hypoglycemia isstrongly associated with mortality in diabetes mellitus patients (5-7). It has been suggested that nocturnal hypoglycemia is associated with not only major hyperglycemia during
the daytime (8, 9), but also increased morning glucose levels (10). We have reported the relationship of major in-

Department of Endocrinology and Diabetes, Ichinomiyanishi Hospital, Japan
Received for publication July 9, 2016; Accepted for publication October 11, 2016
Correspondence to Dr. Soichi Takeishi, souichi19811225@yahoo.co.jp1467

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DOI: 10.2169/internalmedicine.56.7971

creases between the pre- and post-breakfast glucose levels
and nocturnal hypoglycemia in patients with type 2 diabetes (11). We can reduce increases between the pre- and postbreakfast glucose levels and improve the increased glycemic
variability over 24 hours by adjusting a patient’s treatment
to avoid nocturnal hypoglycemia.
Knowledge of a patient’s morning glycemic variability
status is important for improving increased glycemic variability over 24 hours. The measurement of pre- and postbreakfast blood glucose levels is often complicated for patients who do not use injections. Thus, it is desirable to predict morning glycemic variability using an easier method.
We focused on using patient characteristics to predict morning glycemic variability (12). We investigated the relationship between patient characteristics and morning glycemic
variability in type 2 diabetes patients using continuous glucose monitoring (CGM) data.

the post-breakfast glucose gradient (‘increase’/‘highest
time’) (‘gradient’) (11, 13). We analyzed the association between these indices of glycemic variability (response variable) and nocturnal hypoglycemia and the patient characteristics [age, sex, duration of diabetes, body mass index(BMI), glycosylated hemoglobin (HbA1c) concentration, Cpeptide immunoreactivity (CPR), fasting plasma glucose(FPG), the C-peptide index (= fasting C-peptide immunoreactivity/FPG ×100] (CPI) and the presence of antidiabetic
agents) (explanatory variable) using univariate and stepwise(method of increasing and decreasing the variables) multivariate regression analyses.
p values of <0.05 were considered to indicate statisticalsignificance. The data are shown as the mean and standard
deviation (SD). The data were analyzed using the BellCurvefor Excel software program (Social Survey Research Information, Japan).

Materials and Methods

Results

Study design and patient selection

Patient characteristics

We retrospectively analyzed 106 type 2 diabetes patients
who underwent CGM during admission over a 2-year period
from 2013 to 2015. A CGM (Medtronic ipro2; Medtronic
MiniMed, Northridge, USA) device was attached to each patient for 4 days, and we evaluated the CGM data measured
on the third day. The patients were given 3 meals per day,each with 1,440 kcal, 1,600 kcal, or 1,840 kcal (determinedaccording to their physique) (13). Identical test meals were
given to each patient based on the recommendation of theJapan Diabetes Society (carbohydrates, 60%; proteins, 18%;
and lipids, 22%) (breakfast, 30%; lunch, 35%; supper, 35%),
irrespective of differences in their physique. The inclusion
criteria were: 1) patients who were from 20 to 90 years ofage, 2) patients who took the whole quantity of every meal
while undergoing CGM. The exclusion criteria were: 1) patients who were aware of their hypoglycemia and who took
glucose tablets, 2) patients who had been taking αglucosidase inhibitors (because α-glucosidase inhibitors affect the glucose gradient). Nocturnal hypoglycemia was defined as a blood glucose level of <70 mg/dL occurring from0 AM to 8 AM.
The present study was approved by the institutional review board of Ichinomiyanishi Hospital, Japan. All of theextracted patient data were anonymized.

Figure shows the glycemic variability over 24 hours of
CGM in all of the patients. Table 1 shows the patients’ characteristics. The study included 56 men and 50 women. The
baseline characteristics were as follows: mean age, 66.6±
11.0 years; BMI, 23.7±3.9 kg/m2; HbA1c level, 8.7±1.4%(71.2±15.6 mmol/moL); duration of diabetes, 14.7±10.7
years; CPR, 1.4±1.0 ng/mL; FPG, 144.6±64.9 mg/dL; andCPI, 1.0±0.8. The indices of morning glycemic variability
were as follows: pre-breakfast glucose level [7:00], 128.7±
33.8 mg/dL; ‘highest level’, 226.4±62.7 mg/dL; ‘highest
time’, 100.8±42.2 minutes; ‘increase’, 97.7±56.3 mg/dL;‘morning AUC’, 7,027.4±9,268.6 mg・min/dL; and ‘gradient’, 1.1±1.2 mg/dL・min. Twenty-eight patients (26.4%) had
hypoglycemia.

The outcomes and statistical analyses

The parameters used as the indices of morning glycemic
variability included the highest postprandial glucose levelwithin 3 hours after breakfast (‘highest level’), the timefrom the start of breakfast to the highest postprandial glucose level (‘highest time’), the difference between prebreakfast and the highest postprandial breakfast glucose
level (‘increase’), the area under the glucose curve (!180
mg/dL) within 3 hours after breakfast (‘morning AUC’), andPrimary outcomes

According to a univariate analysis, high age, long duration of diabetes, low BMI, high HbA1c, low CPR and hypoglycemia were significantly associated with the ‘highest
level’ (ß=0.38, p=<0.0001; ß=0.36, p=0.0002; ß=-0.36, p=
0.0001; ß=0.25, p=0.008; ß=-0.21, p=0.03; ß=0.25, p=0.01,
respectively). High HbA1c, low CPR, low FPG, low CPI
and hypoglycemia were significantly associated with the‘highest time’ (ß=0.2, p=0.045; ß=0.22, p=0.02; ß=-0.47, p<
0.0001; ß=-0.25, p=0.009; ß=-0.38, p<0.0001; ß=0.19, p=
0.046, respectively). High age, long duration of diabetes,
low BMI, high HbA1c, low CPR, low FPG and hypoglycemia were significantly associated with the ‘increase’ (ß=0.39, p=<0.0001; ß=0.38, p=<0.0001; ß=-0.39; p=<0.0001;
ß=0.25, p=0.009; ß=-0.24, p=0.01; ß=-0.29, p=0.003; ß=
0.41, p=<0.0001, respectively). High age, long duration ofdiabetes, high HbA1c and hypoglycemia were significantly
associated with ‘morning AUC’ (ß=0.33, p=0.0005; ß=0.27,
p=0.005; ß=0.28, p=0.003; ß=0.27, p=0.004, respectively).

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DOI: 10.2169/internalmedicine.56.7971

300

Glucose level (mg/dL)

250

200

150

100

50

0
0:00

2:00

4:00

6:00

8:00

10:00

12:00

14:00

16:00

18:00

20:00

22:00

24:00
Time

Figure. The graph shows the glucose variability over 24 hours during continuous glucose monitoring in all of the patients. The data are shown as the mean (thick lines) and standard deviation (thinlines).

Long duration of diabetes and low BMI were significantly
associated with the ‘gradient’ (ß=0.3, p=0.002; ß=-0.34, p=
0.0003, respectively). The use of antidiabetic agents was not
associated with the indices of morning glycemic variability(Table 2).
After stepwise multivariate adjustment, high age, low
BMI, and high HbA1c were significantly and independently
associated with the ‘highest level’ (ß=0.29, p=0.002; ß=-0.26, p=0.004; ß=0.26, p=0.003, respectively). HighHbA1c, low CPR, and low FPG were significantly and independently associated with the ‘highest time’ (ß=0.21, p=
0.03; ß=-0.34, p=0.0009; ß=-0.23, p=0.02, respectively).
High age, low BMI, high HbA1c, low FPG and hypoglycemia were significantly and independently associated with the‘increase’ (ß=0.23, p=0.009; ß=-0.23, p=0.01; ß=0.36, p<
0.0001; ß=-0.28, p=0.003; ß=0.2, p=0.01, respectively).
High age, high HbA1c and hypoglycemia were significantly
and independently associated with ‘morning AUC’ (ß=0.33,
p=0.0003; ß=0.29, p=0.002; ß=0.2, p=0.03, respectively).
Long duration of diabetes and low BMI were significantly
and independently associated with the ‘gradient’ (ß=0.21, p=
0.03; ß=-0.28, p=0.005, respectively) (Table 3).

The relationship between the highest postprandial
glucose level within 3 hours (‘the highest’) and thepatient characteristics

According to a univariate analysis, high age, long duration of diabetes, low BMI, high HbA1c, low CPR, low FPG,
low CPI and hypoglycemia were significantly associatedwith the ‘the highest’ after lunch (ß=0.34, p=0.0004; ß=
0.41, p=<0.0001; ß=-0.23, p=0.02; ß=0.27, p=0.005; ß=-0.37, p=0.0001; ß=-0.32, p=0.001, ß=-0.32, p=0.0007, ß=
0.24, p=0.01, respectively). High age, long duration of diabetes, low BMI, low CPR and low FPG were significantly
associated with the ‘the highest’ after supper (ß=0.28, p=
0.004; ß=0.40, p=<0.0001; ß=-0.20, p=0.04; ß=-0.22, p=
0.02; ß=-0.27, p=0.005, respectively) (Table 4).
After stepwise multivariate adjustment, high age, highHbA1c low FPG and low CPI were significantly and independently associated with ‘the highest’ after lunch (ß=0.20,
p=0.03; ß=0.28, p=0.003; ß=-0.35, p=0.0003, ß=-0.24, p=
0.008, respectively). A long duration of diabetes was significantly and independently associated with ‘the highest’ after
supper (ß=0.35, p=0.0003) (Table 5).

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Table 1.

DOI: 10.2169/internalmedicine.56.7971

The Baseline Characteristics.

Characteristics
N (Male / Female)Age, years
Duration of diabetes, years
BMI, kg/m2
HbA1c (NGSP), %HbA1c (IFCC), mmol/moL
CPR, ng/mL
FPG, mg/dL
CPI
Pre-breakfast glucose level, mg/dL
Highest glucose level, mg/dL
Highest glucose time, minutes
Increase glucose level, mg/dL
AUC (≥180 mg/dL), mg·min/dL
Glucose gradient, mg/dL·min
Highest during 24 hours, n
Post-breakfast
Post-lunch
Post-supper
Hypoglycemia, n (%)
Sulfonylurea agent, n (%)
Metformin, n (%)
Thiazolidinediones, n (%)α - glucosidase inhibitor, n (%)
Insulin, n (%)
DPP-4 inhibitors, n (%)
GLP-1 receptor agonists, n (%)
Rapid-acting insulin secretagogue, n (%)
SGLT 2 inhibitor, n (%)

106 (56 / 50)
66.6 ± 11.0
14.7 ± 10.7
23.7 ± 3.9
8.7 ± 1.4
71.2 ± 15.6
1.4 ± 1.0
144.6 ± 64.9
1.0 ± 0.8
128.7 ± 33.8
226.4 ± 62.7
100.8 ± 42.2
97.7 ± 56.3
7,027.4 ± 9,268.6
1.1 ± 1.2
46
24
34
28 (26.4)
10 (9.4)
68 (64.2)
17 (16.0)0 (0)70 (66.0)
58 (54.7)
13 (12.3)
11 (10.4)
19 (17.9)

The data are shown as the mean and standard deviation (SD).
BMI: body mass index, HbA1c: glycosylated hemoglobin, CPR: C-peptide immunoreactivity, FPG: fasting plasma glucose, CPI: C-peptide index, Highest glucose level: highest postprandial glucose level within 3
hours after breakfast, Highest glucose time: time from start of breakfast
to the highest postprandial glucose level, Increase glucose level: difference between pre-breakfast and highest postprandial breakfast glucose
levels, AUC (≥180 mg/dL): area under the glucose curve (≥180 mg/dL)
within 3 hours after breakfast, Glucose gradient: post-breakfast glucose
gradient, Highest during 24 hours: highest glucose levels during 24
hours Hypoglycemia, nocturnal hypoglycemia (<70 mg/dL from 0:00
to 8:00), DPP: dipeptidyl-peptidase, GLP: glucagon-like peptide,
SGLT: Sodium glucose co-transporter

Discussion
Overall, the results of our study suggest that: Higher age
and lower BMI are associated with higher ‘highest’ and ‘increase levels’. Higher HbA1c levels are linked to longer‘highest time’, and longer durations of diabetes and lower
BMI are related to higher ‘gradient’.
Regarding the observation that higher age is associatedwith a higher ‘increase’, it has been suggested that elderly
patients with diabetes characteristically have lower prebreakfast glucose levels, but higher post-breakfast glucose
levels (14). The results of our study are in agreement withprevious reports (14). Regarding the observation that a lower
BMI was associated with a higher ‘increase’, we believe thereason for this is that patients can be diagnosed with diabetes despite having a low BMI; the insulin sensitivity of suchpatients increases, while their endogenous insulin secretion
decreases. We therefore believe that the post-breakfast glucose levels can easily increase. Regarding the association
between a higher ‘gradient’ and a longer duration of diabetes and lower BMI, the longer duration of diabetes andlower BMI generally leads to a decrease in endogenous insulin secretion. Decreasing endogenous insulin secretion
mainly causes a higher ‘gradient’. Based on the aforementioned observations, we believe that treatments that decrease
the post-breakfast glucose levels in elderly diabetes patients
as well as delay or reduce the increase in the post-breakfast
glucose levels of diabetes patients with low BMI values
should be considered.
The observation that higher HbA1c levels correspond witha longer ‘highest time’, that lower HbA1c levels are related
to an earlier ‘highest time’ in patients with diabetes, andthat the ‘highest time’ occurs early in the oral glucose tolerance test of early impaired glucose tolerance can possibly be
explained by a decrease in early endogenous insulin secretion and a later recovery in endogenous insulin secretion.
Thus, the ‘highest time’ occurs earlier. In addition, higher
HbA1c is associated with a greater decrease in not only
early but also late endogenous insulin secretion (15). As aresult, the ‘highest time’ occurs later. Thus, we should also
consider treatments that decrease the ‘highest levels’ in thelater time zones from 1 hour to 2 hours after breakfast to
decrease the post-breakfast glucose levels in patients withhigh HbA1c levels.
In the present study, the post-supper or post-lunch glucose
levels may have been the highest over 24 hours because thestudy subjects took various medications. Thus, we also studied the relationships between the highest glucose levels andthe clinical characteristics at post-supper and post-lunch. As
a result, the post-lunch glucose level was associated with thepatients’ clinical characteristics (to the same extent as thepost-breakfast glucose level), but the relationship between
the post-supper glucose level and the clinical characteristics
was not stronger than that observed with the post-breakfast
glucose level. In this study, the number of patients who had
their highest glucose levels (over a 24-hour period) at the
post-breakfast measurement was greater than the number ofpatients whose highest glucose levels were recorded in the
post-lunch measurement (46 vs. 24). We were therefore of
the opinion that the present study, which aimed to predictglycemic variability based on the clinical characteristics,
should focus on the post-breakfast glucose levels.
Our study results were evaluated using CGM data, whichis the most useful method for evaluating glycemic variability
in detail (16, 17). Our results suggested that we could predict morning glycemic variability before and after breakfast
based on patient characteristics and without the use of frequent blood collection (including the self-measurement of

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83.87
227.44195.55362.13129.52243.75248.50238.89217.21225.92228.92224.69226.89219.40226.09225.43222.89The data were subjected to a univariate regression analysis.
a: constant term, ß: standardized partial regression coefficientAge, years
Male sex, nDuration of diabetes, years
BMI, kg/m2
HbA1c (NGSP), %CPR, ng/mL
FPG, mg/dL
CPI
Hypoglycemia, nSulfonylurea agent, n (%)
Metformin, n (%)
Thiazolidinediones, n (%)
Insulin, n (%)
DPP-4 inhibitors, n (%)
GLP-1 receptor agonists, n (%)
Rapid-acting insulin secretagogue, n (%)
SGLT 2 inhibitor, n (%)

0.38
-0.02
0.36
-0.36
0.25
-0.21
-0.16
-0.16
0.25
0.02
-0.03
0.06
-0.01
0.1
0.01
0.05
0.12

<0.0001
0.88
0.00020.0001
0.008
0.03
0.11
0.11
0.01
0.8
0.76
0.52
0.96
0.3
0.88
0.63
0.22

p

a

VariableßHighest glucose level

51.15
107.1892.88
111.8943.98
126.37124.60121.1895.96
102.46
97.66
99.02
95.81
103.56102.15
98.74
99.16

a
0.2
-0.14
0.14
-0.04
0.22
-0.47
-0.25
-0.38
0.19
-0.12
0.06
0.1
0.09
-0.06
-0.08
0.15
0.09

ß
0.045
0.14
0.16
0.66
0.02
<0.0001
0.009<0.0001
0.046
0.22
0.56
0.31
0.38
0.55
0.39
0.13
0.38

p

Highest glucose time

-35.88101.9068.31
230.7911.58
115.39134.20106.09
83.85
97.08
94.50
98.95
96.43
91.48
96.48
95.56
95.95

a
0.39
-0.07
0.38
-0.39
0.25
-0.24
-0.29
-0.12
0.41
0.03
0.04
-0.05
0.02
0.1
0.06
0.11
0.07

ß
<0.0001
0.47<0.0001<0.0001
0.009
0.01
0.003
0.23
<0.0001
0.73
0.66
0.6
0.87
0.3
0.56
0.25
0.5

p

Increase glucose level

The Relationship between Morning Glycemic Variability and the Patient Characteristics.

Univariate

Table 2.

-11,547.79
7,630.21
3,566.07
15,518.35-8,844.09
8,977.63
6,831.99
9,178.57
5,510.05
6,962.32
7,735.95
6,654.22
6,406.27
5,603.08
7,071.91
6,779.17
6,428.94

a
0.33
-0.06
0.27
-0.15
0.28
-0.16
0.009
-0.18
0.27
0.02
-0.06
0.09
0.05
0.14
-0.01
0.08
0.14

ß

0.0005
0.53
0.005
0.12
0.003
0.09
0.92
0.06
0.004
0.82
0.56
0.35
0.62
0.15
0.9
0.42
0.16

p

AUC (≥180 mg/dL)

-0.24
1.05
0.63
3.71
0.76
1.07
1.50
0.94
1.10
1.17
1.05
1.19
1.10
1.20
1.17
1.16
1.17

a

0.19
0.08
0.3
-0.34
0.05
0.05
-0.13
0.14
0.06
-0.04
0.06
-0.07
0.03
-0.04
-0.04
-0.03
-0.04

ß

0.06
0.43
0.002
0.0003
0.6
0.6
0.2
0.17
0.52
0.66
0.54
0.48
0.79
0.7
0.72
0.76
0.69

p

Glucose gradientIntern Med 56: 1467-1473, 2017
DOI: 10.2169/internalmedicine.56.7971

Intern Med 56: 1467-1473, 2017

DOI: 10.2169/internalmedicine.56.7971

Table 3. The Relationship between Morning Glycemic Variability and the Factors That were Significantly Associated with
Morning Glycemic Variability (adjusted).
Highest glucose
level
Variable
Age, years
Duration of diabetes, years
BMI, kg/m2
HbA1c (NGSP), %FPG, mg/dL
CPI
Hypoglycemia, naR2SignificanceHighest glucose
timeßIncrease glucose
level

ß

p

ß

p

ß

p

0.27

0.004

0.17

0.046

0.3

0.0009

-0.25
0.25

0.007
0.005

-0.19
0.33
-0.33

0.02
<0.0001
0.00070.14
120.36
0.26

0.11

0.2
24.03
0.42

0.01

0.20
-0.38
-0.33

p

Glucosegradient

AUC (≥180 mg/dL)

0.04<0.0001
0.0004100.860.26<0.0001<0.0001

0.26

0.003

0.2
-25,722.45
0.21

0.03

ß

p

0.21
-0.28

0.03
0.005

2.83
0.14

<0.0001<0.0001

0.0001The data were subjected to a stepwise multivariate regression analysis. If explanatory variables displayed multicollinearity, either one was eliminated.

Table 4. The Relationship between the Highest Postprandial Glucose Level within 3 Hours(’the Highest’) and the Patient Characteristics.
Highest glucose level
Variable
Age, years
Male sex, nDuration of diabetes, years
BMI, kg/m2
HbA1c (NGSP), %CPR, ng/mL
FPG, mg/dL
CPI
Hypoglycemia, nSulfonylurea agent, n (%)
Metformin, n (%)
Thiazolidinediones, n (%)
Insulin, n (%)
DPP-4 inhibitors, n (%)
GLP-1 receptor agonists, n (%)
Rapid-acting insulin secretagogue, n (%)
SGLT 2 inhibitor, n (%)

LunchSupper

a

ß

p

a

ß

p

85.11
227.16182.20309.88110.92249.88262.19245.91209.25220.59221.05217.97216.16213.23220.36217.10215.60

0.34
-0.12
0.41
-0.23
0.27
-0.37
-0.32
-0.32
0.24
-0.08
-0.03
0.03
0.03
0.08
-0.06
0.08
0.11

0.00040.21<0.0001
0.02
0.005
0.00010.001
0.0007
0.01
0.40
0.79
0.76
0.77
0.42
0.53
0.43
0.28

115.24230.23185.53292.20152.64237.36254.78233.14215.20220.84219.97220.45220.04217.26221.03217.05221.20

0.28
-0.17
0.40
-0.20
0.18
-0.22
-0.27
-0.17
0.12
-0.06
-0.01
-0.03
-0.01
0.03
-0.06
0.12
-0.06

0.004
0.09
<0.0001
0.04
0.07
0.02
0.005
0.08
0.23
0.52
0.96
0.74
0.96
0.73
0.52
0.22
0.57

The data were subjected to a univariate regression analysis.

Table 5. The Relationship between ’the Highest’ and the Factors That were Significantly Associated with ’the Highest’ (adjusted).
Highest glucose level
Variable
Age, years
Duration of diabetes, years
HbA1c (NGSP), %FPG, mg/dL
CPI
a
R2
Significance

Lunch
ß

p

0.20

0.03

0.28
-0.35
-0.24
95.58
0.31

0.003
0.00030.008

Supperßp

0.35

0.0003

-0.16

0.08

211.070.17<0.0001<0.0001

The data were subjected to a stepwise multivariate regression analysis. If explanatory variables displayed multicollinearity, either one was eliminated.

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blood glucose). This information may help to provide appropriate guidance and in the selection of medications. Thus,
the clinical significance of the present study is high. However, it should be noted that this study was retrospective innature and that patients took various medications during thestudy period, including metformin, insulin, and insulin secreting anti-diabetic drugs. Moreover, factors that are needed
to show homeostasis model assessment of insulin resistance(HOMA-R) or other factors showing insulin resistance were
not measured in the subjects of the present study. Thus, thevalidity of these results must be confirmed in a prospective
study in which antidiabetic agents are not used.
The authors state that they have no Conflict of Interest (COI).
Acknowledgement
This work was partially supported by Ichinomiyanishi Hospital.
S.T. designed the study, collected the data, analyzed the data,
and wrote the manuscript. A.M. reviewed the manuscript and revised it critically for important intellectual content. M.K., Y.Y.,
H.H., T.Y., S.I., T.S., N.F., N.O., and H.K. contributed to the review of the manuscript. S.T. is the guarantor of this work and, assuch, had full access to all the data in the study and takes responsibility for the integrity of the data and the accuracy of thedata analysis.

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