1 

Original Article for Chronobiology International

Morningness Eveningness Questionnaire score and metabolic parameters in

patients with type 2 diabetes mellitus

Yusuke Osonoi MD1, Tomoya Mita MD, PhD 1,4, Takeshi Osonoi MD, PhD6, Miyoko 5

Saito MD, PhD6, Atsuko Tamasawa MD, PhD6, Shiho Nakayama MD, PhD 1, Yuki

Someya1, Hidenori Ishida MD6, Akio Kanazawa MD, PhD 1,3, Masahiko Gosho, PhD7,

Yoshio Fujitani MD, PhD 1,2, Hirotaka Watada MD, PhD 1-5

1Department of Metabolism & Endocrinology, 2Center for Beta-Cell Biology and 10

Regeneration, 3Center for Therapeutic Innovations in Diabetes, 4Center for Molecular

Diabetology, 5Sportology Center, Juntendo University Graduate School of Medicine,

Tokyo, Japan, 2-1-1 Hongo, Bunkyoku, Tokyo 113-8421, Japan. Phone:

+81-3-5802-1579. Fax: +81-3-3813-5996

6 Naka Memorial Clinic, 745-5, Nakadai, Naka City, Ibaraki 311-0113, Japan. Phone: 15

+81-29-353-2800. Fax: 81-295-5400

7Unit of Biostatistics, Advanced Medical Research Center, Aichi Medical University,

1-1, Yazakokarimata, Nagakute, Aichi 480-1195, Japan. Phone: +81-561-61-1925.

Fax: 81-561-61-1896

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Running head: Lifestyle patterns and biochemical parameters

Word count, text 2,994, abstract 191, number of reference 28, number of tables 3

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Correspondence: Dr. Tomoya Mita, Department of Metabolism and Endocrinology,

Juntendo University Graduate School of Medicine, 2-1-1 Hongo, Bunkyoku, Tokyo 25

113-8421, Japan. Phone: +81-3-5802-1579. Fax: +81-3-3813-5996

E-mail: tom-m@juntendo.ac.jp

3 

Abstract

“Morningness” and “Eveningness” represent lifestyle patterns including sleep-wake 30

patterns. Although previous studies described a relationship between the

morningness-eveningness trait and glycemic control in patients with type 2 diabetes

mellitus (T2DM), the mechanism underlying this association remains unknown. The

study participants comprised 725 Japanese T2DM outpatient free of history of

cardiovascular diseases. Various lifestyles were analyzed using self-reported 35

questionnaires, including morningness-eveningness questionnaire. The relationships

between morningness-eveningness trait and various biochemical parameters were

investigated by linear regression analysis and logistic regression analysis. We

classified the study patients into three groups, morning type (n=117), neither type

(n=424), and evening type (n=184). Subjects of the evening type had high levels of 40

alanine aminotransferase, triglyceride, fasting blood glucose and HbA1c and low HDL

level in a model adjusted for age and gender. Furthermore, multivariate analysis

showed that the evening type was associated with high HbA1c and eGFR even after

adjustment for other lifestyle factors known to affect metabolic control. The results

suggest that T2DM patients with eveningness trait are under inadequate metabolic 45

control independent of other lifestyle factors. Thus, the evening trait classified by

morningness-eveningness questionnaire of T2DM patients represents an important

target for intervention to ensure appropriate metabolic function.

Key words: morningness-eveningness questionnaire, type 2 diabetes mellitus, 50

4 

Abbreviations:

BDI, Beck Depression inventory;

BDHQ, brief, self-administered diet history questionnaire;

CVD, cardiovascular disease; 55

HDL, high-density lipoprotein-cholesterol;

IPAQ, International Physical Activity Questionnaire;

MEQ, morningness-eveningness questionnaire;

NGSP, National Glycohemoglobin Standardization Program;

OHA, oral hypoglycemic agents; 60

PSQI, Pittsburg Sleep Quality Index;

T2DM, type 2 diabetes mellitus ;

5 

Introduction

The onset of type 2 diabetes mellitus (T2DM) is associated with numerous lifestyle

problems. Furthermore, the incidences of cardiovascular disease (CVD) and 65

microvasuclar events correlate with lifestyle factors in patients with T2DM (Stevens,

Kothari et al., 2001; Balkau, Hu et al., 2004). Recent studies have highlighted the

importance of morningness-eveningness trait, in addition to other life styles, in

glycemic control in patient with T2DM (Iwasaki, Hirose et al., 2013; Reutrakul, Hood

et al., 2013). The morningness-eveningness trait reflects the timing of the sleep-wake 70

pattern and other activities, which are quite variable among individuals. The

preferential timing of wake and bedtime is regulated by mainly endogenous circadian

clock in the suprachiasmatic nucleus of the hypothalamus together with various

environmental cues (Klerman, 2005).

With regard to the circadian clock, early studies on plants confirmed that 75

various 24-hour periodic phenomena arise from biological oscillators that internally

track the rotation of Earth. These clocks are entrained by light and synchronize

energy-harvesting and utilization processes with the rising and setting of the sun (Bass

& Takahashi, 2010). In addition, animal experiments showed that endogenous rhythms

are optimally synchronized to the environment by sunlight, physical activity, sleep and 80

feeding behavior and play important roles in the regulation of energy intake and

consumption, metabolism and hormone secretion, in addition to the sleep-wake

pattern (Turek, Joshu et al., 2005; Salgado-Delgado, Angeles-Castellanos et al., 2010;

Huang, Ramsey et al., 2011).

Humans living in modern industrialized societies have easier access to light 85

6 

and are often forced to be awake by social norms against their preferred times

independent of the master circadian rhythm. These environmental stimuli eventually

lead to the disruption of the circadian system. Thus, both genetic variations in clock

genes and environmental elements affect the distribution of chronotype.

Evening-type individuals show large differences between social rhythms and 90

the circadian clock. These subjects tend to have unhealthy eating habits, behavioral

health problems, sleep complains, more frequently than individuals of the

morning-type (Ostberg, 1973; Broms, Kaprio et al., 2011). These data suggest that

evening-type individuals could have potentially impaired metabolism based on

abnormal circadian rhythm. Indeed, cross-sectional study demonstrated higher 95

prevalence of T2DM and atrial hypertension in the evening-type individuals than in

the general population (Merikanto, Lahti et al., 2013). Furthermore, more recently, we

and other groups reported the relationships between evening type in 101 male

Japanese workers with T2DM and inadequate glycemic control, and between latter

chronotype among 194 non-shift workers with T2DM, and inadequate glycemic 100

control (Iwasaki, Hirose et al., 2013; Reutrakul, Hood et al., 2013).

These limited data suggest that chronotype could potentially affect glucose

metabolism in patients with T2DM. However, the mechanism or the factors that

mediate the association between the morningness-eveningness classified by The

Morning Evening Questionnaire (MEQ) score and biomedical parameters of glycemic 105

control, dyslipidemia, and renal function remains largely unknown in patients with

T2DM. Here, we investigated the relationship between morningness and eveningness

trait classified by MEQ score and various biochemical parameters in patients with

7 

T2DM.

110

Research Design and Methods

Subjects. The subjects of this cohort study were recruited from the Diabetes

Outpatient Clinic of Juntendo University, (Tokyo, Japan) Naka kinen Clinic (Naka,

Japan) or Secomedic Hospital (Funabashi, Japan). The subjects were mainly treated

their diabetes and lifestyle related disease including hypertension, hyperlipidemia and 115

so on. The inclusion criteria were as follows: 1) T2DM patients, 2) ≥25 years of age

and <70 years of age (regardless of gender), and 3) signing consent form for

participation in the study. The following exclusion criteria were also applied: 1) type 1

or secondary diabetes, 2) presence of severe infectious disease, before or after surgery,

or severe trauma, 3) history of myocardial infarction, angina pectoris, cerebral stroke, 120

or cerebral infarction, 4) chronic renal failure requiring hemodialysis, 5) liver cirrhosis,

6) moderate or severe heart failure (NYHA/New York Heart Association stage III or

higher), 7) active malignancy, 8) pregnant, lactating, or possibly pregnant women, or

those planning to become pregnant during the study period, 9) patients judged as

ineligible by the clinical investigators. 125

A total of 1,032 consecutive subjects were screened. Among them, 906 patients

who met the above eligibility criteria were invited to participate in the present study.

After providing information on the purpose and procedures of the study, 736 patients

with T2DM were recruited for this study between June 2013 and January 2014. Blood

and urine samples were taken from the participants and questionnaire surveys were 130

conducted. Data of brachial-ankle pulse wave velocity (baPWV) within about 6

8 

months from the day when questionnaire and blood sample tests were conducted were

used for analysis.

The study was approved by the Institutional Review Board of Juntendo

University Hospital and conducted in accordance with the principles described in the 135

Declaration of Helsinki. All patients provided written informed consent prior to

participation. The study was registered on the University Hospital Medical

Information Network Clinical Trials Registry (UMIN000010932).

Questionnaire survey. The MEQ (Hone & Ostberg, 1976) is a self-assessment 140

questionnaire developed primarily for screening candidates for sleep-related

experiments to evaluate morningness and eveningness in individuals. It consists of 19

items on sleep habits and fatigue. Scoring was based on the original questionnaire by

Östberg (Hone & Ostberg, 1976). The MEQ has a good validity and test-retest

reliability (Hone & Ostberg, 1976) (Taillard, Philip et al., 2004) (Ishihara K, 145

Miyashita A et al., 1986) (Lee, Kim et al., 2014). Briefly, 11 questions allowed for

choice and scored from 1 to 4. Two questions allowed for choice and scored 0, 2, 4

and 6. One question allowed for choice and scored 0, 2, 3 and 5. The remaining 5

questions allowed for choice of time scales and scored from 1 to 5. The sum of all

scores was converted into a three point MEQ scales as follow. scores 16-52: Evening 150

type, scores 53-64: Neither type, scores 65-86: Morning type, as reported previously

(Taillard, Philip et al., 2004).

The Pittsburg Sleep Quality Index (PSQI) (Buysse, Reynolds et al., 1989) is a

self-administered questionnaire designed to evaluate sleep quality and consists of 18

9 

items that in turn are comprised of 7 components, which include subjective sleep 155

quality, sleep duration, sleep onset, habitual sleep efficiency, sleep disturbances, use of

sleeping medications, and daytime dysfunction, with each weighted equally on a 0-3

scale, to be summed to yield the global PSQI score ranging from 0 to 21, where the

higher the scores, the worse the sleep quality. The PSQI has a high test-retest

reliability and a good validity (Backhaus, Junghanns et al., 2002). 160

The BDI (Beck Depression inventory)-II is a 21-item questionnaire that

assesses hopelessness, irritability, cognition, guilt, fatigue, weight loss, and sexual

interest, representing depression-related symptoms in adults and adolescents (Beck,

Steer et al., 1996). Each of the 21 items measures the presence and severity of somatic

or cognitive symptom of depression, rated on a 4-point scale ranging from 0 to 3. The 165

ratings are summed, yielding a total score ranging from 0 to 63. A high score

represents depressive state. The BDI-II has been validated as a sensitive, specific, and

predictive tool for quantitative assessment of the severity of depression (Beck, Steer et

al., 1996) and has been reliable (Kojima, Furukawa et al., 2002).

Dietary habits during the preceding month were assessed with the validated, 170

Brief, self-administered Diet History Questionnaire (BDHQ). The BDHQ is a 4-page

structured questionnaire that asks about consumption frequency of selected foods to

estimate the dietary intake of 56 food and beverage items with specified serving size

described in terms of consumption in general Japanese populations. The dietary intake

of energy, including alcohol and selected nutrients, were estimated using an ad hoc 175

computer algorithm for the 56 foods and beverages of the BDHQ and the Standard

Tables of Food Composition in Japan (Agency, 2005). The BDHQ has a good validity

10 

(Kobayashi, Murakami et al., 2011) and a test-retest reliability (Beliard, Coudert et al.,

2012).

Physical activity level was assessed with the International Physical Activity 180

Questionnaire (IPAQ) that comprises 4 simple questions on physical activity (Craig,

Marshall et al., 2003). The IPAQ has a good validity a high test-retest reliability

(Murase N, Katsumura T et al., 2002) (Hallal & Victora, 2004).The IPAQ results are

expressed as metabolic equivalent scores (METs-hour-week−1).

Workers were defined as full-time employees or shift workers. The work 185

schedule of the subjects was determined by a question in the questionnaire “Which is

your usual work schedule, day, evening, shift, or permanent night work?” Regular

daytime workers were defined as subjects without any evening or night work in their

usual work schedule. We defined shift working as working patterns that differed from

regular daytime working, including irregular or unspecified shifts, mixed schedules, 190

evening shifts, night shifts and rotating shift.

Subjects were asked whether they were currently smokers, had smoked, had

stopped smoking, the date of stopping smoking, and the number of cigarettes smoked

per day. The subjects were classified according to the smoking status into

non-smokers, former smokers or current smokers. Former smokers were those who 195

had not smoked during the month receding the study.

Biochemical tests. Blood samples were obtained at outpatient visits after

overnight fast. Liver and renal function tests, lipids, HbA1c, and glucose (National

Glycohemoglobin Standardization Program) were measured with standard techniques. 200

11 

Urinary albumin excretion (UAE) was measured by latex agglutination assay using a

spot urine sample. The estimated glomerular filtration rate (eGFR) was calculated by

the formula: eGFR (ml/min per 1.73 m2) =194× Age-0.287× serum creatinine-0.1094

(×0.739 for females) (Matsuo, Imai et al., 2009).

205

Measurement of baPWV. baPWV was measured using an automatic

waveform analyzer (BP-203RPE; Colin Medical Technology, Komaki, Japan).

baPWV is a useful independent predictor of mortality and cardiovascular morbidity

even in subjects with T2DM (Maeda, Inoguchi et al., 2014). Briefly, measurement was

performed with the patients in the supine position after resting for five minutes. 210

Occlusion and monitoring cuffs were placed snugly around both areas in the upper

and lower extremities. The pressure waveforms were then recorded simultaneously

from the brachial arteries by the oscillometric method. All scans were automatically

conducted by well-trained investigators who were blinded to the clinical information.

The validity and reproducibility of baPWV measurements are confirmed to be 215

considerably high (Yamashina, Tomiyama et al., 2002).

Statistical analysis. Results are presented as mean±SD or median (interquartile

range: 25% to 75%) for continuous variables or number (proportion) of patients for

categorical variables. Some parameters were logarithmically transformed to 220

approximate normal distribution. Trend association across three groups was evaluated

by linear regression analysis for continuous variables and logistic regression analysis

for categorical variables. We developed three models to evaluate the trend. The first

12 

model was unadjusted, the second was adjusted for age and gender, and third model

was adjusted for age, gender, body mass index, PSQI including sleep duration, BDI-II, 225

energy intake, smoking pattern, alcohol consumption and IPAQ. Statistical tests were

two-sided with 5% significant level. All analyses were performed using the SAS

software version 9.3 (SAS Institute, Cary, NC).

Results 230

Among the 736 participating patients, 11 did not complete the questionnaires and they

were thus excluded from analysis. The clinical characteristics of the 725 Japanese

patients with T2DM who were being treated on an outpatient basis are summarized in

Table 1. The mean age was 57.8±8.6 years, 62.9% male and HbA1c was 7.0±1.0%,

estimated duration of T2DM was 9.9±7.2 years. The majority of the subjects had 235

previously attended educational programs about diet and exercise therapy and

received appropriate medical treatments at our hospital. These factors were considered

to have contributed to the well-controlled glucose, lipids, and blood pressure in our

subjects.

The MEQ results showed that 117 individuals were “morning type”, 424 240

“neither type”, and 184 “evening type” as shown in Table 2. Subjects of the evening

type tended to be young, female, obese, workers and shift workers, and have high

PSQI, high BDI-II and low alcohol consumption in the unadjusted model. In the age-

and gender-adjusted model, the subjects were still shift workers with high PSQI and

high BDI-II. On the other hand, there were no significant trends in other lifestyles, 245

including energy intake, smoking consumption, alcohol consumption and IPAQ. In

13 

addition, those patients were likely to go to bed late, wake up late and sleep for shorter

time, in both the unadjusted model, and age- and gender-adjusted model. Also, they

tended to have late dinner and late breakfast, frequently have late evening snacks, and

less frequently have breakfast, in both the unadjusted model, and age- and 250

gender-adjusted model. In the model adjusted for age, gender, BMI, PSQI, BDI-II,

energy intake, smoking consumption, alcohol consumption and IPAQ, the subjects

were likely to go to bed late, wake up late, and have late dinner, and late breakfast,

frequently have late evening snacks, and less frequently have breakfast.

With regard to biochemical parameters and baPWV, significantly higher levels 255

of alanine aminotransferase (ALT), triglyceride, fasting blood glucose, HbA1c, and

eGFR and lower HDL levels characterized the subjects in the unadjusted model (Table

3). Furthermore, patients of the evening type had significantly high levels of ALT,

triglyceride, fasting blood glucose and HbA1c, and low HDL level even in the model

adjusted for age and gender. Furthermore, HbA1c and eGFR were higher in the model 260

adjusted for age, gender, BMI, PSQI, BDI-II, energy intake, smoking consumption,

alcohol consumption and IPAQ.

Discussion

Recent small sample sized studies showed that evening or later chronotype adversely 265

were associated with poor glycemic control (Iwasaki, Hirose et al., 2013; Reutrakul,

Hood et al., 2013). Our data extended those previous results by demonstrating that the

evening type classified by MEQ score was associated with high ALT and triglyceride,

and low HDL, in addition to poor glycemic control in the age- and gender-adjusted

14 

model. Notably, in those previous studies, other lifestyle factors, including sleep 270

quality, energy intake, physical activity, alcohol consumption and smoking were not

fully taken into consideration. Here, we demonstrated that the evening type classified

by MEQ score was associated with poor glycemic control in the model adjusted for

those other lifestyle factors (Table 3). Therefore, our results suggest that the evening

type classified by MEQ score is an important target for intervention in order to 275

achieve appropriate metabolic control among patients with T2DM.

In this study, total daily energy intake was similar among groups classified by

MEQ score. However, patients of the evening type were considered to consume a

greater amount of daily energy intake at late time of the day, because the evening type

tended to have late dinners, frequently late evening snacks, and less frequent breakfast. 280

Recent clinical studies have suggested that late dinner time promotes high

postprandial glucose levels after breakfast in the following morning, compared to

usual dinner time condition, through a greater effect of late dinners on carbohydrate

digestion and absorption of dietary carbohydrates (Tsuchida, Hata et al., 2013). In

addition, a recent study showed that evening intake of macronutrients and intake 285

before sleep may enhance weight gain in healthy volunteers (Baron, Reid et al., 2013).

Thus, late eating seems to worsen metabolic control.

Patients of the evening type classified by MEQ score were more likely to be

employed as workers including shift workers, with higher frequency of overtime work

beyond 21:00 PM. Such workers may be often forced to stay awake through social 290

cues against their preference regulated at least in part by the master circadian rhythm,

eventually leading to disruption of the circadian system. In this regard, a previous

15 

study demonstrated that short-period circadian misalignment in healthy volunteers

could lead to increase postprandial glucose and insulin levels (Scheer, Hilton et al.,

2009). In addition, it could result in low serum leptin levels, which may increase 295

appetite and reduce energy expenditure, leading, in turn, to the development of obesity

and deterioration of metabolism. Finally, such misalignment could also results in

complete inversion of cortisol profile.

In this study, subjects with the evening type classified by MEQ score tended to

have poor sleep quality and more depression-related symptoms. Recent studies 300

reported that both sleep duration and/or quality affect glucose and lipid metabolism in

patients with T2DM (Knutson, Ryden et al., 2006; Williams, Hu et al., 2007; Ohkuma,

Fujii et al., 2013; Wan Mahmood, Draman Yusoff et al., 2013). Also, depressive status

may also negatively affect glucose metabolism through increased counter-regulatory

hormones (Musselman, Betan et al., 2003). However, we showed that the evening type 305

classified by MEQ score was still associated with poor glycemic control even after

adjustment for the above factors. Thus, the poor glycemic control observed in the

evening type is likely to be independent of sleep quality and depression-related

symptoms.

Despite the large number of risk factors for atherosclerosis, subjects with the 310

evening type did not show increased atrial stiffness. This result may be influenced by

exclusion of patients with history of CVD who are considered increased arterial

stiffness. Additionally, we have to consider the possibility that the state of

atherosclerosis in certain artery including carotid artery and coronary artery may not

reflect the results of baPWV. Alternatively, we are conducting long-term follow-up 315

16 

study that focuses on lifestyle and onset of primary CVD, in the same cohort. On the

other hand, we found that eGFR was higher in subjects with the evening type, which

could reflect hyperglycemia-induced hyperfiltration.

The present study has certain limitations. First, the cross-sectional design does

not allow inference of causal relationship between evening type and metabolic control. 320

Second, we evaluated lifestyles including MEQ by self-reported questionnaires,

although they have been widely used in many studies. The results could be influenced

by social desirability and recall bias. Third, the validity and reproducibility of the

lifestyle patterns identified in this study were not confirmed, although we used

self-reported questionnaires which have good validity and reliability. Forth, we did 325

not evaluate the compliance of drugs, which may affect the anthropometric data, while

there were no significant differences in types of administered drugs including diabetes,

hypertension and hyperlipidemia among groups (data not shown). Finally, there may

be other lifestyle patterns including nap time that should be considered. Thus, further

sample sized studies across the nation are required. 330

In conclusion, the present study demonstrated that evening patients with T2DM

classified by MEQ score suffered inadequate metabolic control among T2DM patients

free of history of CVD. Therefore, our data suggest that the evening type classified by

MEQ score is an important target for intervention in order to achieve appropriate

metabolic function in patients with T2DM. 335

Declaration of Interest

17 

T.M. received research funds from MSD, Takeda and Eli Lilly. T.O. has received

lecture fees from Boehringer Ingelheim, Sanofi-Aventis, Ono Pharmaceutical Co.,

Novo Nordisk Pharma, Kissei Pharma, Mitsubishi Tanabe Pharma, Novartis 340

Pharmaceuticals, Sanwakagaku Kenkyusho, Daiichi Sankyo Inc., Takeda

Pharmaceutical Co., MSD, Dainippon Sumitomo Pharm., Kowa Co. and research

funds from Novo Nordisk Pharma, Dainippon Sumitomo Pharma. A.K. has received

lecture fees from Kissei Pharma, Sanofi-Aventis and Takeda Pharmaceutical Co. M.G.

has received lecture fees from Novartis Pharmaceuticals. Y.F. has received lecture fees 345

from Novartis Pharmaceuticals and Eli Lilly, research funds from Novartis

Pharmaceuticals , MSD and Takeda Pharmaceutical Co. H.W. has received lecture

fees from Boehringer Ingelheim, Sanofi-Aventis, Ono Pharmaceutical Co., Novo

Nordisk Pharma, Novartis Pharmaceuticals, Eli Lilly, Sanwakagaku Kenkyusho,

Daiichi Sankyo Inc., Takeda Pharmaceutical Co., MSD, Dainippon Sumitomo Pharm., 350

Kowa Co. and research funds from Boehringer Ingelheim, Pfizer, Mochida

Pharmaceutical Co., Sanofi-Aventis, Novo Nordisk Pharma, Novartis Pharmaceuticals,

Sanwakagaku Kenkyusho, Terumo Corp. Eli Lilly, Mitsubishi Tanabe Pharma, Daiichi

Sankyo Inc., Takeda Pharmaceutical Co., MSD, Shionogi, Pharma, Dainippon

Sumitomo Pharma, Kissei Pharma, and Astrazeneca. 355

Acknowledgments

The authors thank the following staff who participated in this trial: Ms. Risa

Yamamoto and Ms. Emi Ito (Department of Metabolism and Endocrinology, Juntendo

University Graduate School of Medicine), Ms. Satako Douguchi, Ms. Chiyoko Sato, 360

18 

Ms. Yoko Ono, Mr. Tadanori Koibuchi, Ms. Norie Shiina, Ms. Nana Shiozawa, Ms.

Mariko Kobori, Ms. Misato Ojima, Ms. Akiko Haginoya, Ms. Kumiko Fujisaku and

Mr. Katuhiro Kawauchi (Naka Memorial Clinic) for the excellent technical support.

19 

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1 

Table 1. Patients characteristics (n = 725).

Age (years) 57.8±8.6

Gender (male) 456 (62.9)

Estimated history of diabetes (years) 9.9±7.2

Body mass index (kg/m2) 24.6±4.1

HbA1c (%) 7.0±1.0

HbA1c (mmol/mol) 52.5±10.8

Fasting blood glucose (mg/dl) 134±31

Systolic blood pressure (mmHg) 127±14

Diastolic blood pressure (mmHg) 77±11

Total cholesterol (mg/dL) 185±28

HDL-cholesterol (mg/dL) 59±14

Triglyceride (mg/dL) 100 [70,152]

AST (U/L) 21 [18,27]

ALT (U/L) 22 [16,33]

-GTP (U/L) 25 [17,39]

Uric Acid (mg/dl) 5.5±1.2

eGFR (ml/min/ 1.73 m2) 78±18

UAE (mg/g creatinine) 10 [6,23]

baPWV (cm/s) 1543±279

Morningness-Eveningness Questionnaire 57.4±7.3

Pittsburg Sleep Quality Index 5.1±3.0

Beck Depression inventory -II 9.9±7.6

Energy intake (kcal/day) 1713±582

Physical activity (Mets/h/week) 42.8±70.5

Sleep duration (hours) 6.4±1.2

Number of cigarettes 335±458

Current smoker (yes) 174 (24.0)

Alcohol (g/day) 12.3±21.5

On treatment for (n/%)

Diabetes 620 (85.5)

Hypertension 346 (47.7)

Hyperlipidemia 442 (61.0)

Data are mean±SD or number (proportion) of patients.

ALT: alanine aminotransferase; AST: aspartate aminotransferase; baPWV: 5

brachial-ankle pulse wave velocity; eGFR: estimated glomerular filtration rate,

HDL-C: high-density lipoprotein-cholesterol, UAE, urinary albumin excretion, -GTP,

-glutamyl transpeptidase.

2 

Table 2. Characteristics of each group classified by MEQ score.

Variable Evening type Neither type Morning type Est Est1 Est2 MEQ 47.8± 3.8 58.6 ± 3.3 67.9 ± 2.7 - - - PSQI 6.2 ± 3.5 5.0 ± 2.7 3.9 ± 2.7 -6.72¶ -5.80¶ - BDI 11.6 ± 7.5 9.6 ± 7.7 8.5 ± 7.4 -3.76¶ -2.79† - Energy intake (kcal/day) 1683 ± 567 1743 ± 613 1652 ± 476 -0.16 -1.05 - Current smoking (yes) 48 (26.1) 98 (23.1) 28 (23.9) -0.53 -0.04 - Alcohol 11.0 ± 21.5 11.2 ± 19.9 18.6 ± 25.8 2.66† 1.53 - Physical activity (kcal/day) 33.0 ± 51.7 47.2 ± 81.4 42.3 ± 48.8 1.45 0.96 - Age (years) 53.9 ± 9.6 58.4 ± 57.9 61.8 ± 6.2 8.91¶ - - Gender (male) 108 (58.7) 264 (62.3) 84 (71.8) 2.18¶ - - Body mass index (kg/m2) 25.9 ± 4.5 24.3 ± 3.9 23.7 ± 3.4 -4.91¶ -1.89 - Estimated history of diabetes (years) 9.3±6.8 9.9±7.4 10.6±7.2 1.54 -0.66 -0.20 Anti-diabetes medications (yes) 156(84.8) 360 (84.9) 104 (88.9) 0.88 0.77 0.94 Anti-hypertension medications (yes) 85(46.2) 200 (47.2) 61 (52.1) 0.93 0.19 0.62 Anti-hyperlipidemia medications (yes) 114(62.0) 259 (61.1) 69 (59.0) -0.50 -1.06 -0.87 Working (yes) 149(81.0) 306 (72.2) 78 (66.7) -2.85† -1.21 -0.80 Shift worker (yes) 31(16.8) 43 (10.1) 4 (3.4) -3.67¶ -2.53† -2.42† frequency of overtime work beyond 21:00 PM 1.4±1.1 1.1±0.9 0.9±0.6 -5.41¶ -3.35¶ -2.79† Sleep duration (hours) 6.2±1.2 6.4±1.1 6.9±1.3 4.97¶ 3.47¶ 0.21 Wake time, A.M. 6:30 [6:00,7:18] 6:00 [5:30,6:30] 5:00 [5:00,5:45] -9.53¶ -9.40¶ -8.74¶ Bedtime, P.M. 24:00 [23:00,25:00] 23:00 [22:00,23:30] 22:00 [21:00,22:30] -13.45¶ -11.10¶ -11.31¶ Breakfast time, A.M. 7:30 [7:00,8:00] 7:00 [6:30,7:30] 6:30 [6:00,7:00] -9.29¶ -9.31¶ -8.69¶ Dinner time, P.M. 19:30 [19:00,20:00] 19:00 [18:30,19:30] 19:00 [18:00,19:30] -8.11¶ -6.25¶ -5.90¶ Number of breakfasts (/week) 6.0±1.9 6.8±1.0 6.9±0.4 7.07¶ 6.04¶ 5.53¶ Late evening snack (yes) 80 (43.5) 179 (42.2) 29 (24.8) -2.89† -3.01† -2.49*

Data are meanSD or median (range: 25% to 75%) or number of subjects. 10

EST and EST. P trend values for linear trends across quintiles are based on linear regression analysis for continuous variables or logistic

regression analysis for categorical variables. EST1 and EST1. Ptrend values for linear trends across quintiles are based on linear regression

analysis for continuous variables or logistic regression analysis for categorical variables adjusted for age and gender. EST2 and EST2. Ptrend

values for linear trends across quintiles are based on linear regression analysis for continuous variables or logistic regression analysis for

categorical variables adjusted for age, gender, BMI, PSQI, BDI-II, energy intake, alcohol intake, current smoking, and physical activity. 15

*P<0.05, †P<0.01, ¶P<0.001. BDI: Beck Depression inventory, MEQ: morningness-eveningness questionnaire PSQI: Pittsburg Sleep Quality

Index.

3 

Table 3. Cardio-renal-metabolic parameter according among each group classified by MEQ

score.

Variable Evening type Neither type Morning type Est Est1 Est2

AST (U/L) 22 [18,28] 21 [18,26] 22 [18,28] -0.48 -0.58 -0.18

ALT (U/L) 26 [18,40] 21 [16,31] 21 [16,32] -3.88† -2.36* -1.28

GTP (U/L) 29 [19,46] 24 [17,36] 26 [17,38] -1.77 -1.40 -1.45

Uric Acid (mg/dl) 5.5±1.3 5.4±1.3 5.6±1.1 -0.01 0.26 0.47

eGFR (ml/min/ 1.73 m2) 81±18 77±17 76±18 -2.62† - -2.26*

Total cholesterol (mg/dl) 183±28 186±28 186±27 0.91 1.31 1.50

HDL-C (mg/dl) 58±12 59±15 63±14 3.19 2.38 1.87

Triglycerides (mg/dl) 107 [83,160] 100 [67,152] 89 [66,140] -2.93† -2.05* -1.57

Fasting blood glucose (mg/dl) 142±37 131±28 132±30 -3.07† -1.97* -1.42

HbA1c 7.3±1.3 6.9±0.9 6.7±0.8 -4.99¶ -3.53¶ -2.94†

Systolic BP (mmHg) 127±13 126±14 126±15 -0.75 -0.99 -0.15

Diastolic BP (mmHg) 79±10 76±10 77±15 -1.79 -0.33 0.11

UAE (mg/g creatinine) 11 [6,23] 10 [5,22] 11 [6,24] 0.39 0.02 0.27

baPWV (cm/s) 1493±265 1556±282 1578±285 2.78† -0.96 -0.71

20

Data are meanSD or median (range: 25% to 75%). EST and EST. Ptrend values for linear trends across quintiles are based on linear regression analysis for continuous variables or logistic regression analysis for categorical variables. EST1 and EST1. Ptrend values for linear trends across quintiles are based on linear regression analysis for continuous variables or logistic regression analysis for categorical 25

variables adjusted for age and gender. EST2 and EST2. Ptrend values for linear trends across quintiles are based on linear regression analysis for continuous variables or logistic regression analysis for categorical variables adjusted for age, gender, BMI, morningness-eveningness questionnaire, Pittsburg Sleep Quality Index, Beck Depression inventory, energy intake, alcohol intake, current smoking, and physical activity. 30

4 

*P<0.05, †P<0.01, ¶P<0.001. Abbreviations: see Tables 1 and 2.