Neck Circumference and Incidence of Diabetes Mellitus over 10 Years in the Korean Genome and Epidemiology Study (KoGES)

Abstract

Neck circumference, a proxy for upper-body fat, may be a unique fat depot that indicates metabolic risk beyond whole body fat. We investigated whether neck circumference is associated with development of diabetes mellitus (DM) in a subset of data with Korean Genome and Epidemiology Study (n = 3521, age range = 42–71 years). Nondiabetic subjects at the baseline were categorized into 4 groups (Q1–Q4) according to their neck circumference. Parameters related with β-cell function and insulin resistance including Epworth sleepiness scale and snoring habit were examined. The development of DM was confirmed biannually based on a 75-g oral glucose tolerance test. Over the 10 years, 2623 (74.5%) among 3521 subjects were followed-up. Among them, 632 (24.1%) developed DM. The incidence of DM increased from 17.6% in Q1 to 18.2% in Q2, to 25.4% in Q3, and to 36.0% in Q4 (P < 0.001). After adjusting for most risk factors related with DM, the relative risks of DM development were 0.989 (95% confidence interval, 0.638–1.578), 1.660 (1.025–2.687), and 1.746 (1.037–2.942) in men and 0.939 (0.540–1.769), 1.518 (0.808–2.853), and 2.077 (1.068–4.038) in women in Q2, Q3, and Q4, respectively when compared to Q1. This finding indicates negative impact from large neck circumference in the development of DM.

Full text

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Scientific RepoRts | 5:18565 | DOI: 10.1038/srep18565
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Neck Circumference and Incidence
of Diabetes Mellitus over 10
Years in the Korean Genome and
Epidemiology Study (KoGES)
Nam H. Cho
1
, Tae Jung Oh
2
, Kyoung Min Kim
2
, Sung Hee Choi
2
, Jae Ho Lee
3
, Kyong Soo Park
4
,
Hak Chul Jang
2
, Jong Yeol Kim
5
, Hong Kyu Lee
6
& Soo Lim
2
Neck circumference, a proxy for upper-body fat, may be a unique fat depot that indicates metabolic risk
beyond whole body fat. We investigated whether neck circumference is associated with development
of diabetes mellitus (DM) in a subset of data with Korean Genome and Epidemiology Study (n = 3521,
age range = 42–71 years). Nondiabetic subjects at the baseline were categorized into 4 groups (Q1–Q4)
according to their neck circumference. Parameters related with β-cell function and insulin resistance
including Epworth sleepiness scale and snoring habit were examined. The development of DM was
conrmed biannually based on a 75-g oral glucose tolerance test. Over the 10 years, 2623 (74.5%)
among 3521 subjects were followed-up. Among them, 632 (24.1%) developed DM. The incidence of
DM increased from 17.6% in Q1 to 18.2% in Q2, to 25.4% in Q3, and to 36.0% in Q4 (P < 0.001). After
adjusting for most risk factors related with DM, the relative risks of DM development were 0.989 (95%
condence interval, 0.638–1.578), 1.660 (1.025–2.687), and 1.746 (1.037–2.942) in men and 0.939
(0.540–1.769), 1.518 (0.808–2.853), and 2.077 (1.068–4.038) in women in Q2, Q3, and Q4, respectively
when compared to Q1. This nding indicates negative impact from large neck circumference in the
development of DM.
Regional adipose tissue handles and stores excess dietary energy, which may have substantial cardiometabolic
implications. us, distribution of this regional adipose tissue or ectopic fat may be an important predictor for
cardiometabolic and vascular risks in addition to overall obesity. Among various ectopic fat deposition, the visceral
adipose tissue (VAT) is regarded as the most pathogenic fat depot, indicating metabolic risk above and beyond
the standard obesity indices
1
. It is well known that people with large amounts of visceral fat are at increased risk
of insulin resistance, type 2 diabetes mellitus (T2DM), and cardiovascular disease (CVD)
2–4
. However, VAT does
not account for all cardiometabolic risk. Recently, ectopic fat depots in other areas are reported to contribute to
the development of CVD
1
.
Waist circumference has long been used as a measure of central adiposity and many studies have reported that
it is strongly associated with cardiovascular and metabolic risk
5,6
. However, it comprises both visceral and subcu-
taneous fats despite a strong correlation with VAT
7
. Conversely, neck circumference is a phenotype of upper body
fat depot and it may also aect the cardiometabolic system. Neck circumference has been shown to be correlated
positively with insulin resistance and biochemical components of the metabolic syndrome
8,9
. In the Framingham
Heart Study, study participants with large neck circumference had various cardiometabolic risk factors when
compared to those with small neck circumference even aer adjustment for VAT and body mass index (BMI)
8
.
A large Brazilian population-based study showed that neck circumference was correlated with high triglycerides
and fasting glucose levels, low high-density lipoprotein (HDL)-cholesterol levels, and insulin resistance index
9
.
1
Department of Preventive Medicine, Ajou University School of Medicine, Suwon, Korea.
2
Division of
Endocrinology,Seoul National University College of Medicine and Seoul National University Bundang Hospital,
Seongnam, Korea.
3
Division of Pulmonology, Seoul National University College of Medicine and Seoul National
University Bundang Hospital, Seongnam, Korea.
4
Department of Internal Medicine, Seoul National University
College of Medicine, Seoul, Korea.
5
Division of Constitutional Medicine and Diagnosis Research Group, Korea
Institute of Oriental Medicine, Daejeon, Korea.
6
Department of Internal Medicine, Eulji University, Seoul, Korea.
Correspondence and requests for materials should be addressed to S.L. (email: limsoo@snu.ac.kr)
Received: 18 March 2015
Accepted: 20 November 2015
Published: 18 December 2015
OPEN

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Systemic free fatty acid concentrations are primarily determined by upper-body subcutaneous fat
10
. Although
there is no investigational study that compares the amount of free fatty acids from neck subcutaneous fat with
abdominal subcutaneous fat, the fat amount in the neck area can be substantial according to the result of a study
that measured fat volume around the neck using a computed tomography (CT)
11
. Much evidence suggests that an
increase of circulating free fatty acid levels is associated with insulin resistance and impaired glucose metabolism
12
.
In addition, it was demonstrated that higher levels of upper-body subcutaneous fat were associated with higher
low-density lipoprotein (LDL) and lower HDL-cholesterol concentrations
13
. us, neck circumference may be an
independent correlate of metabolic risk factors, above and beyond BMI and waist circumference
14,15
.
In dierent context, several studies reported that larger neck circumference was an independent risk factor
for sleep apnea syndrome, which might be associated with insulin resistance
16,17
. Neck circumference was also
associated with snoring, which might increase metabolic risk
18
.
So far, few studies have investigated neck circumference and its association with T2DM in a prospective manner,
particularly from Asian studies. In this study, therefore, we investigated the association between neck circumference
and DM development in a large community-based cohort of Koreans.
Materials and Methods
Study Population.
In 2001, the Korean Center for Disease Control and Prevention launched the Korean
Genome and Epidemiologic Study (KoGES), which was based on two communities in South Korea: the Ansung
cohort for a rural community and the Ansan cohort for an urban community. e KoGES is an ongoing prospec-
tive study that involves a biennial examination. Details of KoGES and the methods used have been described
previously
19
. In brief, 10038 subjects aged 40–69 years were recruited to partake in this study (around 5000 from
each community). Each cohort has its own specialized research topic: respiratory diseases in Ansan and endo-
crine diseases in Ansung. Neck circumference was measured in Ansan as an anthropometric index related with
respiratory diseases.
Of the 5020 subjects in Ansan cohort, 4023 nished the second follow-up in 2003-2004. Among them, 583
(11.6%) individuals were previously diagnosed with DM, and neck circumference was not measured in 916 indi-
viduals. Aer excluding these people, 3521 subjects (1784 men and 1737 women), whose neck circumference
was measured in 2003-2004, were enrolled in the present study and followed up for a 10-year period. Every
two years, the incidence of DM was conrmed based on the World Health Organization criteria
20
, using a 75-g
oral-glucose-tolerance test (OGTT).
All subjects participated in the study voluntarily, and informed consent was obtained in all cases. e study
protocol was approved by the Ethics Committee of KoGES at the Korean National Institute of Health and the study
was performed in accordance with the approved guidelines.
Measurement of Anthropometric Parameters. e height and body weight were measured using stand-
ard methods in light clothes, and BMI was calculated (weight divided by height squared, kg/m
2
). For central obesity,
waist circumference was measured at the midpoint between the lower limit of the ribcage and the iliac crest. e
body fat (%) was examined by a tetrapolar bioelectrical impedance analysis (Inbody 3.0
®
, Inbody, Seoul, Korea).
Smoking habit was classied into three categories: non-, ex-, and current. e alcohol consumption status was
categorized into three: non-, ex-, and current. Exercise habit was divided into two categories: none or irregular
(≤ 1/week) and regular (≥ 2/week). One episode of exercise was dened as exercising for at least 30 min.
Neck Circumference Measurement. Participants were asked to stand erect with their head positioned in
the Frankfort horizontal plane. e superior border of a tape measure was placed just below the laryngeal prom-
inence and applied perpendicular to the long axis of the neck. Neck circumference was measured to the nearest
0.1 cm, using a tape measure.
Measurement of Biochemical Parameters. Aer fasting for 12 h, the circulating levels of glucose, total
cholesterol, triglyceride, and HDL-cholesterol were measured, using a Hitachi 747 chemistry analyzer (Hitachi
Ltd, Tokyo, Japan). e LDL-cholesterol level (mg/dl) was calculated using the following formula: [total cholesterol
(mg/dl) – HDL-cholesterol (mg/dl) – triglyceride (mg/dl)/5)]
21
. e glycosylated hemoglobin (HbA1c) level was
determined by high-performance liquid chromatography (Variant II; BioRad Laboratories, Hercules, CA, USA).
e plasma insulin concentrations were measured by radioimmunoassay (LINCO kit, St Charles, MO, USA). White
blood cell (WBC) and hemoglobin were measured using an autoanalyzer (Sysmex, Kobe, Japan). Fasting levels of
creatinine, as well as alanine and aspartate aminotransferases (ALT and AST, respectively) were measured, using
a Hitachi 747 automated analyzer. Plasma renin activity (PRA) was measured by radioimmunoassay using Cobra
r-counter (PACKARD, Meriden, CT, USA). e circulating concentration of high-sensitivity C-reactive protein
(hsCRP) was measured by immunoradiometric assay (ADVIA 1650, Bayer Diagnostics, Tarrytown, NY, USA).
Denition of Diabetes Mellitus and Evaluation of Insulin Resistance and Pancreatic β-Cell
Function.
In a 12-h fasting state, a 75-g oral-glucose-tolerance test (OGTT) was conducted. Fasting and post-
glucose load at 60-min and 2-h plasma glucose and insulin concentrations were measured: FPG, PG60, PG120 and
FPI, PI60, PI120, respectively. DM was dened as ≥ 126 mg/dl in fasting glucose or ≥ 200 mg/dl in postload 2-h
glucose concentrations aer 75-g OGTT based on the WHO criteria
20
. Apart from patients previously diagnosed
with DM, all subjects underwent a 2-h 75-g OGTT at each biannual follow-up visit. To evaluate insulin resistance,
a homeostasis model assessment of insulin resistance (HOMA-IR) was calculated, using the following formula:
[fasting plasma insulin (μ IU/ml) × fasting plasma glucose (mg/dl)/405]
22
. e insulinogenic index (IGI), which
is an estimate of early insulin secretion, was produced by dividing the increase in insulin during the rst 60-min
by the increase in glucose during the same period [60–0 min insulin (IU/ml)/60–0 min glucose (mg/ml)]
23
.

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Denition of Hypertension and Antihypertensive Medications. Blood pressure was recorded three
times in the morning aer the subjects had been in a relaxed state for at least 10 min, and a 5 min rest period was
allowed between each measurement. Hypertension was dened based on the study by Joint National Committee 7:
≥ 140/90 mmHg
24
or antihypertensive medication. Among the 389 study participants taking antihypertensive med-
ications, detailed information about antihypertensive drugs could be obtained from 136 (35.0%). Antihypertensive
drugs in participants were classied as angiotensin-converting enzyme inhibitors or angiotensin II receptor blockers
(n = 86, 22.1%), β -blockers (n = 51, 13.1%), calcium channel blockers (n = 132, 33.9%), diuretics (n = 59, 15.2%),
α -blockers (n = 1.3, 1.2%), and unknown (n = 136, 35.0%). Some people took dual or triple therapy.
Assessment of snoring, witnessed sleep apnea, and Epworth sleepiness scale. Study participants
completed interviewer-administered questionnaires, including questions on their sleep habit and snoring. To meas-
ure the general level of daytime sleepiness, we used the Epworth sleepiness scale (ESS)
25
. e ESS consists of eight
questions about the subject’s likelihood of dozing o or falling asleep in a particular situation that is commonly
encountered in daily life. Respondents use a four-point scale from 0 to 3 for each of the eight questions. Subjects
with ≥ 11 scores were identied to have daytime sleepiness.
Snoring frequency was assessed using a ve-point scale, which was used in the previous analysis
26
: never,
infrequently, 1-3 nights/week, 4-5 nights/week, and ≥ 6 nights/week. Individuals were grouped into non-snorers,
occasional snorers (snoring ≤ 3 nights/week or infrequently) and habitual snorers (snoring ≥ 4 nig hts/week).
Snoring status was conrmed by a bed partner or a family member in a subset of participants who lived together
more than 1 year. In order to validate the questionnaire, a subset of 200 participants in KoGES were queried two
weeks aer the initial test regarding their snoring habits, using the test-retest reliability of the snoring questionnaire.
Agreement between the responses was good, with a κ -statistic value of 0.73. Sleep apnea was diagnosed when a
bed partner or family member witnessed a subject with ceased respiration for at least 10 seconds.
Statistical Analysis. All of the data were expressed as means with standard deviations (SD), or as n with
%. e skewed values such as HOMA-IR and hsCRP were normalized by logarithmic transformation before all
analyses. Correlations between the variables were analyzed using Pearson’s correlation. Categorical variables were
compared among neck circumference quartiles using a χ
2
test. Comparisons of the baseline variables with respect
to quartiles of neck circumference were analyzed using ANOVA for continuous variables.
We mathematically calculated the hazard ratios for incident DM, using Cox proportional hazards models
with potential confounding parameters: adjusted for age, BMI or waist circumference, family history of DM,
anti-hypertensive medication, triglycerides, alanine aminotransferase, hsCRP, PRA, HbA1c, HOMA-IR and IGI.
Daytime sleepiness by Epworth sleepiness scale and snoring habit were further adjusted. ere was no signicant
multicollinearity among the risk factors included in the regression models (all variation ination factors were less
than 5). e analyses were performed using IBM SPSS Statistics for Windows version 20.0 (IBM Corp., Armonk,
NY, USA). For all tests, P < 0.05 was considered statistically signicant.
Results
Baseline characteristics. e mean age was slightly but signicantly higher in women than in men
(49.8 ± 7.1 years in men vs. 50.6 ± 7.6 years in women, P < 0.01). e mean BMI was not dierent between gen-
ders (24.4 ± 2.7 kg/m
2
in men vs. 24.5 ± 3.0 kg/m
2
in women, P > 0.05). e mean ± SD of neck circumference
(ranges) was 37.6 ± 2.0 (31.8–45.3) cm in men and 32.9 ± 1.8 (23.0‒40.0) cm in women, which signicantly was
larger in men than in women by 4.7 cm. Current and ex-smokers were much greater in men than women. Liver
function enzyme activities and serum creatinine levels were greater in men than women. e baseline HbA1c
levels, HOMA-IR, and IGI were not dierent between genders.
Among all subjects, 179 (10.0%) men and 210 (12.1%) women had been taking anti-hypertensive medications.
In lipid-lowering medications, 1.5% of men and 2.1% of women had been taking statin or other lipid-lowering
agents on a regular basis. ere were more occasional and habitual snorers in men than women, although daytime
sleepiness, which was estimated by ≥ 11 of the ESS was not dierent.
e anthropometric and biochemical characteristics of subjects according to the gender-specic quartiles of
neck circumference are shown in Table1. e mean BMI, waist circumference, and percentage body fat increased
with the larger quartiles of neck circumference. ere were increasing trends in the HbA1c levels and the fasting
glucose and postload 2-h glucose concentrations with respect to the higher categories. e fasting and postload
2-h insulin concentrations and HOMA-IR also had similar increasing trends. e total cholesterol, triglyceride,
and LDL-cholesterol levels increased, whereas the HDL-cholesterol and PRA levels decreased with the quartiles
of neck circumference.
In the correlation analysis, neck circumference was correlated with most factors related to obesity, glucose
metabolism, and lipid parameters in both genders (Table2). Blood pressures and hsCRP levels were also positively
correlated with neck circumference. In both gender, there were modest but signicant negative correlations of
neck circumference with plasma renin activity: r = − 0.057, P = 0.016 in men and r = − 0.151, P < 0.001 in women,
respectively.
Follow-up. During the 10 year-study period, 2623 (74.5%) among 3521 subjects were followed-up. Of these
subjects, 632 (24.1%) developed DM during the 10-year follow-up period. e mean ± SD of the follow-up dura-
tion was 104.9 ± 28.6 months (103.3 ± 29.9 months in men and 106.7 ± 27.2 months in women, respectively). e
probability of developing DM increased in study subjects with higher quartiles of neck circumference compared
to those with lowest quartile (P < 0.01) (Fig .1).
Using the Cox proportional hazards models, we investigated the independent risk of neck circumference for
the development of DM during the follow-up period by gender (Table3). Factors that were signicantly associated

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with DM incidence in univariate analysis or were known to be clinically important in the development of DM
were selected as independent variables. Among the variables included in the nal model, a high HbA1c concen-
tration was the strongest predictive factor in the development of DM, regardless of gender. High HOMA-IR and
low IGI were also signicant factors. e relative risks (RRs) for the highest quartile of neck circumference were
1.746 in men and 2.077 in women (both P < 0.05). Older age, family history of DM, and high hsCRP levels were
also associated with greater incidence of DM in both genders. High concentrations of triglycerides and ALT were
also signicant predictors in men. Of the antihypertensive agents, the uses of β -blockers in men and diuretics in
women were associated with higher incidence of DM. Similar results were obtained with waist circumference
instead of BMI: the RRs for the highest quartile of neck circumference were 1.575 (95% condence interval (CI)
1.001–2.511; P = 0.048) in men and 2.062 (95% CI 1.050–4.050; P = 0.036) in women (Supplementary table 1).
Waist circumference was also signicantly associated with incidence of DM. Further adjustments for daytime
sleepiness by Epworth sleepiness scale and snoring habit did not change the association.
Finally, when waist circumference was included in the nal regression model instead of neck circumference, the
highest quartile of waist circumference was independently associated with higher incidence of DM aer adjusting
for the same factors including BMI: 1.986 (95% CI 1.150–3.759; P = 0.035) in men and 2.045 (95% CI 1.000–4.551;
P = 0.049) in women (Supplementary table 2).
Discussion
In this prospective, community-based cohort study of Korean adults, we found that the highest quartile of neck
circumference was associated with a 1.746 and 2.077 fold higher risk of DM development in men and women
Men
Post hoc*
Women
Post hoc*Q1 Q2 Q3 Q4 Q1 Q2 Q3 Q4
Neck circ. (cm) 35.1 0.9 37.0 0.4 38.4 0.4 40.3 1.1 a,b,c,d,e,f 30.7 0.8 32.2 0.3 33.5 0.3 35.2 0.4 b,c,e
(ranges) (31.8–36.2) (36.3–37.6) (37.7–39.0) (39.1–45.3) (23.0–31.6) (31.7–32.8) (32.9–34.0) (34.1–40.0)
Age (years) 50.4 7.5 49.7 6.9 49.8 7.4 49.4 6.5 NS 49.3 7.0 50.1 7.5 51.2 7.6 51.9 8.2 b,c
SBP (mmHg) 110.0 14.5 111.9 13.4 114.6 15.5 115.8 13.7 b,c,d,e 105.7 14.1 107.3 15.9 110.4 15.3 114.8 15.8 b,c,d,e
DBP (mmHg) 73.0 10.1 74.7 9.6 77.0 10.8 78.0 10.4 a,b,c,d,e 68.3 9.7 69.5 10.3 71.3 10.4 74.2 10.5 b,c,d,e,f
BMI (kg/m
2
) 21.8 1.9 23.7 1.6 25.2 1.6 27.2 2.0 a,b,c,d,e,f 21.8 1.9 23.6 1.9 25.4 2.0 27.4 2.8 a,b,c,d,e,f
Waist circ. (cm) 76.3 6.0 81.3 4.8 85.0 4.7 89.6 5.4 a,b,c,d,e,f 70.0 5.1 74.3 5.3 78.3 5.1 83.3 6.4 a,b,c,d,e,f
Body fat (%) 18.1 4.4 20.2 4.1 22.4 3.7 24.7 4.0 a,b,c,d,e,f 27.7 4.6 30.2 4.3 32.1 4.4 34.3 4.4 a,b,c,d,e,f
WBC (× 10
3
/μ l) 5.9 1.7 6.1 1.7 6.4 1.7 6.6 1.7 b,c,d,e 5.2 1.5 5.5 1.4 5.6 1.5 6.2 1.5 b,c,e,f
Hb (g/dl) 14.6 1.0 14.7 1.0 14.9 1.0 15.1 0.9 b,c,d,e,f 12.4 1.1 12.4 1.1 12.5 1.1 12.7 1.2 c,e
AST (IU/l) 24.9 21.5 25.0 20.3 25.4 10.6 26.7 14.6 NS 20.4 5.9 20.5 6.5 21.0 6.4 22.1 10.7 c,e,f
ALT (IU/l) 23.4 18.4 25.6 30.3 28.2 16.2 32.8 19.6 b,c,e,f 16.2 7.0 17.2 8.6 19.1 10.4 21.6 15.0 b,c,d,e,f
Cr (mg/dl) 1.08 0.12 1.10 0.24 1.11 0.21 1.14 0.14 b,c,e 0.88 0.11 0.88 0.16 0.89 0.09 0.91 0.11 b,c,e
HbA1c (%) 5.31 0.37 5.32 0.34 5.35 0.35 5.42 0.41 c,e,f 5.23 0.35 5.29 0.36 5.31 0.35 5.47 0.40 a,b,c,e,f
FPG (mg/dl) 90.6 8.8 92.7 11.8 94.0 11.3 95.3 11.6 b,c,e 87.2 9.8 87.5 7.6 88.3 10.4 90.4 9.9 c,e,f
PG60 (mg/dl) 166.7 45.9 163.7 46.5 174.9 46.0 175.1 42.1 b,c 144.9 39.4 148.7 38.7 155.7 40.0 171.5 39.6 b,c,e,f
PG120 (mg/dl) 132.1 38.8 133.1 41.2 141.5 36.6 147.3 38.2 b,c,d,e 129.1 32.7 137.8 33.2 139.5 33.3 158.5 39.7 a,b,c,e,f
FPI (IU/ml) 7.5 2.6 8.3 4.3 8.9 3.1 10.2 3.7 a,b,c,e,f 8.3 2.8 9.0 4.5 9.0 3.1 10.6 4.0 c,e,f
PI60 (IU/ml) 35.1 26.3 40.6 33.2 45.1 32.5 50.4 42.4 a,b,c 36.4 27.4 44.6 35.1 44.5 31.5 58.3 45.3 c,e,f
PI120 (IU/ml) 30.1 26.1 33.5 28.3 41.7 37.5 44.6 36.0 b,c,d,e 39.4 28.7 48.2 37.4 51.9 45.3 70.7 55.8 b,c,e,f
HOMA-IR
†
1.71 0.65 1.93 1.02 2.11 0.84 2.40 0.92 a,b,c,e,f 1.80 0.67 1.97 1.07 2.01 0.77 2.43 1.06 c,e,f
IGI 0.62 2.26 0.64 1.51 0.46 0.69 0.68 1.75 NS 0.74 2.42 0.79 1.36 0.76 1.22 0.60 1.19 NS
Total C (mg/dl) 191.8 31.4 196.0 29.6 201.1 32.8 206.1 34.0 b,c,d,e,f 195.5 34.9 202.5 33.6 206.8 36.8 209.8 36.0 a,b,c,e
TG (mg/dl) 126.6 99.4 134.5 78.0 161.5 98.9 188.9 120.2 b,c,d,e,f 97.0 62.4 108.6 62.9 119.3 65.7 144.6 73.8 a,b,c,d,e,f
HDL-C (mg/dl) 48.3 10.9 45.7 9.1 44.0 8.3 42.5 8.1 a,b,c,d,e,f 51.2 9.9 49.8 9.9 47.8 9.3 45.8 9.5 b,c,d,e,f
LDL-C (mg/dl) 120.8 30.7 124.6 28.7 127.5 30.3 132.4 35.7 b,c,e,f 125.5 31.3 131.7 30.3 135.9 32.0 136.1 32.6 a,b,c
PRA (ng/ml/h)
†
3.2 2.6 3.2 2.9 3.0 2.5 3.1 3.2 NS 2.3 1.8 2.2 1.9 2.0 2.1 1.8 1.9 c,e
hsCRP (mg/l)
†
1.02 2.06 0.96 1.53 1.37 2.06 1.54 2.32 c,e 1.12 3.46 0.89 1.60 1.03 1.42 1.72 2.34 c,e,f
ESS 5.6 3.3 6.1 3.6 6.0 3.8 6.3 3.9 c 6.6 4.1 6.2 3.7 6.3 3.9 6.1 3.9 NS
Table 1. Anthropometric and biochemical parameters in accordance to quartiles of neck circumference
by gender. *Mean with SD.
†
log-transformed values were used for statistical comparison. Abbreviation: WBC,
white blood cell; Hb, hemoglobin; AST, aspartate aminotransferase; ALT, alanine aminotransferase; FPG, fasting
plasma glucose; PG, postload glucose; FPI, fasting plasma insulin; PI, postload insulin; IGI, insulinogenic
index; C, cholesterol; TG, triglyceride; PRA, plasma renin activity; hsCRP, high sensitivity C-reactive protein;
ESS, Epworth sleepiness scale. *Post hoc analysis by Tukey’s-b t tests for mean dierences between two groups:
a, Q1 vs. Q2; b, Q1 vs. Q3; c, Q1 vs. Q4; d, Q2 vs. Q3; e, Q2 vs. Q4; f, Q3 vs. Q4, P < 0.05 in all cases; NS, not
signicant.

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respectively, aer adjusting for various factors that are known to aect glucose metabolism, including the
HbA1c level, insulin resistance, β -cell function, liver enzyme activity, inammation, as well as antihypertensive
medications.
Previous studies provided a possibility of neck circumference as a cardiometabolic risk factor
8,9,27,28
. However,
these were all cross-sectional studies and the study participants were not from population-based samples in some
studies. A study using a population sample of 1,912 Turkish middle aged men and women showed that neck cir-
cumference was associated with metabolic syndrome more strongly than waist circumference
29
. In a recent study
using Framingham Heart Study ospring participants, neck circumference was associated with increased carotid
intima-media thickness but neither BMI nor waist circumference was associated
30
. ese data support that neck
Men Women
r P r P
Age (years) − 0.056* 0.018 0.139** < 0.001
SBP (mmHg) 0.170** < 0.001 0.203** < 0.001
DBP (mmHg) 0.200** < 0.001 0.199** < 0.001
BMI (kg/m
2
) 0.801** < 0.001 0.744** < 0.001
Waist circumference (cm) 0.740** < 0.001 0.706** < 0.001
Body fat (%) 0.547** < 0.001 0.510** < 0.001
WBC (× 10
3
/μ l) 0.163** < 0.001 0.229** < 0.001
AST (IU/l) 0.033 0.162 0.091** < 0.001
ALT (IU/l) 0.162** < 0.001 0.200** < 0.001
Creatinine (mg/dl) 0.120** < 0.001 0.090** < 0.001
HbA1c (%) 0.151** < 0.001 0.216** < 0.001
FPG (mg/dl) 0.159** < 0.001 0.122** < 0.001
PG60 (mg/dl) 0.087** 0.005 0.225** < 0.001
PG120 (mg/dl) 0.149** < 0.001 0.250** < 0.001
FPI (IU/ml) 0.283** < 0.001 0.206** < 0.001
PI60 (IU/ml) 0.165** < 0.001 0.232** < 0.001
PI120 (IU/ml) 0.184** < 0.001 0.245** < 0.001
HOMA-IR
†
0.317** < 0.001 0.234** < 0.001
IGI
†
0.070* 0.027 0.055 0.161
TG (mg/dl) 0.240** < 0.001 0.256** < 0.001
HDL-C (mg/dl) − 0.246** < 0.001 − 0.223** < 0.001
PRA (ng/ml/h)
†
− 0.057* 0.016 − 0.151** < 0.001
hsCRP (mg/l)
†
0.114** < 0.001 0.091* 0.017
ESS 0.071** 0.003 − 0.034 0.161
Table 2. Simple correlation of neck circumference with various parameters.
*
P < 0.05,
**
P < 0.01,
†
log-transformed values were used for statistical comparison WBC, white blood cell; AST, aspartate
aminotransferase; ALT, alanine aminotransferase; FPG, fasting plasma glucose; PG, postload glucose; FPI,
fasting plasma insulin; PI, postload insulin; IGI, insulinogenic index; C, cholesterol; TG, triglyceride; PRA,
plasma renin activity; hsCRP, high sensitivity C-reactive protein; ESS, Epworth sleepiness scale.
Figure 1. Diabetes mellitus-free survival curve in a 10-year period.

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6
Scientific RepoRts | 5:18565 | DOI: 10.1038/srep18565
circumference, a proxy of upper-body subcutaneous fat, may have a direct inuence on atherosclerosis in adjacent
vasculature. However, there was no study that investigated the role of neck circumference in the development of
DM. In this context, our study has clinical importance of identifying an independent role of large neck circumfer-
ence in the development of DM in a population-based large cohort.
Several mechanisms can be suggested underlying the association between large neck circumference and
impaired glucose metabolism. Larger neck circumference alters peripheral blood ow and leads to endothelial
function
31
, which may reduce insulin delivery and promote insulin resistance in the whole body
32
. A large study
from Brazil showed a signicant association between neck circumference and insulin resistance assessed using a
euglycemic-hyperinsulinemic clamp
9
. In our study, neck circumference was positively correlated with triglycerides
levels and negatively with HDL-cholesterol levels, both of which are robust markers for decreased insulin sensi-
tivity
33
. Larger neck circumference with enhanced sympathetic activity may also contribute to insulin resistance,
which may lead to the development of DM
34
.
In a dierent context, recent studies have reported that neck circumference is an independent predictor of
nonalcoholic fatty liver disease, which is a strong indicator for T2DM
35,36
. Hepatic diacylglycerol content increases
in the fatty liver, leading to, leading to activation of protein kinase Cϵ , which triggers impaired insulin signaling
37
.
Large neck circumference is structurally associated with pharyngeal narrowing and respiratory distress
38
.
Repeated hypoxia and reoxygenation by airway obstruction—provoked by large neck circumference—may increase
the production of reactive oxygen species, which also play an important role in the development of T2DM
39
.
Neck circumference was correlated with log-transformed hsCRP (r = 0.12, P < 0.001) and the hsCRP level
was positively associated with an increased risk of DM in our study. In vitro and in vivo studies have shown that
hsCRP and tumor necrosis factor-α (TNF-α ), which are well-known inammatory markers, play critical roles
in the development of DM
40,41
. us, the systemic vascular resistance associated with large neck circumference
accompanies oxidative stress and inammation. Indeed, large neck circumference is associated with increased levels
of cytokines, which are related to oxidative stress, such as TNF-α , interleukin-6, and nuclear factor κ-B, which in
turn increases insulin resistance
42
. Taken together, large neck circumference might contribute to development of
T2DM through various mechanisms.
Several studies have shown that neck circumference can be inuenced by other factors. A study with retired
National Football League players having calcium and plaque burden in the coronary artery showed that neck
circumference was not associated with coronary or carotid subclinical atherosclerosis, which indicate that neck
circumference may not be an appropriate marker for cardiometabolic risk
43
. Acute non-inammatory status, such
as cervical hematoma or vascular aneurysm, may increase the circumference of the neck
44
. Importantly, large neck
circumference may be associated with lymph node metastasis in men with thyroid cancer
45
.
Men Women
P RR 95.0% CI Lower 95.0% CI Upper P RR 95.0% CI Lower 95.0% CI Upper
Age (years) 0.009
1.027
1.007 1.047 0.010
1.034
1.008 1.061
BMI (kg/m
2
)
23.0-24.9 vs. < 23.0 0.544
0.875
0.569 1.347 0.437
1.243
0.718 2.150
25.0-29.9 vs. < 23.0 0.454
0.833
0.516 1.344 0.474
0.798
0.431 1.479
≥ 30.0 vs. < 23.0 0.049
1.972
1.001 4.349 0.860
0.926
0.395 2.170
Family history of DM
Yes vs. no 0.002
1.779
1.236 2.560 0.028
1.639
1.054 2.550
HT medications
ACE inhibitors or ARBs 0.216
1.644
0.748 3.615 0.098
0.327
0.077 1.398
β -blockers 0.006
2.989
1.377 6.489 0.183
1.773
0.763 4.119
Calcium channel blockers
0.234
0.659
0.332 1.309 0.399
0.679
0.276 1.670
Diuretics 0.135
2.170
0.786 5.994 0.047
2.893
1.015 8.250
Others or unknown 0.364
1.259
0.765 2.072 0.764
1.102
0.584 2.082
Triglycerides (mg/dl) 0.005
1.002
1.001 1.003 0.682
1.001
0.998 1.003
ALT (mg/dl) 0.036
1.006
1.000 1.012 0.081
1.011
0.999 1.024
hsCRP (mg/l) 0.025
1.049
1.006 1.094 0.037
1.079
1.005 1.160
PRA (ng/ml/h) 0.782
0.995
0.959 1.032 0.876
1.006
.936 1.081
HbA1c (%) < 0.001
3.573
2.568 4.972 < 0.001
4.641
2.739 7.863
Log(HOMA-IR) < 0.001
2.478
1.695 3.622 0.002
2.060
1.294 3.280
Insulinogenic index < 0.001
0.656
0.559 0.770 0.012
0.859
0.763 0.967
Neck circumference
2
nd
quartile vs. 1
st
quartile 0.989
1.003
0.638 1.578 0.939
0.977
0.540 1.769
3
rd
quartile vs. 1
st
quartile 0.039
1.660
1.025 2.687 0.195
1.518
0.808 2.853
4
th
quartile vs. 1
st
quartile 0.036
1.746
1.037 2.942 0.031
2.077
1.068 4.038
Table 3. Cox Proportional Hazards Model for Multiple Parameters to Assess the Association Between Neck
Circumference and Incidence of Diabetes Mellitus by Gender. ALT, alanine aminotransferase; hsCRP, high
sensitivity C-reactive protein; PRA, plasma renin activity.

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Scientific RepoRts | 5:18565 | DOI: 10.1038/srep18565
In this study, we adjusted for daytime sleepiness and snoring habit
25,26
. However, they were not associated with
incidence of T2DM and did not change the association of neck circumference with T2DM. is result suggests
that sleep habit may not have a robust role in the incidence of T2DM or it may be attenuated by other factors, such
as insulin resistance or β -cell dysfunction.
e DM incidence rate of 27.7 per 1000 person-years in the current study seems to be slightly higher than that
obtained from the 2009-2011 Korean National Data, showing 8-24 per 1000 person-years from a 40-69 year old
population
46
. is may be because the current study was performed in early 2000s
46
.
Interestingly, we found in this study that high BMI was associated with higher incidence of DM in men but
not in women. When waist circumference was used instead of BMI, larger waist circumference was signicantly
associated with higher incidence of DM. ese results suggest that waist circumference may be a better indicator
of insulin resistance than BMI.
e present study has several advantages. First, possible factors that may aect glucose regulation, such as
age, BMI, lipids, liver function, PRA, hsCRP, antihypertensive drugs, and the HbA1c level were all adjusted.
Daytime sleepiness and snoring status were also evaluated. Second, study participants were from a well-designed
community-based cohort with a single ethnic group, who were within the 42–71 age group
47
. ird, dynamic
indices for insulin resistance and β -cell function, which are not easily captured in clinical practice, were used in
the regression model.
ere are several limitations to be considered in this study. Detailed information about antihypertensive drugs
could be obtained from only about 65% of the study participants. Information regarding changes and compliance
in medications was not evaluated. Other variables that may be related to DM, such as apolipoprotein-B, lipoprotein
(a), sex hormone binding globulin, gamma-glutamyl transpeptidase, or uric acid levels, were not measured. e
neck circumference was not measured in the follow-up studies with this cohort.
In conclusion, to the best of our knowledge, this is the rst longitudinal cohort study that reports the neck cir-
cumference as a predictive risk factor for future DM development in an Asian population. Neck circumference is
a novel, easily measured fat depot, which may be an important predictor of DM. is fat depot may lead to a better
understanding of systemic eect of ectopic fact on glucose homeostasis. is study provides a new insight into the
underlying metabolic pathway between large neck circumference and DM. Future prospective studies are needed to
better understand the extent to which a reduction of neck circumference may have in decreasing DM development.
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Acknowledgements
is research was supported by the National Genome Research Institute, the Korean Center for Disease Control
and Prevention (contract #2001-347-6111-221, 2002-347-6111-221, 2003-347-6111-221, 2004-E71001-00, 2005-
E71001-00, 2006-E71005-00, 2006-E71006-00, 2007-E71001-00, 2007-E71003-00, 2008-E71001-00, 2008-E71005-
00, 2009-E71002-00, 2009-E71007-00, 2010-E71001-00, 2010-E71004-00, 2011-E71004-00, 2011-E71008-00,
2012-E71008-00, 2012-E71005-00). e funding source had no role in the collection of the data or in the decision
to submit the manuscript for publication.
Author Contributions
N.H.C. and S.L. wrote manuscript, researched data, and contributed to discussion, T.J.O., K.M.K., S.H.C., J.H.L.,
K.S.P., H.C.J., J.Y.K. and H.K.L. contributed to discussion, N.H.C. principal investigator and S.L. co-investigator
of the project, contributed to discussion, and reviewed/edited manuscript. S.L. is the guarantor of this work and,
as such, had full access to all the data in the study and takes responsibility for the integrity of the data and the
accuracy of the data analysis.
Additional Information
Supplementary information accompanies this paper at http://www.nature.com/srep
Competing nancial interests: e authors declare no competing nancial interests.
How to cite this article: Cho, N. H. et al. Neck Circumference and Incidence of Diabetes Mellitus over 10 Years
in the Korean Genome and Epidemiology Study (KoGES). Sci. Rep. 5, 18565; doi: 10.1038/srep18565 (2015).
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