Li et al.

Diabetology & Metabolic Syndrome (2023) 15:133 Diabetology & Metabolic

https://doi.org/10.1186/s13098-023-01111-z
Syndrome

REVIEW Open Access

Association between neck circumference

and diabetes mellitus: a systematic review
and meta-analysis
Dandan Li1*†, Yuxin Zhao2†, Lifang Zhang3, Qiqi You4, Qingqing Jiang4, Xiaoxv Yin4 and Shiyi Cao4

Abstract
Background Despite that several original researchers have investigated the association between neck circumference
(NC) and the risk of diabetes mellitus (DM), their results remain controversial. This review aimed to quantitatively
determine the risk of DM in relation to the NC.
Methods We conducted a literature search of PubMed, Embase, and the Web of Science from these databases’
inception through September 2022 to identify observational studies that examined the association between NC
and the risk of DM. A meta-analysis of the random-effects model was applied to combine the results of the enrolled
studies.
Results Sixteen observational studies involving 4,764 patients with DM and 26,159 participants were assessed. The
pooled results revealed that NC was significantly associated with the risk of type 2 DM (T2DM) (OR = 2.17; 95% CI:
1.30–3.62) and gestational DM (GDM) (OR = 1.31; 95% CI: 1.17–1.48). Subgroup analysis revealed that after controlling
for BMI, the relationship between the NC and T2DM remained statistically significant (OR = 1.94; 95% CI: 1.35–2.79).
Moreover, the pooled OR of T2DM was found to be 1.16 (95% CI: 1.07–1.27) for an increment per each centimeter in
the NC.
Conclusions Integrated epidemiological evidence supports the hypothesis that a greater NC is associated with an
increased risk of T2DM and GDM.
Keywords Neck circumference, Type 2 diabetes mellitus, Gestational diabetes mellitus, Meta-analysis

Background
The incidence of diabetes mellitus (DM) has increased
substantially in recent decades [1], which has imposed a
†
Dandan Li and Yuxin Zhao contributed equally to this work.
heavy burden on healthcare systems. Knowledge of early
markers to predict the disease and the adoption of related
*Correspondence:
Dandan Li preventive strategies are of vital public health significance
1536721300@qq.com for improving this situation.
1
Department of Medical Records Management, The First Affiliated Obesity is a well-established risk factor for DM [2].
Hospital of Zhengzhou University, Zhengzhou, Henan, China
2
Shenzhen Fuyong People’s Hospital, Shenzhen, Guangdong, China Several studies have suggested that total body obesity
3
Medical Service, The First Affiliated Hospital of Zhengzhou University, and abdominal obesity, which can be assessed based on
Zhengzhou, Henan, China
4
body mass index (BMI), waist circumference (WC), and
School of Public Health, Tongji Medical College, Huazhong University of
Science and Technology, Wuhan, Hubei, China waist/hip ratio, could predict the risk of developing DM

© The Author(s) 2023. Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use,
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Li et al. Diabetology & Metabolic Syndrome (2023) 15:133 Page 2 of 9

[3]. Recently, upper body subcutaneous fat has drawn the only included the report with the most detailed informa-
attention of researchers, and a study has shown that it tion for both NC and the outcome.
may confer higher risks than visceral abdominal fat [4].
Furthermore, neck circumference (NC) has been consid- Data extraction
ered as a proxy measure for upper body subcutaneous Two authors (D.L. and Y.Z.) independently extracted the
fat distribution [5]. Compared with other anthropomet- following information from the included studies: first
ric indexes, NC measurement is more convenient, shows author, publication year, country or region, study design,
minimal fluctuations, and is not affected by respiratory age, sample size, the number of men and women, the
conditions and diet. A meta-analysis [6] indicated that cutoff point for NC, adjusted OR/RR with 95% CI, and
NC was moderately accurate in identifying overweight the adjusted factors. The differences in data extraction
and obesity in children and adolescents, and another between the two investigators were resolved via discus-
study [7] arrived at a similar conclusion in men and sion with the third investigator (S.C.).
women of different age groups. Moreover, some studies
have demonstrated that NC may be independently corre- Quality assessment
lated with metabolic risk factors above and beyond BMI We assessed the methodological quality of cohort and
and WC [5, 8]. case-control studies with reference to the Newcastle–
Over the past decades, numerous studies have assessed Ottawa Scale, which awards a score of 0–9 based on the
the relationship between NC and DM, but the results selection of participants, comparability of the groups,
remain inconsistent. Some investigations have reported and exposure/outcome assessment [15]. Studies scoring
that NC has a direct relationship with DM [9–11], 0–3, 4–6, and 7–9 were categorized as low-, moderate-,
whereas others have shown that larger NC is not associ- and high-quality studies, respectively.
ated with the risk of DM [12, 13]. Considering the incon- The assessment tool involving 11 items, as recom-
sistencies in the findings of existing studies, a systematic mended by the Agency for Healthcare Research and
review and meta-analysis of observational epidemiologi- Quality, was applied for cross-sectional studies [16]. The
cal studies were performed to evaluate the association quality of the studies was first evaluated with reference
between NC and the risk of DM. to the established questions and then scored according to
the following criteria: 1 point = if the item was considered
Methods in the study and 0 points = if the item was not considered
Literature search strategy or this aspect was ambiguous.
The present systematic review and meta-analysis were Each study was rated independently by two authors
conducted in accordance with the Preferred Report- (D.L. and Y.Z.). Any disagreements were resolved via dis-
ing Items for Systematic Reviews and Meta-Analysis cussion with a third investigator (S.C.).
(PRISMA) statement [14]. PubMed, Embase, and the
Web of Science were searched from their inception until Statistical analysis
September 2022 using the following keywords with no We considered OR as the common measure of associa-
restrictions to identify the relevant citations: ‘neck cir- tion between the NC and the risk for DM. The reported
cumference’ in combination with ‘diabetes,’ ‘impaired RR was considered approximately as the OR. We calcu-
glucose tolerance,’ ‘impaired fasting glucose,’ or ‘insu- lated an overall pooled OR by using a random-effects
lin resistance.’ The reference lists of the retrieved arti- model for the main analysis [17]. If studies reported
cles were also reviewed to identify any other pertinent results separately for different subgroups, we combined
studies. the subgroup estimates by using fixed-effect models
before inclusion in the main meta-analysis. Q statistic
Study selection with a significance level of < 0.10 and I2 statistic were
The studies were included in the meta-analysis if they applied to test the heterogeneity. The I2 statistic measures
met the following inclusion criteria: (i) the study design the percentage of total variation across studies because
was cross-sectional, cohort or case-control, (ii) the odds of heterogeneity rather than because of chance. It was
ratio (OR) or relative risk (RR) with 95% confidence calculated according to the formula by Higgins [18].
interval (CI) of DM incidence related to the NC were Substantial heterogeneity is an I2 value of at least 50%.
reported or could be calculated from the provided data. Sensitivity analyses and subgroup analyses were con-
Abstracts, non-original papers (reviews, editorials, or ducted to evaluate the influences of the study design and
letters), gray literature, unpublished studies, and studies population characteristics on our results. All statistical
providing data on the relationship between the NC and analyses were conducted by using STATA statistical soft-
diabetes-led mortality or complications were excluded. If ware version 13.0 (STATA Corp, College Station, Texas,
there was more than one report from the same study, we
Li et al. Diabetology & Metabolic Syndrome (2023) 15:133 Page 3 of 9

USA). P values were two-sided with a significance level 196 to 8,450, with a total of 26,159, while the number
of 0.05. of cases of DM ranged from 29 to 2,068, with a total of
4,764. Of these studies on the relationship between NC
Results and DM, nine were about type 2 DM (T2DM), and seven
Study selection and evaluation were about gestational DM (GDM). None of the studies
The results of the literature research and selection are focused on the risk of other types of diabetes in relation
illustrated in Fig. 1. Initially, we retrieved 163 citations to the NC. The study locations were as follows: nine stud-
from PubMed, 213 from Embase, and 304 from the Web ies were from Asia, three from Europe, three from South
of Science. After 353 duplicates were excluded, 327 cita- America, and one from North America. In addition, the
tions were screened through titles and abstracts, of which quality scores for the seven cohort studies ranged from 5
264 were excluded because they were reviews, editori- to 9, with an average score of 7.43 from a maximum of 9
als, letters, commentaries, news reports, case reports, (Table A.1). The quality score for one case-control study
or irrelevant studies. After assessing the full texts of the was 7 (Table A.2). The quality assessment scores for the
remaining 63 articles, we excluded 47 articles, as 28 of eight cross-sectional studies ranged from 4 to 7, with a
these did not study the relationship between NC and DM mean score of 5 from a maximum of 11 (Table A.3).
incidence while 19 did not provide useful data to calcu-
late these parameters. Finally, 16 studies [4, 9–13, 19–28] Results of the meta-analysis
were included (including seven cohort studies, one case- Association between the NC and T2DM
control study, and eight cross-sectional studies). The results from the random-effects model combining
the ORs for the relationship of T2DM with NC are shown
Study characteristics in Fig. 2. When compared with people with smaller NC,
The main characteristics of the 16 studies are summa- those with larger NC were at an increased risk for T2DM,
rized in Table 1. These studies were published between and the pooled OR was 2.17 (95% CI: 1.30–3.62). Sub-
2010 and 2022. The study samples ranged in size from stantial heterogeneity was observed (I2 = 82.6%, P = 0.001).

Fig. 1 Flow diagram of studies included in the systematic review and meta-analysis
Li et al. Diabetology & Metabolic Syndrome (2023) 15:133 Page 4 of 9

Table 1 Main characteristics of the included studies involving neck circumference and the risk of diabetes mellitus
Author Year Disease Country Study design Age Simple size Cut- Adjustment
(state) (years) Total Case Male Female off
point
(cm)
Sarah 2010 T2DM USA Cross-sectional 49.8 ± 10.7 3307 193 1718 1589 NR gender, BMI, waist,
Rosner Preis (North (M) age, smoking, alcohol,
et al. America) 52.1 ± 9.9 (F) menopausal status, and
hormone replacement
therapy use
Nam H. Cho 2015 T2DM Korea Cohort 49.8 ± 7.1(M) 2623 632 NR NR NR age, gender, BMI, family
et al. (Asia) 50.6 ± 7.6 (F) history of DM
Mykolay 2016 T2DM Ukraine Cross-sectional ≥ 44 196 54 46 150 38.5 gender, BMI
Khalangot (Europe) (M)
et al. 36.5
(F)
Aline Marca- 2017 T2DM Brazil Cross-sectional 18–80 430 142 145 285 NR age, physical activity,
denti et al. (South smoking and BMI
America)
Yavor As- 2017 T2DM Bulgaria Cross-sectional 49 ± 12 255 29 102 153 38 (M) gender
syov et al. (Europe) 35 (F)
Mingkuo 2018 T2DM China Cohort 51.1 ± 11.9 8450 2068 4431 4019 NR age, sex, education,
Ting et al. (Asia) marital status, occupation,
betel nut chewing, and
hypertension history, waist
width, left thigh circumfer-
ence, right upper arm
circumference
Aléxei 2018 T2DM Brazil Cross-sectional 46.5 ± 18.6 950 170 329 621 39.5 gender, education, race,
Volaco et al. (South (M) (M) smoking, excessive alcohol
America) 47.4 ± 17.6 34.5 consumption
(F) (F)
Wenning Fu 2019 T2DM China Cross-sectional 56.0 ± 9.8 4000 387 1605 2395 36.6 age, sex, smoking, drink-
et al. (Asia) (M) ing and education
33.40
(F)
Qun Yan 2021 T2DM China Cohort 71.0 ± 5.8 2646 219 1288 1358 NR age, exercise, current
et al. (Asia) smoking, alcohol use,
BMI, waist circumfer-
ence, systolic blood
pressure, diastolic blood
pressure, triglycerides,
total cholesterol, alanine
aminotransferase
Fang He 2017 GDM China Case-control 29.1 ± 3.7 255 41 NA 255 NR hemoglobin A1c, 1-h
et al. (Asia) glucose, 2-h glucose, waist
circumference, fasting
blood glucose
Ping Li et al. 2018 GDM China Cross-sectional 30 (27–32) 371 97 NA 371 33.8 BMI, maternal age, gravid-
(Asia) ity and parity
Lilian C 2018 GDM Spain, Cross-sectional 32.1 ± 5.3 971 425 NA 971 NR maternal age, ethnicity,
Mendoza Austria, education, marital status,
et al. Belgium, working status, obstetric
Denmark, history, BMI
Poland,
Italy, Ireland,
The
Netherlands,
The United
Kingdom
(Europe)
Li et al. Diabetology & Metabolic Syndrome (2023) 15:133 Page 5 of 9

Table 1 (continued)
Author Year Disease Country Study design Age Simple size Cut- Adjustment
(state) (years) Total Case Male Female off
point
(cm)
Necati 2020 GDM Turkey Cohort 31 (19–41) 525 49 NA 525 38.5 age, gravidity, parity, BMI
Hancer- (Asia) (GDM);
liogullari 27 (18–44)
et al. (control)
Tahoora 2021 GDM Iran Cohort 28.1 ± 4.4 372 74 NA 372 34.3 age, BMI, fasting blood
Sedighi (Asia) glucose
Barforoush
et al.
Azam Ghor- 2022 GDM Iran Cohort 29.78 ± 4.91 676 110 NA 676 33.5 age, gravid, BMI, waist
bani er al. (Asia) circumference
Camila 2022 GDM Brazil Cohort 32(6) 372 74 NA 372 34.5 age, physical activity, edu-
Rodrigues (South (GDM); cation, and familiar history
de Souza America) 28(6) of diabetes
Carvalho (without
et al. GDM)
Abbreviations: T2DM, type 2 diabetes mellitus; GDM, gestational diabetes mellitus; M, male; F, female; BMI, body mass index; NR, not reported; NA, not applicable

Fig. 2 The association between neck circumference as a categorical variable and type 2 diabetes mellitus risk

Two studies [4, 19] evaluated the risk of T2DM for per on the pooled results, any single study was excluded in
standard deviation increment in the NC, and the OR with turn and the results of the remaining included studies
95% CI was 1.70 (95% CI: 1.35–2.13) and 2.06 (95% CI: were pooled. The pooled OR did not materially change
1.71–2.49), respectively. Three other studies [11, 21, 26] and ranged from 1.55 (95% CI: 1.22–1.99) to 2.71 (95% CI:
reported the risk of T2DM per 1-cm increase in the NC, 1.43–5.14) (Fig. A1).
and the OR with 95% CI was 1.43 (95% CI: 1.05–1.96), Table A.4 shows the results of subgroup analyses on the
1.05 (95% CI: 1.03–1.96), and 1.16 (95% CI: 1.10–1.23), NC and T2DM risk. A larger NC was found to be associ-
respectively. We standardized the two results report- ated with an increased risk for T2DM in most subgroups.
ing OR per standard deviation increment in the NC to Subgroup analysis by the state revealed that the partici-
the form of OR per 1-cm increment and calculated the pants from South America and Europe had a higher risk
pooled OR by using a random-effects model. The pooled of T2DM, and the highest point estimate was recorded
OR of T2DM for an increment per each centimeter in the for Europe (OR = 5.10, 95% CI: 2.64–9.82). The differ-
NC was 1.16 (95% CI: 1.07–1.27), with substantial het- ence in the pooled OR among these three groups showed
erogeneity across studies (I2 = 83.9%, P < 0.001) (Fig. 3). statistical significance (P = 0.003). Subgroup analysis by
controlling for age also indicated a statistically signifi-
Results of sensitivity analyses and subgroup analy- cant difference in results (P = 0.001). No significant differ-
ses To identify the potential influence of a single study ence was detected between the groups in terms of other
Li et al. Diabetology & Metabolic Syndrome (2023) 15:133 Page 6 of 9

Fig. 3 The association between neck circumference as a continuous variable and type 2 diabetes mellitus risk

Fig. 4 The association between neck circumference as a categorical variable and gestational diabetes mellitus risk

variables. Notably, subgroup analyses by controlling for Table A.5 demonstrates the results of subgroup analy-
BMI indicated that the heterogeneity mainly arose from ses about the NC and GDM risk. Subgroup analyses by
studies with unadjusted BMI (I2 = 93.2% for studies with the study design, state, and the cut-off point for NC,
unadjusted BMI and I2 = 0% for studies with adjusted whether controlling for age and controlling for BMI
BMI). showed no statistically significant difference in the out-
comes. Most subgroups indicated a positive and statis-
Association between the NC and GDM tically significant relationship between the NC and an
The results from the random-effects model combin- increased risk of GDM.
ing the ORs for the relationship between GDM and NC
are depicted in Fig. 4. The pooled OR was 1.31 (95% Discussion
CI: 1.17–1.48), and no significant heterogeneity was NC, a novel anthropometric index, is considered a
observed (I2 = 34.6%, P = 0.164). marker of subcutaneous fat distribution in the upper
body and an independent predictor of metabolic disor-
Results of sensitivity analyses and subgroup analy- ders, such as glucose intolerance, hypertension, and fatty
ses The sensitivity analysis indicated that the results were liver disease [29–31]. This systematic review and meta-
unaffected by any single study, with the pooled OR rang- analysis focused on the link between NC and the risk of
ing from 1.25 (95% CI: 1.16–1.40) to 1.36 (95% CI: 1.15– DM. The investigation included 16 observational epi-
1.61) (Fig. A2). demiological studies involving 4,764 patients with DM
Li et al. Diabetology & Metabolic Syndrome (2023) 15:133 Page 7 of 9

and 26,159 participants. Pooled analysis revealed that obesity, especially when conventional anthropometric
NC was positively associated with the risk of DM. Spe- measures are not available, convenient, or practicable
cifically, compared with individuals who had smaller NC, [38].
those with larger NC had a 2.17 times increased risk of Our study has several strengths. First, in this system-
T2DM. Moreover, compared with pregnant women who atic review and meta-analysis, the relationship between
had smaller NC, the risk of GDM was increased by 31% NC and T2DM was evaluated for the first time. Although
for those with larger NC. Rahnemaei FA et al.’s study involved NC and DM, the
Several potential mechanisms have so far been pro- researchers concentrated on the relationship between
posed to describe the relationship between NC and DM. various anthropometric indicators and GDM [41]. Sec-
First, NC is correlated positively with triglyceride levels ond, consistent results from sensitivity analyses among
and negatively with high-density lipoprotein cholesterol the included studies indicate the robustness and reliabil-
levels, both of which are robust markers for decreased ity of our findings.
insulin sensitivity [9, 32]. Additionally, larger NC with However, there are some limitations, which are of
enhanced sympathetic activity may contribute to insu- concern. First, adjusted confounders varied among the
lin resistance, thereby resulting in the development of included studies. Some probably important residual con-
DM [9]. Second, high NC values serve as a predictor of founders, such as BMI, sex, and age, were not adjusted
obstructive sleep apnea in short-sleeping obese men in certain studies. Second, different cutoff points for
and women [33]. Certain studies have documented that NC size were defined across studies, which might have
obstructive sleep apnea is related to abnormal glucose introduced heterogeneity in the obtained results. Third,
metabolism [34, 35]. publication bias was not evaluated owing to the small
Owing to the substantial heterogeneity in studies number of studies on T2DM risk and GDM risk that
exploring the association between NC and the risk of were included in the meta-analysis in relation to the NC.
T2DM, subgroup analyses were conducted based on
various factors. The findings showed that the associa- Conclusion
tion between NC and T2DM risk remained significant in The findings from this meta-analysis suggests that the
most subgroups. The percentage and distribution of body risk of T2DM is elevated in individuals with a high NC.
fat for the same BMI varies across different populations Moreover, pregnant women with high NC values have
[36]. Therefore, a subgroup analysis based on the state higher odds of GDM than those with low values. None-
was performed, which revealed significant differences. theless, the number of included studies was limited, and
Considering the potential differences between men and some possibly important residual confounders, such as
women, sex-based subgroup analyses were conducted, BMI, were not adjusted in certain studies. Thus, more
the results of which demonstrated that larger NC was high-quality studies are required to confirm the predic-
a risk factor for T2DM in both sexes. Moreover, sub- tive potential of NC for DM.
group analyses based on adjusted variables, such as BMI
Abbreviations
and age, were performed to explore their possible influ- BMI Body mass index
ence on the relationship between NC and T2DM risk. CI Confidence interval
According to the obtained results, after adjusting for age, DM Diabetes mellitus
GDM Gestational diabetes mellitus
the combined OR was lower than the unadjusted one. NC Neck circumference
The difference between the two groups was statistically OR Odds ratio
significant, which indicated that age was a positive con- RR Relative risk
T2DM Type 2 diabetes mellitus
founder and that the true correlation effect between NC WC Waist circumference
and T2DM may be weaker.
NC exhibits several advantages against previously used
indices, such as BMI and WC. Although BMI is the most Supplementary Information
widely used index for defining overweight and obesity, it The online version contains supplementary material available at https://doi.
org/10.1186/s13098-023-01111-z.
cannot assess body fat distribution. Likewise, although
WC is a commonly used index for evaluating abdominal Supplementary Material 1
obesity, it fluctuates greatly and can be easily affected by
conditions and time [37]. NC is stable, time-saving, and Acknowledgements
convenient to measure. Previous studies have observed Not applicable.
that NC performs better than WC in evaluating meta-
Authors’ contributions
bolic health [38] and that it can predict excess body fat S.C. and X.Y. conceived the study. D.L. and Y.Z. wrote the main manuscript text.
[39] and cardiovascular risk factors [40]. This may sug- Q.Y. and Q.J. checked the related data information again and assessed their
gest that NC can be considered in guidelines for assessing quality. L.Z. prepared figures. All authors reviewed the manuscript.
Li et al. Diabetology & Metabolic Syndrome (2023) 15:133 Page 8 of 9

Funding meta-analyses. Available from http://www.ohri.ca/programs/clinical_epide-

This research did not receive any specific grant from funding agencies in the miology/nosgen.doc
public, commercial, or not-for-profit sectors. 16. Rostom A, Dubé C, Cranney A, Saloojee N, Sy R, Garritty C, et al. Celiac disease.
Evid Rep Technol Assess (Summ). 2004;104:1–6.
Data Availability 17. DerSimonian R, Laird N. Meta-analysis in clinical trials. Control Clin Trials.
The datasets used during the current study are available from the 1986;7:177–88.
corresponding author on reasonable request. 18. Higgins JP, Thompson SG, Deeks JJ, Altman DG. Measuring inconsistency in
meta-analyses. BMJ. 2003;327:557–60.
19. Volaco A, Martins CM, Soares JQ, Cavalcanti AM, Moyses ST, Filho RP, et al.
Declarations Neck circumference and its correlation to other anthropometric parameters
and finnish diabetes risk score (FINDRISC). Curr Diabetes Rev. 2018;14:464–71.
Ethics approval and consent to participate 20. Fu W, Zou L, Yin X, Wu J, Zhang S, Mao J, et al. Association between neck
Not applicable. circumference and cardiometabolic disease in chinese adults: a community-
based cross-sectional study. BMJ Open. 2019;9:e026253.
Consent for publication 21. Ting MK, Liao PJ, Wu IW, Chen SW, Yang NI, Lin TY, et al. Predicting Type 2
Not applicable. diabetes Mellitus occurrence using three-dimensional anthropometric body
surface scanning measurements: a prospective cohort study. J Diabetes Res.
Competing interests 2018;2018:6742384.
The authors declare no competing interests. 22. Li P, Lin S, Cui J, Li L, Zhou S, Fan J. First Trimester Neck circumference as a
predictor for the development of gestational diabetes Mellitus. Am J Med Sci.
Received: 6 March 2023 / Accepted: 14 June 2023 2018;355:149–52.
23. Mendoza LC, Harreiter J, Simmons D, Desoye G, Adelantado JM, Juarez F, et al.
Risk factors for hyperglycemia in pregnancy in the DALI study differ by period
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