ORIGINAL ARTICLE |
https://doi.org/10.5005/jp-journals-10057-0218 |
To Evaluate the Association of Neck Circumference and Mid-arm Circumference to the Components of Metabolic Syndrome
1–5Department of General Medicine, Mahatma Gandhi University of Medical Sciences and Technology, Mahatma Gandhi Medical College and Hospital, Jaipur, Rajasthan, India
6Department of Pharmacology, Mahatma Gandhi University of Medical Sciences and Technology, Mahatma Gandhi Medical College and Hospital, Jaipur, Rajasthan, India
Corresponding Author: Komal Girdhar, Department of General Medicine, Mahatma Gandhi University of Medical Sciences and Technology, Mahatma Gandhi Medical College and Hospital, Jaipur, Rajasthan, India, Phone: +91 7683021101, e-mail: komalgirdhar2012@gmail.com
Received on: 10 May 2023; Accepted on: 13 June 2023; Published on: 16 September 2023
ABSTRACT
Background: Metabolic syndrome (MS) has been long recognized as a risk factor for diseases like diabetes and coronary diseases; hence an easy and inexpensive screening tool is required for early diagnosis and appropriate intervention. Hence the present study was conducted to establish the role of neck circumference (NC) and to explore the role of mid-arm circumference for the screening of MS in day-to-day practice.
Materials and methods: The present study was a hospital-based observational, descriptive, and comparative analysis conducted at a tertiary care center in West India after taking Ethical Committee clearance and written informed consent. A total of 159 subjects aged 18–65 years were selected consecutively after inclusion and exclusion criteria, from patients attending General Medicine’s Outpatient Department and Inpatient Department. The sample size was calculated at an α-error of 0.05 and a study power of 80%.
Results: Neck circumference (NC) and mid-arm circumference were found to be statistically significantly associated with MS and its individual components and cardiovascular risk factors like lipid profile, fasting blood glucose, blood pressure (BP), and waist circumference.
Conclusion: In this study, NC, waist circumference, and mid-upper arm circumference (MUAC) were all found to be significantly associated with metabolic parameters. Our results indicated that NC, waist circumference, and MUAC in routine clinical measurement are necessary to screen for metabolic disorders, including dyslipidemia, diabetes, and hypertension. However, NC was discovered to be a simple yet reliable measure that can be used to enhance anthropometric indices in the diagnosis of MS and abdominal obesity.
How to cite this article: Girdhar K, Rijhwani P, Sarna M, et al. To Evaluate the Association of Neck Circumference and Mid-arm Circumference to the Components of Metabolic Syndrome. J Mahatma Gandhi Univ Med Sci Tech 2022;7(3):72–74.
Source of support: Nil
Conflict of interest: Dr Puneet Rijhwani is associated as the Editorial Board member of this journal and this manuscript was subjected to this journal’s standard review procedures, with this peer review handled independently of this editorial board member and his research group.
Keywords: Metabolic syndrome, Mid-upper arm circumference, Neck circumference
INTRODUCTION
Metabolic problems are commonly attributed to obesity. In determining the risk for metabolic and cardiovascular disease, the distribution of extra adipose tissue may be thought of as being more significant than the overall amount of fat. It’s critical to develop indicators of obesity quickly and precisely, given the rising percentages of obesity prevalence around the world.1
Waist circumference, fasting blood sugars, triglyceride levels, and high blood pressure (BP) are the criteria that make up the term “metabolic syndrome (MS),” and they indirectly relate to the risk of diabetes and cardiovascular disease.2
In addition to being established as a risk factor for cardiovascular disease, upper-body obesity has been linked to glucose intolerance, diabetes, and hypertriglyceridemia.
The current study has been done to establish the independent role of neck circumference (NC) and mid-arm circumference in MS.3
This work may offer a new and less complicated method for diabetes and cardiovascular disease screening in the general population.
MATERIALS AND METHODS
The present study was a hospital-based observational, descriptive, and comparative analysis conducted at a tertiary care center in West India after taking clearance from an Ethical Committee and signing informed consent. After meeting inclusion and exclusion requirements, 159 participants between the ages of 18 and 65 were arbitrarily chosen from patients who were seen in the Outpatient and Inpatient Departments of Medicine. The sample size was computed with a 0.05 error and an 80% study power.4,5
The study eliminated participants under the age of 18 and those who did not provide consent. Standard protocols were followed to measure the following: a thorough medical history, a general physical examination, anthropometric indices, neck and mid-arm circumferences, fasting blood glucose, and lipid profile.6
Statistical Analysis
Numbers and proportions were used to depict the qualitative data and the Chi-squared test was used to assess the relationships between the qualitative variables. A p-value of 0.05 or less was considered significant.
RESULTS
Table 1 shows the NC among the study subjects. It was seen that 23.90% had normal NC whereas 76.10% had high NC. The mean NC, among the study subjects was 38.18 ± 2.43.
| NC | N = 159 | % |
|---|---|---|
| Normal | 38 | 23.90 |
| High | 121 | 76.10 |
| Mean ± standard deviation (SD) | 38.18 ± 2.43 | |
Table 2 shows the comparison of BP based on the size of the neck in subjects with normal NC, the mean spontaneous bacterial peritonitis (SBP) was 124.64 mm Hg, while in subjects with high NC, it was 135.21 mm Hg. In subjects with normal NC, the mean diastolic BP (DBP) was 76.83 4.14 mm Hg, while in subjects with high NC, it was 86.08 4.98 mm Hg. Every result was statistically significant.
| NC | SBP (mm Hg) | DBP (mm Hg) | ||
|---|---|---|---|---|
| Mean | SD | Mean | SD | |
| Normal | 124.64 | 7.78 | 76.83 | 4.14 |
| High | 135.21 | 8.42 | 86.08 | 4.98 |
| p-value | 0.005* | 0.004* | ||
*, statistically significant
Table 3 shows the fasting blood glucose (FBG) comparison according to NC. It was seen that the mean FBG was 112.54 ± 17.31 among subjects with normal NC and 144.78 ± 41.02 among subjects with high NC. The results were statistically significant.
| NC | FBG | p-value | |
|---|---|---|---|
| Mean | SD | ||
| Normal | 112.54 | 17.31 | <0.01* |
| High | 144.78 | 41.02 | |
*, statistically significant
Neck circumference (NC) had a sensitivity, specificity, positive predictive value, and negative predictive value of 87, 100, 100, and 94%, respectively, in predicting MS. The NC measurement’s accuracy percentage is 84.50% (Fig. 1).
Fig. 1: Accuracy rate of NC
Mean spontaneous bacterial peritonitis (SBP) and DBP were found to be more among subjects with higher mid-upper arm circumference (MUAC) as compared to subjects with normal MUAC with a statistically significant difference of p < 0.05 (Table 4).
| MUAC | SBP (mm Hg) | DBP (mm Hg) | ||
|---|---|---|---|---|
| Mean | SD | Mean | SD | |
| Q1 | 125.05 | 7.10 | 75.73 | 6.11 |
| Q2 | 128.14 | 7.62 | 78.15 | 5.23 |
| Q3 | 132.22 | 8.98 | 81.48 | 6.06 |
| Q4 | 134.70 | 8.43 | 88.23 | 6.72 |
| p-value | 0.034* | 0.023* | ||
*, statistically significant
Mean FBG was found to be more among subjects with higher MUAC as compared to subjects with normal MUAC with a statistically significant difference of p < 0.05 (Table 5).
| MUAC | FBG | p-value | |
|---|---|---|---|
| Mean | SD | ||
| Q1 | 116.71 | 25.43 | 0.009* |
| Q2 | 120.33 | 21.85 | |
| Q3 | 132.89 | 30.12 | |
| Q4 | 144.40 | 37.53 | |
*, statistically significant
Mean triglyceride, low-density lipoprotein (LDL), and very LDL (VLDL) were found to be more among subjects with higher MUAC as compared to subjects with normal MUAC with a statistically significant difference of p <0.05 (Table 6).
| Variables | Q1 | Q2 | Q3 | Q4 | p-value | ||||
|---|---|---|---|---|---|---|---|---|---|
| Mean | SD | Mean | SD | Mean | SD | Mean | SD | ||
| Triglyceride | 98.56 | 25.51 | 122.72 | 41.14 | 159.1 | 43.8 | 178.32 | 37.06 | 0.033* |
| HDL | 56.48 | 9.32 | 47.67 | 9.90 | 41.15 | 10.22 | 36.70 | 9.52 | 0.004* |
| LDL | 109.51 | 30.45 | 117.88 | 34.06 | 130.6 | 23.01 | 134.5 | 27.7 | 0.016* |
| VLDL | 19.09 | 5.06 | 22.64 | 6.77 | 28.11 | 6.89 | 34.04 | 7.2 | 0.009* |
*, statistically significant
DISCUSSION
The present study was undertaken to evaluate the relationship of NC and other anthropometric parameters with MS, which itself is a risk factor for diabetes and cardiovascular diseases.
In this present study significant correlation was found between NC and MS. It was observed that 76.10% had high NC and 23.90% had normal NC. In the study’s participants, the mean NC was 38.18 2.43 cm. Patients with MS had an NC of 36.3 2.6 cm, according to a study by Albassam et al.7 The mean body mass index (BMI) for people with normal NC was found to be 29.72 4.97 kg/m2; however, the mean BMI for subjects with excessive NC was found to be 33.24 5.62 kg/m2. According to a study by Albassam et al., and Hai et al., the average BMI was 32.5 6.2 kg/m2 and 32.8 5.7 kg/m2, respectively.
It was found that the mean FBG for subjects with normal NC was 112.54 17.31 while the mean FBG for subjects with high NC was 144.78 41.02. The mean FBG in a study by Hai et al. was 145.8 6.1. This conclusion was consistent with the present research.
Among normal NC subjects, the mean triglycerides were 97.42 ± 24.56, the mean high-density lipoprotein (HDL) was 54.83 ± 11.27, the mean LDL was 122.55 ± 32.69, and the mean VLDL was 19.04 ± 5.31. The mean triglycerides among high NC patients were 163.75 42.19, the mean HDL was 38.96 9.42, the mean LDL was 114.11 34.66, and the mean VLDL was 33.67 8.82. The mean triglycerides in a study by Hai et al. were 164.9 80.8, the mean HDL was 39.1 10.3, the mean LDL was 110.3 38.2, and the mean VLDL was 33.4 18.4. The results of the present investigation were at odds with those results.8
With a statistically significant difference of p 0.05, it was discovered that subjects with higher MUAC values had higher mean weight, BMI, BP, and FBG. In this study, it was discovered that subjects with higher MUAC levels had higher mean levels of triglycerides, LDL, and VLDL, with a statistically significant difference of p 0.05. Jie Shi et al. in their study similarly reported that MUAC was positively correlated with waist circumference, BMI, fasting insulin, triglycerides, SBP, DBP, and inversely correlated HDL cholesterol.
CONCLUSION
In this study, it was discovered that metabolic indicators were substantially correlated with NC, waist circumference, and MUAC. Our findings suggested that in order to screen for metabolic illnesses such as dyslipidemia, diabetes, and hypertension, the NC, waist circumference, and MUAC should be included in regular clinical measurements.9
To improve anthropometric indices in the diagnosis of MS and abdominal obesity, NC was found to be a straightforward yet accurate assessment. Due to its simplicity of measurement, it can be used as a first step in the screening for metabolic illnesses associated with obesity and can be followed up at regular intervals for monitoring.10,11
ORCID
Puneet Rijhwani https://orcid.org/0000-0002-9454-736X
REFERENCES
1. Kim KY, Moon HR, Yun JM. Neck circumference as a predictor of metabolic syndrome in koreans: a cross-sectional study. Nutrients 2021;13(9):3029. DOI: 10.3390/nu13093029
2. Ataie-Jafari A, Namazi N, Djalalinia S, et al. Neck circumference and its association with cardiometabolic risk factors: a systematic review and meta-analysis. Diabetol Metab Syndr 2018;10:72. DOI: 10.1186/s13098-018-0373-y
3. Akbulut G, Köksal E, Bilici S, et al. Metabolic syndrome (MS) in the elderly: a cross sectional survey. Arch Gerontol Geriatr 2011;53(3):e263–e266. DOI: 10.1016/j.archger.2010.11.021
4. Alberti KG, Eckel RH, Grundy SM, et al. Harmonizing the metabolic syndrome: a joint interim statement of the International Diabetes Federation Task Force on Epidemiology and Prevention; National Heart, Lung, and Blood Institute; American Heart Association; World Heart Federation; International. Circulation 2009;120(16):1640–1645. DOI: 10.1161/CIRCULATIONAHA.109.192644
5. Hoang KC, Le TV, Wong ND. The metabolic syndrome in East Asians. J Cardiometab Syndr 2007;2(4):276–282. DOI: 10.1111/j.1559-4564.2007.07491.x
6. Hwang LC, Bai CH, Chen CJ. Prevalence of obesity and metabolic syndrome in Taiwan. J Formos Med Assoc 2006;105(8):626–635. DOI: 10.1016/S0929-6646(09)60161-3
7. Gupta R, Sharma KK, Gupta A, et al. Persistent high prevalence of cardiovascular risk factors in the urban middle class in India: Jaipur Heart Watch-5. J Assoc Physicians India 2012;60:11–16.
8. Vague J. The degree of masculine differentiation of obesities: a factor determining predisposition to diabetes, atherosclerosis, gout, and uric calculous disease.1956. Nutrition 1999;15(1):89–90. DOI: 10.1016/s0899-9007(98)00131-2
9. Sjöström CD, Håkangård AC, Lissner L, et al. Body compartment and subcutaneous adipose tissue distribution – risk factor patterns in obese subjects. Obes Res 1995;3(1):9–22. DOI: 10.1002/j.1550-8528.1995.tb00116.x
10. Joshipura K, Munoz-Torres F, Vergara J, et al. Neck circumference may be a better alternative to standard anthropometric measures. J Diabetes Res 2016;2016:6058916. DOI: 10.1155/2016/6058916
11. Nestel P, Lyu R, Low LP, et al. Metabolic syndrome: recent prevalence in East and Southeast Asian populations. Asia Pac J Clin Nutr 2007;16(2):362–367.
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