Neck Circumference is Associated with Hypertriglysceridemia in adults

Neck Circumference is Associated with Hypertriglysceridemia in adults | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article Neck Circumference is Associated with Hypertriglysceridemia in adults Ülkügül Yıldırım, Özlem Güç Suvak This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-7406215/v1 This work is licensed under a CC BY 4.0 License Status: Published Journal Publication published 24 Oct, 2025 Read the published version in Journal of Diabetes & Metabolic Disorders → Version 1 posted You are reading this latest preprint version Abstract Objective: Anthropometric measurements are considered a applicable and cost-effective indicator in primary healthcare settings for identifying the risk of obesity and related chronic diseases. This study aimed to elucidate the association between hypertriglyceridemia and neck circumference in adults. Methods: The participants diagnosed with hypertriglyceridemia (HTG) (n=130) and those without HTG (n=130) were assessed in this prospective case-control study. Measurements included body mass index, neck circumference (NC), waist circumference, hip circumference, and various metabolic laboratory parameters. Results: The case group exhibited significantly higher anthropometric indices (body mass index, NC, waist circumference, and hip circumference) as well as higher age, fasting blood glucose, HbA1c, uric acid, hematocrit, hemoglobin, white blood cell count (WBC), low density lipid cholesterol, and triglyceride (TG) compared to the control group (p<0.05). In the HTG subgroup, the mean neck circumference was 38.1 ± 4.1 cm, whereas in the control subgroup it was 35.7 ± 3.8 cm, with a statistically significant difference between the two groups (p<0.001). NC demonstrated statistically significant positive correlations with waist, hip circumference, and TG (r = 0.593, r = 0.461, r = 0.330, and r = 0.243, respectively; p<0.001 for all). Conclusion: Anthropometric measurements like those for neck, waist, and hip circumference correlate positively. This suggests that they can screen for hypertriglyceridemia, a feature of metabolic syndrome. 1. What is already known about this topic? Anthropometric indices are simpleand low-cost quantitative measurements well positioned in primary health care, as they facilitate the early diagnosis of cardiometabolic diseases.⁵ Neck circumference is a simple, cost-effective and time-saving method to ascertain upper body obesity.Numerous studies have focused on the association between BMI, simple antropometric measurements and hypertension, or metabolic syndrome. However, there is little research investigating the primary effect of high triglycerides. 2. What this paper adds: This study demostrated an association between NC and plasma lipid measurements (including TG) with other anthropometric measurements in adults. The study is expected to address research gaps in the area. 3. The implications of this paper: Health expenditure in developing countries should be used wisely, exam-based measurements should be preferred for less cost and efficiency focusing on prevention. Rather than frequent blood tests, primary health care services should promote easy body area measurements like neck circumference. Antropometric measurements Hypertriglyceridemia Neck Circumference BMI Metabolic Syndrome INTRODUCTION As is evidenced across the global population, cardiovascular and cerebrovascular diseases persist in their role as the foremost cause of mortality in the nation. Dyslipidaemia has been demonstrated to be a modifiable and treatable risk factor for metabolic syndrome (MetS), atherosclerosis, coronary heart disease, and related mortality.¹The mean plasma triglyceride concentration, which is the principal component of atherogenic dyslipidaemia, has been reported as 139.2 mg/dL in adult populations in our country.²The optimal concentration of triglycerides is considered to be below 150 mg/dL in the general population, however measurements exceeding 200 mg/dL necessitate therapeutic intervention.³ Nutritional strategies such as low-carbohydrate diets and diets low in trans fats, in addition to regimens with restricted caloric intake (whether low in fat or protein), are recognised as effective approaches for reducing triglyceride (TG).⁴ Anthropometric indices are straightforward, cost-effective quantitative measurements that are well-suited for primary health care centres, as they facilitate the early diagnosis of individuals at risk of cardiometabolic diseases. 5 Neck circumference (NC) measurement is a method employed to ascertain upper body obesity and serves as a simple, cost-effective, and time-saving instrument for identifying overweight and obese individuals. 6 – 8 A substantial body of research has demonstrated that body mass index (BMI), waist circumference (WC), most notably, upper body fat and WC exhibit a stronger correlation with the risk of cardiovascular diseases (CVD) and metabolic syndrome (MetS). 9 In cases of severe obesity, the efficacy of WC measurement in evaluating metabolic health may surpass that of waist circumference. 5 , 10 , 11 There is a plethora of clinical studies have been conducted employing this cost-effective and pragmatic approach to elucidate the correlation between obesity and cardiovascular disease (CVD). A significant proportion of these studies have focused on the association between body mass index (BMI) and hypertension 12 , 13 or metabolic syndrome (MetS) 14 – 19 . However, there is a paucity of research investigating the primary effect of high triglyceride (HTG) 20 or the triglyceride-glucose index. 21 , 22 This study was conducted with the objective of executing the correlation between NC and plasma lipid measurements, included TG, in conjunction with other anthropometric measurements in adults. It is anticipated that the study will contribute meaningfully to the paucity of research in this area in our country. METHOD Study design and participants A single-centre prospective case-control study was conducted. A total of 130 participants aged over 18 were recruited from the family medicine outpatient clinics of a training/research hospital between Jan-Apr 2023. Inclusion criteria were those with measurements TG ≥ 150 mg/dL or who use antilipidemic treatment for HTG (case group) and TG < 150 mg/dL (control group). The process of calculating sample size concluded with a total of 130 participants: 65 in each group by the G*Power 3.1.9.2, Franz-Faul, Universität Kiel, Germany, α = 0.05, power = 0.80, and 95% confidence interval. Participants with anatomical abnormalities in the areas to be measured, physical disabilities that would preclude standing and standing upright, organic disorders (e.g. goiter, Cushing's disease, thyroid tumours) that cause changes in the neck and waist circumference, neck tumours, renal and liver failure, and pregnant women were excluded from the study. Laboratory tests The age, gender, chronic diseases (diabetes mellitus, hypertension, etc.), regular medications, physical activity intensity, smoking and alcohol use of the participants were documented. Plasma lipid measurements (TG, LDL-C, HDL-C), a complete plasma count (haemogram and its sub-parameters: haemoglobin, haematocrit ratio, WBC, mean corpuscular volume (MCV), mean platelet volume (MPV), and biochemical measurements (including platelet count) were analysed. The following parameters were analysed: fasting plasma glucose, alanine aminotransferase (ALT), aspartate aminotransferase (AST), urea, uric acid, creatinine, HbA1c, thyroid-stimulating hormone (TSH), free thyroxine-4 (sT4), and C-reactive protein (CRP). Anthropometric measurements The height and body weight of the participants were measured at the outpatient clinic. WC and HC were measured at the time of presentation in accordance with the established protocol. The body mass index (BMI) was measured under the thyroid and at the midpoint of the neck, with the tape measure held parallel to the ground. WC was measured at the lowest rib and the iliac crest after expiration. Tape measure held parallel to the floor, measuring from the bare abdomen. Hip circumference (HC) was measured from the widest part of the hip while standing upright and minimal clothing was used. The tape measure was selected from a material that does not stretch easily and was held at the right tension, without exerting pressure. A single researcher measured using the same tape measure. The BMI of each participant was subsequently calculated using the formula: body weight (kg)/height (m 2 ), and classified according to the recommendation of the World Health Organisation. Statistical analysis Data were analysed using MedCalc® (MedCalc Software Ltd, Ostend, Belgium; 2022). The distribution of continuous variables was examined using visual (histogram) and Kolmogorov-Smirnov tests. Results are presented as mean and standard deviation (mean ± SD) if normally distributed, and as median, inter-quartile range (median/quartile range) if non-normally distributed. Numbers and percentages are used for categorical data. The Student t-test or Mann-Whitney U test was used to compare continuous variables, and Pearson's chi-squared test or Fisher's exact test to compare categorical variables. Independent risk factors were analysed using univariate linear regression. A two-tailed P value of < 0.05 (95% confidence interval) was considered as significant. RESULTS The mean ages of the participants in the two groups were 54 ± 12 (case) and 45 ± 13 (control). In our study, the mean IC was found to be 38.1 ± 4.1 cm in the case group and 35.7 ± 3.8 cm in the control group. NC were significantly different in both groups. Mean TG were found to be 217 ± 73 (case) and 94 ± 26 (control). Waist circumference was 104.8 ± 13.8 cm (case) and 93.0 ± 14.6 cm (control), with a significant difference between the two. Body weight was recorded at 85.7 ± 17.2 (case) and 75.5 ± 16.4 (control). Most of patients with BMI ≥ 30 kg/m² were in the case group. Those with BMI ≤ 25 kg/m² were significantly fewer. The sociodemographic and anthropometric characteristics of case and control groups are given in Table 1 . Table 1 Comparison of sociodemographic and anthropometric characteristics of the case and control groups Demographic characteristics Case (n = 65), n(%) Control (n = 65),n(%) p-value Gender Male 27 (%41,5) 20 (%31) 0,201 Female 38 (%58,5) 45 (%69) Smoking Yes 14 (%40) 16 (%33,3) 0,677 No 51 (%60) 49 (%66,7) Alcohol Yes 2 (%3) 6 (%9,2) 0,144* No 63 (%97) 59 (%90,8) Chronic disease Yes 47 (%72,3) 33 (%33,3) 0,012 No 18 (%27,7) 32 (%66,7) Diabetes Mellitus (n = 80)*** Yes 24 (%51) 14 (%42,5) 0,446 No 23 (%49) 19 (%57,5) Hypertension (n = 80)*** Yes 30 (%63,8) 11 (%47,8) 0,007 No 17 (%36,2) 12 (%52,2) Asthma(n = 80)*** Yes 4 (%2,1) 6 (%18,2) 0,198 No 43 (%97,9) 27 (%81,8) Physical activity Low 34 (%52,3) 23 (%35,4) 0,010 Intermediate 29 (%44,6) 30 (%46,2) High 2 (%3,1) 12 (%18,4) Body Mass Index 40 6 (%9,2) 2 (%3,1) *Pearson's chi-square test. ***Number of patients for whom chronic disease information was available, Statistically significant difference was defined as p < 0.05. Comparison of the two groups showed that the former had significantly higher measurements than the latter in terms of NC, HC, weight and age. (p 0.05). However, a statistically significant disparity was observed between the two groups with respect to fasting glucose, HbA1c, uric acid, haematocrit, haemoglobin, WBC, and LDL-C, with the case group exhibiting higher than the control group (p < 0.05). Conversely, HDL-C cholesterol concentrations were significantly lower than those in the case group (p = 0.022). TG were significantly higher in the case group (217 ± 73) compared to the normal group (94 ± 26 mg/dL) (p 0.05) (Table 2 ). Table 2 Comparison of anthropometric measurements and laboratory tests of case and control groups Variables Case (n = 65) Control (n = 65) p-value Neck circumference 38,1 ± 4,1 35,7 ± 3,8 < 0,001 Waist circumference 104,8 ± 13,8 93,0 ± 14,6 < 0,001 Hip circumference 112,8 ± 15,0 104,8 ± 12,4 0,001 Age 54 ± 12 45 ± 13 < 0,001 Height 165 ± 10 165 ± 9 0,914 Weight 85,7 ± 17,2 75,5 ± 16,4 < 0,001 TG 217 ± 73 94 ± 26 < 0,001 LDL-C 125 ± 37 108 ± 34 0,005 HDL-C 47 ± 13 53 ± 13 0,022 Hemoglobin 14,4 ± 1,5 13,8 ± 1,6 0,019 Hematocrit 42,7 ± 3,9 40,8 ± 4,2 0,009 WBC 7.600 ± 1.800 6.800 ± 2.300 0,019 MCV 86,1 ± 5,1 85,2 ± 4,6 0,348 MPV 10 (9,7–10,9) 9,9 (9,2–10,8) 0,250 PLT 269.900 ± 64.500 275.500 ± 64.000 0,619 Urea 28,7 ± 8,8 26,4 ± 7,2 0,115 Uric acid 4,9 ± 1,3 4,4 ± 1,2 0,011 ALT 16 (13–24) 16 (13–20) 0,149 AST 17 (14–21) 17 (14–19) 0,708 Vitamin B12 297 (247–410) 299 (244–414) 0,791 CRP 2,7 (1,2–2,5) 2 (0,5 − 3,9) 0,051 Fasting Plasma Glucose 101 (92–125) 92 (86–105) 0,002 Hba1C 6 (5,6–6,9) 5,6 (5,3–6,1) 0,004 Creatinin 0,7 (0,6 − 0,9) 0,7 (0,6 − 0,8) 0,179 TSH 2,1 (1,2–3,0) 1,7 (1,1–2,5) 0,181 Free T4 1,07 (0,9 − 1,16) 1 (0,9 − 1,1) 0,232 Data that conformed to the normal distribution are presented as mean ± standard deviation and comparisons were made using Student's t-test. Data not fitting the normal distribution were presented as median (interquartile/1st and 3rd quartiles) and comparisons were made using the Mann-Whitney U test. Statistically significant difference was defined as p < 0.05. In the present study, a moderate positive correlation was identified between NC and BMI (r = 0.461, p < 0.001), waist circumference (r=:0.593, p < 0.001), hip circumference (r = 0.330, p < 0.001) and TG (r = 0.243, p < 0.001) (Table 3 ). Table 3 Correlation between body mass index, neck circumference, waist circumference, hip circumference and triglycerides Variables BMI NC WC HP TG BMI r 1,000 0,461 0,777 0,666 0,243 p . < 0,001 < 0,001 < 0,001 < 0,001 NC r 0,461 1,000 0,593 0,330 0,319 p < 0,001 . < 0,001 < 0,001 < 0,001 WC r 0,777 0,593 1,000 0,693 0,397 p < 0,001 < 0,001 . < 0,001 < 0,001 HC r 0,666 0,330 0,693 1,000 0,207 p < 0,001 < 0,001 < 0,001 . 0,009 TG r 0,243 0,319 0,397 0,207 1,000 p 0,003 < 0,001 < 0,001 0,009 . r: Pearsons’ correlations, Statistically significant difference was defined as p < 0.05. NC:Neck Circumference, WC:Waist Circumference, HP:Hip Circumference ,TG:Triglysceride Dots and squares represent the study data. The solid blue line is the regression line, the dashed green and orange lines represent its 95% confidence and prediction intervals. R2: Coefficient of Determination. Two-way p-value < 0.05 indicates a statistically significant difference. A statistically significant regression equation was obtained between NC and TG (p < 0.001; log(y) = 1.3423 + 0.02146 x, R2 = 0.150). For each unit increase in IC, the TG increases by 0.02146. (Fig. 1 ) DISCUSSION In this retrospective case-control study, it was obsercved that measurements of NC, WC and HC were significantly higher in adult patients with hypertriglyceridemia than in those with normal TG concentrations. Furthermore, a positive correlation was identified between TG and all anthropometric measurements, including BMI. A weak positive correlation was identified between BMI and TG, suggesting that additional factors may be implicated in the development of HTG. As anticipated, BMI, hip circumference and waist circumference increased in proportion to BMI. A plethora of studies have been conducted on specific sample groups to demonstrate the association of hyperlipidaemia, 5 , 6 , 10 , 11 MetS, 14 – 19 , 21 , 22 T2DM 14 , 18 , 20 and gestational diabetes 23 with anthropometric measurements in terms of atherosclerotic heart diseases. Despite the presence of heterogeneity across studies, a positive correlation has been demonstrated between elevated BMI and a wide range of cardiometabolic risk factors. This finding suggests that early detection of triglyceride measurements may contribute to the early recognition of metabolic syndrome, potentially enhancing survival outcomes. 20 , 21 As with our study, a meta-analysis of the relationship between plasma lipid concentrations and NC revealed a direct correlation between high NC and HDL-C, as well as a direct correlation between low NC and LDL-C,TG, and total cholesterol, for both genders. 6 A variety of studies, including the present one, have demonstrated that changes in NC are significantly associated with TG and other cholesterol values in diverse study populations. Nevertheless, there are still inadequacies in the compilation of such data and the creation of a data pool. 7 , 9 , 14 , 20 A study of young adults reported that obese individuals with normal weight had more lipid profile and cardiometabolic disorder than people of a healthy BMI. 24 In a Nigerian study, participants with CVD risk had higher glucose, lipid profile and Lp-LPA2, and lower HDL-C. 25 As expected, the group with HTG had higher LDL-C and lower HDL-C. Moreover, an elevated rate of HT and a concomitant prevalence of additional chronic diseases were observed in patients with HTG, concurrently with obesity. Neck fat measurement is associated with systemic insulin resistance, low-grade inflammation (hsCRP) and TG. The study revealed that the prevalence of the condition was higher in male subjects and in those with T2DM than normoglysemic participants, and was associated with overall cardiovascular disease (CVD) risk.²⁶ In addition, the triglyceride-glucose (TyG) index was found to be a significant indicator of all-cause mortality in patients with metabolic syndrome.²¹ , ²² In the present study, haemoglobin A1c (HbA1c) and fasting plasma glucose were significantly higher in patients with hypertriglyceridaemia. A few studies, NC has been demonstrated to be positively correlated with hyperuricemia and plasma uric acid measurements among biochemical parameters, as evidenced in the present study. 10 , 27 , 28 A significant and positive correlations were identified between NC and HbA1c, AST, ALT, ferritin and uric acid among metabolic factors, while the AST/ALT ratio was inversely correlated with NC in In a study conducted in patients with non-alcoholic fatty liver disease. 25 It wasn’t observed that any relationship between the liver function tests (AST and ALT) HTG in this study. This may be attributable to two factors: firstly, an absence of focus on this aspect in our study; and secondly, the sample selection. The case group demonstrated higher measurements of haemoglobin and hematocrit; however, it is plausible that this may have been attributable to age, chronic diseases and BMI. Although CRP has been found to be elevated in patients with MetS and hypercholesterolemia in some studies, a relationship was not identified in this particular case. 26 Furthermore, TSH, free T4, urea, creatinine, vitamin B12 and platelet values were not found to be significant variables among laboratory parameters. Further studies focusing on these values may be required to provide more definitive conclusions. In the context of studies conducted within our nation, body mass has been identified as a salient indicator for metabolic syndrome (MetS) in adult populations. The optimal cut-off points for MetS have been determined to be NC measurements of 39 cm for males and 37 cm for females. 20 In the present study, NC measurements were recorded as 38.1 ± 4.1 cm in the HTG group and 35.7 ± 3.8 cm in the non-HTG group. Preliminary findings from studies employing comparable sample groups have yielded similar results. 16 , 17 , 19 Increased BMI and visceral adiposity index have been demonstrated to be significantly associated with a higher prevalence of CVD in both men and women. 29 , 20 Overall, the available literature does not reveal any substantial differences between genders. In the present study, the sample group was not divided according to gender, but was defined as case and control groups. Compared to the control group, NC and other anthropometric measurements were found to be significantly higher in patients with HTG. These results underscore the potential of BMI as a valuable screening tool for obesity-related health risks. The current study demonstrated a positive correlation between TG and BMI as well as WC, HC and BMI measurements. However, the magnitude of this correlation exhibited variation. These results also demonstrate that NC is significantly associated with other components of the metabolic syndrome. 10 – 14 Cardiometabolic problems have been associated with indices such as central (visceral) obesity, abdominal circumference, waist-to-hip ratio, and body roundness index. However, in recent years, there has been a stronger demonstration of the relationship between the body's upper subcutaneous fat stores and metabolic indicators. In the majority of studies, NC measurement has been performed in specific disease sample groups, such as T2DM or HT, which are among cardiometabolic diseases, and the results are heterogeneous. 12 – 14 The relationship between TG and NC has generally been studied as a secondary outcome in patients with metabolic syndrome and T2DM. 7 , 15 – 20 In our study, we compared the measurements of adults with normal and relatively healthy triglyceride measurements with those with hypertriglyceridemia or receiving treatment for it. The present study has demonstrated a robust correlation between triglycerides and neck circumference, thereby substantiating the hypothesis. Strengths and limitations This is the one of few studies focusing on comprehensively evaluation the associations between Triglyceride and antropometric measurements of adult population in our country. Our results highlight the practical application prospect of NC and other basic antropometric measurements in the clinical management of MetS, the group of systemic metabolic disorders. Furthermore, while the present study was conducted based on the data of plasma indicators and anthropometric measurements were only collected at the baseline. These confounding factors may have been introduced into the analyses by the observational study design and imbalanced baseline clinical characteristics. CONCLUSION In this study, when comparing waist circumference, hip circumference, body weight and age, the mean values in the case group were significantly higher than those in the control group. However, a significant correlation was found between NC and HTG. In addition to vital signs, anthropometric measurements are an appropriate, non-invasive and cost-effective screening method for determining chronic disease risk in primary care. It can be used as a complementary tool in clinical practice and screening programmes for screening and diagnosis of risk factors for MetS, atherosclerotic CVD, T2DM and survival. As the importance of preventive medicine is more prominent in such chronic diseases, we believe that the follow-up of such simple methods can make a significant contribution to CVD, morbidity and survival. Hypertriglyceridemia is managed by a multidisciplinary team consisting of endocrinologists, gastroenterologists, internal medicine specialists, family physicians and cardiologists. In addition to pharmacological therapy, lifestyle modification, management of comorbidities and patient education are key to treatment. Declarations Data availability statement The original contributions presented in the study are included in the article/supplementary material. Further inquiries can be directed to the corresponding author. Ethics statement The study conducted with Helsinki Declaration and Human ethics. Ethical approval was obtained from the local ethics committee with protocol number E1/3132/2022 prior to the study. Informed consent was obtained from all participants. Author contributions ÜY designed, interpreted the data, and wrote the manuscript. ÜY collected the data. ÖGS provided the statistical analysis and supervised the article. Funding Statement The study have not founded. Conflict of interest The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest. Acknowledgement The authors thank all team members and participants in the study. In addition, we would like to thank Cenk Aypak, our clinical training supervisor of the hospital. References Oliveira LLH, Assis ACR, Giraldez VZR, Scudeler TL, Soares PR. Dyslipidemia: A narrative review on pharmacotherapy. Pharmaceuticals. 2024;17(3):289. https://doi.org/10.3390/ph17030289 . Kayıkçıoğlu M, Tokgozoğlu L, Kılıçkap M, Göksülük H, Karaaslan D, Özer N, et al. Dyslipidaemia prevalence and lipid data in Turkey: Systematic review and meta-analysis of epidemiological studies on cardiovascular risk factors. Archives Turkish Soc Cardiol. 2018;46(7):556–74. https://doi.org/10.5543/tkda.2018.23450 . Raygor V, Khera A. 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Frontiers in Endocrinology (Lausanne), 15 , 1301543. https://doi.org/10.3389/fendo.2024.1301543 Wan H, Wang Y, Xiang Q, Fang S, Chen Y, Chen C et al. (2020, July 31). Associations between abdominal obesity indices and diabetic complications: Chinese visceral adiposity index and neck circumference. Cardiovascular Diabetology, 19 (1), 118. https://doi.org/10.1186/s12933-020-01095-4 Additional Declarations No competing interests reported. Supplementary Files 1.png Regression analysis plot between neck circumference and individual triglyceride concentrations. Dots and squares represent the study data. The solid blue line is the regression line, the dashed green and orange lines represent its 95% confidence and prediction intervals. R2: Coefficient of Determination. Two-way p-value <0.05 indicates a statistically significant difference. Cite Share Download PDF Status: Published Journal Publication published 24 Oct, 2025 Read the published version in Journal of Diabetes & Metabolic Disorders → Version 1 posted You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. We do this by developing innovative software and high quality services for the global research community. Our growing team is made up of researchers and industry professionals working together to solve the most critical problems facing scientific publishing. Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-7406215","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":506197091,"identity":"3e6de2f2-8088-4972-8794-2500c46630ae","order_by":0,"name":"Ülkügül Yıldırım","email":"","orcid":"","institution":"Dışkapı Yıldırım Beyazıt Eğitim ve Araştırma Hastanesi","correspondingAuthor":false,"prefix":"","firstName":"Ülkügül","middleName":"","lastName":"Yıldırım","suffix":""},{"id":506197092,"identity":"ece51409-c187-4807-b520-727bc1a9c01e","order_by":1,"name":"Özlem Güç Suvak","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAA+0lEQVRIiWNgGAWjYFAC5gY4k7GhAiSAJIIdMCJrOQPSgiRCWEtjG5oINsDPf7Dx0Y1fh+XlZ+QYfpw5rzaavx2o5UfFNpxaJBsONhvn9h023HAjx1hy47bjuTMOMzYw9py5jVOLwcHGNuncnsMJBhJpCZIPtx3LbQBqYWZsw6PlMGP7b5AW+RlpyT8fzjmWO5+glmOMbcw5Pw4nMNxIPia5saEmdwMhLZI9jM3SuQ3phhvOPD5mOePYgdyNQC0H8fmFn//wwc85f6zl5dsTm2/21NTlzjt/+OCDHxW4tYABYxuceRhMHsCvHgT+wFl1hBWPglEwCkbBiAMA6qdjmK9A6EIAAAAASUVORK5CYII=","orcid":"","institution":"Dışkapı Yıldırım Beyazıt Eğitim ve Araştırma Hastanesi","correspondingAuthor":true,"prefix":"","firstName":"Özlem","middleName":"Güç","lastName":"Suvak","suffix":""}],"badges":[],"createdAt":"2025-08-19 08:23:42","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-7406215/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-7406215/v1","draftVersion":[],"editorialEvents":[{"content":"https://doi.org/10.1007/s40200-025-01761-y","type":"published","date":"2025-10-24T16:17:28+00:00"}],"editorialNote":"","failedWorkflow":false,"files":[{"id":94490638,"identity":"274f2a9a-b1a3-4f57-b782-1a29f4efc30b","added_by":"auto","created_at":"2025-10-27 17:13:18","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":748739,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-7406215/v1/b1774643-e165-4d8c-aea4-360e879b1a41.pdf"},{"id":90389685,"identity":"1c5491c3-76b4-4bab-bd59-2acafa055438","added_by":"auto","created_at":"2025-09-02 08:15:33","extension":"png","order_by":1,"title":"","display":"","copyAsset":false,"role":"supplement","size":123908,"visible":true,"origin":"","legend":"\u003cp\u003eRegression analysis plot between neck circumference and individual triglyceride concentrations.\u003c/p\u003e\n\u003cp\u003eDots and squares represent the study data. The solid blue line is the regression line, the dashed green and orange lines represent its 95% confidence and prediction intervals. R2: Coefficient of Determination. Two-way p-value \u0026lt;0.05 indicates a statistically significant difference.\u003c/p\u003e","description":"","filename":"1.png","url":"https://assets-eu.researchsquare.com/files/rs-7406215/v1/d806625336dbbb2ea2c8bd66.png"}],"financialInterests":"No competing interests reported.","formattedTitle":"Neck Circumference is Associated with Hypertriglysceridemia in adults","fulltext":[{"header":"INTRODUCTION","content":"\u003cp\u003eAs is evidenced across the global population, cardiovascular and cerebrovascular diseases persist in their role as the foremost cause of mortality in the nation. Dyslipidaemia has been demonstrated to be a modifiable and treatable risk factor for metabolic syndrome (MetS), atherosclerosis, coronary heart disease, and related mortality.\u0026sup1;The mean plasma triglyceride concentration, which is the principal component of atherogenic dyslipidaemia, has been reported as 139.2 mg/dL in adult populations in our country.\u0026sup2;The optimal concentration of triglycerides is considered to be below 150 mg/dL in the general population, however measurements exceeding 200 mg/dL necessitate therapeutic intervention.\u0026sup3; Nutritional strategies such as low-carbohydrate diets and diets low in trans fats, in addition to regimens with restricted caloric intake (whether low in fat or protein), are recognised as effective approaches for reducing triglyceride (TG).⁴\u003c/p\u003e\u003cp\u003eAnthropometric indices are straightforward, cost-effective quantitative measurements that are well-suited for primary health care centres, as they facilitate the early diagnosis of individuals at risk of cardiometabolic diseases.\u003csup\u003e\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e\u003c/sup\u003eNeck circumference (NC) measurement is a method employed to ascertain upper body obesity and serves as a simple, cost-effective, and time-saving instrument for identifying overweight and obese individuals.\u003csup\u003e\u003cspan additionalcitationids=\"CR7\" citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e\u003c/sup\u003e A substantial body of research has demonstrated that body mass index (BMI), waist circumference (WC), most notably, upper body fat and WC exhibit a stronger correlation with the risk of cardiovascular diseases (CVD) and metabolic syndrome (MetS).\u003csup\u003e\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e\u003c/sup\u003e In cases of severe obesity, the efficacy of WC measurement in evaluating metabolic health may surpass that of waist circumference.\u003csup\u003e\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e,\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e,\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e\u003c/sup\u003eThere is a plethora of clinical studies have been conducted employing this cost-effective and pragmatic approach to elucidate the correlation between obesity and cardiovascular disease (CVD). A significant proportion of these studies have focused on the association between body mass index (BMI) and hypertension\u003csup\u003e\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e,\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e\u003c/sup\u003e or metabolic syndrome (MetS)\u003csup\u003e\u003cspan additionalcitationids=\"CR15 CR16 CR17 CR18\" citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e\u003c/sup\u003e. However, there is a paucity of research investigating the primary effect of high triglyceride (HTG)\u003csup\u003e\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e\u003c/sup\u003e or the triglyceride-glucose index.\u003csup\u003e\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e,\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e\u003c/sup\u003e This study was conducted with the objective of executing the correlation between NC and plasma lipid measurements, included TG, in conjunction with other anthropometric measurements in adults. It is anticipated that the study will contribute meaningfully to the paucity of research in this area in our country.\u003c/p\u003e"},{"header":"METHOD","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e\u003ch2\u003eStudy design and participants\u003c/h2\u003e\u003cp\u003eA single-centre prospective case-control study was conducted. A total of 130 participants aged over 18 were recruited from the family medicine outpatient clinics of a training/research hospital between Jan-Apr 2023. Inclusion criteria were those with measurements TG\u0026thinsp;\u0026ge;\u0026thinsp;150 mg/dL or who use antilipidemic treatment for HTG (case group) and TG\u0026thinsp;\u0026lt;\u0026thinsp;150 mg/dL (control group). The process of calculating sample size concluded with a total of 130 participants: 65 in each group by the G*Power 3.1.9.2, Franz-Faul, Universit\u0026auml;t Kiel, Germany, α\u0026thinsp;=\u0026thinsp;0.05, power\u0026thinsp;=\u0026thinsp;0.80, and 95% confidence interval.\u003c/p\u003e\u003cp\u003eParticipants with anatomical abnormalities in the areas to be measured, physical disabilities that would preclude standing and standing upright, organic disorders (e.g. goiter, Cushing's disease, thyroid tumours) that cause changes in the neck and waist circumference, neck tumours, renal and liver failure, and pregnant women were excluded from the study.\u003c/p\u003e\u003c/div\u003e\n\u003ch3\u003eLaboratory tests\u003c/h3\u003e\n\u003cp\u003eThe age, gender, chronic diseases (diabetes mellitus, hypertension, etc.), regular medications, physical activity intensity, smoking and alcohol use of the participants were documented. Plasma lipid measurements (TG, LDL-C, HDL-C), a complete plasma count (haemogram and its sub-parameters: haemoglobin, haematocrit ratio, WBC, mean corpuscular volume (MCV), mean platelet volume (MPV), and biochemical measurements (including platelet count) were analysed. The following parameters were analysed: fasting plasma glucose, alanine aminotransferase (ALT), aspartate aminotransferase (AST), urea, uric acid, creatinine, HbA1c, thyroid-stimulating hormone (TSH), free thyroxine-4 (sT4), and C-reactive protein (CRP).\u003c/p\u003e\n\u003ch3\u003eAnthropometric measurements\u003c/h3\u003e\n\u003cp\u003eThe height and body weight of the participants were measured at the outpatient clinic. WC and HC were measured at the time of presentation in accordance with the established protocol. The body mass index (BMI) was measured under the thyroid and at the midpoint of the neck, with the tape measure held parallel to the ground. WC was measured at the lowest rib and the iliac crest after expiration. Tape measure held parallel to the floor, measuring from the bare abdomen. Hip circumference (HC) was measured from the widest part of the hip while standing upright and minimal clothing was used. The tape measure was selected from a material that does not stretch easily and was held at the right tension, without exerting pressure. A single researcher measured using the same tape measure. The BMI of each participant was subsequently calculated using the formula: body weight (kg)/height (m\u003csup\u003e\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e\u003c/sup\u003e), and classified according to the recommendation of the World Health Organisation.\u003c/p\u003e\u003cdiv id=\"Sec6\" class=\"Section2\"\u003e\u003ch2\u003eStatistical analysis\u003c/h2\u003e\u003cp\u003eData were analysed using MedCalc\u0026reg; (MedCalc Software Ltd, Ostend, Belgium; 2022). The distribution of continuous variables was examined using visual (histogram) and Kolmogorov-Smirnov tests. Results are presented as mean and standard deviation (mean\u0026thinsp;\u0026plusmn;\u0026thinsp;SD) if normally distributed, and as median, inter-quartile range (median/quartile range) if non-normally distributed. Numbers and percentages are used for categorical data. The Student t-test or Mann-Whitney U test was used to compare continuous variables, and Pearson's chi-squared test or Fisher's exact test to compare categorical variables. Independent risk factors were analysed using univariate linear regression. A two-tailed P value of \u0026lt;\u0026thinsp;0.05 (95% confidence interval) was considered as significant.\u003c/p\u003e\u003c/div\u003e"},{"header":"RESULTS","content":"\u003cp\u003eThe mean ages of the participants in the two groups were 54\u0026thinsp;\u0026plusmn;\u0026thinsp;12 (case) and 45\u0026thinsp;\u0026plusmn;\u0026thinsp;13 (control). In our study, the mean IC was found to be 38.1\u0026thinsp;\u0026plusmn;\u0026thinsp;4.1 cm in the case group and 35.7\u0026thinsp;\u0026plusmn;\u0026thinsp;3.8 cm in the control group. NC were significantly different in both groups. Mean TG were found to be 217\u0026thinsp;\u0026plusmn;\u0026thinsp;73 (case) and 94\u0026thinsp;\u0026plusmn;\u0026thinsp;26 (control). Waist circumference was 104.8\u0026thinsp;\u0026plusmn;\u0026thinsp;13.8 cm (case) and 93.0\u0026thinsp;\u0026plusmn;\u0026thinsp;14.6 cm (control), with a significant difference between the two. Body weight was recorded at 85.7\u0026thinsp;\u0026plusmn;\u0026thinsp;17.2 (case) and 75.5\u0026thinsp;\u0026plusmn;\u0026thinsp;16.4 (control). Most of patients with BMI\u0026thinsp;\u0026ge;\u0026thinsp;30 kg/m\u0026sup2; were in the case group. Those with BMI\u0026thinsp;\u0026le;\u0026thinsp;25 kg/m\u0026sup2; were significantly fewer. The sociodemographic and anthropometric characteristics of case and control groups are given in Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e.\u003c/p\u003e\u003cp\u003e\u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab1\" border=\"1\"\u003e\u003ccaption language=\"En\"\u003e\u003cdiv class=\"CaptionNumber\"\u003eTable 1\u003c/div\u003e\u003cdiv class=\"CaptionContent\"\u003e\u003cp\u003eComparison of sociodemographic and anthropometric characteristics of the case and control groups\u003c/p\u003e\u003c/div\u003e\u003c/caption\u003e\u003ccolgroup cols=\"4\"\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e\u003cthead\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c1\"\u003e\u003cp\u003eDemographic characteristics\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c2\"\u003e\u003cp\u003eCase (n\u0026thinsp;=\u0026thinsp;65), n(%)\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c3\"\u003e\u003cp\u003eControl (n\u0026thinsp;=\u0026thinsp;65),n(%)\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c4\"\u003e\u003cp\u003ep-value\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colspan=\"4\" nameend=\"c4\" namest=\"c1\"\u003e\u003cp\u003eGender\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eMale\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e27 (%41,5)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e20 (%31)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\" morerows=\"1\" rowspan=\"2\"\u003e\u003cp\u003e0,201\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eFemale\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e38 (%58,5)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e45 (%69)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eSmoking\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eYes\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e14 (%40)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e16 (%33,3)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\" morerows=\"1\" rowspan=\"2\"\u003e\u003cp\u003e0,677\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eNo\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e51 (%60)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e49 (%66,7)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colspan=\"4\" nameend=\"c4\" namest=\"c1\"\u003e\u003cp\u003eAlcohol\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eYes\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e2 (%3)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e6 (%9,2)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\" morerows=\"1\" rowspan=\"2\"\u003e\u003cp\u003e0,144*\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eNo\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e63 (%97)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e59 (%90,8)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colspan=\"4\" nameend=\"c4\" namest=\"c1\"\u003e\u003cp\u003eChronic disease\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eYes\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e47 (%72,3)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e33 (%33,3)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\" morerows=\"1\" rowspan=\"2\"\u003e\u003cp\u003e\u003cb\u003e0,012\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eNo\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e18 (%27,7)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e32 (%66,7)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colspan=\"4\" nameend=\"c4\" namest=\"c1\"\u003e\u003cp\u003eDiabetes Mellitus (n\u0026thinsp;=\u0026thinsp;80)***\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eYes\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e24 (%51)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e14 (%42,5)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\" morerows=\"1\" rowspan=\"2\"\u003e\u003cp\u003e0,446\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eNo\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e23 (%49)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e19 (%57,5)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colspan=\"4\" nameend=\"c4\" namest=\"c1\"\u003e\u003cp\u003eHypertension (n\u0026thinsp;=\u0026thinsp;80)***\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eYes\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e30 (%63,8)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e11 (%47,8)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\" morerows=\"1\" rowspan=\"2\"\u003e\u003cp\u003e\u003cb\u003e0,007\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eNo\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e17 (%36,2)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e12 (%52,2)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colspan=\"4\" nameend=\"c4\" namest=\"c1\"\u003e\u003cp\u003eAsthma(n\u0026thinsp;=\u0026thinsp;80)***\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eYes\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e4 (%2,1)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e6 (%18,2)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\" morerows=\"1\" rowspan=\"2\"\u003e\u003cp\u003e0,198\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eNo\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e43 (%97,9)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e27 (%81,8)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colspan=\"4\" nameend=\"c4\" namest=\"c1\"\u003e\u003cp\u003ePhysical activity\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eLow\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e34 (%52,3)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e23 (%35,4)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\" morerows=\"2\" rowspan=\"3\"\u003e\u003cp\u003e\u003cb\u003e0,010\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eIntermediate\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e29 (%44,6)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e30 (%46,2)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eHigh\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e2 (%3,1)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e12 (%18,4)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colspan=\"4\" nameend=\"c4\" namest=\"c1\"\u003e\u003cp\u003eBody Mass Index\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u0026lt;\u0026thinsp;18,5\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e0 (%0)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e2 (%3,1)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\" morerows=\"4\" rowspan=\"5\"\u003e\u003cp\u003e\u003cb\u003e0,031\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e18,5-24.9\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e7 (%10,8)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e16 (%24,6)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e25.0-29.9\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e25 (%38,5)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e29 (%44,6)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e30.0-39.9\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e27 (%41,5)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e16 (%24,6)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u0026gt;\u0026thinsp;40\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e6 (%9,2)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e2 (%3,1)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colspan=\"4\" nameend=\"c4\" namest=\"c1\"\u003e\u003cp\u003e*Pearson's chi-square test. ***Number of patients for whom chronic disease information was available, Statistically significant difference was defined as p\u0026thinsp;\u0026lt;\u0026thinsp;0.05.\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003c/tbody\u003e\u003c/colgroup\u003e\u003c/table\u003e\u003c/div\u003e\u003c/p\u003e\u003cp\u003eComparison of the two groups showed that the former had significantly higher measurements than the latter in terms of NC, HC, weight and age. (p\u0026thinsp;\u0026lt;\u0026thinsp;0.05). However, a non-significant difference was observed in mean height between the two groups (p\u0026thinsp;\u0026gt;\u0026thinsp;0.05). However, a statistically significant disparity was observed between the two groups with respect to fasting glucose, HbA1c, uric acid, haematocrit, haemoglobin, WBC, and LDL-C, with the case group exhibiting higher than the control group (p\u0026thinsp;\u0026lt;\u0026thinsp;0.05). Conversely, HDL-C cholesterol concentrations were significantly lower than those in the case group (p\u0026thinsp;=\u0026thinsp;0.022). TG were significantly higher in the case group (217\u0026thinsp;\u0026plusmn;\u0026thinsp;73) compared to the normal group (94\u0026thinsp;\u0026plusmn;\u0026thinsp;26 mg/dL) (p\u0026thinsp;\u0026lt;\u0026thinsp;0.001). With regard to other biochemical parameters, MPV, MCV, platelets, ALT, AST, TSH, free T4, urea, creatinine, vitamin B12 and CRP were not statistically different (p\u0026thinsp;\u0026gt;\u0026thinsp;0.05) (Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e).\u003c/p\u003e\u003cp\u003e\u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab2\" border=\"1\"\u003e\u003ccaption language=\"En\"\u003e\u003cdiv class=\"CaptionNumber\"\u003eTable 2\u003c/div\u003e\u003cdiv class=\"CaptionContent\"\u003e\u003cp\u003eComparison of anthropometric measurements and laboratory tests of case and control groups\u003c/p\u003e\u003c/div\u003e\u003c/caption\u003e\u003ccolgroup cols=\"4\"\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e\u003cthead\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c1\"\u003e\u003cp\u003eVariables\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c2\"\u003e\u003cp\u003eCase (n\u0026thinsp;=\u0026thinsp;65)\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c3\"\u003e\u003cp\u003eControl (n\u0026thinsp;=\u0026thinsp;65)\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c4\"\u003e\u003cp\u003ep-value\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eNeck circumference\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e38,1\u0026thinsp;\u0026plusmn;\u0026thinsp;4,1\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e35,7\u0026thinsp;\u0026plusmn;\u0026thinsp;3,8\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e\u0026lt;\u0026thinsp;0,001\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eWaist circumference\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e104,8\u0026thinsp;\u0026plusmn;\u0026thinsp;13,8\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e93,0\u0026thinsp;\u0026plusmn;\u0026thinsp;14,6\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e\u0026lt;\u0026thinsp;0,001\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eHip circumference\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e112,8\u0026thinsp;\u0026plusmn;\u0026thinsp;15,0\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e104,8\u0026thinsp;\u0026plusmn;\u0026thinsp;12,4\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e0,001\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eAge\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e54\u0026thinsp;\u0026plusmn;\u0026thinsp;12\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e45\u0026thinsp;\u0026plusmn;\u0026thinsp;13\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e\u0026lt;\u0026thinsp;0,001\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eHeight\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e165\u0026thinsp;\u0026plusmn;\u0026thinsp;10\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e165\u0026thinsp;\u0026plusmn;\u0026thinsp;9\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e0,914\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eWeight\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e85,7\u0026thinsp;\u0026plusmn;\u0026thinsp;17,2\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e75,5\u0026thinsp;\u0026plusmn;\u0026thinsp;16,4\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e\u0026lt;\u0026thinsp;0,001\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eTG\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e217\u0026thinsp;\u0026plusmn;\u0026thinsp;73\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e94\u0026thinsp;\u0026plusmn;\u0026thinsp;26\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e\u0026lt;\u0026thinsp;0,001\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eLDL-C\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e125\u0026thinsp;\u0026plusmn;\u0026thinsp;37\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e108\u0026thinsp;\u0026plusmn;\u0026thinsp;34\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e0,005\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eHDL-C\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e47\u0026thinsp;\u0026plusmn;\u0026thinsp;13\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e53\u0026thinsp;\u0026plusmn;\u0026thinsp;13\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e0,022\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eHemoglobin\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e14,4\u0026thinsp;\u0026plusmn;\u0026thinsp;1,5\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e13,8\u0026thinsp;\u0026plusmn;\u0026thinsp;1,6\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e0,019\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eHematocrit\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e42,7\u0026thinsp;\u0026plusmn;\u0026thinsp;3,9\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e40,8\u0026thinsp;\u0026plusmn;\u0026thinsp;4,2\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e0,009\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eWBC\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e7.600\u0026thinsp;\u0026plusmn;\u0026thinsp;1.800\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e6.800\u0026thinsp;\u0026plusmn;\u0026thinsp;2.300\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e0,019\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eMCV\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e86,1\u0026thinsp;\u0026plusmn;\u0026thinsp;5,1\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e85,2\u0026thinsp;\u0026plusmn;\u0026thinsp;4,6\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e0,348\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eMPV\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e10 (9,7\u0026ndash;10,9)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e9,9 (9,2\u0026ndash;10,8)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e0,250\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003ePLT\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e269.900\u0026thinsp;\u0026plusmn;\u0026thinsp;64.500\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e275.500\u0026thinsp;\u0026plusmn;\u0026thinsp;64.000\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e0,619\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eUrea\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e28,7\u0026thinsp;\u0026plusmn;\u0026thinsp;8,8\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e26,4\u0026thinsp;\u0026plusmn;\u0026thinsp;7,2\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e0,115\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eUric acid\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e4,9\u0026thinsp;\u0026plusmn;\u0026thinsp;1,3\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e4,4\u0026thinsp;\u0026plusmn;\u0026thinsp;1,2\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e0,011\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eALT\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e16 (13\u0026ndash;24)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e16 (13\u0026ndash;20)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e0,149\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eAST\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e17 (14\u0026ndash;21)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e17 (14\u0026ndash;19)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e0,708\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eVitamin B12\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e297 (247\u0026ndash;410)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e299 (244\u0026ndash;414)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e0,791\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eCRP\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e2,7 (1,2\u0026ndash;2,5)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e2 (0,5\u0026thinsp;\u0026minus;\u0026thinsp;3,9)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e0,051\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eFasting Plasma Glucose\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e101 (92\u0026ndash;125)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e92 (86\u0026ndash;105)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e0,002\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eHba1C\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e6 (5,6\u0026ndash;6,9)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e5,6 (5,3\u0026ndash;6,1)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e0,004\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eCreatinin\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e0,7 (0,6\u0026thinsp;\u0026minus;\u0026thinsp;0,9)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e0,7 (0,6\u0026thinsp;\u0026minus;\u0026thinsp;0,8)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e0,179\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eTSH\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e2,1 (1,2\u0026ndash;3,0)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e1,7 (1,1\u0026ndash;2,5)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e0,181\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eFree T4\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e1,07 (0,9\u0026thinsp;\u0026minus;\u0026thinsp;1,16)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e1 (0,9\u0026thinsp;\u0026minus;\u0026thinsp;1,1)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e0,232\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colspan=\"4\" nameend=\"c4\" namest=\"c1\"\u003e\u003cp\u003eData that conformed to the normal distribution are presented as mean\u0026thinsp;\u0026plusmn;\u0026thinsp;standard deviation and comparisons were made using Student's t-test. Data not fitting the normal distribution were presented as median (interquartile/1st and 3rd quartiles) and comparisons were made using the Mann-Whitney U test. Statistically significant difference was defined as p\u0026thinsp;\u0026lt;\u0026thinsp;0.05.\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003c/tbody\u003e\u003c/colgroup\u003e\u003c/table\u003e\u003c/div\u003e\u003c/p\u003e\u003cp\u003eIn the present study, a moderate positive correlation was identified between NC and BMI (r\u0026thinsp;=\u0026thinsp;0.461, p\u0026thinsp;\u0026lt;\u0026thinsp;0.001), waist circumference (r=:0.593, p\u0026thinsp;\u0026lt;\u0026thinsp;0.001), hip circumference (r\u0026thinsp;=\u0026thinsp;0.330, p\u0026thinsp;\u0026lt;\u0026thinsp;0.001) and TG (r\u0026thinsp;=\u0026thinsp;0.243, p\u0026thinsp;\u0026lt;\u0026thinsp;0.001) (Table\u0026nbsp;\u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e3\u003c/span\u003e).\u003c/p\u003e\u003cp\u003e\u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab3\" border=\"1\"\u003e\u003ccaption language=\"En\"\u003e\u003cdiv class=\"CaptionNumber\"\u003eTable 3\u003c/div\u003e\u003cdiv class=\"CaptionContent\"\u003e\u003cp\u003eCorrelation between body mass index, neck circumference, waist circumference, hip circumference and triglycerides\u003c/p\u003e\u003c/div\u003e\u003c/caption\u003e\u003ccolgroup cols=\"7\"\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e\u003cthead\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c1\"\u003e\u003cp\u003eVariables\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/th\u003e\u003cth align=\"left\" colname=\"c3\"\u003e\u003cp\u003eBMI\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c4\"\u003e\u003cp\u003eNC\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c5\"\u003e\u003cp\u003eWC\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c6\"\u003e\u003cp\u003eHP\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c7\"\u003e\u003cp\u003eTG\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eBMI\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003er\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e1,000\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e0,461\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e0,777\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e0,666\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e0,243\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003ep\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e.\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e\u0026lt;\u0026thinsp;0,001\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e\u0026lt;\u0026thinsp;0,001\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e\u0026lt;\u0026thinsp;0,001\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e\u0026lt;\u0026thinsp;0,001\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eNC\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003er\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e0,461\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e1,000\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e0,593\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e0,330\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e0,319\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003ep\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e\u0026lt;\u0026thinsp;0,001\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e.\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e\u0026lt;\u0026thinsp;0,001\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e\u0026lt;\u0026thinsp;0,001\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e\u0026lt;\u0026thinsp;0,001\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eWC\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003er\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e0,777\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e0,593\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e1,000\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e0,693\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e0,397\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003ep\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e\u0026lt;\u0026thinsp;0,001\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e\u0026lt;\u0026thinsp;0,001\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e.\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e\u0026lt;\u0026thinsp;0,001\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e\u0026lt;\u0026thinsp;0,001\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eHC\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003er\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e0,666\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e0,330\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e0,693\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e1,000\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e0,207\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003ep\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e\u0026lt;\u0026thinsp;0,001\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e\u0026lt;\u0026thinsp;0,001\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e\u0026lt;\u0026thinsp;0,001\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e.\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e0,009\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eTG\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003er\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e0,243\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e0,319\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e0,397\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e0,207\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e1,000\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003ep\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e0,003\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e\u0026lt;\u0026thinsp;0,001\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e\u0026lt;\u0026thinsp;0,001\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e0,009\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e.\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003c/tbody\u003e\u003c/colgroup\u003e\u003ctfoot\u003e\u003ctr\u003e\u003ctd colspan=\"7\"\u003er: Pearsons\u0026rsquo; correlations, Statistically significant difference was defined as p\u0026thinsp;\u0026lt;\u0026thinsp;0.05.\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd colspan=\"7\"\u003eNC:Neck Circumference, WC:Waist Circumference, HP:Hip Circumference ,TG:Triglysceride\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd colspan=\"7\"\u003eDots and squares represent the study data. The solid blue line is the regression line, the dashed green and orange lines represent its 95% confidence and prediction intervals. R2: Coefficient of Determination. Two-way p-value\u0026thinsp;\u0026lt;\u0026thinsp;0.05 indicates a statistically significant difference.\u003c/td\u003e\u003c/tr\u003e\u003c/tfoot\u003e\u003c/table\u003e\u003c/div\u003e\u003c/p\u003e\u003cp\u003eA statistically significant regression equation was obtained between NC and TG (p\u0026thinsp;\u0026lt;\u0026thinsp;0.001; log(y)\u0026thinsp;=\u0026thinsp;1.3423\u0026thinsp;+\u0026thinsp;0.02146 x, R2\u0026thinsp;=\u0026thinsp;0.150). For each unit increase in IC, the TG increases by 0.02146. (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e)\u003c/p\u003e\u003cp\u003e\u003c/p\u003e"},{"header":"DISCUSSION","content":"\u003cp\u003eIn this retrospective case-control study, it was obsercved that measurements of NC, WC and HC were significantly higher in adult patients with hypertriglyceridemia than in those with normal TG concentrations. Furthermore, a positive correlation was identified between TG and all anthropometric measurements, including BMI. A weak positive correlation was identified between BMI and TG, suggesting that additional factors may be implicated in the development of HTG. As anticipated, BMI, hip circumference and waist circumference increased in proportion to BMI.\u003c/p\u003e\u003cp\u003eA plethora of studies have been conducted on specific sample groups to demonstrate the association of hyperlipidaemia,\u003csup\u003e\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e,\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e,\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e,\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e\u003c/sup\u003e MetS,\u003csup\u003e\u003cspan additionalcitationids=\"CR15 CR16 CR17 CR18\" citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e,\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e,\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e\u003c/sup\u003e T2DM\u003csup\u003e\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e,\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e,\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e\u003c/sup\u003e and gestational diabetes\u003csup\u003e\u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e\u003c/sup\u003e with anthropometric measurements in terms of atherosclerotic heart diseases. Despite the presence of heterogeneity across studies, a positive correlation has been demonstrated between elevated BMI and a wide range of cardiometabolic risk factors. This finding suggests that early detection of triglyceride measurements may contribute to the early recognition of metabolic syndrome, potentially enhancing survival outcomes.\u003csup\u003e\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e,\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e\u003c/sup\u003e As with our study, a meta-analysis of the relationship between plasma lipid concentrations and NC revealed a direct correlation between high NC and HDL-C, as well as a direct correlation between low NC and LDL-C,TG, and total cholesterol, for both genders.\u003csup\u003e\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e\u003c/sup\u003e A variety of studies, including the present one, have demonstrated that changes in NC are significantly associated with TG and other cholesterol values in diverse study populations. Nevertheless, there are still inadequacies in the compilation of such data and the creation of a data pool.\u003csup\u003e\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e,\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e,\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e,\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e\u003c/sup\u003e\u003c/p\u003e\u003cp\u003eA study of young adults reported that obese individuals with normal weight had more lipid profile and cardiometabolic disorder than people of a healthy BMI.\u003csup\u003e\u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e\u003c/sup\u003e In a Nigerian study, participants with CVD risk had higher glucose, lipid profile and Lp-LPA2, and lower HDL-C.\u003csup\u003e\u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e\u003c/sup\u003e As expected, the group with HTG had higher LDL-C and lower HDL-C. Moreover, an elevated rate of HT and a concomitant prevalence of additional chronic diseases were observed in patients with HTG, concurrently with obesity. Neck fat measurement is associated with systemic insulin resistance, low-grade inflammation (hsCRP) and TG.\u003c/p\u003e\u003cp\u003eThe study revealed that the prevalence of the condition was higher in male subjects and in those with T2DM than normoglysemic participants, and was associated with overall cardiovascular disease (CVD) risk.\u0026sup2;⁶ In addition, the triglyceride-glucose (TyG) index was found to be a significant indicator of all-cause mortality in patients with metabolic syndrome.\u0026sup2;\u0026sup1;\u003csup\u003e,\u003c/sup\u003e\u0026sup2;\u0026sup2; In the present study, haemoglobin A1c (HbA1c) and fasting plasma glucose were significantly higher in patients with hypertriglyceridaemia.\u003c/p\u003e\u003cp\u003eA few studies, NC has been demonstrated to be positively correlated with hyperuricemia and plasma uric acid measurements among biochemical parameters, as evidenced in the present study.\u003csup\u003e\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e,\u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e,\u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e\u003c/sup\u003e A significant and positive correlations were identified between NC and HbA1c, AST, ALT, ferritin and uric acid among metabolic factors, while the AST/ALT ratio was inversely correlated with NC in In a study conducted in patients with non-alcoholic fatty liver disease.\u003csup\u003e\u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e\u003c/sup\u003e It wasn\u0026rsquo;t observed that any relationship between the liver function tests (AST and ALT) HTG in this study. This may be attributable to two factors: firstly, an absence of focus on this aspect in our study; and secondly, the sample selection. The case group demonstrated higher measurements of haemoglobin and hematocrit; however, it is plausible that this may have been attributable to age, chronic diseases and BMI. Although CRP has been found to be elevated in patients with MetS and hypercholesterolemia in some studies, a relationship was not identified in this particular case.\u003csup\u003e\u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e\u003c/sup\u003e Furthermore, TSH, free T4, urea, creatinine, vitamin B12 and platelet values were not found to be significant variables among laboratory parameters. Further studies focusing on these values may be required to provide more definitive conclusions.\u003c/p\u003e\u003cp\u003eIn the context of studies conducted within our nation, body mass has been identified as a salient indicator for metabolic syndrome (MetS) in adult populations. The optimal cut-off points for MetS have been determined to be NC measurements of 39 cm for males and 37 cm for females.\u003csup\u003e\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e\u003c/sup\u003e In the present study, NC measurements were recorded as 38.1\u0026thinsp;\u0026plusmn;\u0026thinsp;4.1 cm in the HTG group and 35.7\u0026thinsp;\u0026plusmn;\u0026thinsp;3.8 cm in the non-HTG group. Preliminary findings from studies employing comparable sample groups have yielded similar results.\u003csup\u003e\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e,\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e,\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e\u003c/sup\u003e Increased BMI and visceral adiposity index have been demonstrated to be significantly associated with a higher prevalence of CVD in both men and women.\u003csup\u003e\u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e29\u003c/span\u003e,\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e\u003c/sup\u003e Overall, the available literature does not reveal any substantial differences between genders. In the present study, the sample group was not divided according to gender, but was defined as case and control groups. Compared to the control group, NC and other anthropometric measurements were found to be significantly higher in patients with HTG. These results underscore the potential of BMI as a valuable screening tool for obesity-related health risks. The current study demonstrated a positive correlation between TG and BMI as well as WC, HC and BMI measurements. However, the magnitude of this correlation exhibited variation. These results also demonstrate that NC is significantly associated with other components of the metabolic syndrome.\u003csup\u003e\u003cspan additionalcitationids=\"CR11 CR12 CR13\" citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e\u003c/sup\u003e Cardiometabolic problems have been associated with indices such as central (visceral) obesity, abdominal circumference, waist-to-hip ratio, and body roundness index. However, in recent years, there has been a stronger demonstration of the relationship between the body's upper subcutaneous fat stores and metabolic indicators. In the majority of studies, NC measurement has been performed in specific disease sample groups, such as T2DM or HT, which are among cardiometabolic diseases, and the results are heterogeneous.\u003csup\u003e\u003cspan additionalcitationids=\"CR13\" citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e\u003c/sup\u003eThe relationship between TG and NC has generally been studied as a secondary outcome in patients with metabolic syndrome and T2DM.\u003csup\u003e\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e,\u003cspan additionalcitationids=\"CR16 CR17 CR18 CR19\" citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e\u003c/sup\u003eIn our study, we compared the measurements of adults with normal and relatively healthy triglyceride measurements with those with hypertriglyceridemia or receiving treatment for it. The present study has demonstrated a robust correlation between triglycerides and neck circumference, thereby substantiating the hypothesis.\u003c/p\u003e\n\u003ch3\u003eStrengths and limitations\u003c/h3\u003e\n\u003cp\u003eThis is the one of few studies focusing on comprehensively evaluation the associations between Triglyceride and antropometric measurements of adult population in our country. Our results highlight the practical application prospect of NC and other basic antropometric measurements in the clinical management of MetS, the group of systemic metabolic disorders.\u003c/p\u003e\u003cp\u003eFurthermore, while the present study was conducted based on the data of plasma indicators and anthropometric measurements were only collected at the baseline. These confounding factors may have been introduced into the analyses by the observational study design and imbalanced baseline clinical characteristics.\u003c/p\u003e"},{"header":"CONCLUSION","content":"\u003cp\u003eIn this study, when comparing waist circumference, hip circumference, body weight and age, the mean values in the case group were significantly higher than those in the control group. However, a significant correlation was found between NC and HTG. In addition to vital signs, anthropometric measurements are an appropriate, non-invasive and cost-effective screening method for determining chronic disease risk in primary care. It can be used as a complementary tool in clinical practice and screening programmes for screening and diagnosis of risk factors for MetS, atherosclerotic CVD, T2DM and survival. As the importance of preventive medicine is more prominent in such chronic diseases, we believe that the follow-up of such simple methods can make a significant contribution to CVD, morbidity and survival. Hypertriglyceridemia is managed by a multidisciplinary team consisting of endocrinologists, gastroenterologists, internal medicine specialists, family physicians and cardiologists. In addition to pharmacological therapy, lifestyle modification, management of comorbidities and patient education are key to treatment.\u003c/p\u003e"},{"header":"Declarations","content":"\u003ch2\u003e\u003cem\u003eData availability statement\u003c/em\u003e\u003c/h2\u003e\n\u003cp\u003eThe original contributions presented in the study are included in the article/supplementary material. Further inquiries can be directed to the corresponding author.\u003c/p\u003e\n\u003ch2\u003e\u003cem\u003eEthics statement\u003c/em\u003e\u003c/h2\u003e\n\u003cp\u003eThe study conducted with Helsinki Declaration and Human ethics. Ethical approval was obtained from the local ethics committee with protocol number E1/3132/2022 prior to the study. Informed consent was obtained from all participants.\u003c/p\u003e\n\u003ch2\u003e\u003cem\u003eAuthor contributions\u003c/em\u003e\u003c/h2\u003e\n\u003cp\u003eÜY designed, interpreted the data, and wrote the manuscript. ÜY collected the data. ÖGS provided the statistical analysis and supervised the article.\u003c/p\u003e\n\u003ch2\u003e\u003cem\u003eFunding Statement\u003c/em\u003e\u003c/h2\u003e\n\u003cp\u003eThe study have not founded.\u0026nbsp;\u003c/p\u003e\n\u003ch2\u003e\u003cem\u003eConflict of interest\u003c/em\u003e\u003c/h2\u003e\n\u003cp\u003eThe authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.\u003c/p\u003e\u003ch2\u003eAcknowledgement\u003c/h2\u003e\u003cp\u003eThe authors thank all team members and participants in the study. In addition, we would like to thank Cenk Aypak, our clinical training supervisor of the hospital.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\u003cli\u003e\u003cspan\u003eOliveira LLH, Assis ACR, Giraldez VZR, Scudeler TL, Soares PR. Dyslipidemia: A narrative review on pharmacotherapy. 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Associations between abdominal obesity indices and diabetic complications: Chinese visceral adiposity index and neck circumference. \u003cem\u003eCardiovascular Diabetology, 19\u003c/em\u003e(1), 118. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1186/s12933-020-01095-4\u003c/span\u003e\u003cspan address=\"10.1186/s12933-020-01095-4\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":true,"highlight":"","institution":"","isAcceptedByJournal":true,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true},"keywords":"Antropometric measurements, Hypertriglyceridemia, Neck Circumference, BMI, Metabolic Syndrome","lastPublishedDoi":"10.21203/rs.3.rs-7406215/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-7406215/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003e\u003cstrong\u003eObjective:\u003c/strong\u003e Anthropometric measurements are considered a applicable and cost-effective indicator in primary healthcare settings for identifying the risk of obesity and related chronic diseases. This study aimed to elucidate the association between hypertriglyceridemia and neck circumference in adults.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eMethods:\u003c/strong\u003e The participants diagnosed with hypertriglyceridemia (HTG) (n=130) and those without HTG (n=130) were assessed in this prospective case-control study. Measurements included body mass index, neck circumference (NC), waist circumference, hip circumference, and various metabolic laboratory parameters.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eResults:\u003c/strong\u003e The case group exhibited significantly higher anthropometric indices (body mass index, NC, waist circumference, and hip circumference) as well as higher age, fasting blood glucose, HbA1c, uric acid, hematocrit, hemoglobin, white blood cell count (WBC), low density lipid cholesterol, and triglyceride (TG) compared to the control group (p\u0026lt;0.05). In the HTG subgroup, the mean neck circumference was 38.1 ± 4.1 cm, whereas in the control subgroup it was 35.7 ± 3.8 cm, with a statistically significant difference between the two groups (p\u0026lt;0.001). NC demonstrated statistically significant positive correlations with waist, hip circumference, and TG (r = 0.593, r = 0.461, r = 0.330, and r = 0.243, respectively; p\u0026lt;0.001 for all).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConclusion:\u003c/strong\u003e Anthropometric measurements like those for neck, waist, and hip circumference correlate positively. This suggests that they can screen for hypertriglyceridemia, a feature of metabolic syndrome.\u003c/p\u003e\n\u003cp\u003e1. What is already known about this topic?\u003c/p\u003e\n\u003cp\u003eAnthropometric indices are simpleand low-cost quantitative measurements well positioned in primary health care, as they facilitate the early diagnosis of cardiometabolic diseases.⁵\u003c/p\u003e\n\u003cp\u003eNeck circumference is a simple, cost-effective and time-saving method to ascertain upper body obesity.Numerous studies have focused on the association between BMI, simple antropometric measurements and hypertension, or metabolic syndrome. However, there is little research investigating the primary effect of high triglycerides.\u003c/p\u003e\n\u003cp\u003e2. What this paper adds: This study demostrated an association between NC and plasma lipid measurements (including TG) with other anthropometric measurements in adults. The study is expected to address research gaps in the area.\u003c/p\u003e\n\u003cp\u003e3. The implications of this paper: Health expenditure in developing countries should be used wisely, exam-based measurements should be preferred for less cost and efficiency focusing on prevention. Rather than frequent blood tests, primary health care services should promote easy body area measurements like neck circumference.\u003c/p\u003e","manuscriptTitle":"Neck Circumference is Associated with Hypertriglysceridemia in adults","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2025-09-02 08:15:28","doi":"10.21203/rs.3.rs-7406215/v1","editorialEvents":[{"type":"communityComments","content":0}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"cf315e2c-f465-4731-b86d-fea57125e104","owner":[],"postedDate":"September 2nd, 2025","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[],"tags":[],"updatedAt":"2025-10-27T16:35:27+00:00","versionOfRecord":{"articleIdentity":"rs-7406215","link":"https://doi.org/10.1007/s40200-025-01761-y","journal":{"identity":"journal-of-diabetes-and-metabolic-disorders","isVorOnly":false,"title":"Journal of Diabetes \u0026 Metabolic Disorders"},"publishedOn":"2025-10-24 16:17:28","publishedOnDateReadable":"October 24th, 2025"},"versionCreatedAt":"2025-09-02 08:15:28","video":"","vorDoi":"10.1007/s40200-025-01761-y","vorDoiUrl":"https://doi.org/10.1007/s40200-025-01761-y","workflowStages":[]},"version":"v1","identity":"rs-7406215","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-7406215","identity":"rs-7406215","version":["v1"]},"buildId":"8U1c8b4HqxoKbykW_rLl7","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}