Predictability of Obesity and Metabolic Syndrome by Neck Circumference in Nigerian Adolescents with Obesity.

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Olukemi T. Bamigboye-Taiwo, Samson Afolabi, Olabamiji Abiodun Ajose, and 1 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-5837003/v1 This work is licensed under a CC BY 4.0 License Status: Under Review Version 1 posted 4 You are reading this latest preprint version Abstract Background Metabolic syndrome is a rapidly emerging global health challenge characterized cardiometabolic risk factors that increase the likelihood of developing cardiovascular disease and type 2 diabetes. While manifesting majorly in adults, evidence suggests these risk factors emerge in childhood. Neck circumference, has shown promise as a simple, inexpensive, and non-invasive screening tool for obesity and related risks in adolescents, though its relationship with metabolic syndrome risk factors remains unclear. Objectives To evaluate the association of neck circumference (NC) with obesity and cardio-metabolic risk factors in Nigerian adolescents with and without obesity. Methods A study was conducted among 250 adolescents aged 10 to 19 years (125 with obesity and 125 without). Anthropometric parameters, blood pressure and pulse rate were measured. Venous samples were obtained for fasting plasma lipids [Total cholesterol (TC), high density lipoprotein – cholesterol (HDL-C), low density lipoprotein – cholesterol (LDL-C), Triglycerides (TG)] and fasting plasma glucose (FPG) estimation. Results There were 24 (19.2%) males and 101 (80.8%) females in each group, giving a male to female ratio of 1: 4.2. Median (SD) age for the adolescents with and without obesity was 15.69 (2.24) and 15.74 (2.25) years respectively. Neck circumference correlated positively with weight ( r = 0.265, p = 0.003), height ( r = 0.222, p = 0.013), and BMI ( r = 0.209, p = 0.019) but not with waist circumference ( r = 0.167, p = 0.063) in adolescents with obesity. There was no relationship between neck circumference and TC, HDL-C, LDL-C, TG, or FPG in either of the two groups of adolescents. Conclusions From this study, neck circumference can predict obesity but not central obesity and other cardiometabolic risks in Nigerian adolescents. Neck circumference obesity metabolic syndrome cardiometabolic risk factors INTRODUCTION Metabolic syndrome (MS) is a rapidly emerging global health challenge and has been defined in adults as a cluster of cardiometabolic risk factors which increase an individual’s chance of developing cardiovascular disease and type 2 diabetes. ( 1 , 2 ). These risk factors include abdominal obesity, dyslipidaemia, hypertension, abnormal glucose metabolism ( 2 ). Although MS was initially reported in adults, it is now evident that the clustering of cardiometabolic risk factors starts much earlier in childhood ( 1 , 3 ). This is due to the rapidly increasing obesity epidemic within this young population ( 2 ). Insulin resistance forms the pathophysiologic basis of MS and is closely associated with obesity ( 4 ). Insulin resistance is a decreased tissue response to cellular actions mediated by insulin which results in significant metabolic dysfunction throughout the body ( 5 ). A number of definitions of MS in children have been put forward by various study and research groups. The application of the different definitions to the same patient cohort have resulted in varying prevalence outcomes ( 6 ). All the definitions share common features which include obesity, (defined by waist circumference or BMI), elevated blood pressure, ‘dyslipidaemia’ (elevated triglycerides and low HDL cholesterol), and abnormal glucose metabolism ( 2 ). Waist circumference (WC) has been used extensively to define central obesity for its correlation to abdominal visceral fat ( 7 ) and is regarded as the fundamental element of MS in several diagnostic criteria ( 8 ). Waist circumference in children is an independent predictor of insulin resistance, lipid levels and blood pressure which are all components of MS ( 9 , 10 ). Despite the widespread use of WC as a means of recognition of obesity and MS, it has its limitations. A standard site of measurement is lacking and different studies have reported various ways to determine the specific site for measuring WC, this may influence the measured WC values ( 11 ). In addition, WC also varies during the course of the day and may be influenced by changes of the abdominal wall and size of the abdominal cavity ( 12 ). The most commonly utilised method to classify overweight and obesity in children and to predict cardiometabolic risk is the body mass index (BMI) ( 13 ). However, BMI is not without its shortcomings. It is regarded as an unsuitable measure of adiposity, because it fails to differentiate between muscle mass and fat mass, and requires the use of calculations and charts which may not be readily available ( 13 , 14 ). Alternative parameters such as the waist-to-hip ratio (WHR) give some indication of fat distribution, but like the waist circumference it has not been accepted as a gold standard measure to identify cardiovascular and metabolic risk ( 15 ) Neck circumference (NC) is a relatively new anthropometric parameter representative of upper-body adiposity and has been reported to be more convenient for screening overweight or obesity ( 14 , 16 ). There is increasing evidence to indicate its ability to effectively diagnose obesity and metabolic syndrome. Recent studies in adults have shown NC to be an independent predictor of metabolic risk and has been found to correlate positively with insulin resistance and central obesity in adults ( 17 ), but few studies have been conducted to determine its association with upper body adiposity and cardio-metabolic risk factors in children and adolescents ( 18 , 19 ) NC is a simple, inexpensive and remains unchanging all through the day ( 20 ). Its usefulness in developing countries where resources are scarce cannot be over- emphasised. Few studies have investigated its performance in Nigerian adolescents hence, this present study in we evaluated the relationship between neck circumference (NC) and obesity, and other cardio-metabolic risk factors using correlation coefficient (r). METHODOLOGY Study design and population This cross-sectional study was conducted between February 2019 to October 2019 in Ile- Ife, Southwest Nigeria. One hundred and twenty -five (125) apparently healthy adolescents aged 10 to 19 years with obesity along with one hundred and twenty- five (125) age- and sex- matched adolescents without obesity were recruited from secondary schools in Ile- Ife. Adolescents with acute or chronic medical illnesses and those who were on medications that could alter body weight, blood pressure, glycaemic levels or lipid profile were excluded from the study. A purposive sampling technique was adopted to select participants into this study. Assessment The study was conducted in the early morning after a 10–12 hour overnight fast. Each participant filled out a study proforma detailing biodata and information on medical history. Physical examination which included measuring of weight, height, waist circumference neck circumference, and blood pressure and pulse rate was done. Body mass index (BMI) was computed using the Quetelet index: BMI = Weight (kg)/ Height (m) 2 ( 22 ). The World Health Organization (WHO) Growth Median body mass index (BMI) -for-age chart (5–19 years) was used to classify the participants into normal BMI (-1 to + 1 SD for age and sex) or obese BMI (> 2SD for age and sex) ( 23 ). The waist circumference (cm) was assessed at the level midpoint between the lower margin of the last palpable rib and the tip of iliac crest using a measuring tape. Measurement was taken at the end of a normal expiration with the participant standing upright. Abdominal obesity was determined by the IDF criteria of > 90th percentile as a cut-off for waist circumference using the waist circumference percentile regression values in the United States for males and females ( 2 , 24 ). Neck circumference was measured using a measuring tape at a point mid- neck height with head erect, eyes facing forward and shoulders relaxed as described by previous studies ( 14 , 25 ). In individuals with laryngeal prominence, the neck circumference was measured just below the prominence ( 25 ). Blood pressure was determined with the OMRON M2 basic blood pressure monitor. Elevated BP according to the IDF criteria for MS in children was systolic blood pressure ≥ 130 mmHg and or diastolic blood pressure ≥ 85 mmHg ( 2 ). Pulse rate was recorded with the same device. Fasting venous samples were obtained after 10- 12hrs overnight fast to determine fasting plasma lipids and plasma glucose levels. Fasting plasma glucose was analysed by glucose oxidase (GOD)/ /glucose peroxidase (POD) method using a commercial glucose RANDOX (GLUC-PAP) kit. HDL-C was measured by precipitation method using the commercially available Refloton HDL Cholesterol strip. Triglycerides was determined by Glycerol phosphate oxidase/ peroxidase method using the commercially available RANDOX kit. Low density lipoproteins cholesterol (LDL-C) was calculated from the Friedwald formula ( 26 ): LDL-C(mmol/l) = TC-HDL-TG/2.2. Ethical Consideration The study was approved by the Ethics and Research Committee of the OAUTHC, Ile- Ife (NHREC/27/02/2009a). Written informed consent from parents/ caregivers of participants was obtained before the study. Confidentiality of participants’ information was ensured by anonymizing data. Data Analysis Data was analysed using statistical package for social sciences (SPSS version 21). Continuous variables were presented as mean, median, standard deviation. Tests of statistical significance between the two groups were done using the independent t-test. The Pearson’s coefficients of correlation ( r ) associated p -values were derived. Statistical significance was expressed as p -value < 0.05 and 95% confidence interval. RESULTS The ages of the participants ranged between 10 and 19 years (Table 1 ). The median (SD) age for the adolescents with obesity was 15.69 (2.24) years while it was 15.74 (2.25) years for the adolescents without obesity. There were 24 (19.2%) males and 101 (80.8%) females in each group, giving a male to female ratio of 1: 4.2 (Table 1 ). Table 1 Age and Sex Distribution of all Participants Obese Non-obese Total χ 2 p value Variable n (%) n (%) N (%) Age (years) 10–15 48 (38.4) 45 (36.0) 93 (37.2) 0.154 0.695 16–19 77 (61.6) 80 (64.0) 157 (62.8) Mean ± SD 15.69 ± 2.24 15.74 ± 2.25 -0.197 0.844 Sex Male 24 (19.2) 24 (19.2) 48 (19.2) 0.000 1.000 Female 101 (80.8) 101 (80.8) 202 (80.8) χ 2 : Chi square test Participants with obesity had significantly higher body weight, waist circumference, hip circumference, neck circumference and BMI than the participants without obesity (Table 2 ). In addition, the mean systolic and diastolic blood pressures were significantly higher in the adolescents with obesity. However, the mean values for the pulse rates and height for both groups were very similar (Table 2 ). Table 2 Anthropometry, Blood Pressure and Pulse Rate of all Participants Obese Non-obese t p value Variable Mean ± SD Mean ± SD Weight (Kg) 84.18 ± 15.70 52.96 ± 7.43 20.094 0.001* Height (m) 1.62 ± 0.08 1.61 ± 0.08 0.920 0.359 BMI (kg/m 2 ) 31.93 ± 4.49 20.36 ± 2.12 26.042 0.001* Waist circumference (cm) 96.14 ± 8.74 72.56 ± 7.57 22.794 0.001* Hip circumference (cm) 112.44 ± 12.90 88.87 ± 10.03 16.122 0.001* Neck circumference (cm) 36.37 ± 7.54 33.56 ± 9.43 2.605 0.010* Pulse rate (beats/min) 81.51 ± 13.50 81.90 ± 13.24 -0.232 0.817 SBP (mmHg) 122.03 ± 13.93 109.82 ± 12.07 7.405 0.001* DBP (mmHg) 76.06 ± 10.22 66.78 ± 9.18 7.550 0.001* t: Independent Samples T test *: Statistically significant (p < 0.05). SBP: Systolic blood pressure. DBP: Diastolic blood pressure. BMI: Body mass index A significant difference was observed in the fasting HDL- C and FPG of the adolescents with and without obesity (Table 3 ). Among the participants with obesity, there was a positive relationship between neck circumference and anthropometric parameters including weight, height, and BMI even though the relationship was not quite strong (Table 4 ). While in the participants without obesity, it was only the waist circumference that demonstrated a relationship with neck circumference. This relationship was negative and weak. Amongst both groups of participants, there was no relationship was demonstrated between neck circumference and any of the laboratory parameters (lipid profile and fasting plasma glucose). Table 3 Fasting Lipid Profile, Plasma Glucose and Uric Acid of all Participants Obese Non-obese Variable Mean ± SD Mean ± SD t p value Total cholesterol (mmol/L) 3.56 ± 0.93 3.55 ± 1.04 0.077 0.939 HDL- C (mmol/L) 0.97 ± 0.28 1.11 ± 0.38 -3.401 0.001* Total triglycerides (mmol/L) 0.82 ± 0.32 0.87 ± 0.20 -1.456 0.147 LDL- C (mmol/L) 2.20 ± 0.95 2.02 ± 0.94 1.504 0.134 FPG (mmol/L) 4.30 ± 0.78 3.95 ± 0.83 3.452 0.001* t : Independent Samples T test HDL- C : High density lipoprotein cholesterol LDL- C Low density lipoprotein cholesterol FBG : Fasting plasma glucose Table 4 Correlation of Neck Circumference with Clinical and Laboratory Parameters in all Participants Obese Non-obese r p value r p value SBP (mmHg) 0.118 0.190 -0.035 0.698 DBP (mmHg) 0.092 0.310 0.011 0.907 Pulse rate (beats/mins) -0.073 0.419 -0.001 0.988 Weight (Kg) 0.265 0.003* 0.087 0.336 Height (cm) 0.222 0.013* -0.020 0.825 BMI (Kg/m 2 ) 0.209 0.019* 0.141 0.117 Waist circumference (cm) 0.167 0.063 -0.260 0.003* Hip circumference (cm) -0.333 < 0.001* -0.596 < 0.001* Total cholesterol (mmol/L) -0.059 0.514 0.143 0.111 HDL-C (mmol/L) -0.110 0.222 0.133 0.139 Total triglyceride (mmol/L) 0.022 0.810 0.003 0.978 LDL- C (mmol/L) -0.035 0.698 0.036 0.690 FPG (mmol/L) -0.114 0.207 -0.035 0.699 Uric acid (µmol/ L) 0.081 0.369 -0.023 0.802 r : Pearson Correlation coefficient; * : p value < 0.05 SBP : Systolic blood pressure DBP : Diastolic blood pressure BMI : Body mass index HDL- C : High density lipoprotein cholesterol LDL- C : Low density lipoprotein cholesterol FPG : Fasting plasma glucose DISCUSSION This present study demonstrated a positive relationship between neck circumference and weight, height and body mass index (BMI) in adolescents with obesity, even though the relationship was not quite strong. In the adolescents without obesity, there was no relationship between these parameters and neck circumference. Significant differences in the weight, BMI, waist circumference, hip circumference, neck circumference, blood pressures (systolic and diastolic), HDL-C and fasting plasma glucose of the adolescents with and without obesity were also noted. In a study of 897 Nigerian adolescents, Igbafe et al ( 27 ) found that neck circumference was able to predict the presence of overweight and obesity. Other researchers have elaborated on the reliability of neck circumference as a screening tool for obesity both in adolescents and in adults ( 28 , 29 , 30 , 31 ). In a meta- analysis, Pei et al ( 32 ) noted that NC was an inadequate tool in screening individuals with central obesity but valuable in screening individuals with overweight/obesity, especially females. A national survey conducted among 23,043 Iranian children reported that in all age groups and genders, NC performed relatively well in classifying participants to overweight, general obesity and abdominal obesity ( 33 ). González-Cortés et al ( 34 ) in a cohort of 548 children and adolescents aged 6–18 years old found that NC was significantly associated with BMI and WC. This was unlike the current study in which there was no demonstrable relationship between neck circumference and waist circumference among adolescents with obesity while it correlated negatively and weakly in the adolescents without obesity. The conflicting outcome of the two studies may be due to the difference in sample sizes of the two studies and the age groups studied. The combination of these reports alongside ours shows that NC accurately predicts adiposity may likely be an indicator of upper body fat distribution ( 25 ). In addition, it may become an ideal screening method particularly for obesity-related chronic diseases. It is believed NC has the extra advantage of being a more convenient measure than other parameters that indicate fatness such as the waist circumference, waist over hip ratio (WHR) ( 25 ). The neck is often without covering by clothing thus making it readily accessible for measurements. Neck circumference measurements are less intrusive and less cumbersome than those of WC and BMI. The role of NC as a community-based screening tool among adolescents should be further explored to establish its validity in identifying obesity and overweight. A larger study among Nigerian adolescents would be required to further establish the relationship between NC and adiposity and also to determine the optimal cut-off points of NC for diagnosing obesity and overweight in Nigerian adolescents`. In this study we found no relationship between neck circumference and any of the clinical and laboratory risk factors for metabolic syndrome including the blood pressure (systolic and diastolic), fasting plasma glucose and fasting lipid profile in adolescents with and without obesity. Even though there was a negative correlation with HDL-C in both groups of adolescents. This was unlike the findings of Gomez-Arbelaez et al ( 14 ), in a study of 669 school children, aged 8–14, they reported that NC was correlated positively with fasting plasma glucose and triglycerides and systolic and diastolic blood pressure, and negatively with HDL-C ( 27 ). The strength of their study was the large population of children they studied. In a fairly recent meta- analysis to determine the association of NC and cardio metabolic risk factors, Ataie-Jafari et al ( 35 ) reported that among children, NC was positively related to fasting blood sugar, total triglycerides, and total cholesterol levels but not with LDL- C. However, the authors advised that the findings should be interpreted with caution due to high heterogeneity of the study population. Shirley et al ( 36 ) assessed NC and BMI with cardiometabolic parameters in 371, 5-8-year-old Brazilian children, they reported that NC was significantly associated with SBP and but not DBP, HDL-C, LDL-C, or triglycerides. Castro-Piñero et al in a study of 2198 students in Spain found that NC was positively associated with SBP, DBP, TC/ HDL-c, TG. It does appear that there are still varied reports on the predictability of metabolic risk factors by neck circumference. These discrepancies suggest that large scale studies on various child and adolescent age groups, possibly across centres and nations, are required in order to conclude on the ability of neck circumference to predict specific metabolic risk factors/ metabolic syndrome in children. CONCLUSION This study highlights the potential of neck circumference (NC) as a convenient, inexpensive, and non-invasive anthropometric tool for screening obesity and overweight in adolescents, particularly in resource-limited settings like Nigeria. The findings demonstrated a positive association was observed between NC and anthropometric measures such as weight, height, and BMI in adolescents with obesity, supporting its role as an indicator of adiposity. However, no significant relationship was found between NC and clinical or laboratory markers of metabolic syndrome, highlighting limitations in its ability to predict cardiometabolic risk factors. These findings emphasize the need for further large-scale, multi-centre studies to establish population-specific NC cut-off points and evaluate its utility as a screening tool for obesity-related metabolic disorders in diverse paediatric populations. Declarations Ethics approval and consent to participate: Ethics approval was obtained from the Ethics and Research Committee of the OAUTHC, Ile-Ife (NHREC/27/02/2009a), and written informed consent was obtained from parents/caregivers of participants. Consent for publication: Not applicable. Competing interests: The authors declare no competing interests. Funding: No financial support was received for this study. Author Contribution B.O contributed to the conception and design of the work. All authors contributed to the acquisition, analysis and interpretation of data. The first draft of the manuscript was written and revised critically for important intellectual content by all the authors. All the authors agree to be accountable for all aspects of the work in ensuring that questions related to the accuracy or integrity of any part of the work are appropriately investigated and resolved. Acknowledgement We acknowledge the participants, their families, and staffs for their cooperation in ensuring the completion of the project. Availability of data and material: Data supporting the findings are available upon reasonable request. References Agirbasli M, Tanrikulu AM. GS Berenson Metabolic Syndrome: Bridging the Gap from Childhood to Adulthood. Cardiovasc Ther. 2016;34:30–6. The IDF consensus definition of the metabolic syndrome in children and adolescents, Alberti G, Zimmet P, Kaufman F, Tajima N, Silink M, Arslanian S, Wong G, Bennett P, Shaw J, Caprio S. International Diabetes Federation, 2007ISBN 2-930229-49-7. Webber LS, Osganian V, Luepker RV, et al. Cardiovascular risk factors among third grade children in four regions of the United States. 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Evaluation of neck circumference as a predictor of elevated cardiometabolic risk outcomes in 5–8-year-old Brazilian children. Child Adolesc Obes CHAO. 2019;3(1):1–19. https://doi.org/10.1080/2574254X.2020.1738837 . Castro-Piñero J, Delgado-Alfonso A, Gracia-Marco L, Gómez-Martínez S, Esteban-Cornejo I, Veiga OL, Marcos A, Segura-Jiménez V, The, UP&DOWN Study Group. Neck circumference and clustered cardiovascular risk factors in children and adolescents: cross-sectional study. BMJ Open. 2017;7:e016048. 10.1136/bmjopen-2017-016048 . Additional Declarations No competing interests reported. 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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-5837003","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":408680490,"identity":"6cc7931a-2c05-48ba-98fc-62d83ebb823a","order_by":0,"name":"Olukemi T. Bamigboye-Taiwo","email":"","orcid":"","institution":"Department of Paediatrics, Obafemi Awolowo University Teaching Hospitals Complex/ Obafemi Awolowo University","correspondingAuthor":false,"prefix":"","firstName":"Olukemi","middleName":"T.","lastName":"Bamigboye-Taiwo","suffix":""},{"id":408680491,"identity":"532b4660-4530-4851-89cc-9d9bc4acf9d8","order_by":1,"name":"Samson Afolabi","email":"data:image/png;base64,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","orcid":"","institution":"Department of Paediatrics, Obafemi Awolowo University Teaching Hospitals Complex/ Obafemi Awolowo University","correspondingAuthor":true,"prefix":"","firstName":"Samson","middleName":"","lastName":"Afolabi","suffix":""},{"id":408680492,"identity":"e005cfb3-443c-495d-ad65-e6bf8737b0ee","order_by":2,"name":"Olabamiji Abiodun Ajose","email":"","orcid":"","institution":"Department of Chemical Pathology, Obafemi Awolowo University Teaching Hospitals Complex/ Obafemi Awolowo University","correspondingAuthor":false,"prefix":"","firstName":"Olabamiji","middleName":"Abiodun","lastName":"Ajose","suffix":""},{"id":408680493,"identity":"c333a5b9-df3d-4aa5-b511-5a17d1acfdbd","order_by":3,"name":"O Ogunlade","email":"","orcid":"","institution":"Department of Internal Medicine, Obafemi Awolowo University Teaching Hospitals Complex","correspondingAuthor":false,"prefix":"","firstName":"O","middleName":"","lastName":"Ogunlade","suffix":""}],"badges":[],"createdAt":"2025-01-15 20:08:12","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-5837003/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-5837003/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":75065251,"identity":"cec2f793-3d0f-447f-9387-258c99590f15","added_by":"auto","created_at":"2025-01-30 05:37:39","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":667752,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-5837003/v1/88f878c6-421a-4815-b215-30701154a5be.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"Predictability of Obesity and Metabolic Syndrome by Neck Circumference in Nigerian Adolescents with Obesity.","fulltext":[{"header":"INTRODUCTION","content":"\u003cp\u003eMetabolic syndrome (MS) is a rapidly emerging global health challenge and has been defined in adults as a cluster of cardiometabolic risk factors which increase an individual\u0026rsquo;s chance of developing cardiovascular disease and type 2 diabetes. (\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e, \u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e). These risk factors include abdominal obesity, dyslipidaemia, hypertension, abnormal glucose metabolism (\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eAlthough MS was initially reported in adults, it is now evident that the clustering of cardiometabolic risk factors starts much earlier in childhood (\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e, \u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e). This is due to the rapidly increasing obesity epidemic within this young population (\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e). Insulin resistance forms the pathophysiologic basis of MS and is closely associated with obesity (\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e). Insulin resistance is a decreased tissue response to cellular actions mediated by insulin which results in significant metabolic dysfunction throughout the body (\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eA number of definitions of MS in children have been put forward by various study and research groups. The application of the different definitions to the same patient cohort have resulted in varying prevalence outcomes (\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e). All the definitions share common features which include obesity, (defined by waist circumference or BMI), elevated blood pressure, \u0026lsquo;dyslipidaemia\u0026rsquo; (elevated triglycerides and low HDL cholesterol), and abnormal glucose metabolism (\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e). Waist circumference (WC) has been used extensively to define central obesity for its correlation to abdominal visceral fat (\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e) and is regarded as the fundamental element of MS in several diagnostic criteria (\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e). Waist circumference in children is an independent predictor of insulin resistance, lipid levels and blood pressure which are all components of MS (\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e, \u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e). Despite the widespread use of WC as a means of recognition of obesity and MS, it has its limitations. A standard site of measurement is lacking and different studies have reported various ways to determine the specific site for measuring WC, this may influence the measured WC values (\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e). In addition, WC also varies during the course of the day and may be influenced by changes of the abdominal wall and size of the abdominal cavity (\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eThe most commonly utilised method to classify overweight and obesity in children and to predict cardiometabolic risk is the body mass index (BMI) (\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e). However, BMI is not without its shortcomings. It is regarded as an unsuitable measure of adiposity, because it fails to differentiate between muscle mass and fat mass, and requires the use of calculations and charts which may not be readily available (\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e, \u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eAlternative parameters such as the waist-to-hip ratio (WHR) give some indication of fat distribution, but like the waist circumference it has not been accepted as a gold standard measure to identify cardiovascular and metabolic risk (\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e)\u003c/p\u003e \u003cp\u003eNeck circumference (NC) is a relatively new anthropometric parameter representative of upper-body adiposity and has been reported to be more convenient for screening overweight or obesity (\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e, \u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e). There is increasing evidence to indicate its ability to effectively diagnose obesity and metabolic syndrome.\u003c/p\u003e \u003cp\u003eRecent studies in adults have shown NC to be an independent predictor of metabolic risk and has been found to correlate positively with insulin resistance and central obesity in adults (\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e), but few studies have been conducted to determine its association with upper body adiposity and cardio-metabolic risk factors in children and adolescents (\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e, \u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e)\u003c/p\u003e \u003cp\u003eNC is a simple, inexpensive and remains unchanging all through the day (\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e). Its usefulness in developing countries where resources are scarce cannot be over- emphasised. Few studies have investigated its performance in Nigerian adolescents hence, this present study in we evaluated the relationship between neck circumference (NC) and obesity, and other cardio-metabolic risk factors using correlation coefficient (r).\u003c/p\u003e"},{"header":"METHODOLOGY","content":"\u003cp\u003eStudy design and population\u003c/p\u003e \u003cp\u003eThis cross-sectional study was conducted between February 2019 to October 2019 in Ile- Ife, Southwest Nigeria. One hundred and twenty -five (125) apparently healthy adolescents aged 10 to 19 years with obesity along with one hundred and twenty- five (125) age- and sex- matched adolescents without obesity were recruited from secondary schools in Ile- Ife. Adolescents with acute or chronic medical illnesses and those who were on medications that could alter body weight, blood pressure, glycaemic levels or lipid profile were excluded from the study. A purposive sampling technique was adopted to select participants into this study.\u003c/p\u003e \u003cp\u003eAssessment\u003c/p\u003e \u003cp\u003eThe study was conducted in the early morning after a 10\u0026ndash;12 hour overnight fast. Each participant filled out a study proforma detailing biodata and information on medical history. Physical examination which included measuring of weight, height, waist circumference neck circumference, and blood pressure and pulse rate was done. Body mass index (BMI) was computed using the Quetelet index: BMI\u0026thinsp;=\u0026thinsp;Weight (kg)/ Height (m)\u003csup\u003e2\u003c/sup\u003e (\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e). The World Health Organization (WHO) Growth Median body mass index (BMI) -for-age chart (5\u0026ndash;19 years) was used to classify the participants into normal BMI (-1 to +\u0026thinsp;1 SD for age and sex) or obese BMI (\u0026gt;\u0026thinsp;2SD for age and sex) (\u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e). The waist circumference (cm) was assessed at the level midpoint between the lower margin of the last palpable rib and the tip of iliac crest using a measuring tape. Measurement was taken at the end of a normal expiration with the participant standing upright. Abdominal obesity was determined by the IDF criteria of \u0026gt;\u0026thinsp;90th percentile as a cut-off for waist circumference using the waist circumference percentile regression values in the United States for males and females (\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e, \u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e). Neck circumference was measured using a measuring tape at a point mid- neck height with head erect, eyes facing forward and shoulders relaxed as described by previous studies (\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e, \u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e). In individuals with laryngeal prominence, the neck circumference was measured just below the prominence (\u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e). Blood pressure was determined with the OMRON M2 basic blood pressure monitor. Elevated BP according to the IDF criteria for MS in children was systolic blood pressure\u0026thinsp;\u0026ge;\u0026thinsp;130 mmHg and or diastolic blood pressure\u0026thinsp;\u0026ge;\u0026thinsp;85 mmHg (\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e). Pulse rate was recorded with the same device. Fasting venous samples were obtained after 10- 12hrs overnight fast to determine fasting plasma lipids and plasma glucose levels. Fasting plasma glucose was analysed by glucose oxidase (GOD)/ /glucose peroxidase (POD) method using a commercial glucose RANDOX (GLUC-PAP) kit. HDL-C was measured by precipitation method using the commercially available Refloton HDL Cholesterol strip. Triglycerides was determined by Glycerol phosphate oxidase/ peroxidase method using the commercially available RANDOX kit. Low density lipoproteins cholesterol (LDL-C) was calculated from the Friedwald formula (\u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e):\u003c/p\u003e \u003cp\u003eLDL-C(mmol/l)\u0026thinsp;=\u0026thinsp;TC-HDL-TG/2.2.\u003c/p\u003e \u003cp\u003eEthical Consideration\u003c/p\u003e \u003cp\u003e The study was approved by the Ethics and Research Committee of the OAUTHC, Ile- Ife (NHREC/27/02/2009a). Written informed consent from parents/ caregivers of participants was obtained before the study. Confidentiality of participants\u0026rsquo; information was ensured by anonymizing data.\u003c/p\u003e \u003cdiv id=\"Sec3\" class=\"Section2\"\u003e \u003ch2\u003eData Analysis\u003c/h2\u003e \u003cp\u003eData was analysed using statistical package for social sciences (SPSS version 21). Continuous variables were presented as mean, median, standard deviation. Tests of statistical significance between the two groups were done using the independent t-test. The Pearson\u0026rsquo;s coefficients of correlation (\u003cem\u003er\u003c/em\u003e) associated \u003cem\u003ep\u003c/em\u003e-values were derived. Statistical significance was expressed as \u003cem\u003ep\u003c/em\u003e-value\u0026thinsp;\u0026lt;\u0026thinsp;0.05 and 95% confidence interval.\u003c/p\u003e \u003c/div\u003e"},{"header":"RESULTS","content":"\u003cp\u003eThe ages of the participants ranged between 10 and 19 years (Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e). The median (SD) age for the adolescents with obesity was 15.69 (2.24) years while it was 15.74 (2.25) years for the adolescents without obesity. There were 24 (19.2%) males and 101 (80.8%) females in each group, giving a male to female ratio of 1: 4.2 (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\u003eAge and Sex Distribution of all Participants\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"6\"\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=\"char\" char=\".\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eObese\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eNon-obese\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eTotal\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eχ\u003csup\u003e2\u003c/sup\u003e\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003e\u003cem\u003ep\u003c/em\u003e value\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eVariable\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cb\u003en (%)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cb\u003en (%)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003eN (%)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAge (years)\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 \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e10\u0026ndash;15\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e48 (38.4)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e45 (36.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e93 (37.2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.154\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.695\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e16\u0026ndash;19\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e77 (61.6)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e80 (64.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e157 (62.8)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMean\u0026thinsp;\u0026plusmn;\u0026thinsp;SD\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e15.69\u0026thinsp;\u0026plusmn;\u0026thinsp;2.24\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e15.74\u0026thinsp;\u0026plusmn;\u0026thinsp;2.25\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e-0.197\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.844\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSex\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 \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\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\u003e24 (19.2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e24 (19.2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e48 (19.2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.000\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e1.000\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\u003e101 (80.8)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e101 (80.8)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e202 (80.8)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003ctfoot\u003e \u003ctr\u003e\u003ctd colspan=\"6\"\u003e\u003cb\u003eχ\u003c/b\u003e\u003csup\u003e\u003cb\u003e2\u003c/b\u003e\u003c/sup\u003e: Chi square test\u003c/td\u003e\u003c/tr\u003e \u003c/tfoot\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003eParticipants with obesity had significantly higher body weight, waist circumference, hip circumference, neck circumference and BMI than the participants without obesity (Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e). In addition, the mean systolic and diastolic blood pressures were significantly higher in the adolescents with obesity. However, the mean values for the pulse rates and height for both groups were very similar (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\u003eAnthropometry, Blood Pressure and Pulse Rate of all Participants\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"5\"\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=\"char\" char=\".\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eObese\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eNon-obese\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003et\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u003cem\u003ep\u003c/em\u003e value\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eVariable\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cb\u003eMean\u0026thinsp;\u0026plusmn;\u0026thinsp;SD\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cb\u003eMean\u0026thinsp;\u0026plusmn;\u0026thinsp;SD\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eWeight (Kg)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e84.18\u0026thinsp;\u0026plusmn;\u0026thinsp;15.70\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e52.96\u0026thinsp;\u0026plusmn;\u0026thinsp;7.43\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e20.094\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.001*\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHeight (m)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1.62\u0026thinsp;\u0026plusmn;\u0026thinsp;0.08\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1.61\u0026thinsp;\u0026plusmn;\u0026thinsp;0.08\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.920\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.359\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eBMI (kg/m\u003csup\u003e2\u003c/sup\u003e)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e31.93\u0026thinsp;\u0026plusmn;\u0026thinsp;4.49\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e20.36\u0026thinsp;\u0026plusmn;\u0026thinsp;2.12\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e26.042\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.001*\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eWaist circumference (cm)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e96.14\u0026thinsp;\u0026plusmn;\u0026thinsp;8.74\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e72.56\u0026thinsp;\u0026plusmn;\u0026thinsp;7.57\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e22.794\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.001*\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHip circumference (cm)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e112.44\u0026thinsp;\u0026plusmn;\u0026thinsp;12.90\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e88.87\u0026thinsp;\u0026plusmn;\u0026thinsp;10.03\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e16.122\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.001*\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNeck circumference (cm)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e36.37\u0026thinsp;\u0026plusmn;\u0026thinsp;7.54\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e33.56\u0026thinsp;\u0026plusmn;\u0026thinsp;9.43\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e2.605\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.010*\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePulse rate (beats/min)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e81.51\u0026thinsp;\u0026plusmn;\u0026thinsp;13.50\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e81.90\u0026thinsp;\u0026plusmn;\u0026thinsp;13.24\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e-0.232\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.817\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSBP (mmHg)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e122.03\u0026thinsp;\u0026plusmn;\u0026thinsp;13.93\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e109.82\u0026thinsp;\u0026plusmn;\u0026thinsp;12.07\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e7.405\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.001*\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eDBP (mmHg)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e76.06\u0026thinsp;\u0026plusmn;\u0026thinsp;10.22\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e66.78\u0026thinsp;\u0026plusmn;\u0026thinsp;9.18\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e7.550\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.001*\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\u003e \u003cb\u003et: Independent Samples T test\u003c/b\u003e *: Statistically significant (p\u0026thinsp;\u0026lt;\u0026thinsp;0.05).\u003c/p\u003e \u003cp\u003eSBP: Systolic blood pressure. DBP: Diastolic blood pressure. BMI: Body mass index\u003c/p\u003e \u003cp\u003eA significant difference was observed in the fasting HDL- C and FPG of the adolescents with and without obesity (Table\u0026nbsp;\u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e3\u003c/span\u003e). Among the participants with obesity, there was a positive relationship between neck circumference and anthropometric parameters including weight, height, and BMI even though the relationship was not quite strong (Table\u0026nbsp;\u003cspan refid=\"Tab4\" class=\"InternalRef\"\u003e4\u003c/span\u003e). While in the participants without obesity, it was only the waist circumference that demonstrated a relationship with neck circumference. This relationship was negative and weak. Amongst both groups of participants, there was no relationship was demonstrated between neck circumference and any of the laboratory parameters (lipid profile and fasting plasma glucose).\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\u003eFasting Lipid Profile, Plasma Glucose and Uric Acid of all Participants\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"5\"\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 \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eObese\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eNon-obese\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eVariable\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cb\u003eMean\u0026thinsp;\u0026plusmn;\u0026thinsp;SD\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cb\u003eMean\u0026thinsp;\u0026plusmn;\u0026thinsp;SD\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003et\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u003cem\u003ep\u003c/em\u003e value\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eTotal cholesterol (mmol/L)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e3.56\u0026thinsp;\u0026plusmn;\u0026thinsp;0.93\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e3.55\u0026thinsp;\u0026plusmn;\u0026thinsp;1.04\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.077\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.939\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHDL- C (mmol/L)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.97\u0026thinsp;\u0026plusmn;\u0026thinsp;0.28\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1.11\u0026thinsp;\u0026plusmn;\u0026thinsp;0.38\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-3.401\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.001*\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eTotal triglycerides (mmol/L)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.82\u0026thinsp;\u0026plusmn;\u0026thinsp;0.32\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.87\u0026thinsp;\u0026plusmn;\u0026thinsp;0.20\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-1.456\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.147\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eLDL- C (mmol/L)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e2.20\u0026thinsp;\u0026plusmn;\u0026thinsp;0.95\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e2.02\u0026thinsp;\u0026plusmn;\u0026thinsp;0.94\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1.504\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.134\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eFPG (mmol/L)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e4.30\u0026thinsp;\u0026plusmn;\u0026thinsp;0.78\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e3.95\u0026thinsp;\u0026plusmn;\u0026thinsp;0.83\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e3.452\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.001*\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003ctfoot\u003e \u003ctr\u003e\u003ctd colspan=\"5\"\u003e\u003cb\u003et\u003c/b\u003e: Independent Samples T test\u003c/td\u003e\u003c/tr\u003e \u003ctr\u003e\u003ctd colspan=\"5\"\u003e\u003cb\u003eHDL- C\u003c/b\u003e: High density lipoprotein cholesterol\u003c/td\u003e\u003c/tr\u003e \u003ctr\u003e\u003ctd colspan=\"5\"\u003e\u003cb\u003eLDL- C\u003c/b\u003e Low density lipoprotein cholesterol\u003c/td\u003e\u003c/tr\u003e \u003ctr\u003e\u003ctd colspan=\"5\"\u003e\u003cb\u003eFBG\u003c/b\u003e: Fasting plasma glucose\u003c/td\u003e\u003c/tr\u003e \u003c/tfoot\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab4\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 4\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eCorrelation of Neck Circumference with Clinical and Laboratory Parameters in all Participants\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"5\"\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 \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colspan=\"2\" nameend=\"c3\" namest=\"c2\"\u003e \u003cp\u003eObese\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"2\" nameend=\"c5\" namest=\"c4\"\u003e \u003cp\u003eNon-obese\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cb\u003er\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cb\u003ep\u003c/b\u003e \u003cb\u003evalue\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003er\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u003cem\u003ep\u003c/em\u003e value\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSBP (mmHg)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.118\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.190\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-0.035\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.698\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eDBP (mmHg)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.092\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.310\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.011\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.907\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePulse rate (beats/mins)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e-0.073\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.419\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.988\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eWeight (Kg)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.265\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\u003e0.087\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.336\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHeight (cm)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.222\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.013*\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-0.020\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.825\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eBMI (Kg/m\u003csup\u003e2\u003c/sup\u003e)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.209\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.019*\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.141\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.117\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eWaist circumference (cm)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.167\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.063\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-0.260\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.003*\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHip circumference (cm)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e-0.333\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-0.596\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\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\u003eTotal cholesterol (mmol/L)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e-0.059\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.514\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.143\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.111\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHDL-C (mmol/L)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e-0.110\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.222\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.133\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.139\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eTotal triglyceride (mmol/L)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.022\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.810\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.003\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.978\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eLDL- C (mmol/L)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e-0.035\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.698\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.036\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.690\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eFPG (mmol/L)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e-0.114\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.207\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-0.035\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.699\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eUric acid (\u0026micro;mol/ L)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.081\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.369\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-0.023\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.802\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003ctfoot\u003e \u003ctr\u003e\u003ctd colspan=\"5\"\u003e\u003cb\u003er\u003c/b\u003e: Pearson Correlation coefficient;\u003c/td\u003e\u003c/tr\u003e \u003ctr\u003e\u003ctd colspan=\"5\"\u003e\u003cb\u003e*\u003c/b\u003e: \u003cem\u003ep\u003c/em\u003e value\u0026thinsp;\u0026lt;\u0026thinsp;0.05\u003c/td\u003e\u003c/tr\u003e \u003ctr\u003e\u003ctd colspan=\"5\"\u003e\u003cb\u003eSBP\u003c/b\u003e: Systolic blood pressure\u003c/td\u003e\u003c/tr\u003e \u003ctr\u003e\u003ctd colspan=\"5\"\u003e\u003cb\u003eDBP\u003c/b\u003e: Diastolic blood pressure\u003c/td\u003e\u003c/tr\u003e \u003ctr\u003e\u003ctd colspan=\"5\"\u003e\u003cb\u003eBMI\u003c/b\u003e: Body mass index\u003c/td\u003e\u003c/tr\u003e \u003ctr\u003e\u003ctd colspan=\"5\"\u003e\u003cb\u003eHDL- C\u003c/b\u003e: High density lipoprotein cholesterol\u003c/td\u003e\u003c/tr\u003e \u003ctr\u003e\u003ctd colspan=\"5\"\u003e\u003cb\u003eLDL- C\u003c/b\u003e: Low density lipoprotein cholesterol\u003c/td\u003e\u003c/tr\u003e \u003ctr\u003e\u003ctd colspan=\"5\"\u003e\u003cb\u003eFPG\u003c/b\u003e: Fasting plasma glucose\u003c/td\u003e\u003c/tr\u003e \u003c/tfoot\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e"},{"header":"DISCUSSION","content":"\u003cp\u003eThis present study demonstrated a positive relationship between neck circumference and weight, height and body mass index (BMI) in adolescents with obesity, even though the relationship was not quite strong. In the adolescents without obesity, there was no relationship between these parameters and neck circumference. Significant differences in the weight, BMI, waist circumference, hip circumference, neck circumference, blood pressures (systolic and diastolic), HDL-C and fasting plasma glucose of the adolescents with and without obesity were also noted.\u003c/p\u003e \u003cp\u003eIn a study of 897 Nigerian adolescents, Igbafe et al (\u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e) found that neck circumference was able to predict the presence of overweight and obesity. Other researchers have elaborated on the reliability of neck circumference as a screening tool for obesity both in adolescents and in adults (\u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e, \u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e29\u003c/span\u003e, \u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e30\u003c/span\u003e, \u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e31\u003c/span\u003e). In a meta- analysis, Pei et al (\u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e32\u003c/span\u003e) noted that NC was an inadequate tool in screening individuals with central obesity but valuable in screening individuals with overweight/obesity, especially females. A national survey conducted among 23,043 Iranian children reported that in all age groups and genders, NC performed relatively well in classifying participants to overweight, general obesity and abdominal obesity (\u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e33\u003c/span\u003e). Gonz\u0026aacute;lez-Cort\u0026eacute;s et al (\u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e34\u003c/span\u003e) in a cohort of 548 children and adolescents aged 6\u0026ndash;18 years old found that NC was significantly associated with BMI and WC. This was unlike the current study in which there was no demonstrable relationship between neck circumference and waist circumference among adolescents with obesity while it correlated negatively and weakly in the adolescents without obesity. The conflicting outcome of the two studies may be due to the difference in sample sizes of the two studies and the age groups studied. The combination of these reports alongside ours shows that NC accurately predicts adiposity may likely be an indicator of upper body fat distribution (\u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e). In addition, it may become an ideal screening method particularly for obesity-related chronic diseases. It is believed NC has the extra advantage of being a more convenient measure than other parameters that indicate fatness such as the waist circumference, waist over hip ratio (WHR) (\u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e). The neck is often without covering by clothing thus making it readily accessible for measurements. Neck circumference measurements are less intrusive and less cumbersome than those of WC and BMI. The role of NC as a community-based screening tool among adolescents should be further explored to establish its validity in identifying obesity and overweight. A larger study among Nigerian adolescents would be required to further establish the relationship between NC and adiposity and also to determine the optimal cut-off points of NC for diagnosing obesity and overweight in Nigerian adolescents`.\u003c/p\u003e \u003cp\u003eIn this study we found no relationship between neck circumference and any of the clinical and laboratory risk factors for metabolic syndrome including the blood pressure (systolic and diastolic), fasting plasma glucose and fasting lipid profile in adolescents with and without obesity. Even though there was a negative correlation with HDL-C in both groups of adolescents. This was unlike the findings of Gomez-Arbelaez et al (\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e), in a study of 669 school children, aged 8\u0026ndash;14, they reported that NC was correlated positively with fasting plasma glucose and triglycerides and systolic and diastolic blood pressure, and negatively with HDL-C (\u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e). The strength of their study was the large population of children they studied. In a fairly recent meta- analysis to determine the association of NC and cardio metabolic risk factors, Ataie-Jafari et al (\u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e35\u003c/span\u003e) reported that among children, NC was positively related to fasting blood sugar, total triglycerides, and total cholesterol levels but not with LDL- C. However, the authors advised that the findings should be interpreted with caution due to high heterogeneity of the study population.\u003c/p\u003e \u003cp\u003eShirley et al (\u003cspan citationid=\"CR36\" class=\"CitationRef\"\u003e36\u003c/span\u003e) assessed NC and BMI with cardiometabolic parameters in 371, 5-8-year-old Brazilian children, they reported that NC was significantly associated with SBP and but not DBP, HDL-C, LDL-C, or triglycerides. Castro-Pi\u0026ntilde;ero et al in a study of 2198 students in Spain found that NC was positively associated with SBP, DBP, TC/ HDL-c, TG. It does appear that there are still varied reports on the predictability of metabolic risk factors by neck circumference. These discrepancies suggest that large scale studies on various child and adolescent age groups, possibly across centres and nations, are required in order to conclude on the ability of neck circumference to predict specific metabolic risk factors/ metabolic syndrome in children.\u003c/p\u003e"},{"header":"CONCLUSION","content":"\u003cp\u003eThis study highlights the potential of neck circumference (NC) as a convenient, inexpensive, and non-invasive anthropometric tool for screening obesity and overweight in adolescents, particularly in resource-limited settings like Nigeria. The findings demonstrated a positive association was observed between NC and anthropometric measures such as weight, height, and BMI in adolescents with obesity, supporting its role as an indicator of adiposity. However, no significant relationship was found between NC and clinical or laboratory markers of metabolic syndrome, highlighting limitations in its ability to predict cardiometabolic risk factors. These findings emphasize the need for further large-scale, multi-centre studies to establish population-specific NC cut-off points and evaluate its utility as a screening tool for obesity-related metabolic disorders in diverse paediatric populations.\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eEthics approval and consent to participate:\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eEthics approval was obtained from the Ethics and Research Committee of the OAUTHC, Ile-Ife (NHREC/27/02/2009a), and written informed consent was obtained from parents/caregivers of participants.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConsent for publication:\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eNot applicable.\u003c/p\u003e\n\u003ch2\u003eCompeting interests:\u003c/h2\u003e\n\u003cp\u003eThe authors declare no competing interests.\u003c/p\u003e\n\u003ch2\u003eFunding:\u003c/h2\u003e\n\u003cp\u003eNo financial support was received for this study.\u003c/p\u003e\n\u003ch2\u003eAuthor Contribution\u003c/h2\u003e\n\u003cp\u003eB.O contributed to the conception and design of the work. All authors contributed to the acquisition, analysis and interpretation of data. The first draft of the manuscript was written and revised critically for important intellectual content by all the authors. All the authors agree to be accountable for all aspects of the work in ensuring that questions related to the accuracy or integrity of any part of the work are appropriately investigated and resolved.\u003c/p\u003e\n\u003ch2\u003eAcknowledgement\u003c/h2\u003e\n\u003cp\u003eWe acknowledge the participants, their families, and staffs for their cooperation in ensuring the completion of the project.\u003c/p\u003e\n\u003ch2\u003eAvailability of data and material:\u003c/h2\u003e\n\u003cp\u003eData supporting the findings are available upon reasonable request.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\u003cli\u003e\u003cspan\u003eAgirbasli M, Tanrikulu AM. GS Berenson Metabolic Syndrome: Bridging the Gap from Childhood to Adulthood. 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Child Adolesc Obes CHAO. 2019;3(1):1\u0026ndash;19. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1080/2574254X.2020.1738837\u003c/span\u003e\u003cspan address=\"10.1080/2574254X.2020.1738837\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eCastro-Pi\u0026ntilde;ero J, Delgado-Alfonso A, Gracia-Marco L, G\u0026oacute;mez-Mart\u0026iacute;nez S, Esteban-Cornejo I, Veiga OL, Marcos A, Segura-Jim\u0026eacute;nez V, The, UP\u0026amp;DOWN Study Group. Neck circumference and clustered cardiovascular risk factors in children and adolescents: cross-sectional study. BMJ Open. 2017;7:e016048. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1136/bmjopen-2017-016048\u003c/span\u003e\u003cspan address=\"10.1136/bmjopen-2017-016048\" 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":false,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"bmc-cardiovascular-disorders","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"bcar","sideBox":"Learn more about [BMC Cardiovascular Disorders](http://bmccardiovascdisord.biomedcentral.com/)","snPcode":"","submissionUrl":"https://www.editorialmanager.com/bcar/default.aspx","title":"BMC Cardiovascular Disorders","twitterHandle":"BMC_series","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"em","reportingPortfolio":"BMC Series","inReviewEnabled":true,"inReviewRevisionsEnabled":true},"keywords":"Neck circumference, obesity, metabolic syndrome, cardiometabolic risk factors","lastPublishedDoi":"10.21203/rs.3.rs-5837003/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-5837003/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003ch2\u003eBackground\u003c/h2\u003e \u003cp\u003eMetabolic syndrome is a rapidly emerging global health challenge characterized cardiometabolic risk factors that increase the likelihood of developing cardiovascular disease and type 2 diabetes. While manifesting majorly in adults, evidence suggests these risk factors emerge in childhood. Neck circumference, has shown promise as a simple, inexpensive, and non-invasive screening tool for obesity and related risks in adolescents, though its relationship with metabolic syndrome risk factors remains unclear.\u003c/p\u003e\u003ch2\u003eObjectives\u003c/h2\u003e \u003cp\u003eTo evaluate the association of neck circumference (NC) with obesity and cardio-metabolic risk factors in Nigerian adolescents with and without obesity.\u003c/p\u003e\u003ch2\u003eMethods\u003c/h2\u003e \u003cp\u003eA study was conducted among 250 adolescents aged 10 to 19 years (125 with obesity and 125 without). Anthropometric parameters, blood pressure and pulse rate were measured. Venous samples were obtained for fasting plasma lipids [Total cholesterol (TC), high density lipoprotein \u0026ndash; cholesterol (HDL-C), low density lipoprotein \u0026ndash; cholesterol (LDL-C), Triglycerides (TG)] and fasting plasma glucose (FPG) estimation.\u003c/p\u003e\u003ch2\u003eResults\u003c/h2\u003e \u003cp\u003eThere were 24 (19.2%) males and 101 (80.8%) females in each group, giving a male to female ratio of 1: 4.2. Median (SD) age for the adolescents with and without obesity was 15.69 (2.24) and 15.74 (2.25) years respectively. Neck circumference correlated positively with weight (\u003cem\u003er\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.265, \u003cem\u003ep\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.003), height (\u003cem\u003er\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.222, \u003cem\u003ep\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.013), and BMI (\u003cem\u003er\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.209, \u003cem\u003ep\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.019) but not with waist circumference (\u003cem\u003er\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.167, \u003cem\u003ep\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.063) in adolescents with obesity. There was no relationship between neck circumference and TC, HDL-C, LDL-C, TG, or FPG in either of the two groups of adolescents.\u003c/p\u003e\u003ch2\u003eConclusions\u003c/h2\u003e \u003cp\u003eFrom this study, neck circumference can predict obesity but not central obesity and other cardiometabolic risks in Nigerian adolescents.\u003c/p\u003e","manuscriptTitle":"Predictability of Obesity and Metabolic Syndrome by Neck Circumference in Nigerian Adolescents with Obesity.","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2025-01-30 05:29:35","doi":"10.21203/rs.3.rs-5837003/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"decision","content":"Revision requested","date":"2025-01-29T14:19:19+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2025-01-28T13:26:10+00:00","index":"","fulltext":""},{"type":"checksComplete","content":"","date":"2025-01-28T13:23:40+00:00","index":"","fulltext":""},{"type":"submitted","content":"BMC Cardiovascular Disorders","date":"2025-01-15T20:04:54+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"bmc-cardiovascular-disorders","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"bcar","sideBox":"Learn more about [BMC Cardiovascular Disorders](http://bmccardiovascdisord.biomedcentral.com/)","snPcode":"","submissionUrl":"https://www.editorialmanager.com/bcar/default.aspx","title":"BMC Cardiovascular Disorders","twitterHandle":"BMC_series","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"em","reportingPortfolio":"BMC Series","inReviewEnabled":true,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"8a9f894f-a801-4380-89f8-411d85d7fac9","owner":[],"postedDate":"January 30th, 2025","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"under-review","subjectAreas":[],"tags":[],"updatedAt":"2025-11-21T16:23:22+00:00","versionOfRecord":[],"versionCreatedAt":"2025-01-30 05:29:35","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-5837003","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-5837003","identity":"rs-5837003","version":["v1"]},"buildId":"8U1c8b4HqxoKbykW_rLl7","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}