Evaluation of Arterial Stiffness and Its Relation to Innovative Anthropometric Indices in Persian Adults

Ataee, Zahra; Aghaee, Atena; Sobhani, Seyyed Reza; Ebrahimi Miandehi, Elaheh; Pirzadeh, Parisa; Alinezhad-Namaghi, Maryam; Eslami, Saeid; Sobhani, Sahar

doi:https://doi.org/10.1155/2023/2180923

International Journal of Hypertension

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Abstract Introduction Materials and Methods Results Discussion Conclusion Data Availability Ethical Approval Consent Conflicts of Interest Acknowledgments References Copyright Related Articles

Research Article | Open Access

Volume 2023 | Article ID 2180923 | https://doi.org/10.1155/2023/2180923

Evaluation of Arterial Stiffness and Its Relation to Innovative Anthropometric Indices in Persian Adults

Zahra Ataee,¹Atena Aghaee,²Seyyed Reza Sobhani,³Elaheh Ebrahimi Miandehi,⁴Parisa Pirzadeh,⁵Maryam Alinezhad-Namaghi,^3,6Saeid Eslami,⁷and Sahar Sobhani⁴

Academic Editor: Giacomo Pucci

Received06 Oct 2022

Revised02 Dec 2022

Accepted04 Jan 2023

Published23 Jan 2023

Abstract

Background. BMI has been evaluated as an old criterion to evaluate obesity in individuals, but it does not assess abdominal obesity and lean mass. We aimed to evaluate the possible relationship of new anthropometric indices (namely, a body shape index (ABSI), the body roundness index (BRI), the visceral adiposity index (VAI), the visceral fat area (VFA), and waist-hip ratio (WHR)), with one of the known critical factors of atherosclerosis, arterial stiffness. Methods. Overall 5921 individuals were enrolled and were divided into four groups according to BMI. Novel anthropometric parameters including, ABSI, BRI, VAI, VFA, and WHR were calculated. The carotid-femoral pulse wave velocity (cf-PWV) was used to evaluate arterial stiffness. Multiple regression analysis was performed to assess the relationship between cf-PWV and innovative Anthropometric indices. Results. This study population consisted of 3109 women and 2812 males. In men with overweight, cf-PWV was significantly related to BMI, ABSI, BRI, WC, VAI, VFA, and WHR. However, among men with obesity, cf-PWV was associated with BRI, VAI, and VFA. Among women with overweight, cf-PWV was also related to all mentioned indices except ABSI; although, cf-PWV was only associated with VFA and WHR in women with obesity. Conclusion. Our results showed that VFA in women and VAI in men are strongly related to arterial stiffness and can be used to identify predictors of vascular disease or organic vascular dysfunction.

1. Introduction

Obesity is one of the problems of today’s world that has affected almost all societies and leads to significant complications such as increased insulin resistance, hyperlipidaemia, and hypertension [1]. Various studies have shown that one of the types of increased body fat and obesity associated with cardiovascular complications is increased abdominal fat and abdominal obesity [2].

BMI has been evaluated as an old criterion to check obesity in people, but it does not evaluate abdominal obesity and lean mass; therefore, in recent years, newer criteria are used in addition to BMI to evaluate obesity [3]. New indices, namely, a body shape index (ABSI), the body roundness index (BRI), the visceral adiposity index (VAI), the visceral fat area (VFA), and waist-hip ratio (WHR), have been recently proposed as anthropometric measures. ABSI is statistically independent of height, BMI, and WC (waist circumference) and can be better regarded as abdominal obesity [4]. The BRI is another composition index that is based on WC and height [5]. VAI is a sex-specific surrogate indicator of visceral adiposity accumulation and dysfunction, and it is calculated with both common anthropometric (body mass index (BMI) and waist circumference (WC)) and lipidemic (triglycerides (TG) and high-density lipoprotein (HDL) cholesterol) measurements and is independently related with cardiometabolic risk. Also, VAI was proposed as a new anthropometric measure in 2010 [6]. VFA measures the fat that is stored around a number of critical internal organs, including liver, intestine, and pancreas [7]. WHR is one of the markers of abdominal obesity and has shown an improved ability to identify cardiovascular disease [3]. One study showed that VAI was the useful tool in the men population for the assessment of cardiometabolic risk associated with visceral obesity [6]; furthermore, VFA can be used to predict atherosclerotic cardiovascular diseases in both genders [8, 9].

Several studies have indicated that VAI is more strongly associated with cardiovascular risk and metabolic risk [10]. Also, VFA correlated significantly with glucose intolerance, hypertriglyceridemia [11], hypertension, and cardiac dysfunction in obese subjects [12]. Very few studies to date have examined the differences between VFA, VAI, WHR, and other anthropometric indices on identifying hypertension and cardiovascular disease (CVD).

CVD is one of the most important causes of death in the world, and about 50% of the causes of death are caused by noncommunicable diseases [12]. Arteriosclerosis is influenced by various factors such as age, increased blood pressure, inflammation, and hyperlipidaemia [12], and it has been shown in various studies that the increase in arteriosclerosis has a direct relationship with the increase in cardiovascular events [13–15].

Therefore, knowing the risk factors and preventing them and using a safe method to determine the presence of arterial stiffness is very essential. Aortic arterial stiffness, which can be indirectly measured by pulse wave velocity (PWV) reflects changes in arteriosclerosis [16]. PWV is one of the safe, robust, reproducible, and noninvasive methods to evaluate arterial stiffness [17].

Since arterial stiffness is related to cardiovascular events, identifying predisposing factors for arterial stiffness and prevention and treatment of these factors are helpful in preventing cardiovascular events. Also, previous studies in different countries and ethnicities claimed that anthropometric measurements have different prognostic values for arterial stiffness, and the predictive power of anthropometric indices should be identified for different ethnicities [18, 19]. Therefore, in this study, we decided to evaluate the relationship between arterial stiffness and new body composition indices in the Persian cohort study.

2. Materials and Methods

2.1. Subjects

The PERSIAN Organizational Cohort Study in Mashhad (POCM) was launched in 2017 to investigate lifestyle and risk factors for noncommunicable diseases (especially cardiovascular events). Details of the Persian Cohort Study have been reported formerly [20]. Between August 2017 and May 2022, individuals (aged 30–70 years) were selected to enroll in the present study. A total of 6093 participants qualified for the analyses. Among these 6093 individuals, 172 were excluded; 102 were excluded due to incomplete arterial stiffness data, and 70 were excluded due to the nonexistence of other data. After these exclusions, 5921 participants (2812 men and 3109 women) were eligible for the studies. Baseline assessments were obtained by face-to-face interviews or examinations. The questionnaires consist of demographic characteristics such as marital status and education years (low education means < 9 years, middle education means 9–12 years, high education means > 12 years) and physical activity (light < 3.0, intermediate 3.0–5.9, high ≥ 6.0) [21, 22], personal and familial medical history, and also smoking and the related data were collected by a standardized questionnaire [16, 22]. The Persian cohort study was approved by the Institutional Ethics Committee of Mashhad University of Medical Sciences (IR.MUMS.REC.1395.526; January 2017) and was conducted according to the guidelines of the Declaration of Helsinki. The informed consent was achieved from all participants before participation.

2.2. Clinical and Biochemical Analyses

At the baseline POCM examination, calibrated devices and standardized questionnaires were utilized by expert personnel (cardiologists, general practitioners, nurses, and dietitians) to collect all the data/information required by the study protocol [15, 20, 23, 24]. Weight (kilograms), waist and hip circumference (centimeter), height (meters), BMI (kg/m²), and anthropometric measurements were calculated using US National Institutes of Health protocols [25]. ABSI and BRI were calculated using the following formulas [5, 26]:

The VAI was calculated based on the following sex-specific formulas [6]:

Biochemical measurements were collected in a sitting position after 12 hours of fasting in the morning (BT1500 auto analyzer, Biotechnical Instruments, Rome, Italy). We used the standard methods of the World Health Organization (WHO) to measure fasting blood sugar (FBS), liver enzyme levels, serum lipid profiles, and other biochemical parameters. The Carotid-femoral pulse wave velocity (cf-PWV), used to evaluate arterial stiffness, was measured with the SphygmoCor XCEL System (AtCor Medical Incorporation) [27]. The test needs at least a 6 h fasting state and no caffeine, tobacco, and alcohol use for 12 hours prior to performing the test [28, 29]. The details of cf-PWV have been explained in previous studies [20, 27].

2.3. Statistical Analysis

Descriptive statistics of the study population were divided based on men and women and BMI (underweight <18.5 kg/m², normal: 18.5–24.9 kg/m², overweight: 25–29.9 kg/m², and obese: 30 kg/m²). Continuous variables were expressed as mean ± standard deviation and discrete variables were expressed as a number and percentages. Differences among the groups were tested with a one-way analysis of variance (ANOVA) (continuous variables) or χ² test (categorical variables). Multiple regression analysis was used to determine the association of anthropometrics variables on cf-PWV. The following factors were considered as independent variables: age, SBP, DBP, FBS, TG, and hypertension. All analyses were performed using SPSS software version 22, and was considered statistically significant.

3. Results

A total of 5921 Persian adults (2812 men, 47.5%; 3109 women, 52.5%) were divided into four groups according to the BMI classification of the World Health Organization (WHO). The baseline characteristics such as demographic, anthropometric, arterial stiffness, laboratory findings, and clinical history are shown in Tables 1 and 2. Men had higher proportions of diabetes, age, cf-PWV, waist circumference, smoking, FBS, SBP, and DBP than women, but women had significantly higher VFA and hypertension than men. The mean VAI was 2.04 (underweight; n = 26), 3.38 (normal; n = 883), 4.51 (overweight; n = 1447), and 4.66 (obesity = 456) in men. The mean VFA were 48.9 in underweight, 98.5 in normal, 140.5 in overweight, and 187.3 in obese women.

Correlations between cf-PWV and the anthropometric measurements are shown in Table 3. In men with overweight, cf-PWV was significantly related to all indices: BMI (coefficient = 0.07, ), ABSI (coefficient = 0.14, ), BRI (coefficient = 0.2, ), WC (coefficient = 0.14, ), VAI (coefficient = 0.08, ), VFA (coefficient = 0.2, ), and WHR (coefficient = 0.15, ). However, among men with obesity, cf-PWV was associated with BRI (coefficient = 012, ) VAI (coefficient = 1.01, ) and VFA (coefficient = 0.17, ). Among overweight women, cf-PWV was also related to all indices: BMI (coefficient = 0.14, ), BRI (coefficient = 0.06 ), WC (coefficient = 0.06, ), VAI (coefficient = 0.16, ), WHR (coefficient = 0.13, ), and VFA (coefficient = 0.19, ) except ABSI (coefficient = 0.003, ). Although, cf-PWV was only associated with VFA (coefficient = 0.186, ), and WHR (coefficient = 0.17, ) in women with obesity.

As shown in Table 4, multiple regression analysis was then performed to detect the variables that were strongly related to cf-PWV. The interaction between cf-PWV and anthropometric indices was influenced by age, SBP, DBP, FBS, TG, and hypertension in both men and women. Notably, the results were different between men with obesity and men with overweight. As shown in model III, cf-PWV was significantly associated with VAI (β = 0.54, ), VFA (β = 0.07, ), WC (β = 0.04, ), and WHR (β = 0.08, ) in men living with overweight. However, cf-PWV was only related to VAI (β = 0.65, ) in men with obesity. In women living with overweight, cf-PWV was significantly associated with BMI (β = 0.06, ), VFA (β = 0.10, ), and WHR (β = 0.07, ) in model III. Similarly, cf-PWV was significantly associated with VFA (β = 0.11, ) and WHR (β = 0.05, ) in women with obesity. Our results showed that VFA in women and VAI in men were the key factor that was strongly correlated with cf-PWV.

4. Discussion

In our cross-sectional study conducted in the population of 5921 Persian adults, after removing all confounding factors, we found that among the anthropometric indicators, VFA in women and VAI in men are related to arterial stiffness.

Arterial stiffness is known as a strong predictor of atherosclerosis, and as reported in various studies, atherosclerosis is strongly associated with cardiovascular events and mortality [30, 31]. Therefore, by evaluating the stiffness in the artery in patients and normal people, an estimate of cardiovascular events can be obtained.

In general, it has been seen that the use of anthropometric indices as new methods of evaluating central obesity and visceral obesity to determine the prognosis of arterial stiffness and subsequent cardiovascular events is reasonable [32].

In our study, in men with overweight, the arterial stiffness index was related to BMI-ABSI-BRI-WC-VAI-VFA-WHR and among men with obesity, a significant relationship was reported with BRI-VAI-VFA. Also, after modeling and removing confounding factors such as age, SBP, DBP TG, and hypertension, we came to the conclusion that arterial stiffness in overweight men is related to VAI-VFA-WC-WHR, and in men with obesity, it is only related to VAI. Also, in women with overweight, arterial stiffness index is related to BMI-BRI-WC-VAI-WHR-VFA criteria, and it is not related to ABSI. In women living with obesity, this index is related to VFA-WHR. But after modeling, it was found that in women with overweight, arterial stiffness is related to BMI-VFA-WHR, and in women with obesity, it is related to VFA-WHR.

BMI is one of the oldest measures to evaluate obesity in people; still, this measure does not differentiate between fat tissue and muscle mass [33, 34]. In addition, BMI does not distinguish the distribution of body fat in peripheral and abdominal areas [34, 35] although various studies have shown that fat deposits in the center and viscera are especially more harmful [36].

Several studies have reported that in Asian people, the distribution of fat, especially in the abdominal area, is more common than in European people. This factor is more common in Asian people than in European people with the same BMI and WC, despite the presence of metabolic syndrome and the risk of cardiovascular events [37, 38].

Also, in the study of Choi et al., it was reported that BMI is inversely related to arterial stiffness in men, and BMI, WC, and BRI in women are related to arterial stiffness, and this difference is due to the different distribution of fat in the body of women and men [39]. Because the majority of fat in men’s bodies is visceral fat and subcutaneous fat in women’s bodies. Considering the above, BMI is not a suitable factor for assessing the risk of cardiovascular events, especially in Asian people. In various studies, the role of BMI in relation to the evaluation of arterial stiffness has not been completely eliminated, but in various articles, new anthropometric factors have a greater and more important role in the evaluation of arterial stiffness in people with weight gain and obesity because in these new factors, the role of fat visceral is bolder and more important [16].

In the recent reports of the World Health Organization, it has been stated that WC is a substitute for BMI to determine the risk of diseases [40]. However, in Zhang et al.’s study, it was shown that WC has a weak relationship with arterial stiffness in women without the risk factors of diabetes and high blood pressure. It has an inverse relationship with arterial stiffness in men [32].

BMI and WC could not accurately represent abdominal visceral fat, so the newer ABSI and BRI measures were used, although these older measures of BMI, WC, and WHR were essential in previous studies to assess cardiovascular metabolic risk [40].

A valuable anthropometric index that was investigated in our study subjects was the ABSI index, which in our study was related to arterial stiffness with weight gain in men, but after removing the confounding factors, this factor was not significantly associated with arterial stiffness in any of the groups.

This index has been mentioned in various studies as an independent factor of weight height and BMI and it has been reported that it has a direct relationship with visceral fat and the risk of mortality and disease [1, 26]. In several studies, the relationship of this index with cancer mortality and cardiovascular disorders was compared with BMI, WC, and WHtR indices, and the relationship of this index was reported to be stronger and it was even accepted that this index is a marker of arterial stiffness in type 2 diabetes patients [1, 41] But later in several studies, it was seen that this index is a weaker index than BMI and WC for evaluating cardiovascular events and metabolic syndrome [42–44] Zhang et al. also concluded that in the population of Chinese people, this index is not a very good index for evaluating arterial stiffness [32].

In previous studies, it has also been reported that WHR, ABSI, and BRI have a strong relationship with arterial stiffness in both sexes, while BMI and WC have an inverse relationship with arterial stiffness. Also, two new anthropometric indices, ABSI and BRI, can predict Arterial stiffness indicators are valuable [44]. In this cross-sectional study, we found that new anthropometric indices had a significant relationship with PWV in both gender categories, while BMI and WC showed a negative relationship with PWV [32].

Another studied index is BRI, which has been shown in studies to be a better index than BMI and WC for evaluating body fat and visceral adipose tissue volume [5] But compared to other anthropometric indicators, not many studies have been conducted to assess the risk of metabolic syndrome and cardiovascular events. Only a few studies have described this index as valuable in evaluating cardiovascular events [44–46].

In our study, arterial stiffness in men with weight gain, men with obesity, and women with weight gain had a significant relationship with this index. In another published study, it was also reported that the BRI index with stiffness arterial correlates in the Chinese population [32].

One of the anthropometric indicators that had a significant relationship with arterial stiffness in both women and men in our study was the WHR factor, which measures the ratio of waist circumference to hip circumference. In the study of Zhou et al., it was reported that this factor has the best relationship with increased blood pressure in men [47].

WHR is one of the obesity parameters that are more related to abdominal obesity and has been shown in studies to be related to cardiovascular and cerebrovascular diseases [48].

In our study, this index was related to weight gain in men and in women with weight gain and in women with obesity and arterial stiffness and after removing the confounding factors of this WHR index with arterial stiffness in men with weight gain and women with weight gain and Obesity is related.

It was also seen in a systematic review that WHR is a suitable screening assessment for metabolic syndrome in adults [49], and this factor can determine the risk of cardiovascular events and metabolic syndrome in nonobese people [50]. This case was the same as the findings of the Zhang et al. study [32]. All these cases show that WHR is a suitable index for evaluating central obesity and can be a reliable measure in evaluating diseases related to central obesity, including metabolic syndrome and cardiovascular disorders.

Another anthropometric index is VAI, which was shown in our study to be very strongly related to arterial stiffness in men.

VAI is an index that shows the distribution of fat in the body based on BMI, WC, TG levels, and HDL levels. In the study of Yang et al., it was shown that this index could be a measure of obesity and assessment of atherosclerosis [51] And, in Cho et al. study and arterial stiffness in the Korean population, it was seen that VAI in men and women is related to arterial stiffness [39].

Another essential index in evaluations is VFA, which in our study was found to be strongly related to arterial stiffness in women. In the Li et al. study, it was also shown that this index has a direct relationship with arterial stiffness [16]. Also, in this study, it was shown that VFA in people with weight gain and obesity is related to arterial stiffness, and the relationship of this index with arterial stiffness is more potent than other indices [16]. Although in some previous studies, it was shown that the correlation of this index with arterial stiffness is weak [1].

In the Zajac et al. study, which investigated the relationship between VFA and metabolic syndrome in the female population, they concluded that metabolic syndrome in women is directly related to the VFA index [8]. In Zhang et al. study, they also concluded that the VFA index in women has a strong relationship with hypertension [7]. Several studies have reported that in Asians, the distribution of total body fat in the abdomen is higher and the incidence of CVD and metabolic risk factors are higher than in European people with the same BMI [37, 38] Therefore, BMI as a predictor of vascular disease or organic vascular dysfunction, it is not suitable especially for Asians [32].

Population-based cohort design, with a large number of participants, in Mashhad, the second largest city in Iran and, considering innovative Anthropometric indices in Persian adults are some of the strengths of the current study. The standard questionnaires consist of demographic characteristics, physical activity, personal and familial medical history, and smoking. Also, clinical and biochemical analyses may improve the judgment of the results. Using Pulse wave velocity (PWV), the safe, robust, reproducible, and noninvasive methods to evaluate arterial stiffness are strengths.

Although this study’s findings may not be generalizable to other ethnicities, the results might still be applicable because of mostly consistent with previous studies around the world.

5. Conclusion

The result of the current study confirmed that the VFA index in women and the VAI index in men are strongly related to arterial stiffness. Therefore, the recommendation to improve these indices, such as lifestyle modifications and exercise habits developments, can improve arterial stiffness, which logically results in less cardiovascular disease.

Data Availability

The data used to support the study are included in the paper.

Ethical Approval

All procedures involving human participants were in accordance with the Ethical Standards of the National Research Committee and the 1964 Helsinki Declaration and its later amendments or comparable ethical standards.

All participants signed informed consent regarding publishing their data.

Conflicts of Interest

The authors declare that there are no conflicts of interest.

Acknowledgments

The authors would like to express their gratitude to the staff of PERSIAN Cohort Epidemiologic Studies, Mashhad site. This research was supported by the vice-chancellor of the Mashhad University of Medical Sciences under Grant no. 981695.

References

R. Bouchi, M. Asakawa, N. Ohara et al., “Indirect measure of visceral adiposity ‘A Body Shape Index’(ABSI) is associated with arterial stiffness in patients with type 2 diabetes,” BMJ Open Diabetes Research & Care, vol. 4, no. 1, Article ID e000188, 2016.
View at: Publisher Site | Google Scholar
B. Balkau, J. E. Deanfield, J.-P. Després et al., “International Day for the Evaluation of Abdominal Obesity (IDEA) a study of waist circumference, cardiovascular disease, and diabetes mellitus in 168 000 primary care patients in 63 countries,” Circulation, vol. 116, no. 17, 2007.
View at: Publisher Site | Google Scholar
P. K. Myint, C. S. Kwok, R. N. Luben, N. J. Wareham, and K.-T. Khaw, “Body fat percentage, body mass index and waist-to-hip ratio as predictors of mortality and cardiovascular disease,” Heart, vol. 100, no. 20, 2014.
View at: Publisher Site | Google Scholar
N. Y. Krakauer and J. C. Krakauer, “Dynamic association of mortality hazard with body shape,” PLoS One, vol. 9, no. 2, Article ID e88793, 2014.
View at: Publisher Site | Google Scholar
D. M. Thomas, C. Bredlau, A. Bosy-Westphal et al., “Relationships between body roundness with body fat and visceral adipose tissue emerging from a new geometrical model,” Obesity, vol. 21, no. 11, pp. 2264–2271, 2013.
View at: Publisher Site | Google Scholar
M. C. Amato, C. Giordano, M. Galia et al., “Visceral Adiposity Index: a reliable indicator of visceral fat function associated with cardiometabolic risk,” Diabetes Care, vol. 33, no. 4, pp. 920–922, 2010.
View at: Publisher Site | Google Scholar
B. Zhang, Y. Fan, Y. Wang et al., “Comparison of bioelectrical body and visceral fat indices with anthropometric measures and optimal cutoffs in relation to hypertension by age and gender among Chinese adults,” BMC Cardiovascular Disorders, vol. 21, no. 1, pp. 2-3, 2021.
View at: Publisher Site | Google Scholar
I. Zając-Gawlak, B. Kłapcińska, A. Kroemeke, D. Pośpiech, J. Pelclová, and M. Přidalová, “Associations of visceral fat area and physical activity levels with the risk of metabolic syndrome in postmenopausal women,” Biogerontology, vol. 18, no. 3, pp. 357–366, 2017.
View at: Publisher Site | Google Scholar
A. Polcrova, I. Pavlovska, G. A. Maranhao Neto et al., “Visceral fat area and cardiometabolic risk: the Kardiovize study,” Obesity Research & Clinical Practice, vol. 15, no. 4, pp. 368–374, 2021.
View at: Publisher Site | Google Scholar
E. Koloverou, D. B. Panagiotakos, I. Kyrou et al., “Visceral adiposity index outperforms common anthropometric indices in predicting 10-year diabetes risk: results from the ATTICA study,” Diabetes/metabolism research and reviews, vol. 35, no. 6, Article ID e3161, 2019.
View at: Publisher Site | Google Scholar
S. Fujioka, Y. Matsuzawa, K. Tokunaga, and S. Tarui, “Contribution of intra-abdominal fat accumulation to the impairment of glucose and lipid metabolism in human obesity,” Metabolism, vol. 36, no. 1, pp. 54–59, 1987.
View at: Publisher Site | Google Scholar
M. D. Marques, R. D. Santos, J. R. Parga et al., “Relation between visceral fat and coronary artery disease evaluated by multidetector computed tomography,” Atherosclerosis, vol. 209, no. 2, pp. 481–486, 2010.
View at: Publisher Site | Google Scholar
J. A. Chirinos, P. Segers, T. Hughes, and R. Townsend, “Large-artery stiffness in health and disease: JACC state-of-the-art review,” Journal of the American College of Cardiology, vol. 74, no. 9, pp. 1237–1263, 2019.
View at: Publisher Site | Google Scholar
T. Ohkuma, T. Ninomiya, H. Tomiyama et al., “Brachial-ankle pulse wave velocity and the risk prediction of cardiovascular disease: an individual participant data meta-analysis,” Hypertension, vol. 69, no. 6, pp. 1045–1052, 2017.
View at: Publisher Site | Google Scholar
S. Sobhani, S. Vakili, D. Javid Jam et al., “Relationship between anthropometric indices and arterial stiffness: insights from an epidemiologic study,” Obesity Science & Practice, vol. 8, no. 4, pp. 494–499, 2022.
View at: Publisher Site | Google Scholar
G. Li, T. Yao, X. Wu et al., “Novel and traditional anthropometric indices for identifying arterial stiffness in overweight and obese adults,” Clinical Nutrition, vol. 39, no. 3, pp. 893–900, 2020.
View at: Publisher Site | Google Scholar
M. F. O'rourke, S. S. Franklin, I. Wilkinson, H. Struijker-Boudier, and S. Laurent, “Arterial stiffness: reflections on the arterial pulse,” European Heart Journal, vol. 27, no. 21, pp. 2497-2498, 2006.
View at: Publisher Site | Google Scholar
H. K. Chung, B. Kang, J. H. Lee et al., “Increased arterial stiffness is associated with reduced plasma levels of β-carotene in treated hypertensive patients with type 2 diabetes mellitus,” Nutrition, Metabolism, and Cardiovascular Diseases, vol. 19, no. 6, pp. e9–e11, 2009.
View at: Publisher Site | Google Scholar
A. Wykretowicz, K. Adamska, P. Guzik, T. Krauze, and H. Wysocki, “Indices of vascular stiffness and wave reflection in relation to body mass index or body fat in healthy subjects,” Clinical and Experimental Pharmacology and Physiology, vol. 34, no. 10, pp. 1005–1009, 2007.
View at: Publisher Site | Google Scholar
F. Tohidinezhad, A. Khorsand, S. R. Zakavi et al., “The burden and predisposing factors of non-communicable diseases in Mashhad University of Medical Sciences personnel: a prospective 15-year organizational cohort study protocol and baseline assessment,” BMC Public Health, vol. 20, no. 1, pp. 2–9, 2020.
View at: Publisher Site | Google Scholar
M. A. Mendes, I. Da Silva, V. Ramires et al., “Metabolic equivalent of task (METs) thresholds as an indicator of physical activity intensity,” PLoS One, vol. 13, no. 7, Article ID e0200701, 2018.
View at: Publisher Site | Google Scholar
H. Poustchi, S. Eghtesad, F. Kamangar et al., “Prospective epidemiological research studies in Iran (the Persian Cohort Study): rationale, objectives, and design,” American Journal of Epidemiology, vol. 187, no. 4, pp. 647–655, 2018.
View at: Publisher Site | Google Scholar
S. Sobhani, R. Aryan, M. AkbariRad et al., “The association between anthropometry indices and serum concentrations of gamma-glutamyl transferase, alkaline phosphatase, alanine aminotransferase, and aspartate aminotransferase,” BioMed Research International, vol. 2021, Article ID 2365399, 6 pages, 2021.
View at: Publisher Site | Google Scholar
S. Sobhani, R. Sara, A. Aghaee, P. Pirzadeh, E. E. Miandehi, and S. Shafiei, “Body mass index, lipid profile, and hypertension contribute to prolonged QRS complex,” Clinical Nutrition ESPEN, vol. 50, 2022.
View at: Publisher Site | Google Scholar
Centers for Disease Control and Prevention, National Health and Nutrition Examination Survey (NHAN ES). Anthropometry ProceduresManual, Centers for Disease Control and Prevention, Atlanta, GA, USA, 2007.
N. Y. Krakauer and J. C. Krakauer, “A new body shape index predicts mortality hazard independently of body mass index,” PLoS One, vol. 7, no. 7, Article ID e39504, 2012.
View at: Publisher Site | Google Scholar
M. H. Hwang, J. K. Yoo, H. K. Kim et al., “Validity and reliability of aortic pulse wave velocity and augmentation index determined by the new cuff-based SphygmoCor Xcel,” Journal of Human Hypertension, vol. 28, no. 8, pp. 475–481, 2014.
View at: Publisher Site | Google Scholar
Y. Ben-Shlomo, M. Spears, C. Boustred et al., “Aortic pulse wave velocity improves cardiovascular event prediction: an individual participant meta-analysis of prospective observational data from 17, 635 subjects,” Journal of the American College of Cardiology, vol. 63, no. 7, pp. 636–646, 2014.
View at: Publisher Site | Google Scholar
K. Luo, X. Feng, B. Xu, and H. Long, “Association between arterial stiffness and risk of coronary artery disease,” Pakistan Journal of Medical Sciences, vol. 30, no. 6, pp. 1314–1318, 2014.
View at: Publisher Site | Google Scholar
K. Cruickshank, L. Riste, S. G. Anderson, J. S. Wright, G. Dunn, and R. G. Gosling, “Aortic pulse-wave velocity and its relationship to mortality in diabetes and glucose intolerance: an integrated index of vascular function?” Circulation, vol. 106, no. 16, pp. 2085–2090, 2002.
View at: Publisher Site | Google Scholar
A. S. Mansour, A. Yannoutsos, N. Majahalme et al., “Aortic stiffness and cardiovascular risk in type 2 diabetes,” Journal of Hypertension, vol. 31, no. 8, 2013.
View at: Publisher Site | Google Scholar
J. Zhang, L. Fang, L. Qiu, L. Huang, W. Zhu, and Y. Yu, “Comparison of the ability to identify arterial stiffness between two new anthropometric indices and classical obesity indices in Chinese adults,” Atherosclerosis, vol. 263, pp. 263–271, 2017.
View at: Publisher Site | Google Scholar
A. M. Nevill, A. D. Stewart, T. Olds, and R. Holder, “Relationship between adiposity and body size reveals limitations of BMI,” American Journal of Physical Anthropology, vol. 129, no. 1, 2006.
View at: Publisher Site | Google Scholar
J. Gómez-Ambrosi, C. Silva, J. C. Galofré et al., “Body mass index classification misses subjects with increased cardiometabolic risk factors related to elevated adiposity,” International Journal of Obesity, vol. 36, no. 2, 2012.
View at: Publisher Site | Google Scholar
C. M. Phillips, A. C. Tierney, P. Perez-Martinez et al., “Obesity and body fat classification in the metabolic syndrome: impact on cardiometabolic risk metabotype,” Obesity, vol. 21, no. 1, pp. E154–E161, 2013.
View at: Publisher Site | Google Scholar
C. E. Ruhl and J. E. Everhart, “Trunk fat is associated with increased serum levels of alanine aminotransferase in the United States,” Gastroenterology, vol. 138, no. 4, pp. 1346–1356.e3, 2010.
View at: Publisher Site | Google Scholar
S. A. Lear, M. Toma, C. L. Birmingham, and J. J. Frohlich, “Modification of the relationship between simple anthropometric indices and risk factors by ethnic background,” Metabolism, vol. 52, no. 10, pp. 1295–1301, 2003.
View at: Publisher Site | Google Scholar
P. Deurenberg, M. Deurenberg-Yap, and S. Guricci, “Asians are different from Caucasians and from each other in their body mass index/body fat per cent relationship,” Obesity Reviews, vol. 3, no. 3, pp. 141–146, 2002.
View at: Publisher Site | Google Scholar
H. S. Choi, Y. H. Cho, S. Y. Lee et al., “Association between new anthropometric parameters and arterial stiffness based on brachial-ankle pulse wave velocity&lt,” Diabetes, Metabolic Syndrome and Obesity: Targets and Therapy, vol. 12, pp. 1727–1733, 2019.
View at: Publisher Site | Google Scholar
C. Nishida, G. T. Ko, and S. Kumanyika, “Body fat distribution and noncommunicable diseases in populations: overview of the 2008 WHO expert consultation on waist circumference and waist–hip ratio,” European Journal of Clinical Nutrition, vol. 64, no. 1, pp. 2–5, 2010.
View at: Publisher Site | Google Scholar
K. Dhana, M. Kavousi, M. A. Ikram, H. W. Tiemeier, A. Hofman, and O. H. Franco, “Body shape index in comparison with other anthropometric measures in prediction of total and cause-specific mortality,” Journal of Epidemiology & Community Health, vol. 70, no. 1, pp. 90–96, 2016.
View at: Publisher Site | Google Scholar
S. He and X. Chen, “Could the new body shape index predict the new onset of diabetes mellitus in the Chinese population?” PLoS One, vol. 8, no. 1, Article ID e50573, 2013.
View at: Publisher Site | Google Scholar
Y. B. Cheung, “A Body Shape Index” in middle-age and older Indonesian population: scaling exponents and association with incident hypertension,” PLoS One, vol. 9, no. 1, Article ID e85421, 2014.
View at: Publisher Site | Google Scholar
Y. Chang, X. Guo, Y. Chen et al., “A body shape index and body roundness index: two new body indices to identify diabetes mellitus among rural populations in northeast China,” BMC Public Health, vol. 15, no. 1, pp. 794–798, 2015.
View at: Publisher Site | Google Scholar
M. F. H. Maessen, T. M. H. Eijsvogels, R. J. H. M. Verheggen, M. T. E. Hopman, A. L. M. Verbeek, and Fd Vegt, “Entering a new era of body indices: the feasibility of a body shape index and body roundness index to identify cardiovascular health status,” PLoS One, vol. 9, no. 9, Article ID e107212, 2014.
View at: Publisher Site | Google Scholar
Y. Chang, X. Guo, L. Guo, Z. Li, Y. Li, and Y. Sun, “The feasibility of two new anthropometric indices to identify hypertension in rural China: a cross-sectional study,” Medicine, vol. 95, no. 44, Article ID e5301, 2016.
View at: Publisher Site | Google Scholar
J. Baulmann, U. Schillings, S. Rickert et al., “A new oscillometric method for assessment of arterial stiffness: comparison with tonometric and piezo-electronic methods,” Journal of Hypertension, vol. 26, no. 3, 2008.
View at: Publisher Site | Google Scholar
M. Dempster and M. Donnelly, “Measuring the health related quality of life of people with ischaemic heart disease,” Heart, vol. 83, no. 6, 2000.
View at: Publisher Site | Google Scholar
M. Ashwell, P. Gunn, and S. Gibson, “Waist-to-height ratio is a better screening tool than waist circumference and BMI for adult cardiometabolic risk factors: systematic review and meta-analysis,” Obesity Reviews, vol. 13, no. 3, pp. 275–286, 2012.
View at: Publisher Site | Google Scholar
Q. Zhu, F. Shen, T. Ye, Q. Zhou, H. Deng, and X. Gu, “Waist-to-height ratio is an appropriate index for identifying cardiometabolic risk in Chinese individuals with normal body mass index and waist circumference,” Journal of Diabetes, vol. 6, no. 6, pp. 527–534, 2014.
View at: Publisher Site | Google Scholar
F. Yang, G. Wang, Z. Wang et al., “Visceral adiposity index may be a surrogate marker for the assessment of the effects of obesity on arterial stiffness,” PLoS One, vol. 9, no. 8, Article ID e104365, 2014.
View at: Publisher Site | Google Scholar

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Copyright © 2023 Zahra Ataee et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

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