Brachial-ankle pulse wave velocity as a risk factor for high body fat mediated by blood pressure

ABSTRACT

Background

Brachial-ankle pulse wave velocity (baPWV) is an important clinical indicator of aortic stiffness and a risk predictor of cardiovascular disease and associated with obesity. However, whether body mass index (BMI) is associated with baPWV remains controversial. In our study, body fat-related indicators, including BMI, body fat rate (BFR), body fat volume (BFV), waist circumference (WC) were examined from healthy volunteers. We investigated the correlation of baPWV with these indicators and also assessed whether baPWV has the potential to predict these indicators.

Methods

A total of 429 healthy participants were enrolled in this study. Body fat indices, blood pressures, baPWV and blood metabolic indices were measured and recorded. The association of baPWV and indices reflecting body fat and blood pressure, as well as mediation effect were analyzed.

Results

Three different types of baPWV values were significantly correlated. Mean level of baPWV was an independent risk factor for WC, BMI, BFR, and BFV (exp(β) = 1.011, 1.004, 1.010 and 1.009, respectively, P < .001 for all) but not BMR. As for mediation effects, baPWV positively influenced WC (Total effect = 0.011, P < .001), BMI (Total effect = 0.004, P < .001) and BFV (Total effect = 0.009, P < .001) in indirect way mediated by SBP and DBP, while baPWV influenced BFR in both direct (Effect = 0.004, P = .018) and indirect way.

Conclusions

Levels of baPWV correlated with obesity and is an independent risk factor for WC, BMI, BFR and BFV. Besides, baPWV positively associated with WC, BMI and BFV mainly in indirect way mediated by SBP and DBP, and baPWV associated with BFR in both direct and indirect way.

KEYWORDS:

• Arterial stiffness
• brachial-ankle pulse wave velocity
• hypertension
• obesity

Introduction

Aortic stiffness is a major indicator of vascular aging and is known to predict cardiovascular events and mortality independently (1, 2). Brachial-ankle pulse wave velocity (baPWV) is a significant clinical indicator of aortic stiffness and an important predictor of cardiovascular disease (3). Several previous studies have found a significant association between baPWV and various conditions, including hypertension (4), coronary heart disease (5), heart failure (6), and stroke (7) etc. A recent study has shown that baPWV can also predict the risk of diabetes (8), thereby expanding our understanding of its clinical utility.

Obesity, similar to diabetes, is a significant risk factor for cardiovascular disease. In most studies, obesity is defined as high body fat and is typically evaluated using body mass index (BMI) (9). Obesity is known to be associated with increased aortic PWV (10), but whether BMI is correlated with baPWV is still controversial (11,12). Recent research has suggested that baPWV is more closely related to abdominal obesity, as measured by waist-hip ratio (WHR) and visceral fat area (VFA), rather than overall obesity, as measured by BMI or waist circumference (WC) (13,14). However, the strong association between baPWV and obesity remains unexplained. Therefore, further evidence is needed to explore the relationship between baPWV and obesity, especially body fat. Additionally, whether baPWV can be used to evaluate body fat remains unknown. In this study, we examined body fat-related indicators, including BMI, body fat rate (BFR), body fat volume (BFV), and waist circumference (WC), and we investigated the correlation between baPWV and these indicators and assessed whether baPWV has the potential to predict them.

Methods

Study population

This cross-sectional study was performed between January 2021 and December 2021 based on the Monitoring of Cardiovascular Disease and Its Risk Factors in Chinese Residents Project (2020) which selected 10 sampling points in Sichuan Province through stratified sampling. Our team was randomly assigned to responsible for the investigation of 500 Han Chinese adults over 18 years old people in two of these points, namely Pidu County and Meishan City in Sichuan Province, and conducting the newest survey of cardiovascular disease and related risk factors for Chinese residents. In this study, by using questionnaires and medical history inquiries, the participants on hypoglycemic medicine, lipid-lowering drugs, and antihypertensive drugs were excluded. In addition, neoplastic patients, pregnant women, and the participants who had heart failure, coronary heart disease, stroke, peripheral arterial disease (defined as an ankle-branchial index [ABI]＜0.9) were also excluded. Subjects with integrated medical data, including demographic information, past illness history, personal history, blood biochemistry, and baPWV, were included in the whole cohort final database. Finally, a total 429 participants were included. All the procedures involving human were approved by the ethics committee of West China Hospital, Sichuan University and the study was registered at the Chinese Clinical Trial Registry (registration number: ChiCTR2100054493).

Data collection

Basic individual information, medical history, and drug therapy of chronic disease, including hypertension, diabetes mellitus, were collected by well-trained investigators. Physical examination (height, weight, and BP) was conducted in the quiet room with a temperature of about 25°C. The verified electronic sphygmomanometers (OMRON HEM-7200) were used to measure the office BP. All the participants were required to take a rest 5 min before the measurement. Systolic and diastolic BP were obtained three times on the right arm in a sitting position. The average value of the three readings was used for the final analyses. The blood sample was collected from each participant in the morning after 8 h of overnight fasting. FBG, triglyceride (TG), total cholesterol (TC), high-density lipoprotein cholesterol (HDL-C), and low-density lipoprotein cholesterol (LDL-C) were measured by an automatic biochemical analyzer. Measurements of baPWV were made by the trained physician using an automated device (BP-203RPEII, Nihon Colin, Japan) as previously described (15). Fat-related indicators, including BMI, BFR, BFV, were measured by InBody H20B (InBody Co., Ltd., Seoul, South Korea), WC was measured by tape measure when participants exhaling in a standing position. BMI= weight(kg)/height(m)^2, BFR= body fat/total body weight. Participants were asked not to consume alcohol for 24 h before testing and not to smoke, eat or drink irritant beverages including tea or coffee for 2 h before testing. The operator applied an inflated cuff to the upper and lower limbs, clamped the electrodes of the ECG device to both wrists, and placed the heart sound sensor at the left sternal border. The device automatically checked and recorded baPWV on the left and right sides. The mean values of the baPWV bilaterally were used for analysis. It’s been reported that baPWV≥1400 cm/s is an independent variable for risk stratification by Framingham score and a parameter of early target organ damage evaluation for hypertension (16). Hence, in this present study, high baPWV was defined as baPWV≥1,400 cm/s (either one result of the three baPWV tests[right, left and up]), which was also the early stages of arterial stiffness (17).

Statistical analysis

All data were analyzed using R software version 4.1.3 (2022-03-10) and SPSS 27.0 (IBM, USA) with process 4.1 packages by Andrew F. Hayes. The distribution of data was analyzed by Shapiro–Wilk test. As all data were not normally distributed. Continuous variables were presented as median with interquartile range and differences were compared by Mann–Whitney test between groups. Categorical values were presented as number with proportion and differences were compared by chi-square test. Spearman correlation test was applied to evaluate correlation between variables. Adjusted linear regression was used to evaluate the effects of baPWV values on indices reflecting body fat and blood pressure. Bootstrap resampling method (5000 resampling) was used to determine the mediation effect of blood pressure in the way baPWV influencing body fat. Adjusted decision curve analysis was depicted to evaluate the performance of baPWV in predicting body fat. Two-sided P < .05 was considered statistically significant.

Results

Baseline characteristics

A total of 429 healthy volunteers were included in the study and baseline demographics are presented in Table 1. The mean age was 42.6(20.0–71.0) years old and 146(34.0%) of them were female. Volunteers with smoking or drinking history took up about one-third of all participants, respectively. Volunteers were classified into Positive group if either one result of the three baPWV tests (right, left, and up) was higher than 1400. There was no difference between normal group and positive group in gender, age and smoking/drinking condition. However, regarding family history, there were significantly more participants in positive group with hypertension and hyperlipidemia history than in normal group (P = .012 and 0.015). There was no difference in other family history between the two groups.

Table 1. Baseline characteristics grouped by baPWV values.

	Total (N = 429)	Normal (N = 283)	Positive (any*, N = 146)	P value
Gender				0.882
Male	283(66.0%)	186(65.7%)	97(66.4%)
Female	146(34.0%)	97(34.3%)	49(33.6%)
Age	44.0(34.0–51.0)	45.0(35.0–51.0)	42.0(33.0–49.0)	0.276
Smoking	135(31.5%)	90(31.8%)	45(30.8%)	0.836
Drinking	160(37.3%)	98(34.6%)	62(42.5%)	0.112
Family history
Hypertension	104(24.2%)	58(20.5%)	46(31.5%)	0.012
Hyperlipidemia	14(3.3%)	5(1.8%)	9(6.2%)	0.015
Diabetes	24(5.6%)	17(6.0%)	7(4.8%)	0.605
Coronary Heart Disease	15(3.5%)	7(2.5%)	8(5.5%)	0.108
Stroke	5(1.2%)	2(0.7%)	3(2.1%)	0.218

*Volunteers were classified into Positive group if either one result of the three baPWV tests(right, left and up) was higher than 1400.

The distribution of baPWV and correlation with blood tests

The distributions of baPWV grouped by gender and age were shown in Supplementary Figures S1, and the results indicated that all the three baPWV values were rather evenly distributed among different age and gender groups. Besides, Pearson correlation test suggested that baPWV values were significantly correlated with most metabolic blood indices, except HDL-c and UCr values, as shown in Supplementary Figures S2. We then calculated the correlation among the three baPWV, as shown in Figure 1, indicating that the three baPWV values were significantly closely correlated. Based on this result, mean baPWV values of baPWV (right) and baPWV (left) were used for the following analyses.

Figure 1. Correlations among different baPWV values the color indicates the degree of correlation, with red being a positive correlation. baPWVL, left brachial – ankle pulse wave velocity; baPWVR, right brachial – ankle pulse wave velocity; baPWVU, the higher side of the bilateral brachial – ankle pulse wave velocity.

Levels of baPWV in evaluating body fat and blood pressure

To determine the quantitative impact of baPWV on the increase of body fat and blood pressure, we then performed linear regression analyses adjusted by age, gender, smoking, and drinking condition and family history of hypertension, hyperlipidemia, diabetes, coronary heart disease, stroke. The specific exp(β) and P values in evaluating different indices are listed in Tables 2 and 3. As for body fat indices, baPWV was the independent risk factor for WC, BMI, BFR and BFV (exp(β) = 1.011, 1.004, 1.010, and 1.009, respectively, P < .001 for all) but not BMR. Likewise, baPWV was the independent risk factor for SBP (up), DBP (up), SBP (down), DBP (down) and ABI (exp(β) = 1.047, 1.034, 1.034, 1.033, and 0.999, respectively, P < .001 for all).

Table 2. Mean baPWV in evaluating body fat by crude and adjusted linear regression.

	Crude			Adjusted*
	Exp(β)	95%CI	P	Exp(β)	95%CI	P
WC	1.013	1.008–1.018	<0.001	1.011	1.007–1.016	<0.001
BMI	1.005	1.003–1.006	<0.001	1.004	1.002–1.006	<0.001
BFR	1.009	1.005–1.012	<0.001	1.010	1.006–1.013	<0.001
BFV	1.009	1.005–1.012	<0.001	1.009	1.006–1.013	<0.001
BMR	1.014	0.924–1.113	0.762

*Adjusted by age, gender, smoking, and drinking condition and family history of hypertension, hyperlipidemia, diabetes, coronary heart disease, stroke.

baPWV, brachial – ankle pulse wave velocity; BFR, body fat rate; BFV, body fat Volume; BMI, body mass index; BMR, basal metabolic rate; WC, waist circumference.

Table 3. Mean baPWV in evaluating blood pressure by crude and adjusted linear regression.

	Crude			Adjusted*
	Exp(β)	95%CI	P	Exp(β)	95%CI	P
SBP (up)	1.049	1.041–1.056	<0.001	1.047	1.039–1.054	<0.001
DBP (up)	1.036	1.030–1.042	<0.001	1.034	1.029–1.040	<0.001
SBP (down)	1.035	1.029–1.041	<0.001	1.034	1.028–1.040	<0.001
DBP (down)	1.034	1.029–1.040	<0.001	1.033	1.027–1.038	<0.001
ABI	0.999	0.999–0.999	<0.001	0.999	0.999–0.999	<0.001

*Adjusted by age, gender, smoking, and drinking condition and family history of hypertension, hyperlipidemia, diabetes, coronary heart disease, stroke.

ABI, ankle brachial pressure index; baPWV, brachial – ankle pulse wave velocity; DBP, diastolic blood pressure; SBP, systolic blood pressure.

Mediation effect of BP in the way baPWV influencing body fat

In our chain mediation model, mean baPWV and indices of body fat were the dependent variables; SBP and DBP were chain mediators; age, gender, smoking/drinking condition and family history were adjusted. The results of the path coefficients calculated by bootstrap resampling method were shown in Figure 2. The results indicated that baPWV positively influenced WC (Total effect = 0.011, P < .001), BMI (Total effect = 0.004, P < .001) and BFV (Total effect = 0.009, P < .001) mainly in indirect way mediated by SBP and DBP, while baPWV influenced BFR in both direct (Effect = 0.004, P = .018) and indirect way (Effect_{baPWV-SBP-BFR} = 0.0015, Effect_{baPWV-DBP-BFR} = 0.0013, Effect_{baPWV-SBP-DBP-BFR} = 0.0025).

Figure 2. Chain mediation role of SBP and DBP in the body fat influenced by baPWV mean values. Analyses were adjusted by age, gender, smoking and drinking condition and family history of hypertension, hyperlipidemia, diabetes, coronary heart disease, stroke. Solid line arrow indicated direct effect and dashed line arrow indicated indirect effect. ABI, ankle brachial pressure index; baPWV, brachial – ankle pulse wave velocity; BFR, body fat rate; BFV, body fat volume; BMI, body mass index; DBP, diastolic blood pressure; SBP, systolic blood pressure; WC, waist circumference.

Clinical application

To verify the clinical benefits, that is, the net benefits of patients with high body fat by baPWV, we conducted a clinical decision analysis on the baPWV. The decision curve analysis and clinical impact curves of the risk of high body fat prediction is presented in Figure 3. The figure showed that for a threshold probability of 1.8% to 3.1%, the application of baPWV for predicting waistline>80 cm would add net benefit compared to either the treat-all strategy or the treat-none strategy. In addition, for a threshold probability of>1.8%, the application of baPWV for predicting high BFR and high BMI would add net benefit. The decision curve indicated that the risk of high body fat has a good effect on guiding clinical practice, of which baPWV has the most net benefits in predicting waist circumference.

Figure 3. Performance of baPWV in predicting waist circumstance>80 cm, high body fat rate and high BMI by baPWV. (a) Decision curve analysis. The y-axis represents the net benefit. The colored lines indicate the indices of high body fat risk. The thin solid line represents the assumption that all patients have high body fat. The thick solid line represents the assumption that no patients have high body fat. (b)(c)(d) Clinical impact curves. The solid lines with 95% CI mean the numbers of people classified as high risk by baPWV at each threshold probability, dashed line means the true positive numbers at each threshold probability. baPWV, brachial – ankle pulse wave velocity; BFR, body fat rate; BMI, body mass index; DBP, diastolic blood pressure; SBP, systolic blood pressure; WC, waist circumference.

Discussion

The relationship between baPWV and obesity, particularly BMI, is still controversial. One previous study reported a correlation between baPWV and BMI or WC only in women but not in men (18), another study also observed a negative relationship between BMI and baPWV in male hypertension populations (14). These findings are inconsistent with our study and other studies (10,12,19). Notably, a previous study in a pooled analysis of diet- and surgery-induced weight loss showed that aortic arch PWV decreased by an average of 0.2 m/s (2%) (10), while a recent study demonstrated that weight loss of nearly 10% was associated with improvements in aortic arch PWV (7.8%) in the exercise plus moderate caloric restriction group (20). These results suggest that reducing body weight can lower PWV, supporting the association of baPWV with obesity.

In our study, the results showed that baPWV was an independent risk factor for WC, BMI, BFR, and BFV, but not for BMR. WC, BMI, BFR, and BFV are all indicators of obesity onset and progression, whereas BMR is biased toward individual metabolic profiles. This suggests that baPWV could be a potential marker for predicting the onset or progression of obesity, but not for metabolism, and these findings have not been previously reported. The reasons why baPWV might be a potential marker for predicting obesity onset or progression are unclear. Our results demonstrated that baPWV was an independent risk factor for SBP (increased), DBP (increased), SBP (decreased), and DBP (decreased), and baPWV was positively associated with WC, BMI, and BFV mainly through indirect effects mediated by SBP and DBP, and baPWV was associated with BFR through both direct and indirect pathways. Arterial stiffness is a critical cause of isolated systolic hypertension (1), and excessive caloric intake interacting with an inappropriately activated renin-angiotensin-aldosterone system and inflammation promotes vascular insulin resistance, decreased bioavailable NO, maladaptive immune inflammatory response, and dysfunctional perivascular adipose tissue, all of which contribute to cardiac and vascular stiffness (21). Obesity is strongly associated with high blood pressure (22,23), results suggest that baPWV plays a role in predicting obesity mainly by affecting changes in blood pressure. A previous study showed that each unit increase in body mass index and systolic BP significantly increased PWV in children, suggesting an interactive relationship between obesity, hypertension, and arterial stiffness. Additionally, in our study, BFR better reflects the amount of body fat in an individual compared to WC, BMI, or BFV. This suggests a better correlation between baPWV and visceral fat, which is consistent with previous findings (18).

One of the main limitations of this study is that it is a cross-sectional study, which means that we cannot establish a cause-and-effect relationship between baPWV and the body fat-related indicators we examined. Additionally, our study did not have a long-term follow-up of participants, so we cannot assess the predictive value of baPWV for the onset or progression of obesity or cardiovascular disease.

Conclusion

Our finding demonstrated that baPWV correlated with obesity and served as an independent risk factor for WC, BMI, BFR, and BFV. Furthermore, our results suggest that baPWV’s positive association with WC, BMI, and BFV is mainly mediated indirectly through SBP and DBP, while its association with BFR is both direct and indirect. Our study provided new evidence to explain the relationship between arterial stiffness, hypertension, and obesity.

Authors’ contributions

WP collected and analyzed the data, drafted the manuscript.

LGH and WX collected the data, YRT analyzed the data, interpreted the results and drafted the manuscript. MJ drafted the manuscript, organized and supervised the study. All authors read and approved the final manuscript.

Acknowledgments

We thank Pidu District People’s Hospital and Meishan City People’s Hospital for their help in clinical data collection.

Disclosure statement

No potential conflict of interest was reported by the author(s).

Correction Statement

This article has been corrected with minor changes. These changes do not impact the academic content of the article.

Additional information

Funding

Studies were funded by the National Natural Science Foundation of China (No. 81900404), the Postdoctoral Research Foundation of Chongqing Medical University (No. 2-01-02-04-P0474).