Arterial stiffness and wave reflection profiles in patients with asthma: the role of hemodynamic determinants

Abstract

Background:

Asthma is a heterogeneous inflammatory airway disease increasingly recognised to be associated with elevated cardiovascular risk. Arterial stiffness, commonly assessed by pulse wave velocity (PWV), is a well-established predictor of cardiovascular events. However, it remains unclear whether vascular involvement in asthma reflects true arterial stiffening or predominantly altered arterial wave reflection.

Objectives:

To investigate arterial stiffness and wave reflection characteristics in patients with controlled and uncontrolled asthma compared with healthy controls.

Design:

Cross-sectional observational study.

Methods:

A total of 158 participants (56 healthy controls, 50 patients with controlled asthma, and 52 patients with uncontrolled asthma) underwent non-invasive arterial stiffness and hemodynamic assessments. Peripheral and central blood pressures, PWV, augmentation pressure, augmentation index and reflection magnitude were measured. Group comparisons were performed using unadjusted analyses and multivariable analysis of covariance (ANCOVA). Multivariate analysis of covariance (MANCOVA) was used to evaluate wave reflection parameters simultaneously, adjusting for age, body mass index, smoking status, heart rate and systolic blood pressure.

Results:

PWV differed significantly between groups in unadjusted analyses, with higher values observed in asthma groups. However, this association was no longer significant after multivariable adjustment, with age and systolic blood pressure emerging as the strongest independent determinants of PWV. In contrast, MANCOVA revealed a significant overall group effect on wave reflection parameters. Subsequent univariate analyses demonstrated that reflection magnitude remained significantly higher in both controlled and uncontrolled asthma groups compared with healthy controls after adjustment, whereas augmentation pressure and augmentation index did not show independent group effects.

Conclusion:

Vascular involvement in asthma appears to be characterised primarily by altered arterial wave reflection rather than overt arterial stiffening. These findings suggest that vascular alterations observed in asthma are primarily related to changes in arterial wave reflection and may be influenced by systemic hemodynamic factors (e.g. blood pressure and body composition), rather than asthma control itself.

Plain language summary

Blood vessel function in asthma: why wave reflection matters more than arterial stiffness

People with asthma showed differences in blood vessel function compared with individuals without asthma; however, after accounting for age and blood pressure, asthma was not independently associated with increased arterial stiffness. In contrast, blood pressure wave reflection remained higher in people with asthma regardless of asthma control status, suggesting that vascular involvement in asthma may primarily reflect early functional hemodynamic changes rather than permanent arterial stiffening. These findings indicate that assessing wave reflection parameters may add value to cardiovascular risk evaluation in patients with asthma beyond standard measures of arterial stiffness.

Keywords

arterial stiffness asthma asthma control hemodynamic determinants pulse wave velocity wave reflection

Introduction

Asthma is a heterogeneous disease characterised by chronic airway inflammation associated with airway hyperresponsiveness to direct or indirect stimuli. Treatment aims to control asthma by suppressing inflammation.¹ Asthma control can be assessed using tests such as the Asthma Control Test (ACT), a 5-question questionnaire completed by the patient. A score above 20 indicates that asthma is under control.^1–3

Arterial stiffness parameters have been shown to be highly associated with cardiovascular (CV) events. The gold standard measurement is carotid–femoral pulse wave velocity (PWV).⁴ In the Framingham study, high PWV was associated with a 48% increase in the risk of a first major CV event even after adjusting for classic risk factors.⁵ Among arterial stiffness parameters, augmentation index (AIx) and augmentation pressure (AP) are sensitive to arterial stiffness, wave reflection timing and amplitude, heart rate, height, age and blood pressure. AIx is strongly associated with systemic vascular resistance and more weakly with PWV; in multivariate models, age and systemic vascular resistance are the most significant predictors of AIx.⁶ Mechanical models and in vivo data have shown that AIx is not a pure ‘wave reflection magnitude’ or pure stiffness measure; it also reflects cardiac contraction properties.⁷ PWV, particularly carotid–femoral measurement, reflects aortic (macrovascular) stiffness and is a strong, independent biomarker for CV events/death. Wave reflection measures (Pb, reflection magnitude, AP, AIx), on the other hand, primarily reflect the interaction between aortic stiffness and peripheral resistance and reflection regions; therefore, they can provide complementary but more complex information than PWV. Therefore, wave reflection parameters can be considered integrated indicators that reflect not only stiffness but also hemodynamic load and peripheral resistance components.

Various studies have reported that indicators of arterial stiffness may be elevated in asthma patients and that this condition is more closely associated with cardiovascular risk factors.^8–11 It has been recommended that arterial stiffness measurements be performed in patients with asthma to assess cardiovascular disease (CVD) risk.^8–10 In adults with asthma who underwent 24-h arterial stiffness monitoring, aortic PWV and AIx were higher in severe and uncontrolled asthma compared to mild–moderate asthma and controls, with nighttime values being even higher.¹² In the same asthma series, body mass index (BMI), age, systolic blood pressure and hypertension duration were reported to show strong correlations with PWV/AIx. However, these effects did not evaluate asthma control status, asthma duration and multiple arterial stiffness parameters simultaneously; multivariate analyses were used to a limited extent, and the relationships with the drugs used were not sufficiently clarified.⁹

Asthma is primarily a disease of airway inflammation, and disease control is mainly pursued to reduce symptoms, prevent exacerbations and limit treatment-related morbidity.¹ Systemic inflammatory activity may be increased in patients with frequent exacerbations and more severe disease,¹³ and some studies have suggested a potential link between increased inflammatory burden and oxidative stress.^13,14 However, oxidative stress is not considered a central driver of asthma management, and its role in cardiovascular alterations remains less clearly defined. In contrast, increasing evidence highlights the contribution of treatment-related factors, particularly oral corticosteroid exposure, to cardiovascular risk in asthma.¹⁵ Despite these observations, relatively few studies have directly compared asthma control levels with arterial stiffness and wave reflection parameters.

In most existing studies, PWV has been evaluated alone, while wave reflection parameters have either not been examined at all or have not been considered together in multivariate models. However, it has been observed that parameters such as reflection magnitude, AP and augmentation index have not been sufficiently studied in asthma, and models that examine them together have been investigated primarily when considered individually.^11,16,17 It has been suggested that evaluating these parameters together (multivariate) may be more meaningful from a pathophysiological perspective.

In this study, arterial stiffness and pulse wave reflection parameters were evaluated in healthy individuals and patients with controlled and uncontrolled asthma using multivariate models to assess their effects independent of asthma control level and traditional cardiovascular risk factors.

Hypothesis 1: In asthma patients, particularly those with uncontrolled asthma, PWV may be higher than in healthy individuals; however, the independence of this relationship from traditional cardiovascular risk factors may be limited.

Hypothesis 2: The wave reflection profile (especially reflection magnitude) in asthmatic patients may differ from that in healthy individuals, and these differences may become more pronounced when multiple wave reflection parameters are evaluated together.

Hypothesis 3: Reflection magnitude may be higher in asthmatic patients compared to healthy controls, and this relationship may persist independently of age, blood pressure and other traditional risk factors.

The aim of this study was not only to assess arterial stiffness via PWV but also to evaluate whether vascular involvement in asthma is better characterised by alterations in wave reflection parameters, which reflect integrated hemodynamic load rather than purely structural arterial stiffness.

Methods

Study population

Participants were enrolled in the cross-sectional study at the Pulmonology and Cardiology Outpatient, a tertiary hospital, between June and December 2025. Using power analysis (G*Power), with a type 1 error rate of 5%, a power of 90%, and a high effect size (0.4), the minimum sample size required was 138 participants. The study groups were planned based on the power analysis, with a target sample size of approximately n = 49 per group: healthy controls, uncontrolled asthma and controlled asthma. After application of the inclusion and exclusion criteria, a total of 158 participants, including 102 asthma patients and 56 healthy controls, formed the final study sample. Participants were recruited consecutively from outpatient clinics during the study period.

Healthy controls: Healthy controls were recruited from individuals undergoing routine health evaluations, including pre-employment or general medical assessments, and had no known cardiovascular or metabolic disease. These individuals were not evaluated due to active clinical complaints.

Uncontrolled Asthma group: Patients with a physician-diagnosed asthma according to current international guidelines, who were followed in the pulmonary outpatient clinic and met the criteria for uncontrolled asthma. Uncontrolled asthma was defined as an ACT score < 20 despite regular inhaled controller therapy. Patients in this group were clinically stable at the time of arterial stiffness assessment and were not experiencing an acute exacerbation.

Controlled Asthma group: Patients with a physician-diagnosed asthma who were followed in the pulmonary outpatient clinic and met the criteria for controlled asthma, defined as an ACT score ⩾ 20. All patients in this group were receiving regular inhaled maintenance therapy and were clinically stable at the time of arterial stiffness measurement.

During the study recruitment period, 192 patients with asthma were recruited from the Chest Diseases and Cardiology Outpatient Clinic at a tertiary hospital. Of these, 34 patients were excluded due to additional physical illnesses and comorbid chest pathologies, 12 patients due to inability to complete the spirometry test, nine patients due to coronary artery disease, and thirteen patients due to dyslipidemia diagnoses. The remaining 158 individuals and 56 healthy participants formed the final study sample. According to the Global Initiative for Asthma (GINA) 2025 guidelines, patients diagnosed with asthma by a pulmonologist were included as participants.¹

Inclusion criteria: Participants must meet the study’s group definitions, be between 18 and 65 years of age, and have no contraindications to participating in the study or to administering the scale.

Exclusion criteria: Individuals with acute infections or other systemic diseases and those with major cardiometabolic diseases that could directly affect arterial stiffness were excluded from the study. Individuals with known cardiovascular disease (e.g. coronary artery disease), hypertension, diabetes mellitus, dyslipidemia, chronic kidney disease, or any acute or chronic systemic inflammatory condition were excluded.

Data collection tools

Socio-demographic and Clinical Data Form: This form includes basic socio-demographic information such as age, gender and occupation. Clinical data such as duration of asthma, smoking duration (pack-years), comorbidities, medications used and number of asthma attacks in the previous year are also recorded.

Spirometry: Spirometric measurements were performed using EasyOne Connect[3.7.1.9] and Medizintechnik, Switzerland, in accordance with ATS/ERS guidelines. Predicted spirometric values were calculated using device-based reference equations, which are not specifically derived from the Turkish population.¹⁸

Asthma Control Test: The Turkish version of the ACT, adapted by Uysal et al., consists of five questions (Cronbach’s alpha: 0.84). The total ACT score is calculated by adding 1–5 points to each question.^2,3 A total score of 25 points indicates complete asthma control, 20–25 points indicates partial asthma control, and < 20 points indicates uncontrolled asthma.

Arterial Stiffness Device: Arterial stiffness and cardiovascular hemodynamic parameters were assessed using the Mobil-O-Graph NG^® device (I.E.M. GmbH, Stolberg, Germany), a validated oscillometric system for noninvasive pulse wave analysis. The device was used to measure peripheral systolic and diastolic blood pressure, mean arterial pressure, pulse pressure, central pulse pressure, cardiac output, total peripheral resistance, AP, reflection magnitude and PWV. The Mobil-O-Graph NG^® system has been previously validated for the assessment of central hemodynamic parameters and pulse wave velocity using oscillometric pulse wave analysis methods.^19,20 PWV values obtained by Mobil-O-Graph represent the estimated aortic PWV derived from brachial oscillometric waveforms.

All measurements were performed in the morning under standardised conditions. Participants were seated comfortably and allowed to rest for at least 10 min before the measurement. An appropriately sized cuff was selected for each individual and placed on the upper arm. During the measurement, the cuff was automatically inflated to a suprasystolic pressure level to occlude the brachial artery transiently. Pressure waveforms generated by arterial pulsations were recorded by high-fidelity pressure sensors integrated into the cuff.

The recorded pulse waveforms were subsequently analysed using the HMS Client Server software (Version 4.7.1^®, I.E.M. GmbH, Stolberg, Germany), which applies a validated transfer function to derive central hemodynamic parameters and arterial stiffness indices. The same trained operator obtained all measurements to minimise inter-observer variability.

This study was approved by a local scientific research ethics committee. Written informed consent was obtained from all participants. The study was conducted in accordance with the principles of the Declaration of Helsinki and its latest revision.

Statistical analysis

Statistical analyses were performed using IBM SPSS Statistics for Windows, Version 27.0 (IBM Corp., Armonk, NY, USA). The normality of the data distribution was assessed using the Kolmogorov–Smirnov and Shapiro–Wilk tests. Numerical data were presented as mean ± standard deviation (SD) for normally distributed variables and as median (interquartile range, Q1–Q3) for non-normally distributed variables. Categorical variables were expressed as frequency and percentage (%).

Comparisons among the three study groups were performed using one-way analysis of variance (ANOVA) or the Kruskal–Wallis test, as appropriate. Post-hoc analyses were conducted using Tukey, Games–Howell, or Bonferroni correction depending on variance homogeneity. Categorical variables were compared using the chi-square test.

PWV was defined as the primary marker of arterial stiffness. Unadjusted group differences were first evaluated using ANOVA. Subsequently, analysis of covariance (ANCOVA) was applied to assess adjusted group differences in PWV, controlling for age, BMI, systolic blood pressure, heart rate and smoking status. Adjusted marginal means and 95% confidence intervals were reported. Type III sums of squares were used because of unequal group sizes.

To evaluate whether asthma status was associated with an overall alteration in arterial wave reflection profile, a multivariate analysis of covariance (MANCOVA) was performed, including reflection magnitude, AP and augmentation index as dependent variables, adjusted for the same covariates. When a significant multivariate effect was detected, univariate ANCOVA analyses were conducted for individual parameters. Asthma-specific variables such as disease duration and treatment were not included in the primary ANCOVA/MANCOVA models, as these variables were not applicable to the healthy control group. To address this, additional regression analyses were performed within the asthma subgroup.

Hierarchical linear regression analysis was used to identify independent determinants of PWV. Variables were entered sequentially to represent clinical, anthropometric and hemodynamic domains. Changes in explained variance (ΔR²) were reported. Multicollinearity was assessed using tolerance and variance inflation factor values. Statistical significance was set at p < 0.05.

The reporting of this study conforms to the ‘Strengthening the Reporting of Observational Studies in Epidemiology (STROBE)’ guideline.²¹

Results

One hundred fifty-eight participants were included in the study (56 healthy controls, 52 uncontrolled asthma and 50 controlled asthma; Table 1). A significant difference in age was found between the groups, with the mean ages of the uncontrolled and controlled asthma groups being higher than that of the healthy control group (p = 0.026). Similarly, BMI was significantly higher in the asthma groups (p = 0.037).

Table 1.

Characteristics of participants (n = 158).

Variable	Healthy control (n = 56)	Uncontrolled asthma (n = 52)	Controlled asthma (n = 50)	p-Value
Age, years (mean ± SD)	43.6 ± 13.0	50.6 ± 14.3	49.1 ± 15.2	0.026
BMI (kg/m², mean ± SD)	27.2 ± 4.6	29.4 ± 5.6	29.2 ± 4.8	0.037
Sex, n (%)				0.029
Female	36 (64.3)	45 (86.5)	37 (74)
Male	20 (35.7)	7 (13.5)	13 (26)
Place of residence, n (%)				0.05
Urban	47 (83.9)	33 (63.5)	35 (70)
Rural	9 (16.1)	19 (36.5)	15 (30)
Marital status, n (%)				0.001
Married	40 (71.4)	42 (80.8)	31 (62)
Single	8 (14.3)	6 (11.5)	11 (22)
Widowed/Divorced	8 (13.3)	4 (7.7)	8 (16)
Educational level, n (%)				0.292
No formal education	2 (3.6)	2 (11.5)	2 (4)
Primary school	27 (48.2)	31 (59.6)	27 (59.6)
High school	10 (17.9)	7 (13.5)	10 (20)
University	17 (30.4)	8 (15.4)	11 (22)
Employment status, n (%)				0.008
Unemployed	21 (37.5)	34 (66.7)	25 (52.1)
Employed	27 (48.2)	10 (19.6)	12 (25)
Retired	8 (14.3)	7 (13.7)	11 (22.9)
Financial Status, n (%)				0.063
Low	11 (19.6)	20 (38.5)	12 (24.5)
Middle	20 (35.7)	21 (40.4)	22 (44.9)
High	25 (44.6)	11 (21.2)	15 (30.6)
Smoking status, n (%)				0.068
Current smoker	0 (0)	16 (30.8)	16 (32)
Former smoker	56 (100)	36 (69.2)	34 (68)
Comorbidity, n (%)				0.003
Yes	19 (33.9)	33 (63.5)	30 (60)
No	37 (66.1)	19 (36.5)	20 (40)
Pack-years, median (Q1–Q3)	2.0 (1.3–2.8)	3.9 (2.7–5.1)	3.7 (2.9–4.5)	0.014
ACT	−	13.2 ± 3.0	21.0 ± 2.1	<0.001
Asthma Attack in the past 12 months
Yes	−	31 (59.6)	11 (22)
No	−	21 (40.4)	39 (78)
Asthma Attack requiring hospitalisation in the last 12 months
Yes	−	4 (7.7)	0 (0)
No	−	48 (92.3)	50 (100)
Asthma treatment
ICS (Alone)	−	11 (21.2)	13 (26)
Low- to moderate-dose ICS+LABA	−	16 (30.8)	16 (32)
Moderate- to High-dose ICS+LABA	−	22 (42.3)	16 (32)
ICS+LABA+LAMA	−	3 (5.8)	5 (10)
FEV₁ (%predicted)	85.25 ± 14.9	79.67 ± 17.1	87.68 ± 13.5
FVC (%predicted)	89.87 ± 14.4	72.80 ± 13.2	78.96 ± 11.7

Values are presented as mean ± standard deviation or number (percentage) unless otherwise indicated. Group comparisons were performed using one-way ANOVA or Kruskal–Wallis test for continuous variables and chi-square test for categorical variables, as appropriate. ACT, asthma attacks, and treatment-related variables were applicable only to asthma groups. ICS dose categories were defined according to guideline-recommended equivalent daily doses.

ACT, Asthma Control Test; FEV1%, forced expiratory volume in one second; FVC, forced vital capacity; ICS, Inhaled Corticosteroids; LABA, Long Acting Bβ Agonist; LAMA, Long Acting Muscarinic Antagonist.

When asthma-specific clinical variables were examined, ACT scores were significantly lower in the uncontrolled asthma group (p < 0.001). The rate of asthma attacks in the past 12 months was higher in the uncontrolled asthma group, and attacks requiring hospitalisation were observed only in this group (Table 1).

Table 2 shows that, when arterial stiffness and wave reflection parameters were examined, PWV differed significantly between groups (p = 0.041). Post-hoc analyses revealed that PWV was higher in the uncontrolled asthma group compared to healthy controls. PWV values in the controlled asthma group were intermediate between the two groups and did not differ significantly. While unadjusted analyses suggested differences in PWV between groups, these differences were no longer significant after adjustment for age and other covariates.

Table 2.

Comparison of arterial stiffness and hemodynamic parameters between groups.

	Healthy control (n = 56, HC)	Uncontrolled asthma (n = 52), UA	Controlled asthma (n = 50), CA	Post hoc	p-Value
Peripheral blood pressure
pSBP (mmHg)	132.1 ± 19.1	133.5 ± 18.9	133.1 ± 16.8		0.929
pDBP (mmHg)	86.1 ± 10.4	86.8 ± 10.4	85.3 ± 12.2		0.796
MAP (mmHg)	107.2 ± 13.0	108.2 ± 12.8	107.1 ± 12.2		0.894
HR (1/min)	93.2 ± 16.3	87.6 ± 14.8	87.6 ± 13.9		0.085
PP (mmHg)	46.0 ± 15.2	46.7 ± 15.4	47.8 ± 15.8		0.841
Central/hemodynamic assessments
cSBP (mmHg)	120.1 ± 17.2	122.6 ± 16.5	121.4 ± 14.8		0.725
cDBP (mmHg)	87.8 ± 10.5	88.6 ± 10.5	87.0 ± 11.9		0.749
cPP (mmHg)	32.3 ± 11.4	34.0 ± 11.8	34.5 ± 11.0		0.578
CO (l/min)	5.0 ± 0.7	5.2 ± 0.8	5.2 ± 0.8		0.257
TPR (s × mmHg/ml)	1.30 ± 0.15	1.27 ± 0.19	1.25 ± 0.19		0.294
CI (l/min × 1/m²)	2.77 ± 0.48	2.84 ± 0.46	2.86 ± 0.49		0.618
BSA (m²)	1.82 ± 0.18	1.84 ± 0.19	1.84 ± 0.21		0.816
Arterial stiffness & wave reflection parameters
AP (mmHg)	8.1 ± 5.4	8.9 ± 6.7	8.0 ± 4.6		0.654
RM (%)	58.4 ± 8.8	61.4 ± 6.7	61.6 ± 8.4		0.075
AI (%)	31.7 ± 10.2	30.3 ± 11.7	28.9 ± 11.8		0.442
PWV (m/s)	7.01 ± 1.59^a	7.89 ± 2.04^b	7.58 ± 1.85^ab	HC vs UA	0.041

Values are presented as mean ± standard deviation unless otherwise indicated. Group comparisons were performed using one-way ANOVA. Post-hoc comparisons were conducted using Tukey or Games–Howell tests, as appropriate. Different superscript letters indicate statistically significant differences between groups.

AI, Augmentation Index; AP, augmentation pressure; BSA, body surface area; CA, Controlled asthma; cDBP, central diastolic blood pressure; CI, cardiac index; CO, cardiac output; cPP, central pulse pressure; cSBP, central systolic blood pressure; HR, heart rate; HC, Healthy control; MAP, mean arterial pressure; pDBP, peripheral diastolic blood pressure; PP, pulse pressure; pSBP, peripheral systolic blood pressure; PWV, pulse wave velocity; RM, reflection magnitude; TPR, total peripheral resistance; UA, Uncontrolled asthma.

Bold values indicate statistically significant results, including overall and post hoc comparisons (p < 0.05).

In unadjusted analyses, no significant differences were observed between groups in wave reflection parameters, including AP, reflection magnitude (RM), and augmentation index. However, subsequent multivariable analyses demonstrated significant differences in RM after adjustment, indicating that group differences in wave reflection became apparent after controlling for confounding factors.

As shown in Table S1, subgroup analyses by asthma treatment regimen (ICS alone, low-to-moderate dose ICS+LABA, moderate-to-high dose ICS+LABA and ICS+LABA+LAMA) revealed no significant differences in peripheral and central blood pressure measurements or hemodynamic parameters.

In the multivariate ANCOVA analysis reported in Table 3 to evaluate differences in PWV between groups, raw PWV values showed a significant group difference (p = 0.041). However, after adjusting for age, systolic blood pressure, BMI, pulse rate and smoking status, the difference between groups lost its statistical significance (p = 0.361).

Table 3.

Multivariable ANCOVA results for PWV.

Adjusted comparison of arterial stiffness between study groups
Variable	Healthy controls (n = 56)	Controlled asthma (n = 50)	Uncontrolled asthma (n = 52)	F	p-Value	Partial η²
Unadjusted PWV (m/s), mean ± SD	7.01 ± 1.59	7.58 ± 1.85	7.89 ± 2.04	3.259	0.041	0.040
Adjusted PWV (m/s), mean ± SE	7.43 ± 0.09	7.43 ± 0.09	7.58 ± 0.09	1.026	0.361	0.013
95% CI for adjusted PWV	7.26–7.60	7.26–7.60	7.41–7.75	–	–	–
Covariate effects in the ANCOVA model
Covariate		B (β)	Standard Error	F	p-Value	Partial η²
Age (years)		+0.101	0.004	617.06	<0.001	0.804
Systolic blood pressure (mmHg)		+0.035	0.003	149.40	<0.001	0.499
Body mass index (kg/m²)		−0.025	0.011	5.23	0.024	0.034
Heart rate (beats/min)		−0.004	0.003	1.03	0.313	0.007
Smoking status		−0.056	0.102	0.30	0.582	0.002

Model summary. R² = 0.895; Adjusted R² = 0.891; Error mean square = 0.376; Levene’s test (p) = 0.024. Values are presented as mean ± standard deviation (SD) for unadjusted analyses and adjusted mean ± standard error (SE) for ANCOVA results. The ANCOVA model was adjusted for age, body mass index, smoking status, heart rate and systolic blood pressure. Smoking status was included as a categorical covariate. Bonferroni correction was applied for pairwise comparisons. Although Levene’s test indicated mild heterogeneity, the ANCOVA results were considered robust due to balanced group sizes and the use of Type III sums of squares.

Age and systolic blood pressure emerged as the strongest independent predictors of PWV (p < 0.001 for both), while BMI showed a weaker but significant association (p = 0.024). Heart rate and smoking status were not independently associated with PWV.

These findings indicate that the differences in PWV observed in unadjusted analyses are largely explained by traditional cardiovascular determinants. In contrast, RM remained significantly associated with study groups after adjustment. In Table 4, the MANCOVA analysis evaluating wave reflection profiles in a multivariate manner showed that the study group variable was significant at the multivariate level (Wilks’ Lambda, p = 0.015; Pillai’s Trace, p = 0.017). This result indicates that wave reflection parameters differ between groups when considered together.

Table 4.

Multivariable multivariate analysis of covariance (MANCOVA) for wave reflection parameters.

Adjusted multivariate comparison of arterial wave reflection profiles between study groups
Effect	Test	Value	F	Hypothesis df	Error df	p-Value	Partial η²
Study group	Wilks’ Lambda	0.899	2.684	6	296	0.015	0.052
	Pillai’s Trace	0.101	2.637	6	298	0.017	0.050
	Hotelling’s Trace	0.111	2.731	6	294	0.013	0.053
	Roy’s Largest Root	0.109	5.390	3	149	0.002	0.098
Univariate follow-up tests (ANCOVA) for individual wave reflection parameters
Dependent variable		F		p-Value		Partial η²
Reflection magnitude		7.44		0.001		0.090
Augmentation pressure		0.60		0.553		0.008
Augmentation index		0.31		0.738		0.004
Covariates included in the multivariate model
Covariate		Multivariate p-Value				Partial η²
Age		0.469				0.017
Body mass index		0.001				0.099
Systolic blood pressure		<0.001				0.535
Smoking status		0.002				0.093
Heart rate		<0.001				0.619

Model characteristics: Multivariate general linear model, Type III sums of squares, Smoking status entered as categorical covariate, no significant multicollinearity detected, Box’s M test not violated. Multivariate significance was primarily driven by group differences in RM, whereas AP and augmentation index did not show independent group effects after adjustment.

Bold values indicate statistical significance at p < 0.05.

Follow-up analyses of individual variables revealed that the multivariate significance was primarily due to group differences in RM, whereas no independent group effect was found for AP or augmentation index. In the model, systolic blood pressure, pulse, BMI and smoking status were found to have significant multivariate effects on wave reflection parameters.

As shown in Table 5, in the univariate ANCOVA analysis for RM, a significant difference was found between groups in both raw and adjusted values (p = 0.001). In post-hoc analyses, the RM values in the healthy control group were significantly lower than those in both the controlled and uncontrolled asthma groups.

Table 5.

Adjusted group differences in reflection magnitude.

Univariate ANCOVA results for reflection magnitude
Variable	Healthy controls (n = 56)	Controlled asthma (n = 50)	Uncontrolled asthma (n = 52)	F	p-Value	Partial η²
Unadjusted reflection magnitude, mean ± SD	58.39 ± 8.79	61.56 ± 8.43	61.37 ± 6.75	7.44	0.001	0.090
Adjusted reflection magnitude, mean ± SE	57.42 ± 0.94	62.15 ± 0.97	61.85 ± 0.95	7.44	0.001	0.090
95% CI for adjusted means	55.57–59.27	60.24–64.06	59.97–63.74	–	–	–
Post-hoc pairwise comparisons (Bonferroni-adjusted) • Healthy controls versus Controlled asthma: p = 0.002 • Healthy controls versus Uncontrolled asthma: p = 0.004 • Controlled versus Uncontrolled asthma: p = 1.000
Covariate		B (β)	Standard error	F	p-Value	Partial η²
Age (years)		−0.028	0.045	0.40	0.530	0.003
Body mass index (kg/m²)		−0.481	0.122	15.53	<0.001	0.094
Systolic blood pressure (mmHg)		+0.260	0.036	50.93	<0.001	0.253
Heart rate (beats/min)		+0.062	0.039	2.61	0.108	0.017
Smoking status		+1.922	1.126	2.91	0.090	0.019

Values are presented as mean ± standard deviation (SD) for unadjusted analyses and adjusted mean ± standard error (SE) for ANCOVA results. The ANCOVA model was adjusted for age, body mass index, smoking status, heart rate and systolic blood pressure. A Bonferroni correction was applied for post-hoc comparisons. Type III sums of squares were used due to unequal group sizes.

Bold values indicate statistical significance at p < 0.05.

Post-hoc analyses revealed significant differences between healthy controls and controlled asthma (p = 0.002) and between healthy controls and uncontrolled asthma (p = 0.004), but no difference between the controlled and uncontrolled asthma groups.

In the model, BMI and systolic blood pressure emerged as the strongest independent predictors of RM (p < 0.001 for both). Age, pulse rate, and smoking status were not found to be independently significant.

To address the role of asthma-specific variables, an additional regression analysis was performed in the asthma subgroup (Table 6). The results demonstrated that RM was independently associated with systolic blood pressure and BMI, but not with asthma control after adjustment.

Table 6.

Multivariable linear regression analysis for reflection magnitude in asthma subgroup.

Dependent variable: Reflection magnitude (%)
Variable	B	Standard error	β	t	p-Value
(Constant)	55.74	6.47	–	8.62	<0.001
ACT total score	0.086	0.155	0.053	0.555	0.580
Age (years)	0.033	0.054	0.063	0.602	0.549
Sex	0.789	1.836	0.042	0.430	0.668
BMI (kg/m²)	−0.459	0.149	−0.313	−3.074	0.003
Systolic BP (mmHg)	0.119	0.043	0.281	2.775	0.007

Model Summary: R² = 0.158, Adjusted R² = 0.114, F = 3.589, p = 0.005. Multiple linear regression analysis was performed in the asthma subgroup (n = 102). Reflection magnitude was independently associated with systolic blood pressure and body mass index, whereas asthma control, age and sex were not independently associated.

Discussion

In the present study, arterial stiffness and pulse wave velocity parameters were compared between healthy individuals and controlled and uncontrolled asthma patients. Although the analyses revealed significant differences between the groups in terms of PWV, this relationship disappeared when key cardiovascular determinants such as age, systolic blood pressure, BMI, heart rate and smoking status were controlled for. This suggests that the PWV differences observed in asthmatic patients are largely explained by strong determinants, such as age and hemodynamic load, rather than by asthma-specific vascular stiffness. The fact that PWV is a parameter highly dependent on age and systolic blood pressure is the key factor explaining the weakening of the group effect in multivariate models. This finding is consistent with previous studies showing that PWV is highly dependent on age and systolic blood pressure.^11,12 In subgroup analyses restricted to asthma patients, asthma control and disease duration were additionally evaluated; however, these variables were not independently associated with RM after adjustment.

In contrast, the RM parameter of the wave reflection profile was significantly higher in asthmatic patients than in healthy controls in multivariate analyses, and this relationship persisted even after adjustment for traditional cardiovascular risk factors. This finding suggests that vascular involvement in asthma may be associated with functional changes in arterial load distribution and peripheral reflection characteristics rather than with initial structural arterial stiffness. Wave reflection parameters are more complex hemodynamic indicators that reflect the contributions of peripheral resistance and reflection regions, as well as aortic stiffness, and thus provide information distinct from and complementary to PWV. The literature has reported increased PWV in asthma studies, but findings on RM, AP and Alx have been reported to a limited extent.^11,16,17 Our findings suggest that arterial wave reflection may deteriorate early in asthmatic patients and that this may be associated with a hemodynamic burden that could be clinically significant in terms of cardiovascular risk.

Wave reflection parameters reflect the component of the pressure wave propagating forward in the arterial system that is reflected back from peripheral resistance areas, as well as the effect of this reflection on the central circulation.^22,23 RM provides a comprehensive indicator of arterial load distribution and peripheral reflection characteristics by expressing the ratio between forward and backward wave amplitudes.²³ In this study, the fact that RM remained significantly elevated in asthmatic patients even after multiple adjustments for key determinants such as age, systolic blood pressure, BMI, heart rate and smoking status, and that it was the main variable driving the group effect in the MANCOVA analysis, suggests that the findings are not random. In contrast, the lack of significance for other wave reflection indicators, such as the augmentation index (AIx) and AP, may be due to their greater sensitivity to heart rate, height and ventricular contraction characteristics. This physiological dependence may have limited Aix’s ability to reflect group differences after multiple adjustments.^7,22 In contrast, RM, due to its relatively independent structure from heart rate, better reflected peripheral reflection characteristics and revealed the group effect more clearly.

In the present study, multivariable regression analysis further demonstrated that RM was independently associated with systolic blood pressure and BMI, whereas asthma control was not independently related to this parameter. These findings may also partly reflect treatment-related effects, particularly oral corticosteroid exposure, which is known to be associated with increased blood pressure and BMI. However, as asthma control in this study was based on patient-reported measures, it may not fully capture disease severity. Future studies should further investigate arterial waveform parameters in relation to cumulative corticosteroid exposure. This finding suggests that the observed differences in wave reflection may be more strongly driven by systemic hemodynamic load, particularly systolic blood pressure and BMI, rather than disease control per se, and may partly reflect treatment-related effects such as oral corticosteroid exposure.

Asthma primarily affects the airways, but an increasing number of studies show that it has a systemic inflammatory component.¹³ It is suggested that, particularly in uncontrolled asthma, increased chronic inflammatory burden, disruption of autonomic nervous system balance, and changes in endothelial function may influence vascular responses through such mechanisms.^13,14,24 It appears biologically plausible that these processes alter reflection properties in peripheral resistance regions, increasing wave reflection without causing significant structural stiffening of the arterial wall. Indeed, endothelial dysfunction and impaired sympatho-vagal balance can affect arterial load distribution without a significant increase in PWV. However, due to the cross-sectional design of our study, it is not possible to establish a causal relationship between these mechanisms; the aforementioned explanations should be considered as possible pathophysiological pathways suggested in light of the current findings. These mechanisms may not be solely related to disease activity but could also reflect treatment-related effects. In addition, treatment-related factors, particularly intermittent exposure to oral corticosteroids in patients with more severe disease, may contribute to cardiovascular alterations in asthma, as demonstrated in large population-based studies. This may partly explain why RM differed between asthma groups independently of asthma control, suggesting that factors beyond disease activity, including treatment exposure, may contribute to the observed hemodynamic alterations.

These findings point to a clinically important issue: Even if classic indicators of arterial stiffness, such as blood pressure and PWV, are within normal limits in an asthmatic patient, wave reflection may be increased. This situation may indicate hemodynamic stress that places an additional burden on the central circulation, often overlooked in routine clinical evaluations. Increased wave reflection, detected particularly in patients with uncontrolled asthma, suggests that the cardiovascular risk window opens at an early stage. Therefore, focusing solely on symptom control in asthma management may not be sufficient; close monitoring and control of modifiable factors, such as body weight, pulse rate, systolic blood pressure and smoking, may be important for reducing cardiovascular risks. These findings may also be interpreted within the framework of the ‘treatable traits’ approach, emphasising the importance of managing modifiable risk factors such as blood pressure, body weight and smoking status in patients with asthma.

The majority of previous studies examining the relationship between asthma and arterial stiffness have focused primarily on a single parameter, such as PWV, and have included only limited multivariate analyses.^9,11,12 This approach makes it difficult to distinguish between different dimensions of vascular involvement. The present study is one of the few in the literature to distinguish between the structural and functional components of vascular involvement in asthma, simultaneously evaluating multiple arterial stiffness and wave reflection parameters and attempting to distinguish between these components using the MANCOVA approach. Our findings indicate that vascular involvement in asthma is heterogeneous and that early functional changes, which may be more clinically meaningful than arterial stiffness, could occur at the level of wave reflection.

This study has some limitations. First, the cross-sectional design does not allow for assessing the direction of vascular changes over time or their clinical outcomes. The study was conducted at a single centre, and the lack of long-term cardiovascular outcome data may also limit its generalisability. In addition, differences in age and sex distribution between the groups represent important limitations, given their known influence on cardiovascular parameters. Although multivariable adjustment was performed, residual confounding cannot be excluded. Another limitation is that spirometric predicted values were calculated using device-based reference equations that are not specifically derived from the Turkish population, which may have influenced the absolute values observed in the control group. Finally, asthma-specific variables such as treatment exposure and cumulative corticosteroid use were not directly quantified.

Conclusion

In conclusion, vascular alterations in asthma appear to be characterised primarily by changes in arterial wave reflection rather than structural arterial stiffness. These changes seem more closely related to systemic hemodynamic factors, particularly blood pressure and body composition, rather than to asthma control itself, and may partly reflect treatment-related effects, such as exposure to oral corticosteroids.

Supplemental Material

sj-docx-1-tar-10.1177_17534666261454200 – Supplemental material for Arterial stiffness and wave reflection profiles in patients with asthma: the role of hemodynamic determinants

Supplemental material, sj-docx-1-tar-10.1177_17534666261454200 for Arterial stiffness and wave reflection profiles in patients with asthma: the role of hemodynamic determinants by Şaban Melih Şimşek, Gökhan Gök, Hayriye Bektaş Aksoy, Selda Günaydın and Numan Kılıç in Therapeutic Advances in Respiratory Disease

Supplemental Material

sj-docx-2-tar-10.1177_17534666261454200 – Supplemental material for Arterial stiffness and wave reflection profiles in patients with asthma: the role of hemodynamic determinants

Supplemental material, sj-docx-2-tar-10.1177_17534666261454200 for Arterial stiffness and wave reflection profiles in patients with asthma: the role of hemodynamic determinants by Şaban Melih Şimşek, Gökhan Gök, Hayriye Bektaş Aksoy, Selda Günaydın and Numan Kılıç in Therapeutic Advances in Respiratory Disease

Footnotes

Acknowledgements

None.

Declarations

ORCID iDs

Şaban Melih Şimşek

Gökhan Gök

Hayriye Bektaş Aksoy

Selda Günaydın

Numan Kılıç

Supplemental material

Supplemental material for this article is available online.

Use of AI for writing assistance

No generative artificial intelligence tools were used in the development of the scientific content of this manuscript. Language editing and grammar corrections were performed using Grammarly.

Clinical trial number

Not applicable.

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