Stress-induced cardiac autonomic reactivity and preclinical atherosclerosis: does arterial elasticity modify the association?

Abstract

The effect of acute mental stress on atherosclerosis can be estimated using arterial elasticity measured by carotid artery distensibility (Cdist). We examined the interactive effect of acute stress-induced cardiac reactivity and Cdist to preclinical atherosclerosis assessed by carotid intima-media thickness (IMT) in 58 healthy adults aged 24–39 years participated in the epidemiological Young Finns Study. Cdist and IMT were measured ultrasonographically. Impedance electrocardiography was used to measure acute mental stress-induced cardiac autonomic responses: heart rate (HR), respiratory sinus arrhythmia and pre-ejection period after the mental arithmetic and the public speaking tasks. Interactions between HR reactivity and Cdist in relation to preclinical atherosclerosis were found. The results imply that elevated HR reactivity to acute mental stress is related to less atherosclerosis among healthy participants with higher arterial elasticity. Possibly, increased cardiac reactivity in response to challenging tasks is an adaptive reaction related to better cardiovascular health.

• Acute mental stress
• cardiovascular diseases
• cardiovascular ultrasound
• carotid artery distensibility
• heart rate
• intima-media thickness

Introduction

Atherosclerosis – the fundamental pathology of cardiovascular diseases (CVD) – has complex etiology with multiple factors, including elevated blood cholesterol, inflammation, hypertension, smoking, obesity, and diabetes, contributing to its development. Damaging of endothelium is the first stage of atherosclerosis rendering the endothelium vulnerable to the accumulation of lipids (Ross, 1993). This process leads to arterial wall thickening and reducing arterial elasticity (increasing arterial stiffness). Artery stiffening is one of the key factors of cardiovascular events risk (Correia & Haynes, 2007). Increased local arterial stiffness reflects early arterial functional abnormalities even in individuals with normal intima-media thickness (IMT) (Novo et al., 2013). Carotid IMT is an index of general atherosclerosis widely used for the detection of the disease (O'Leary & Polak, 2002).

Individual differences in acute mental stress reactivity are related to hypertension and increased IMT (Chida & Steptoe, 2010) and, therefore, to future CVD development (Hintsa et al., 2012). The associations between cardiac autonomic stress responses and future CVD, however, depend on prior cardiovascular health. Poor cardiovascular health has been suggested to interact with stress responses in producing CVD outcomes. The health effects of stress responses may be more profound in people with deteriorated endothelial functioning. Associations between stress and CVD vary according to whether it is studied in healthy populations or in populations with diminished vascular health. However, even in healthy subjects, vascular functioning is sensitive to acute mental stress, which induces both transient (Ghiadoni et al., 2000) and prolonged (Spieker et al., 2002) endothelial dysfunction. Endothelial dysfunction reflects impaired functioning of endothelium that leads to decreased arterial elasticity (Correia & Haynes, 2007). Acute mental stress has been shown to reduce vascular elasticity and injure endothelium (Tsai et al., 2003).

Autonomic nervous system (ANS) imbalance with heightened sympathetic activity and reduced parasympathetic drive is one potential mechanism of atherosclerosis and CVD development (Marwah et al., 2007). Acute mental stressors influence autonomic function by sympathetic or parasympathetic tone alteration (Cacioppo et al., 1994). Pre-ejection period (PEP) is commonly used as an indicator of cardiac sympathetic control (Cacioppo et al., 1994), whereas respiratory sinus arrhythmia (RSA) – as an index of parasympathetic function (Berntson et al., 1997; Cacioppo et al., 1994). Heart rate (HR) reflects the sympathetic/parasympathetic balance (Palatini, 1999). Supressed ANS control is related with atherosclerotic processes and CVD through the negative influence on endothelium (Harris & Matthews, 2004).

This study investigates whether the effect of acute mental stress-related cardiac reactivity on atherosclerosis depends on arterial elasticity assessed by carotid artery distensibility (Cdist). Arterial distensibility, which is defined as the vessel diameter change during systole and diastole divided by pulse pressure was estimated noninvasively with ultrasound (Juonala et al., 2005). Reduced Cdist indicates vascular stiffening and it has been related to autonomic balance alterations and to adverse outcomes for the cardiovascular system (Giannattasio & Mancia, 2002; Koskinen et al., 2011). We hypothesize that autonomic stress responses will have less detrimental atherosclerotic effects in individuals with healthier arteries (as measured by higher Cdist) compared to individuals with less-healthy arteries. Preclinical atherosclerosis was assessed by carotid IMT. Common carotid IMT is a marker of total atherosclerotic alterations in human arteries and it serves as a validated indicator of cardiovascular risk (O'Leary & Polak, 2002). Increased IMT and decreased Cdist are markers of preclinical atherosclerosis (Juonala, 2005).

Methods

Sample

The participants are derived from one of the largest population-based epidemiological national studies – the on-going prospective Young Finns Study, which was established at the end of the 1970s to examine cardiovascular risk factors from childhood to adulthood (Raitakari et al., 2008). In 1980, 3596 subjects (children, adolescents and young adults) participated in the baseline study. Thereafter, several follow-up studies are carried out at intervals of 3 or 5 years. Of the original sample, 2109 participants had data on ultrasound investigations taken in 2001 (21-year follow-up). In 1999, the stress testing (the public speaking task and the mental arithmetic task) was administered in a subsample of 95 participants. In this study, complete data on psychophysiological reactivity, ultrasound and clinical measurements was obtained from 58 participants (due to missing data in some of the variables) who took part in psychophysiological experiment in 1999. The study was approved by local ethics committees in Helsinki, Turku and Tampere Universities and conducted according to the guidelines of the Helsinki Declaration. In 1999 and in 2001, all participants gave their written, informed consent.

Ultrasound imaging

Ultrasound investigations were performed using Sequoia-512 ultrasound mainframes (Acuson, Mountain View, CA) with 13.0 MHz linear array transducer between September 2001 and January 2002 (Raitakari et al., 2003). Re-examination, 3 months after the initial visit, was conducted for 57 participants (2.5% random sample) to evaluate intra-individual reproducibility of ultrasound measurements.

Carotid intima-media thickness

Carotid intima-media thickness (IMT) was measured on the posterior (far) wall of the left carotid artery in accordance with standardized protocol (Raitakari et al., 2003). To assess mean carotid IMT, four measurements were taken approximately 10 mm proximal to the bifurcation. We reported a 6.4% between-visit coefficient of variation of IMT measurements (Raitakari et al., 2003).

Carotid artery distensibility

Moving image clips of the beginning of the carotid bifurcation and the common carotid artery with duration of 5 s were acquired and stored in digital format for subsequent offline analysis (Juonala et al., 2005). The best quality cardiac cycle was selected from the clip images. The carotid diameter was measured at least twice (spatial measurements) in end diastole and end systole, respectively. The mean of the measurements was used as the end-diastolic or end-systolic diameter. During the ultrasound study, systolic blood pressure (SBP) and diastolic blood pressure (DBP) were measured with an automated sphygmomanometer (Omron M4, Omron Matsusaka Co., Ltd, Japan). Ultrasound and concomitant brachial blood pressure (BP) measurements were used to calculate Cdist = ([D_s − D_d]/D_d)/(P_s − P_d), where D_d is the diastolic diameter; D_s, the systolic diameter; P_s, SBP; and P_d, DBP. The between-visit coefficient of variation was 2.7% for diastolic diameter and 16.3% for Cdist (Juonala et al., 2005).

Cardiovascular risk factors

Cardiovascular risk factors were measured in 2001; all measurements of lipids levels were performed in duplicate in the same laboratory using standard methods: standardized enzymatic methods – for measuring levels of triglycerides and serum high-density lipoprotein (HDL) cholesterol (Raitakari et al., 2003); the Friedewald formula was used to calculate serum low-density lipoprotein (LDL) cholesterol concentration (Friedewald et al., 1972). For measuring serum insulin, microparticle enzyme immunoassay kit (Abbott Laboratories, Diagnostic Division, Dainabot, Japan) was used. Height and weight were measured, and body mass index (BMI) was calculated as participants' weight (kg) divided by their height (m²). Blood pressure was measured with a random-zero sphygmomanometer (Raitakari et al., 2003). Average of three BP measurements was used in the analysis.

Experimental procedure to examine stress reactivity

Before the experimental procedure, the subjects were informed about the nature of the study and they gave written informed consent. The experiment was conducted in a sound-attenuated room equipped with a video system. Each participant was studied using a standardized computer-controlled protocol. The following five tasks were used: (1) emotion-evoking picture viewing, (2) acoustic startle stimuli, (3) a mental arithmetic task, (4) a reaction-time task, and (5) a public-speaking task. The experiment started and ended with a resting period of 10 min, each task was followed by a rest period; thus, experimental procedure included five tasks and six resting periods. The stress studies were performed at a single site. In the present study, the emotion-evoking picture-viewing task, the acoustic startle and the reaction-time task were omitted. The mental arithmetic task and the speech task were used because these tasks are active coping tasks, which require active behavioral responses; they produce stable and uniform reactivity profiles: an increase in HR, a decrease in RSA, and a shortening of PEP (Al’Absi et al., 1997; Cacioppo et al., 1994). The public speaking task is considered a natural stressor, which involves social-evaluative elements and happens frequently in daily life (Al’Absi et al., 1997). Mental arithmetic is an active coping task with appetitive elements (a reward was given for the best performance), which involves sensory rejection and influences working memory (Al’Absi et al., 1997).

Mental arithmetic

During the mental arithmetic task, the participants were asked to perform continuously six 1-min serial subtraction problems. The minuend was 297, 688, 955, 593, 1200 and 1741 for minutes 1, 2, 3, 4, 5 and 6, respectively. The subtrahend in minute 1 was 3. To maintain maximal task involvement and moderate task difficulty (i.e., approximately 10 correct answers/min), the subtrahend specified for each subsequent minute was contingent on the participant’s performance during the preceding minute. The minuend and the subtrahends were presented on the computer screen, and participants gave their answers using the keyboard. The participants were informed that the three best participants would be awarded a prize of $40, which made mental arithmetic an appetitive task.

Speech task

In the speech task, the participants were asked to construct a 3-min public speech after a 3-min preparation period. An audience (one male, one female) presented in the room during giving speech and the speech was videotaped. The participants were told that the speech would be evaluated later and that the best-rated speeches would be awarded a prize of $40. Three different scenarios for constructing speeches were suggested (Al'Absi et al., 1997). The scenarios were presented in a counterbalanced order: (a) a presentation based on a Reader’s Digest article about the need for sleep (high in informational content but lacking emotional content); (b) the participant’s own reasoned opinion about homosexuals’ rights to marry and adopt children (at that time a much discussed topic in the media); and (c) a speech in which the participants were to defend themselves in a hypothetical scenario in which they were wrongly accused of shoplifting. The speech task has a great deal of social relevance and ecological validity (Al’Absi et al., 1997).

Cardiac measures and data treatment

Heart rate, RSA and PEP were assessed with impedance electrocardiography. Electrocardiogram (ECG) and the first derivative of the pulsatile impedance signal (dZ/dt) were measured continuously during the experiment with Minnesota Impedance Cardiograph Model 304B (Surcom Inc., Minneapolis, MN), using the standard tetrapolar band electrode configuration (Sherwood et al., 1990). The ECG and dZ/dt signals were sampled continuously at 500 Hz via a 12-bit 8-channel A/D converter and stored on the hard disk of a PC. Custom-programmed Labview data acquisition software (National Instruments Co., Austin, TX) was used for on-line data reduction. The interbeat intervals (IBIs), in ms, were determined from the ECG signal and deviant IBI values were identified using a 20% change from the previous IBI as a criterion. They were corrected following the guidelines of Porges & Byrne (1992). The beat-to-beat IBI data were transformed to equidistant IBI time series with 200 ms intervals using the weighted-average interpolation method (Cheung & Porges, 1977). The spectral analyses were conducted on 60 s segments of the heart period series. To exclude long-term changes in the time series, the mean and trend were removed from each IBI segment. The impedance data were ensemble averaged within 60 s blocks. The Q-wave positions in the ECG and the B-point in the dZ/dt signal were detected by visual examination with the assistance of self-programmed software (Labview, National Instruments Co., TX).

Heart rate (in bpm) was calculated for each participant in 60-s interval from the mean IBI. We computed RSA separately for each 60 s data segment. The logarithm of the variance (ms²) within the frequency band associated with respiration (i.e. 0.12–0.40 Hz) was summed to index RSA (Berntson et al., 1997). We computed PEP as the interval (in ms) between the Q wave of the ECG and the B-point of the dZ/dt waveform (Cacioppo et al., 1994).

Means of HR, RSA and PEP were calculated for each subject across each minute during the tasks. Task HR, RSA and PEP data were averaged across the 6 min of the mental arithmetic task and across the 3 min of each speech task. The mean of three speeches was calculated and only the speech delivery period was used in the present study. For calculating HR, RSA and PEP baselines data were averaged across minutes 6, 7 and 8 during the 10 min initial baseline. Reactivity scores were calculated by subtracting the initial mean baseline value from average task value (for each task separately). Finally, the averaged value for the reactivity score across the two tasks was calculated.

Statistical analysis

Statistical analyses were performed using PASW Version 21.0. We examined main effects of Cdist and cardiac autonomic measures with linear regressions; analyses were conducted separately for HR, RSA or PEP reactivity. Cdist was the dependent variable in unadjusted (examining associations between cardiac reactivity and Cdist) and age and gender adjusted models. Interactions between cardiac autonomic measures and Cdist on carotid IMT were tested by linear regression. All analyses on interactions were conducted separately for HR, RSA and PEP. In addition to Cdist and reactivity interactions, the effects of age, gender, Cdist, and the reactivity score measure in question as well as the interactive effects gender × Cdist, age × Cdist; reactivity score × age, reactivity score × gender were controlled for in Model 1. In Models 2–5, also cardiovascular risk factors main effects and their interactions with Cdist and with the reactivity score in question were additionally included: Model 2: adjusted for SBP and DBP; Model 3: adjusted for metabolic risk factors (plasma insulin and BMI); Model 4: adjusted for lipids levels (triglycerides, LDL and HDL cholesterols); Model 5: the fully adjusted model adjusted for BMI, plasma insulin, BP and lipids levels. When interactions between autonomic measures and Cdist on IMT were found, additional analyses were performed in high and low Cdist groups. That is, the associations between the autonomic measure in question and IMT were examined separately in the high Cdist group and in the low Cdist group. Also, in these analyses, first age and gender were used as covariates (Model 1), and additionally, the main effects of cardiovascular risk variables were included (Models 2–5: similarly, as it is described for interactions analyses).

Results

Table 1 shows characteristics of the study participants (N = 58).

Table 1. Characteristics of the study participants.

Variables	Mean	SD
Age in 2001 (24–39), years	30.67	5.03
Cdist, %/10 mmHg	2.25	0.58
IMT, mm	0.59	0.09
HR baseline, bpm	71.13	8.97
RSA baseline, log ms^2	2.83	0.25
PEP baseline, ms	96.28	11.81
HR reactivity score, bpm	15.91	10.55
RSA reactivity score, log ms^2	−0.10	0.25
PEP reactivity score, ms	−14.63	10.62
LDL cholesterol, mmol/l	3.21	0.73
HDL cholesterol, mmol/l	1.28	0.30
Triglycerides, mmol/l	1.26	0.56
Insulin, mU/l	7.74	4.71
Systolic BP, mmHg	114.12	14.03
Diastolic BP, mmHg	70.06	10.24
BMI, kg/m^2	25.06	4.43

Cdist, carotid artery distensibility; IMT, intima-media thickness; HR, heart rate; RSA, respiratory sinus arrhythmia; PEP, pre-ejection period; HDL, high-density lipoprotein; LDL, low-density lipoprotein; BP, blood pressure; BMI, body mass index; SD, standard deviation.

Table 2 presents the bivariate associations between the cardiovascular risk factors variables. Age and LDL-cholesterol level positively correlated with IMT (p < 0.001 and p = 0.045, respectively), whereas age inversely correlated with Cdist (p = 0.026). Higher HDL-cholesterol level was found among women (p = 0.003); SBP positively correlated with DBP (p < 0.001). Age positively correlated with LDL-cholesterol level (p < 0.01). Cdist was not related to IMT (p = 0.870).

Table 2. Bivariate correlations between the cardiovascular risk factors variables.

	1.	2.	3.	4.	5.	6.	7.	8.	9.	10.	11.
1. Gender^a	1
2. Age	0.09	1
3. BMI	0.09	0.02	1
4. LDL cholesterol	−0.01	0.36**	0.06	1
5. HDL cholesterol	−0.39**	−0.00	−0.08	−0.08	1
6. Triglycerides	0.13	−0.10	−0.08	0.21	−0.20	1
7. Insulin	0.22	0.14	−0.16	−0.23	−0.06	−0.12	1
8. Systolic BP	0.19	0.25	−0.17	0.02	−0.16	0.10	0.17	1
9. Diastolic BP	0.09	0.08	−0.14	−0.02	−0.08	0.13	0.23	0.77***	1
10. Cdist	−0.24	−0.29*	−0.03	−0.24	0.09	−0.11	−0.11	−0.10	−0.01	1	−0.02
11. IMT	0.10	0.50***	0.23	0.26*	−0.04	−0.14	0.06	0.18	−0.10	−0.02	1

***p < 0.001, **p < 0.01, *p < 0.05; Cdist, carotid artery distensibility (%/10 mmHg); IMT, intima-media thickness (mm); BMI, body mass index (kg/m²); HDL, high-density lipoprotein (mmol/l); LDL, low-density lipoprotein (mmol/l); BP, blood pressure (mmHg).

^aGender coded so that higher values represent men.

Associations between cardiac measures and Cdist

Baseline HR (p = 0.176) and baseline RSA (p = 0.823) were unrelated to Cdist. These associations remained non-significant after adjustments for age and gender (p = 0.086 and p = 0.392, respectively). Baseline PEP was negatively related to Cdist (β = −0.33, p = 0.013); after adjustment for age and gender: β = −0.30, p = 0.017. Baselines HR, RSA and PEP were unrelated to IMT (p > 0.130); after adjustments for age and gender: p > 0.378. The main effects of the autonomic reactivity measures on IMT have been reported in our previous study (Heponiemi et al., 2007) and are, thus, not reported here. HR, RSA and PEP reactivity scores were not related to Cdist (p ≥ 0.172), after adjustments for age and gender: p ≥ 0.130.

Interactive effects of cardiac measures and Cdist on carotid IMT

Table 3 shows the results of interaction analyses of cardiac reactivity with Cdist on IMT.

Table 3. Interactive effects of HR, RSA and PEP reactivity and arterial elasticity on IMT.

	*df corrected model	df error	df	F	η^2	p value
HR reactivity × Cdist
Model 1	9	48		6.03	0.112	0.018
HR reactivity score			1	2.09	0.042	0.155
Cdist			1	7.13	0.129	0.010
Age			1	7.78	0.140	0.008
Gender			1	0.10	0.02	0.755
Model 2	15	42		2.48	0.056	0.123
Model 3	15	42		8.62	0.170	0.005
HR reactivity score			1	4.36	0.094	0.043
Cdist			1	2.03	0.046	0.162
Age			1	8.93	0.175	0.005
Gender			1	0.53	0.012	0.471
BMI			1	0.003	0.000	0.960
Insulin in plasma			1	0.16	0.004	0.690
Model 4	18	39		0.55	0.014	0.461
Model 5	30	27		1.67	0.058	0.207
RSA reactivity × Cdist
Model 1	9	48		6.10	0.113	0.017
RSA reactivity score			1	0.73	0.015	0.398
Cdist			1	5.80	0.108	0.020
Age			1	9.78	0.169	0.003
Gender			1	0.10	0.002	0.758
Model 2	15	42		2.68	0.060	0.109
Model 3	15	42		7.09	0.144	0.011
RSA reactivity score			1	1.62	0.037	0.210
Cdist			1	4.64	0.100	0.037
Age			1	8.55	0.169	0.006
Gender			1	0.32	0.008	0.571
BMI			1	1.07	0.025	0.306
Insulin in plasma			1	0.39	0.009	0.537
Model 4	18	39		0.001	0.000	0.980
Model 5	30	27		0.056	0.002	0.815
PEP reactivity × Cdist
Model 1	9	48		2.56	0.051	0.116
Model 2	15	42		0.64	0.015	0.428
Model 3	15	42		3.41	0.075	0.072
Model 4	18	39		1.01	0.025	0.320
Model 5	30	27		0.37	0.013	0.550

HR, heart rate (bpm); RSA, respiratory sinus arrhythmia (log ms²); PEP, pre-ejection period (ms); Cdist, carotid artery distensibility (%/10 mmHg); BMI, body mass index (kg/m²). Main effects were included in each analysis but they are presented for significant interactions only. Each interaction is examined in a separate analysis; Model 1: includes the main effects of gender, age, Cdist and the reactivity scores measure in question as well as interactive effects between reactivity and Cdist, Cdist and age/gender; reactivity and age/gender; Model 2: adjusted for BP and additionally includes the main effects of SBP and DBP as well as interactions between Cdist and BP; interactions between reactivity scores and BP; Model 3: adjusted for plasma insulin level and BMI and additionally includes the main effects of plasma insulin and BMI as well as interactions between Cdist and insulin level or BMI, interactions between reactivity scores and insulin level/BMI; Model 4: adjusted for lipoproteins and additionally includes the main effects of triglycerides, LDL and HDL cholesterols as well as interactions between Cdist and lipids levels, interactions between reactivity scores and lipids levels; Model 5: the fully adjusted model: adjusted for cardiovascular risk factors and additionally includes the main effects of LDL and HDL cholesterols, triglycerides, plasma insulin, BMI, SBP and DBP as well as interactions between Cdist and risk factors; interactions between reactivity scores and risk factors.

*df total = 58 (for all the models); df corrected total = 57 (for all the models).

HR reactivity × Cdist interaction in relation to IMT was found (p = 0.018, N = 58) (Model 1), as well as after controlling for metabolic factors: plasma insulin and BMI (p = 0.005) (Model 3), but no interactions were found after controlling for BP (p = 0.123) (Model 2), lipids levels (p = 0.461) (Model 4) and after adjusting for all cardiovascular risk factors in the fully adjusted model (p = 0.207) (Model 5). Additional linear regression analyses performed separately for high and low Cdist groups (divided at the median) showed that higher HR reactivity was associated with lower IMT among higher Cdist individuals (β = −0.46, p = 0.020, N = 29) (Model 1) as well as in the model controlled for BMI and plasma insulin (β = −0.45, p = 0.024, N = 29) (Model 3). HR reactivity was not associated with IMT in participants with lower Cdist (β = −0.02, p = 0.872, N = 29) (Model 1); after controlling for metabolic risk factors: β = 0.01, p = 0.906, N = 29 (Model 3).

RSA reactivity × Cdist interactive effect on IMT (p = 0.017, N = 58) was shown when the effects of age, gender, Cdist and RSA reactivity score and their interactions were controlled for (Model 1) as well as after controlling for metabolic risk factors (p = 0.011) (Model 3). Adjusting for BP (Model 2), lipoproteins (Model 4) and all cardiovascular risk factors in the fully adjusted model (Model 5) showed no interactive effect (p ≥ 0.109, N = 58). Separate linear regression analyses for high and low Cdist groups showed no associations between RSA reactivity and IMT among low (β = 0.03, p = 0.836, N = 29) or high Cdist individuals (β = 0.33, p = 0.092, N = 29) (Model 1). When metabolic risk factors were controlled for in high/low Cdist groups separately, no effects of RSA reactivity on IMT were shown in higher Cdist group (β = 0.32, p = 0.116, N = 29) or in lower Cdist group (β = −0.08, p = 0.537, N = 29). No interactions between Cdist and PEP reactivity on IMT were found in either model (p ≥ 0.072, for all the models).

Discussion

We found that higher HR reactivity related to lower IMT among participants with higher Cdist. In other words, in individuals with more elastic blood vessels greater HR responses to acute mental stress were associated with better cardiovascular health, as indicated by less IMT. Accordingly, our previous results showed associations between elevated HR reactivity and decreased IMT (Heponiemi et al., 2007), as well as some earlier studies found associations between lower HR reactivity and increased atherosclerosis (Barnett et al., 1997). Our results support the suggestion that increased cardiac reactivity may be an adaptive reaction to stress (Tomaka et al., 1993). This seems to apply especially to healthy individuals with higher level of Cdist and thus relatively good vascular health. Accordingly, women with heart diseases (acute myocardial infarction or unstable angina pectoris) have demonstrated suppressed mental stress-induced cardiac reactivity (lower HR responses) as compared to healthy women (Weidner et al., 2001). In our previous study, reduced HR reactivity to acute mental stress has been related to greater IMTs among exhausted men (Chumaeva et al., 2009).

One of the mechanisms resulting to stress-induced decreasing of elasticity and, therefore, CVD development has been suggested to be prolonged sympathetic activation (Marwah et al., 2007; Tsai et al., 2003). No interactions between PEP reactivity (indicator of cardiac sympathetic control) and Cdist on IMT were found in our study. However, an increase in HR is a marker of relative sympathetic dominance resulted from autonomic imbalance (Palatini, 1999). We found that higher HR is associated with lower IMT, that is, less atherosclerosis, suggesting protective role of elevated sympathetic response in challenging situations. In accordance, higher acute stress HR reactivity has been related to lower risk of obesity, and low HR reactivity – to increased obesity risk that suggests reduced reaction of sympathetic nervous system to challenging task indicating a risk for obesity (Carroll et al., 2008). Our results imply that an ability to evoke relatively high reactivity to acute mental stress may be a normal adaptive physiological reaction especially in individuals demonstrating good vascular parameters. Activation of autonomic and neuroendocrine responses during acute stress protects the body in stressful situations (Brosschot, 2010; Tomaka et al., 1993). However, prolonged or chronic physiological activity induced by stress leads to pathophysiological states and diseases (Brosschot, 2010).

Reduction in arterial elasticity, especially stiffening in large arteries is, in turn, responsible for decreasing cardiac autonomic control through impairing baroreflex sensitivity that modulates HR reactivity (Bruno et al., 2012). Relations between arterial elasticity and sympathetic function realized through the mechanism of baroreflex sensitivity alterations have been suggested to predispose to an increased risk of hypertension and atherosclerosis (Bruno et al., 2012; Okada et al., 2012). Independent associations between HR variability (an index of vagal modulation of HR) and Cdist have recently been found in a large sample of healthy middle-aged adults in the Young Finns Study (Koskinen et al., 2011). Moreover, associations between high-frequency component of HR variability and Cdist have been found independently of IMT and cardiovascular risk factors, suggesting that arterial distensibility itself participates in vagal tone regulation (Koskinen et al., 2011). On the other hand, HR is a powerful functional factor, which influences arterial elasticity independently of structural component of elasticity modulation: an increase in HR has been related to a decrease in arterial distensibility that leads to vessel stiffening even in structurally normal vessels (Giannattasio & Mancia, 2002; Giannattasio et al., 2003). Several mechanisms have been suggested to explain these relations: viscoelastic properties alterations, decreased endothelial nitric oxide release and increased sympathetic activity resulted from an unloading of cardiac receptors and baroreceptors (Giannattasio & Mancia, 2002; Giannattasio et al., 2003).

Interactive effect of RSA reactivity with Cdist in relation to atherosclerosis was also found. The recent findings show correlations between parasympathetic function and large arterial stiffness in patients with early stage of diabetes-1 (Liatis et al., 2011) and correlations between parasympathetic activity and aortic distensibility in healthy individuals (Nemes et al., 2010). However, in our study, no associations between RSA reactivity and IMT were found when examined separately in low/high Cdist groups. These null findings may reflect limited statistical power. Future studies with larger samples are needed to verify whether parasympathetic function, that is., RSA reactivity, is related to atherosclerosis, especially in individuals with high or reduced vessels elasticity.

Controlling for cardiovascular risk factors attenuated interactive effects size on IMT to nonsignificant value. It is possible that cardiovascular risk factors markedly influence the effect of Cdist × cardiac autonomic responses on IMT. Age, obesity, smoking, BP and lipoproteins level have been related to markers of carotid artery elasticity (Juonala et al., 2005). Controlling for BP and lipoproteins in the separate models showed no interactions between cardiac stress responses and Cdist on IMT in the present study. The results are in line with our previous findings implying that BP and lipoproteins are essential risk factors, which influence arterial elasticity (Juonala et al., 2005). Further investigations are required to clarify complex causal effects.

After controlling for metabolic risk factors the interactions between Cdist and HR (or RSA) reactivity on IMT were found suggesting that BMI and plasma insulin level do not influence the interactions between Cdist and cardiac reactivity on IMT. However, separate analyses in low/high Cdist groups showed no associations between RSA reactivity and IMT and demonstrated only associations between greater HR reactivity and less IMT in individuals with higher Cdist independent from BMI and plasma insulin level. The results are in accordance with the recent findings showing that HR responses to acute psychological stress have not been impaired in men with low or moderate level of overweight/obesity as compared to men with normal BMI (Jayasinghe et al., 2014). It has been suggested that acute stress responsiveness depends on adiposity level and individuals with higher BMI or body fat percentage appear to demonstrate a difference in HR responses compared to non-obese individuals. The degree of obesity and its pathological components as well as other stress-sensitive risk factors (cytokines and/or opioids), which lead to chronic diseases progression may underlay different responses to stress (Jayasinghe et al., 2014). Persons with progressive obesity having a higher BMI have demonstrated reduced BP and HR responses to acute stress (Burch & Allen, 2014). On the other hand, healthy participants investigated in the Young Finns Study have shown associations between BMI and IMT in childhood and in adulthood (Raitakari et al., 2003). Thus, investigations in larger populations are required.

Brief laboratory mental stressors, for example, the arithmetic test, are considered in stress research as less powerful stressors than those that individuals encounter in real life. Nevertheless, arithmetic and speech tests are widely used in the laboratory as acute mental stressors. The stressful acute events in real life may induce more powerful cardiac and vascular reactions, and they can even evoke acute cardiovascular events (Steptoe & Kivimäki, 2012). It is likely that stress-induced reactivity depends on the level of stress, and our results might be stronger if more severe mental stressors would be applied. Moreover, effects of the same acute mental stressors on vascular health can differ between different populations, such as in patients with heart diseases (Deley et al., 2009) or in older age groups (Lipman et al., 2002).

Vascular reactions play more important role in the progression of atherosclerosis than cardiac reactions: systolic BP reactivity to acute mental stress has been related to IMT even in children, whereas cardiac reactivity has not been related to IMT (Roemmich et al., 2009). The role of vascular reactivity in stressful situations for atherosclerosis development is an important topic in future. There are no studies that would have compared acute stress-induced cardiac reactivity among individuals with different elasticity properties of the vessels. Our findings imply that future studies should focus more on cardiac stress reactions among individuals with poor parameters of vascular health. As a clinical implication, the present study suggests that psychosocial stress may be a warning sign for atherosclerotic risk, particularly in individuals who are known to have damaged, or sub-optimally functioning, vessels. Individuals with healthy vessels may have greater physiological resistance toward stress, and therefore, health-related outcomes of stress may be less severe.

Methodological considerations

The present study has limitations that need to be considered when interpreting the results. First, we studied only cardiac reactivity to acute stress and vascular elasticity and thus cannot generalize our results to vascular reactivity to acute stress. Second, we did not measure respiration. Thus, we cannot exclude the possibility that respiration might not have fallen within the frequency band used to compute RSA estimates. However, uncorrected RSA has been shown to be eligible in indexing within-subject changes in parasympathetic control of HR in majority of stress studies (Houtveen et al., 2002). Third, ultrasound measurements were performed manually, and not with automated system, but the reproducibility of IMT and elasticity measurements are comparable with other reports (Arnett et al., 1999; Kanters et al., 1997). An important limitation of our study is the blood pressure measurement method. The pulse pressure used in the equation to calculate Cdist was measured from the brachial artery, not from the artery in question. The use of brachial pressures may overestimate pulse pressure in central arteries (Karamanoglu et al., 1993). However, the difference between central and peripheral pulse pressure is likely to be similar between study subjects within a narrow age range, as in our study. Borow & Newburger (1982) have shown an excellent correlation of r = 0.98 between systolic blood pressures and r = 0.97 between diastolic pressures measured invasively from ascending aorta and noninvasively from brachial artery. Techniques similar to those in the present study are commonly used in cardiovascular research (Salomaa et al., 1995; Tounian et al., 2001).

In the current study, we conducted the analyses in subjects aged 24 to 39 years; therefore, we cannot generalize our results to older participants with more developed atherosclerosis. Finally, we performed cardiac autonomic measurements and ultrasound examinations only once, and we cannot make conclusions regarding the progression of atherosclerosis. As the cohort is comprised of young adults, we were not able to study associations with clinical cardiovascular events. However, we used surrogate markers of atherosclerosis as outcomes. Suggesting their validity as intermediate phenotypes of atherosclerosis, these measures have been shown to predict clinical atherosclerotic events independent of conventional cardiovascular risk factors (Lorenz et al., 2007; van Sloten et al., 2014; Yeboah et al., 2009). The small number of participants is the main limitation in the present study. Our results should be considered preliminary until replication in larger populations.

The present study has also strengths. First, the study is the first to examine the interactive effect between acute stress-induced cardiac reactivity and Cdist in relation to atherosclerosis in healthy young and middle-aged adults. Second, our results add to knowledge of how acute stress may influence on atherosclerosis and to psycho-emotional theory of atherogenesis, which postulates that stress can promote atherosclerotic process by psychophysiologically based mechanisms.

Conclusions

The results imply that elevated cardiac reactivity in response to mental stress may be a normal reaction inducing stress adaptation processes. Individuals having higher arterial elasticity may be better protected against adverse health outcomes of stress and among them the ability to show elevated cardiac reactivity in challenging tasks seems to be related to better cardiovascular health.

Declaration of interest

This study was supported by the Academy of Finland (grant number 258578 to M.H., and 265977 to M.E.), Wihuri Foundation (N.C.), Emil Aaltonen Foundation (M.H.), Ella and Georg Ehrnrooth Foundation (M.H. and T.H.), Signe and Ane Gyllenberg Foundation (M.H. and L.P.-R.), Finnish Foundation for Cardiovascular Research (M.H.), Juho Vainio Foundation (L.P.-R.), Bothnia Welfare Coalition for Research and Knowledge network (L.P.-R.) and National Institute of Health and Welfare in Vaasa (L.P.-R.). The Young Finns Study has been financially supported by the Academy of Finland: grants 126925, 121584, 124282, 129378, 117797, and 41071, the Social Insurance Institution of Finland, Kuopio, Tampere and Turku University Hospital Medical Funds, Juho Vainio Foundation, Paavo Nurmi Foundation, Finnish Foundation of Cardiovascular Research and Finnish Cultural Foundation, Sigrid Juselius Foundation, Tampere Tuberculosis Foundation and Emil Aaltonen Foundation. The authors declare that they have no competing interests. The authors alone are responsible for the content and writing of the paper.