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Psychosomatic Medicine 64:247-257 (2002)
© 2002 American Psychosomatic Society

ORIGINAL ARTICLES

Relationship of Clinic, Ambulatory, and Laboratory Stress Blood Pressure to Left Ventricular Mass in Overweight Men and Women With High Blood Pressure

Andrew Sherwood, PhD, Elizabeth C. D. Gullette, PhD, Alan L. Hinderliter, MD, Anastasia Georgiades, PhD, Michael Babyak, PhD, Robert A. Waugh, MD and James A. Blumenthal, PhD

From the Departments of Psychiatry and Behavioral Sciences (A.S., E.C.D.G., A.G., M.B., J.A.B.) and Medicine (R.A.W.), Duke University Medical Center, Durham, NC, and the Department of Medicine (A.L.H.), University of North Carolina, Chapel Hill, NC.

Address reprint requests to: Andrew Sherwood, PhD, Box 3119, Duke University Medical Center, Durham, NC 27710; Fed Ex/UPS address: Room 4569, Duke Hospital South, Trent Drive, Durham, NC 27710, Email: Andrew.Sherwood{at}duke.edu


   ABSTRACT
TOP
 ABSTRACT
INTRODUCTION
 METHODS
 RESULTS
 DISCUSSION
 NOTES
 ACKNOWLEDGMENTS
 REFERENCES
 
OBJECTIVE: This study was designed to evaluate the relationship between left ventricular (LV) mass and blood pressure (BP) recorded in the following contexts: in the clinic, using standard auscultatory procedures, during a typical day using ambulatory BP monitoring, and in the laboratory environment during behavioral stress testing.

METHODS: Ninety-seven men and women with clinic systolic blood pressure (SBP) of 130 to 180 mm Hg and/or diastolic blood pressure (DBP) of 85 to 110 mm Hg and mild to moderate obesity were included in the study. Laboratory stressors included the following tasks: Public Speaking; Anger Interview; Mirror Trace; and Cold Pressor. LV mass was measured using echocardiography and adjusted for body size by dividing by height2.7 to yield LV mass index (LVMI).

RESULTS: LVMI was positively correlated with clinic SBP (r = 0.24, p < .05), ambulatory SBP (r = 0.34, p < .01), and aggregated laboratory stress SBP (r = 0.28, p < .01). Of the individual stressors, only SBP responses to the Mirror Trace and Cold Pressor tasks were independently correlated with LVMI (r = 0.35 and 0.34, respectively, p values < .01). Hierarchical regression analyses revealed that laboratory stress SBP remained a significant predictor of LVMI, after controlling for BMI and clinic pressure.

CONCLUSIONS: These findings suggest that cardiovascular responses to behavioral stress are associated with individual differences in LVMI in men and women with high blood pressure who are overweight. Laboratory studies of behavioral stress may help promote our understanding of the pathophysiology of LVH.

Key Words: left ventricular mass, • ambulatory blood pressure, • psychological stress, • hypertension.

Abbreviations: SBP = systolic blood pressure;; DBP = diastolic blood pressure;; LVMI = left ventricular mass index;; LVH = left ventricular hypertrophy;; SVRI = systemic vascular resistance index;; HR = heart rate;; CI = cardiac index;; BMI = body mass index.


   INTRODUCTION
TOP
 ABSTRACT
 INTRODUCTION
METHODS
 RESULTS
 DISCUSSION
 NOTES
 ACKNOWLEDGMENTS
 REFERENCES
 
Although hypertension is defined by elevated arterial blood pressure (BP), its clinical significance is primarily due to morbid events affecting the heart and brain. Complications of hypertension, such as myocardial infarction and stroke, are not directly due to elevated pressures, but to the resulting structural changes in the heart and blood vessels. Left ventricular hypertrophy (LVH) is a structural consequence of hypertension that is the strongest known predictor of cardiovascular morbidity and mortality (1, 2). Echocardiographically determined LVH predicts these clinical outcomes both in individuals with hypertension (3) and healthy individuals (4), independent of other conventional risk factors.

LVH is a consequence of increased ventricular afterload due to chronically elevated BP. Correlations between clinic BP and left ventricular mass (LV mass) are relatively weak (5), which may reflect the inability of clinic BP measurements to capture the dynamic nature of BP during daily life or to accurately reflect the afterload placed on the left ventricle over the course of a normal day. Ambulatory BP measured throughout the day is a better predictor of cardiac end-organ involvement than resting BP, suggesting the possibility that stress effects on blood pressure also may be important (6). Consistent with this view, ambulatory BP at work is typically higher than at home (7) and is more closely correlated with LV mass than non-workday ambulatory pressures (6, 8–10). Other sources of real-life stress, such as low marital cohesion have also been related to elevated ambulatory BP, although their impact on LV mass is less clear (11, 12)

There also is growing evidence that BP measured in the laboratory setting during stress is associated with increased risk for hypertension and LVH (13–19). However, the extent to which stress BP contributes additional prognostic information over and above clinic or resting BP remains uncertain. For example, in the CARDIA study, a significant relationship between stress BP response and LV mass was observed in young men and women only in unadjusted analyses; after controlling for other predictors, only exercise stress SBP response and LV mass remained significant, and only in white men (20). Georgiades and colleagues (18) found that BP reactivity was unrelated to LV mass in borderline hypertensive and normotensive Swedish men. However, the absolute BP levels induced by stress were correlated positively with LV mass in the borderline hypertensives, but not in the men with normal BP. Women were not studied, however, and the contribution of stress BP compared with ambulatory or clinic BP was not assessed.

The purpose of the present study was to compare clinic BP, ambulatory BP, and stress BP as predictors of LV mass in overweight men and women with unmedicated high BP. To provide a reliable assessment of BP during behavioral stress, a battery of four different laboratory stressors was used that would allow the derivation of an aggregate stress BP response (22, 23). We also examined underlying hemodynamic response patterns by measuring cardiac output (CO) and systemic vascular resistance (SVR) responses during stress. We hypothesized that both stress BP and ambulatory BP would account for individual differences in LV mass, even after accounting for the contribution of clinic BP. Because of some previous reports (14–16), we also explored whether laboratory stressors that typically increase BP by vasoconstriction (Mirror Trace and Cold Pressor) would be more closely related to individual differences in LV mass than other stressors, and how SVR responses during these stressors would relate to LV mass.


   METHODS
TOP
 ABSTRACT
 INTRODUCTION
 METHODS
RESULTS
 DISCUSSION
 NOTES
 ACKNOWLEDGMENTS
 REFERENCES
 
Subjects
One hundred forty-four men and women were recruited from newspaper, TV, and radio advertisements, local clinics, and screenings at community health fairs and local shopping centers. Details of subject recruitment are presented elsewhere (24). Of these 144 volunteers, echocardiographic data were unavailable for 47 individuals: 1 individual did not undergo the assessment, 6 participants did not have their data recorded onto videotape due to a failure, and 40 participants’data was found to be inadequate for interpretation. Thus 97 participants, including 40 men and 57 women, were included in the present sample.

Participants were eligible if they were at least 29 years old, with unmedicated high normal BP or stage 1 to 2 hypertension (mean clinic SBP = 130–180 mm Hg and/or mean clinic DBP = 85 –110 mm Hg on four separate occasions over a 3-week period). In addition, participants were sedentary (not currently performing regular aerobic exercise) and overweight or obese (BMI = 25–37 kg/m2), as defined in the National Institutes of Health (NIH) statement on obesity treatment (25). These characteristics of the present study sample reflect the eligibility criteria for a larger study (24) examining diet and exercise interventions on blood pressure. Subjects were randomized to interventions after completing all of the assessments described in the present report.

Participants previously treated for hypertension were included if they had been on no more than one medication that had been discontinued for at least 6 weeks. Initial medical screening procedures included a medical history and physical examination to rule out secondary hypertension. Additional reasons for patient exclusion included history of cardiac disease, secondary hypertension, renal disease, AV conduction defects or high grade arrhythmias, valvular disease, severe asthma or chronic obstructive pulmonary disease, diabetes requiring insulin or hypoglycemic agents, significant orthopedic or musculoskeletal disease, a comorbid medical condition requiring intensive treatment such as cancer, use of any medications known to affect the cardiovascular system (eg, antihistamines and decongestants), or a history of drug abuse or alcoholism. Characteristics of the study sample are summarized in Table 1. It should be noted that the sample of 97 subjects on whom data were available for analysis differed from the 47 subjects on whom complete data were unavailable only in that BMI was significantly higher in the excluded subjects, which likely reflects the difficulty with echocardiographic imaging in obese individuals. This study was approved by the Institutional Review Board at Duke University Medical Center, Durham, NC, and informed consent was obtained from all subjects before their participation.


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  		Table 1. Demographic and Clinical Characteristics of the Study Sample (N = 97)
 
Blood Pressure Measurements
Clinic blood pressure.
BP measurements were obtained by a trained technician with a random zero sphygmomanometer and were standardized for cuff size and position. Measurements were made on four separate visits over a 3-week period. At each visit, BP was measured four times at 2-minute intervals after an initial rest period of 5 minutes. The first BP measurement of each visit was discarded and the average of the remaining three measurements represented the clinic-visit BP. The overall clinic BP was then determined by averaging the mean BP over the four visits.

Ambulatory blood pressure.
The use of ambulatory BP monitoring provides an opportunity to assess BP during routine activities of daily life. Because data from ambulatory BP monitoring studies suggest that BP is highest during working hours (7), subjects were studied during a typical workday. Subjects were fitted with an Accutracker II ABP monitor (Suntech, Raleigh, NC) between 0800 and 1000 hours, and SBP and DBP recordings were verified by simultaneous manual readings. The Accutracker II measures BP noninvasively using the auscultatory technique, in which a microphone records and processes Korotkoff sounds; it uses ECG R-wave gating to correctly identify Korotkoff sounds originating from the brachial artery. The Accutracker II model has been validated independently (26). The monitor was programmed to obtain readings at an average frequency of four times per hour until bedtime. During ambulatory monitoring, subjects were instructed to maintain a diary, which included information about their posture, mood, and activities. All ambulatory BP measurements were checked and readings judged invalid (eg, due to artifact) were excluded. The mean ambulatory SBP and DBP were then computed based on all remaining readings.

Stress blood pressure.
BP was measured using a Suntech 4240 Exercise BP monitor (Raleigh, NC) during a stress protocol consisting of a 20-minute baseline rest period and four stress tasks with 10 minutes of rest between tasks. Throughout the stress testing protocol subjects sat in a comfortable recliner chair, in a sound-attenuated, electrically shielded room. Subjects were randomized to one of four possible task orders defined by a special 4 x 4 Latin Square, known as a Williams Square. This approach provides balance for order by providing four order across which each task occurs first, second, third, and fourth only once, and furthermore, that each task precedes and follows each other task exactly once. Subjects participated in each of the following tasks:

Public speaking, in which subjects were asked to give a 3-minute talk about a current events topic. Subjects were given a list of six topics to choose from and allowed 2 minutes to prepare what they would say. Two Research Assistants were present before the subject, "evaluating" the speech. If subjects failed to speak for a full 3 minutes, a Research Assistant used standardized verbal prompts to encourage continuation of the speech.
Mirror trace, in which subjects had 3 minutes to outline a star while viewing only its reflection in a mirror, as many times as possible, while making a minimum of errors. Deviating from the star activated a mechanical counter, in full view of the subject, which recorded errors.
Anger interview, in which subjects were given 3 minutes to relate an interpersonal situation that had made them angry during the previous week. Subjects were given a 2-minute preparation time and asked to structure their description around a brief outline of the situation, how they responded, and how satisfied they were with the outcome.
Cold pressor, in which subjects placed one foot, up to the ankle, in a bucket containing a mixture of two parts ice to one part water (0°C to 4°C) for 2 minutes.

Stress hemodynamics.
Impedance cardiography was used to measure cardiac performance noninvasively (27). A Hutcheson Impedance Cardiograph (Model HIC-1, Bio-Impedance Technology, Chapel Hill, NC) was used in conjunction with a tetrapolar band-electrode system. The inner two recording electrode bands were positioned around the base of the neck and around the thorax, over the xiphoid process. The outer two current electrode bands were positioned to encompass the neck and thorax, at least 3 cm distanced from each of the recording electrodes. The electrocardiogram (ECG) was recorded using disposable ECG electrodes. The basal thoracic impedance (Zo), the first derivative of the pulsatile impedance (dZ/dt) and the ECG waveforms were processed using specialized ensemble-averaging software (COP, BIT Inc., Chapel Hill) which was used to derive stroke volume (SV) using the Kubicek equation (28), heart rate (HR), and cardiac output (CO). CO was divided by body surface area to give cardiac index (CI). Systemic vascular resistance index (SVRI) was derived on the basis of the concurrently recorded blood pressure and cardiac output, using the equation:

SVRI (dyne-seconds.cm-5.m2) = (MAP/CI)*80.

Echocardiography
Echocardiography studies were performed with a Hewlett-Packard imaging system equipped with a 2.5-MHz phased array transducer. Images were obtained with the patient in the partial left lateral decubitus position and were recorded on S-VHS videotape. The studies were subsequently quantified by a single, experienced observer (A.L.H.) who was blinded to the subject’s identifying information. Left ventricular end-diastolic diameter (LVEDD), posterior wall thickness (PWT), and interventricular septal thickness were measured at end diastole using a leading edge-to-leading edge convention (29). Left ventricular mass was estimated using a cube function model with a correction factor as described by Devereux et al. (30). To adjust for variations in heart size due to differences in body size, LV mass index (LVMI) was calculated as ventricular mass/height2.7 (31).

Previous investigators have demonstrated a high degree of test-retest reliability of echocardiographic measurements of LV mass, and close agreement between echocardiographic and necropsy mass measurements. In a study of 96 patients with mild or moderate hypertension who had 2 M-mode echocardiographic measurements of LV mass performed 6 to 8 days apart, the intraclass coefficient of correlation was 0.86, and the mean percent error was 11% (32). Comparisons of M-mode echocardiographic and necropsy measurement of LV mass have consistently demonstrated correlation coefficients >0.80, with standard deviations ranging from 29 to 60 g (33–35). Estimates of LV mass derived from two-dimensional linear measurements, as used in the current study, correlate closely (r = 0.97) with M-mode echocardiographic measurements (36).

Data Reduction and Analysis
Predictors of LVMI,1 including demographic and anthropometric characteristics and clinic, ambulatory, and stress BPs were considered in the analyses. Based on evidence that stress BP responses are more reliable when an aggregate BP across a series of stressors is computed (22, 23), our primary analyses focused on stress BP as indexed by BP averaged across the four stressors used in the present study. Because stressors may elicit different patterns of cardiovascular response and we were particularly interested in stressors that result in vasoconstriction (ie, Cold Pressor and Mirror Trace), we also examined the relationship between these stressors and LVMI (37). During stress, additional hemodynamic measures (HR, CO, and SVR) also were considered as predictors of LVMI. Data were analyzed: 1) using simple correlation (Pearson R) analyses, and 2) by hierarchical multiple regression analyses. In terms of the regression analyses, two primary models were developed to determine the relative importance of BP in predicting LVMI under each condition (eg, clinic, laboratory, and daily life), while controlling for BMI. In each model, BMI was entered as the predictor variable in the first step, followed by clinic BP as the predictor variable in the second step. In Model 1, ambulatory BP was entered as the predictor variable in the third step, whereas in Model 2, stress BP was entered in the third step.2


   RESULTS
TOP
 ABSTRACT
 INTRODUCTION
 METHODS
 RESULTS
DISCUSSION
 NOTES
 ACKNOWLEDGMENTS
 REFERENCES
 
Correlational Analyses of BP and LVMI
Mean SBP and DBP values recorded in the clinic, during daytime ABP monitoring, and averaged across the four stress tasks are presented in Table 2. There were no significant relationships between LVMI and age, ethnicity, or gender (Table 3). By contrast, LVMI was significantly correlated with both weight and BMI. LVMI also was correlated with SBP measured in the clinic, during ambulatory monitoring, and in the laboratory both at rest and during stress. A similar pattern of correlations was observed for posterior wall thickness (PWT): there were no significant correlations between PWT and demographic variables, but PWT was correlated with clinic SBP (r = 0.23, p < .05), ambulatory SBP (r = 0.35, p < .01), and stress SBP (r = 0.27, p < .01).


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  		Table 2. Blood Pressures Measured During Standard Clinical Assessment, by Ambulatory Monitoring During Waking Hours, and During Laboratory Stress
 

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  		Table 3. Demographic, Anthropometric, and Hemodynamic Correlates of Left Ventricular Mass Index (N = 97)
 
Mean hemodynamic responses for each of the four stress tasks and their correlations with LVMI are presented in Table 4. All four tasks gave rise to significant increases in SBP and DBP (p values < .001). SBP showed a significant positive correlation with LVMI only for Mirror Trace and Cold Pressor. DBP also was correlated with LVMI during Cold Pressor. SVRI responded differentially according to task, decreasing during Public Speaking (p < .001) and Anger Interview (p < .001), increasing during Mirror Trace (p < .001) and showing no significant change during Cold Pressor (Table 4). Therefore, SVRI was higher during the Mirror Trace and Cold Pressor than the other two tasks (p < .001). However, HR, CI, and SVRI responses were unrelated to LVMI during each of the stressors.


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  		Table 4. Hemodynamic Responses in the Laboratory at Rest and During Stress Testing: Mean Values and Correlation With Left Ventricular Mass Index (N = 97)
 
Multivariate Models of Predictors of LVMI
Only significant independent predictors of LVMI were considered in the development of multivariate models. As shown in Table 3, significant predictors included BMI, and SBP in the clinic, during ABP monitoring, and during stress. Results of hierarchical multiple regression analyses examining the relative importance of SBP in predicting LVMI under each measurement context are presented in Table 5, including the p value and standardized beta for each variable, indicating the unique contribution of that variable to the prediction of LVMI. In addition, the increase in adjusted R2 from the previous step, the model F value, and overall p value are presented for each step.


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  		Table 5. Hierarchical Multiple Regression Analysis Predicting Left Ventricular Mass Index (g/m2.7) (N = 97)
 
BMI was a significant predictor of LVMI (p < .0001), accounting for 14% of the variance. Clinic SBP also was a significant predictor of LVMI (p < .01), contributing an additional 5% of the variance. However, when ambulatory SBP was added to the model, clinic SBP was no longer significant and ambulatory SBP contributed an additional 5% of the variance in LVMI over BMI and clinic SBP. Thus, the full Model 1 accounted for 24% of the variance in LVMI, adjusted R2 = 0.24, F(3,92) = 10.86, p <= .0001. For Model 2, when stress SBP was added to BMI and clinic SBP in the third step, clinic SBP was no longer significant, and stress SBP contributed an additional 3% of the variance in LVMI over BMI and clinic SBP. The full Model 2 accounted for 22% of the variance in LVMI, R2 = 0.25, F(3,90) = 9.92, p <= .00012. As an exploratory step, after BMI and clinic BP had been entered, both ambulatory and stress BP were entered simultaneously. In this analysis, neither ambulatory SBP nor stress SBP was significant when both were included, suggesting that they accounted for related variance in predicting LVMI.

In addition to the two primary models comparing the predictive value of ambulatory BP and aggregate stress BP, a third model was developed. This model examined the relative importance of BP aggregated across the vasoconstriction-inducing Mirror Trace and Cold Pressor tasks in predicting LVMI. With the addition of the aggregate "vasoconstrictive" stress SBP to the BMI and clinic SBP model, clinic SBP was no longer significant and the "vasoconstrictive" stress SBP contributed an additional 7% of the variance in LVMI (p < .005). The full model accounted for 26% of the variance in LVMI, which was greater than the overall stress BP. Moreover, even with both clinic SBP and ambulatory SBP already in the model, the "vasoconstrictive"stress SBP still predicted additional variance in LVMI (increase in adjusted R2 = 0.03, p < .05; adjusted model R2 = 0.27, F(4,89) = 9.3, p <= .0001).

Left Ventricular Hypertrophy
To examine the clinical significance of the relationship between BP and LVMI, LVH was defined as LVMI > 49.7 g/m2.7 for men and LVMI > 47.2 g/m2.7 for women (31). As shown in Figure 1, SBP was greater in subjects with LVH than in subjects without LVH in the clinic (mean ± SE = 143 ± 1.5 vs. 137 ± 1.5 mm Hg, p < .01), during ambulatory monitoring (146 ± 1.8 vs. 137 ± 1.9 mm Hg, p < .01), and during stress (166 ± 2.5 vs. 156 ± 2.5 mm Hg, p < .01). SBP differences between participants with and without LVH were most pronounced during "vasoconstrictive" stressors of Mirror Trace and Cold Pressor (163 ± 2.4 vs. 150 ± 2.5 mm Hg, p < .001; Figure 1).



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  		Fig. 1. Systolic blood pressure (SBP) in the clinic, during ambulatory monitoring, during stress, and during the "vasoconstrictive" stressors (aggregate of mirror trace and cold pressor) in subjects with LVH (N = 50) and with normal LVMI (N = 47), controlling for BMI. Statistical significance values for differences in SBP associated with each BP measurement condition are indicated as probability (p) values.

 

   DISCUSSION
TOP
 ABSTRACT
 INTRODUCTION
 METHODS
 RESULTS
 DISCUSSION
NOTES
 ACKNOWLEDGMENTS
 REFERENCES
 
The present study confirms previous findings that clinic SBP is only modestly related to LVMI (5). Also consistent with previous studies, ambulatory SBP recorded during the waking hours of a typical workday was more closely related to LVMI than clinic BP (6, 8–11). Findings for aggregated laboratory-stress SBP paralleled the findings for ambulatory SBP, with stress SBP accounting for individual differences in LVMI by both encompassing and extending the variance accounted for by clinic SBP. DBP showed relatively weaker associations with LVMI under all measurement conditions, which also is consistent with previous studies (39, 40). Although we focused on LVMI as a measure of cardiac hypertrophy, the relationships of BP in the clinic, during ambulatory monitoring, and during stress testing to LVMI were in large part due to similar associations with LV PWT.

Our findings are consistent with the notion that clinic BP is an imprecise marker of LVH risk. Ambulatory and stress SBP were related to LVMI even after accounting for clinic BP, suggesting that such measures provide a more reliable and valid indication of the prevailing pressure load that may promote LV remodeling. For ambulatory BP, improved precision is likely a result of more frequent and extensive sampling of BP than clinic measurement across normal daily activities that include rest and physical exertion, as well as psychological demands. It may be less obvious why stress BP should more accurately reflect the pressor stimulus for cardiac hypertrophy than clinic BP. Observations from both animal models (41) and humans (42) suggest that transient and periodic pressor episodes may result in substantive cardiac adaptations. Julius, et al. (41) used hindquarter compression in dogs to elicit transient sympathetically mediated increases in BP for 6 hours per day. After 9 weeks of this manipulation, there was no persistent elevation in BP, but a 28% increase in LV mass was observed. For patients with hypertension, higher ambulatory BP variability has been found to be associated with increased LV mass, independent of mean ambulatory BP levels (42). These observations are consistent with the notion that laboratory stress BPs may be important if they reflect individual differences in peak pressures occurring during daily life. However, in a test of this hypothesis, BP responses to mental arithmetic stress were found to correlate positively and significantly, but only modestly, with ambulatory BP variability (43).

Among the stressors used in the current study, BP responses to the Mirror Trace and Cold Pressor tasks were the only tasks that exhibited significant simple correlations with LVMI. When these two tasks were aggregated together in a regression model, they accounted for additional variance in LVMI, even after both clinic and ambulatory BP were included. This finding is consistent with findings from previous studies that have incorporated similar challenges in their battery of stressors (14–16). For example, Allen and colleagues (16) performed comprehensive hemodynamic assessments in 115 children and adolescents who were exposed to the Mirror Trace, Cold Pressor and Reaction Time tasks, and a Social Competence Interview. Only BP responses to Mirror Trace and Cold Pressor were significantly related to LVMI. Allen et al. (16) also found that the SVR increase during these stressors showed a strong relationship with LVMI, suggesting that challenges eliciting vasoconstriction may be the best predictors of LVMI. However, we found no evidence of a relationship between SVR responses and LVMI in the present study.

One possible explanation for our failure to find support for the hypothesized relationship between stress SVR response and LVMI relates to obesity, which may obscure the impact of individual differences that otherwise may be link LVH with stress hemodynamics. Obesity in the absence of hypertension appears to be associated with high CO and normal or lowered SVR (44). Observations of the hemodynamic characteristics of obese hypertensive patients have been mixed, however. Although a number of studies have found obese hypertension to be characterized by elevated CO and lower SVR than in lean hypertensives (45), this observation has not been universal (46). There are several factors that might account for inconsistent findings. Age may be especially important, with SVR typically rising with advancing years, and the natural history of hypertension being one of a progressive increase in SVR (47). Studies reporting normal CO and elevated SVR in obese hypertensives have been conducted on patients who are middle-aged or older (46). Obesity in the context of hypertension may have mixed hemodynamic effects, which may be moderated by other individual difference characteristics, resulting in a variety of hemodynamic challenges to the heart. This may explain why, in our study, gender and ethnicity were unrelated to LVMI, while BMI was the single most robust predictor.

Recent studies of gender differences in LVH have shown that obesity seems to convey a disproportionate increased risk of LVH in women compared with men, offsetting the otherwise greater risk in men (48). The majority of echocardiographic studies comparing African Americans and white hypertensive patients have found greater LVH in African Americans (49–51). Our failure to observe a significant association between ethnicity and LVMI may have been due to the relatively small number of African Americans (N = 29). However, ethnic differences in LV pathophysiology also may have been affected by the presence of obesity. Consistent with this possibility, we observed that SVR responses during stress testing were similar in African American and white subjects, which is contrary to numerous reports, including our own studies, that African Americans typically exhibit greater vasoconstrictive responses during stressors such as Mirror Trace and Cold Pressor (52, 53). Collectively, the foregoing evidence raises the possibility that LV pathophysiology may take a different course when hypertension exists in the presence of obesity.

It is becoming increasingly evident that demographic and anthropometric characteristics of a study sample may have substantial bearing on how hemodynamic factors are related to LV mass. The work of Devereux and colleagues (36) has documented the close relationship between LV mass and body size. While in infancy, variations in LV mass are almost entirely accounted for by body size, this relationship deteriorates progressively with aging, partly as a consequence of developing individual differences in hemodynamic load (54). In the Tecumseh study, BP was not found to be an independent predictor of LV mass in a group of young (18–42 years), primarily normotensive individuals (55). This observation led the authors to suggest that BP makes a more important contribution to LV structure in hypertensives and in older individuals. Age and blood pressure status also may be important moderators of the relationship between BP responses to stress and LVMI. Recent evidence from the Kuopio Ischemic Heart Disease Risk Factor Study is to some extent consistent with this possibility (56). In a population-based sample of 876 men, anticipatory BP responses to exercise, viewed by the authors as representing a response to psychological demands, was related to LVMI only among subjects with elevated resting BP who were under 50 years of age. Other studies that have included both normotensive and hypertensive subjects also suggest that elevated resting BP may be an important prerequisite to stress BP relating to individual differences in LVMI (18). The failure to find an independent relationship of BP during laboratory mental arithmetic and cold pressor stress and LV geometry, reported by Rostrup and colleagues (57) in young (19 years of age) healthy men, is consistent with age being an important moderator variable. However, other studies’ results do not lend themselves to forming clear guidelines regarding a simple set of important moderator variables. For example, Treiber and colleagues (14) have observed that stress BP is related to LVM in healthy children (ages 6–18 years), and Hinderliter et al. (19) reported a similar relationship in normotensive young adults. Allen et al. (16) found stress BP related to LVMI in adolescents, but not in younger, prepubertal children. A recent study reported by Kop and colleagues (58) also showed with multivariate analyses that, in normotensive men and women (mean age = 34 years), aggregate SBP responses to a battery of laboratory mental stressors predicted LVMI over and above baseline SBP and demographic variables. In considering their findings in the context of the existing studies, these investigators underscore the potential importance of gender, noting a good degree of consistency across studies that LVMI may be less likely to relate to stress SBP in premenopausal women than in men. Although we did not find gender to be an important determinant of LVMI in the present study, as noted earlier, the effects of obesity may mask the contribution of other individual difference characteristics that may be important in a broader population-based sample (50). In some ways, this limitation of our study underscores the difficulty in integrating the inconsistent findings from cross-sectional studies relating stress SBP and LVMI. However, although the present findings may not achieve clarification of the field, they are consistent with the suggestion that high blood pressure and advancing age may be more likely to favor observations of a link between stress BP and LVMI.

Another unresolved issue concerns the salient characteristics of stressors. As observed in the current study, such laboratory stressors as Mirror Trace and Cold Pressor seem more likely to evidence a relationship between BP responses and LVMI (14, 16, 18). Although abnormally pronounced {alpha}-adrenergic receptor-mediated vasoconstriction has been speculated to be the basis of this phenomenon (16), our failure to observe a role for SVR responses suggests that other mechanisms are likely to be involved. Stress BP may also be important because it reflects the degree of sympathetic nervous system (SNS) activation. The role of the SNS in the pathophysiology of hypertension is well established, and there is growing evidence that it may be important in the development of LVH (59, 60). Observations that norepinephrine causes myocardial hypertrophy in cultured cardiomyocytes (61, 62) and produces cardiac hypertrophy in animals (63–65) has led to examination of the relationship between norepinephrine and LVMI in humans. Kelm and colleagues (66) found that cardiac sympathetic activity, as indicated by release of norepinephrine, predicted LVMI over and above BP in 39 subjects with a broad range of BP and LV mass. Interestingly, such vasoconstrictive stressors as Cold Pressor seem to achieve their pressor effects through SNS activation, which is mediated almost exclusively via norepinephrine release (67). In contrast, pressor responses to other stressors, such as Public Speaking and reaction-time tasks, seem to invoke adrenal medullary activation, with both epinephrine and norepinephrine release characterizing the SNS response (67, 68). One possibility is that the SBP response to stressors that favor vasoconstriction may be a particularly sensitive index of norepinephrine release during stress, making it a sensitive marker of pathophysiological response.

A limitation of the present findings is the cross-sectional study design, which precludes any inferences regarding the cause-effect relationship between stress BP and LVMI. There is, however, some evidence that stress BP is a prognostic marker of the development of cardiovascular disease. For example, several studies have shown that BP responses during stress are predictive of future hypertension (69–73). More recent evidence suggests that stress BP may predict change in LV mass. In an evaluation of borderline hypertensive men, Georgiades et al. (21) devised an index describing the stress BP response by aggregating measurements made during a mental arithmetic and a handgrip stressor. Men who showed higher BP reactivity to these laboratory challenges had significantly greater LVMI than low-reactive men at the 3-year follow-up. Similarly, in a retrospective study of adolescents, LVH was related to an aggregate measure of BP responses to a battery of four physical and psychological challenges conducted 2.5 years earlier (15). These provocative findings underscore the need for comprehensive long-term prospective studies evaluating the prognostic significance of stress BP in relation to the development of LVH. In addition to helping resolve the issue of cause and effect between stress BP and LVMI, observations from prospective studies should help us develop a conceptual framework that may reconcile the inconsistent findings that have emerged so far from the published cross-sectional studies.

In summary, our findings add to the emerging evidence that BP responses during stress are related to LVMI and LVH. Demographic, anthropometric, hemodynamic, and other patient characteristics seem to moderate the extent to which stress BP is relevant to explaining variations in LVMI. The present study extends previous work by reporting an association of LVMI with stress BP in a biracial sample of mild to moderately overweight men and women with Stage 1 to 2 hypertension or high normal clinic BP. In the present sample, BMI was strongly correlated with LVMI, underscoring how the characteristics of a given study sample may have an important bearing on the observed predictors of LV mass. Nonetheless, stress BP further explained individual differences in LVMI, even after accounting for the contribution of BMI, as well as clinic BP. Additional research is necessary to determine whether stress is a marker and/or a mechanism of the development of LVH, and if interventions that modify the stress response can alter progression of LV pathology.


   ACKNOWLEDGMENTS
TOP
 ABSTRACT
 INTRODUCTION
 METHODS
 RESULTS
 DISCUSSION
 NOTES
 ACKNOWLEDGMENTS
REFERENCES
 
The authors wish to acknowledge the assistance of Joseph Kislo and David Adams for making available the resources of the Duke Medical Center echocardiography laboratory, and Mohan Chilukuri for performing physical examinations. The authors are also grateful to the staff of the General Clinical Research Center for their support of this research program.

This research was supported by Grants HL 49572 and HL 59672 from the National Institutes of Health (NIH) and M01-RR-30 General Clinical Research Centers Program, National Center for Research Resources, NIH, Bethesda, Maryland.


   NOTES
TOP
 ABSTRACT
 INTRODUCTION
 METHODS
 RESULTS
 DISCUSSION
 NOTES
ACKNOWLEDGMENTS
 REFERENCES
 
1 The close relationship between LV mass and body size is well documented. To examine the role of hemodynamic factors in the current study, we follow the current echocardiographic standards established by the Cornell group (36) for correcting LV mass for body size, by expressing it in grams divided by height raised to the 2.7th power (g/m2.7). All analyses and results presented in the present manuscript are based upon LV mass indexed in this way (LVMI). Because obesity is a characteristic of our study sample, our development of regression models necessarily includes body mass index (BMI), expressed in kg/m2, as a critical factor explaining individual differences in LVMI. This approach might suggest the introduction of a statistical confound by examining the association of indices (LVMI, BMI) whose derivation share a common factor (height). In our study sample, however, BMI was found to be almost entirely independent of height (Pearson R = -0.005, p > .95, N = 97). Nonetheless, we conducted the same correlation and regression analyses as reported in this manuscript using raw LV mass. As would be expected, the overall magnitude of association for hemodynamic variables was substantially weaker with raw LV mass compared with LVMI, but importantly the pattern of observations across the various BP measurement contexts remained fundamentally similar for raw LV mass to those reported here for LVMI. Back

2 In Model 2, the inclusion of clinic BP followed by stress BP could be considered similar to an evaluation of the role of BP "reactivity" to stress. The reader is referred to the approach adopted in some reactivity studies, whereby stress BP is residualized for resting baseline BP (38). However, it should be underscored that we chose to include clinic BP (based upon standard readings taken over multiple days—see Methods) because it is the most widely used BP measurement, with an established relationship to end-organ disease. Back

Received for publication January 3, 2001.


   REFERENCES
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 ABSTRACT
 INTRODUCTION
 METHODS
 RESULTS
 DISCUSSION
 NOTES
 ACKNOWLEDGMENTS
 REFERENCES
 

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