| ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
(Circulation. 1996;93:1677-1684.)
© 1996 American Heart Association, Inc.
Articles |
Mean Red Cell Volume as a Correlate of Blood Pressure
From the Honolulu Epidemiology Research Unit (D.S.S., C.M.B.), Field Studies and Clinical Epidemiology Scientific Research Group, Epidemiology and Biometry Program, Division of Epidemiology and Clinical Applications, National Heart, Lung, and Blood Institute, Honolulu, Hawaii; Honolulu Heart Program (J.D.C., B.L.R., K.Y.), Kuakini Medical Center, Honolulu, Hawaii; Department of Medicine (J.D.C., I.J.S., B.L.R.), John A. Burns School of Medicine, University of Hawaii at Manoa (Honolulu); and Department of Physiology and Biophysics (H.J.M., T.C.F.), University of Southern California School of Medicine (Los Angeles).
Correspondence to Dr Dan S. Sharp, Honolulu Heart Program, National Heart, Lung, and Blood Institute, 347 N Kuakini St, Honolulu, HI 96817. E-mail dan@hhs.cba.hawaii.edu.
 |
Abstract |
|---|
 Top Abstract IntroductionMethodsResultsDiscussionReferences |
|---|
Background Clinical studies suggest that hypertensives have lower mean corpuscular volume (MCVs) than do normotensives. Epidemiological studies show no relation or higher MCVs. In the present study of elderly men (71 to 93 years of age) of the Honolulu Heart Program, elements of both findings are confirmed.
Methods and Results Three groups are identified: (1) those receiving no hypertension treatment, (2) those receiving treatment with any diuretic, and (3) those receiving treatment with nondiuretics only. MCV is lower in group 3 than in group 1 (-0.85 fL, P<.001) but the same in groups 1 and 2. Within groups 1 and 3, inverse relations of -0.22 and -0.09 mm Hg/fL (P<.05) are noted for systolic (SBP) and diastolic (DBP) blood pressures. No relations are observed in group 2. MCV and red blood cell count (RBC) are inversely correlated (r=-.45). In group 2, adjustment for RBC unmasks a direct relation between MCV and SBP (0.5 mm Hg/fL, P=.02) and DBP (0.3 mm Hg/fL, P=.02). In groups 1 and 3, relations between SBP and MCV are lost after adjustment for RBC (0.005 mm Hg/fL). For DBP, adding RBC plus an MCVxRBC interaction is significant (P<.001). DBP is 5 mm Hg greater in the highest RBC quartile than in the lowest. A +3 mm Hg difference between extreme MCV quartiles is noted only at high RBC levels.
Conclusions The relation between blood pressure and red cell measures is probably mediated by whole blood viscosity. Hematocrit is a determinant of whole blood viscosity. Viscosity affects peripheral resistance to blood flow, and peripheral resistance affects DBP. At high RBC levels, MCV may be "downregulated." This may lower whole blood viscosity and partially reduce DBP without compromising flow.
Key Words: blood pressure • blood viscosity • erythrocytes • vascular resistance
|
Introduction |
|---|
|
TopAbstractIntroductionMethodsResultsDiscussionReferences |
|---|
Recent reports suggest that people with hypertension have lower MCVs than do subjects with normal blood pressure.1 2 Two animal models support such a relation, with derangement in transmembrane sodium flux control implicated as a cause of cell volume regulation and of blood pressure control, particularly DBP.3 However, a recent cross-sectional population-based study of 317 employed men in Italy with a low prevalence of elevated blood pressure demonstrated no relation between MCV and blood pressure, with or without adjustment for alcohol and smoking behaviors.3 Similarly, preliminary analysis of data from the Gubbio Population Study in Italy indicates that men and women diagnosed as hypertensive had statistically significantly higher MCVs than did normotensive control subjects.4
There is significant literature documenting relations of blood pressure with the erythrocyte measures of RBC, hematocrit, and hemoglobin in clinical and epidemiological studies but not with MCV.
Since the turn of this century,5 clinical studies have indicated a class of patient with positively correlated erythrocyte measures (eg, RBC, hematocrit, and hemoglobin) and blood pressure. This condition, variously called "stress polycythemia," "relative polycythemia," "spurious polycythemia," and "pseudopolycythemia," has been used to describe a clinical condition in which a raised hematocrit is associated with a normal total-body red cell mass, with normal or slightly reduced total-body plasma volume, and with hypertension, obesity, "stress," and heavy cigarette smoking.6 The topic was reviewed in 1987 by Isbister,7 and a significant role for whole blood viscosity is identified as a mediator of these relations.
Population-based studies extending to the mid-1960s uniformly demonstrate positive relations of blood pressure with the erythrocyte measures of RBC, hematocrit, and hemoglobin.8 9 10 11 12 13 14 15 16 Almost every one of these studies demonstrate positive correlation coefficients on the order of .1 to .2 with DBP, but weaker positive relations involving SBP are noted only in some subsets of subjects.
In neither the clinical studies5 6 7 nor the epidemiological studies8 9 10 11 12 13 14 15 16 was the role of MCV in relations with blood pressure examined, except for the four studies reporting apparently conflicting results.1 2 3 4
In seemingly healthy populations, the MCV appears to be negatively correlated with RBC consistently with a coefficient of -.4 to -.5.3 17 The basis for this negative relation is not clear. Because hematocrit is directly proportional to the simple product of RBC and MCV, these statistical and mathematical relations produce circumstances in which negative confounding may operate to obscure the nature of relations between blood pressure and specific erythrocyte measures, particularly MCV.
The fourth examination of men of the Honolulu Heart Program offers the opportunity to assess whether the MCV is directly or inversely related to blood pressure. This assessment demonstrates that elements of both claims are true, depending on whether one is examining differences in average MCV between groups of nontreated men and of men treated for hypertension or relations within groups, focusing on the regression relation between blood pressure and MCV. The results of the latter relations, in particular, suggest a complex interrelation between DBP and erythrocyte indexes that is hypothesized to reflect alterations in long-term pressure/flow regulation mediated by blood viscosity mechanisms.
|
Methods |
|---|
|
TopAbstractIntroductionMethodsResultsDiscussionReferences |
|---|
Study Population
The Honolulu Heart Program is a population-based longitudinal study initiated in 1965 to identify risk factors for cardiovascular disease in Japanese-American men living in Hawaii. A baseline examination of 8006 men who were living on the island of Oahu and were born between 1900 and 1919 was conducted between 1965 and 1968. The men's ages ranged between 45 and 68 years at the time of their examination. Subjects were identified through Selective Service records, and the results of recruitment and the methods of data collection have been described previously.18 19
Of these 8006 men, 4678 were eligible for participation in examination 4 between 1991 and 1993. The examination and informed consent protocol were reviewed and approved by the Kuakini Medical Center Research Institutional Review Board, and all procedures were in accordance with institutional guidelines. A total of 3741 examinations were conducted among survivors, including 3194 clinic visits, 485 home visits, and 62 nursing home visits. In addition to the 3741 examinations, a long telephone interview was obtained for 104 men, and a short telephone interview was obtained for 718 men. Thus, some information was available for a total of 4563 men. Of the 3741 men participating in some form of examination, 3363 of them had complete measurements on all covariates of interest in this study, including red cell measurements.
Baseline Interview and Clinical Examination
Participants were asked to fast for 12 hours before the clinic
visit. Procedures included seated, supine, and standing blood pressure
measures and resting 12-lead ECG followed by venipuncture
and a physical examination. After the fasting blood sample was drawn,
other examination components were scheduled throughout the morning.
Anthropometric measurements included standing height without shoes and
weight.
Red cell indexes were measured on blood collected in a standard 5-mL EDTA specimen tube with a Coulter Counter S Plus (Coulter Corp). The tube was stored at room temperature until laboratory analysis 2 to 4 hours later. Specimens from home visits were analyzed 4 to 6 hours after specimen collection. The Coulter Counter directly measures RBC and MCV and calculates hematocrit as a scaled product of the two.
Blood pressure measurements were obtained on five occasions during the examination; these included two sitting measurements, a supine measurement, and a standing measurement with a conventional mercury sphygmomanometer and a sitting measurement with a Hawksley random zero mercury sphygmomanometer. Technicians were trained to use standardized blood pressure measurement techniques, which included measurement of midarm circumference and selection of appropriate-sized cuffs, stethoscope placement, determination of peak inflation level, appropriate deflation rate (2 mm Hg/s), identification of first-phase (systolic) and fifth-phase (diastolic) Korotkoff sounds, avoidance of digit preference, and proper operation of the Hawksley random zero sphygmomanometer. Technicians were initially certified, recertified 1 month later, and thereafter recertified every 6 months. An average of the five measurements was used as the measure of blood pressure after demonstrating that similar patterns of relation existed for separate measures.
Subjects were asked to bring to the examination all prescription medications, which were recorded by name. Prescription medications were being taken by 2783 men, of whom 1553 were taking antihypertensive medications. A direct question about the use of prescribed antihypertensive agents identified 333 men who denied taking such drugs but who nevertheless reported taking a drug that could be prescribed for hypertension control. Although a portion of these men may have been prescribed such medications for other conditions, such as congestive heart failure, angina, and/or arrhythmias, they were identified as taking antihypertensive agents in the belief that many of them were probably unaware of why they were taking a medication or that the impact of such medication use on blood pressure/erythrocyte measure relations would be unrelated to indication for treatment.
With the use of the strategy of Cirillo et al,20 men with complete data on all covariates were classified into three groups based on treatment status and the known impact of diuretics on plasma volume, which affects red cell measurements.21 These groups were (1) 1810 men taking no antihypertensive drugs, including men having elevated blood pressure of >140 mm Hg SBP or >90 mm Hg DBP; (2) 477 men taking diuretics either alone or in combination with other types of antihypertensive agents; and (3) 1076 men taking nondiuretic antihypertensive agents. Nondiuretic agents included vasodilators, angiotensin-converting enzyme inhibitors, calcium channel blockers, ß-blockers, and combinations of these.
Statistical Analysis
Analyses were conducted with the SAS
program, version 6.08, for Windows-based desktop personal
computers.22 Descriptive statistics such as mean and SD
values among the medication groups were calculated and compared with
the use of PROC T TEST, and multiple linear regression
modeling was done with the use of PROC REG. The progression
of analyses is detailed in "Results." Significance for
two-sided type I statistical error was arbitrarily chosen to be
<.05.
A series of three models was used to sequentially examine the relation
between SBP or DBP and (1) MCV; (2) MCV plus RBC; and (3) MCV, RBC, and
their interaction (MCVxRBC). The interaction of MCV and RBC is
directly proportional to the hematocrit (hematocrit 
MCVxRBC), and,
indeed, the Coulter Counter determines the hematocrit by directly
measuring the MCV and the RBC and then calculating the scaled
product of the two. Thus, models containing the terms MCV, RBC, and
hematocrit are equivalent to a model testing the significance of the
statistical interaction between MCV and RBC. For this reason, although
RBC and hematocrit are highly correlated (r
.9), because
they are mathematically related as a multiplicative interaction, issues
of colinearity are not relevant.
Reported relations between red cell measures and blood pressure were statistically adjusted for age, weight, and height. In analyses where men were pooled from two treatment groups, group membership was coded as a two-level covariate and taken into account as a statistical adjustment factor. Additional analyses that were also adjusted for smoking and alcohol consumption habits had no impact in altering the magnitude or significance of regression coefficients or of differences in mean values of blood pressure among categories of red cell measures. Thus, only age-, weight-, height-, and, as appropriate, treatment group–adjusted statistics are reported.
|
Results |
|---|
|
TopAbstractIntroductionMethodsResultsDiscussionReferences |
|---|
Between-Group Comparisons
Men receiving treatment for hypertension are notably heavier (2.5 to 3.0 kg) than men not under treatment (Table 1
). Men
exclusively receiving nondiuretics are, on average, 7 to
9 months younger than the no-treatment and
diuretic-treatment groups. SBP is notably higher in treated
groups—3.6 mm Hg higher in the diuretic group and almost
10 mm Hg higher in the group treated only with
nondiuretics.
|
RBC and hematocrit are significantly higher in both treatment groups. However, MCV is notably lower in men treated exclusively with nondiuretic agents, whereas no difference from the no-treatment group is noted for men treated with any diuretics. These differences, although clinically small, are 16% to 19% of respective SDs.
Within-Group Relations
The regression relation predicting SBP and DBP from MCV changed
dramatically as RBC and then hematocrit (MCVxRBC) are sequentially
added to age-, weight-, and height-adjusted models (Table 2).
|
For SBP, the regression coefficient for MCV is initially negative for the no-treatment group (1) and nondiuretic-treated group (3) and statistically significant (P=.007) for the former group. However, with the addition of RBC as a covariate, the MCV regression coefficients of both groups are markedly decreased in magnitude—effectively to zero—whereas the regression coefficients for RBC are strongly significant and approximately of the same positive magnitude in the two groups. The addition of hematocrit, which is effectively a model for statistical interaction, accounts for no significant additional variation in SBP, as indicated by the lack of statistical significance of the hematocrit regression coefficient.
For the group treated with any diuretic (group 2), the
regression coefficient for MCV predicting SBP is slightly positive
although not statistically significant (P=.43). However,
with the addition of RBC as a covariate, the magnitude of the MCV
regression coefficient increases more than threefold and becomes
significant (P=.02). The general pattern of SBP among joint
categories of RBC and MCV confirms the elevation of blood pressure with
increased count but what may be a slight flattening of the direct
relation between blood pressure with MCV at higher RBC counts (Fig 1). This suggested pattern of relation involving MCV is
in contrast to the other two treatment groups (discussed later),
although it may be a random effect given the marginal statistics when
hematocrit is added to the model. The addition of hematocrit,
effectively a test of an interaction model between MCV and RBC,
produces a marginally significant regression coefficient for hematocrit
(P=.072). The pattern of positive and negative coefficients
for MCV, RBC, and hematocrit is notably opposite of the pattern for the
no-treatment group (1) and the nondiuretic-treated
group (3), although interaction models in these groups do not produce
statistically significant regression coefficients.
|
For DBP, the regression coefficient for MCV is also initially negative
in all three groups and statistically significant (P=.015)
for the no-treatment group (Table 2
). The addition of RBC as a
covariate results in positive MCV regression coefficients,
statistically significant in men taking any diuretic (group 2)
and men taking nondiuretics only (group 3). Interaction
models are statistically significant for the no-treatment group (1)
and the nondiuretic-treated group (3) as reflected in the
significance of the hematocrit coefficient. Both the sign and the
magnitudes of the MCV, RBC, and hematocrit coefficients are comparable
although slightly larger in the latter group.
The model predicting DBP and containing hematocrit as variables
reflecting the MCVxRBC interaction is not significant
(P=.28) for the group treated with any diuretic
(group 2), although the model including only MCV and RBC does produce
statistically significant coefficients for both of these variables.
As with SBP, DBP systematically increases with increasing RBC, and a
hint of flattening of the direct relation of blood pressure with MCV at
higher RBC counts is noted (Fig 2), although the
statistics for an interaction model suggest that this is nothing more
than random variation. Although not significant at <.05, the
patterns of positive and negative coefficients for the interaction
model of MCV, RBC, and hematocrit (MCVxRBC) are completely opposite
those noted for the no-treatment and the
nondiuretic-treated groups (groups 1 and 3,
respectively).
|
In aggregate, these findings suggest that relations among blood pressure and erythrocyte measures are different in men treated with diuretics, and it is not advisable to pool data from men in this group with data in men treated only with nondiuretics.
Pooled Group Relations
Men in groups 1 and 3 (no treatment and nondiuretics
only) demonstrate similar patterns of regression relation. Accordingly,
men in these groups are combined into a single group for
analyses, although an indicator variable reflecting
original group membership is added to models to take into account group
differences in mean blood pressure and erythrocyte indexes (see Table 1).
In this combined sampling frame, the models that include MCV alone
indicate an inverse relation of SBP and DBP with MCV (Table 3). The pattern of that relation among quartile
groupings of MCV reveals markedly lower blood pressure at the highest
MCV grouping for both measurements (Fig 3). A
statistical test that adds a squared term in MCV to the model suggests
a significant relation for DBP (P=.05) but not SBP
(P=.56). However, the addition of RBC as a covariate
markedly attenuates the relation between SBP and MCV, and the model
predicting DBP from MCV, RBC, and hematocrit produces statistically
significant regression coefficients for all three erythrocyte
measurements, with the MCVxRBC interaction variable hematocrit
being the most prominent (P<.001).
|
|
The nature of relations between SBP and quartile groupings of RBC for
the associations described in Table 3 indicates a graded increase in
blood pressure with increasing RBC, 5 mm Hg between the lowest and
highest quartiles (Fig 4). Within RBC quartile
groupings, no relation with MCV is noted.
|
The nature of the same relation for DBP reveals a similar graded
increase in blood pressure with increasing quartile group of RBC but
also reveals the nature of the association of DBP with MCV and the
interaction of MCV with RBC (Fig 5). At the lowest level
of RBC, there appears to be no relation between DBP and MCV. However,
with increasing RBC, a direct relation becomes apparent such that at
the highest levels of RBC, the DBP/MCV relation is at its steepest.
Within the highest quartile grouping of RBC
(
5.0x1012/L), the difference in DBP between the
lowest (<92.5 fL) and the highest (97.5 fL) MCV quartile groups is
on the order of 3 mm Hg. This finding significantly contrasts with the
suggestions of a flat blood pressure/MCV relation at higher RBCs among
men treated with any diuretic (group 2) and a direct relation
at lower RBCs (Figs 1 and 2). Too few observations and the attendant
marginal statistical significance of the interaction models in this
group (n=477) preclude any definitive assessment of this contrast.
|
- |
Discussion |
|---|
|
TopAbstractIntroductionMethodsResultsDiscussionReferences |
|---|
Consistency of Findings
Without taking into consideration joint relations with other red cell measures, the MCV appears to be inversely related to SBP and DBP. This is demonstrated by the average SBP and DBP being higher and the average MCV being lower in group 3 (men treated exclusively with nondiuretic medication) than in group 1 (men with no treatment for hypertension) (Table 1
). Within these groups, both
separately and after pooling, an inverse regression relation is also
noted between SBP or DBP and MCV (Table 3 and Fig 3). It appears that
this negative regression relation is primarily driven by data from the
no-treatment group (Table 2, MCV Alone). These results are
consistent with the clinical studies reported by Bruschi et
al1 and Postnov et al2 but
inconsistent with the population-based studies of
Strazzullo et al3 and Cirillo and
Laurenzi.4
After adjustment for RBC, the MCV remains -0.49±0.16 fL lower
(P=.002, not reported in tables) in men treated exclusively
with nondiuretics (group 3) compared with men not treated
(group 1) for hypertension (-0.85±0.18 fL without RBC
adjustment, Table 1). However, within each of these groups, the
regression relation between blood pressure and MCV after adjustment for
RBC is either nonexistent (eg, SBP) or positive (eg, DBP) (Tables 2 and 3). Thus, elements of both the clinical1 2 and the
population-based3 4 studies are supported, depending
on how the comparisons are structured.
Hypertension Treatment Effects
Observations among men treated with diuretics may be
related to an effect of diuretics to reduce total plasma
volume. Men treated with any diuretic had the highest
hematocrit compared with the other two groups (Table 1). Such
"hemoconcentration" effects are well established.21
Simple correlations between MCV and RBC within the three groups (no
treatment, any diuretic, and only nondiuretics) are
remarkably comparable (-0.448, -0.453, and -0.448,
respectively), although the SD of RBC (Table 1) is significantly larger
in men treated with any diuretic compared with the other two
groups (0.49, 0.56 [P<.001], and
0.49x1012/L, respectively). Unfortunately, without
measurements of total red cell mass and total plasma volume, contrasts
of RBC and MCV among these treatment groups are difficult to
interpret.
The aged nature of the Honolulu Heart Program population in this analysis may be a significant factor in explaining differences among the three treatment groups. Hemodynamic patterns of hypertensive disease in younger men are distinctly different than patterns noted in older men. Cardiac output is notably lower and total peripheral resistance is higher in older hypertensive men than in age-matched normotensives.23
Hemodynamic Implications
Consistent among all three treatment groups is the
relatively "strong" relation among RBC, SBP, and DBP.
Population-based studies have consistently demonstrated
direct relations between blood pressure and simple measures of
erythrocyte properties, particularly hematocrit.8 9 10 11 12 13 14 15 16 The
relation of hematocrit with blood pressure appears to be mediated by an
impact on whole blood viscosity.16 24 25 Animal
experiments indicate a causal relation between viscosity and both
pulmonary and peripheral resistance to blood
flow.26 Clinical studies in humans confirm this
finding.27 28 Such a finding, although not necessarily
sufficient to explain the relation between erythrocyte measures and
blood pressure in studies such as this one, does suggest that a
portion of that relation may be driven by fluid mechanical
considerations whereby blood flow (U) to an organ system
through a vessel of fixed diameter (d) and length
(l) is maintained by an increase in blood pressure
(P) when blood viscosity (
) becomes elevated,
or (see Reference 2929 ):
 |
A ratio of P/U reflects resistance to flow, thus implying that blood flow resistance is determined by blood viscosity and by "vascular hindrance," this latter term representing the contribution of vascular geometry (d and l).30
Empirical equations for the viscosity of a suspension of particles
(s) relative to the viscosity of the
suspending phase (o) are defined in terms of
the volume fraction of the particles in the total volume of the
suspension (
) by (see Reference 3131 ).
 |
where 
and 
are empirically estimated coefficients, and
higher orders of the volume fraction, , may be necessary
to fully describe the relation. The volume fraction can be considered
analogous to the hematocrit and, thus, blood viscosity changes
nonlinearly with hematocrit.32 However, the relation
between whole blood viscosity and the constituents of blood is complex
and can be affected by red cell deformability, reversible aggregation
between red cells, and flow characteristics in the
vasculature.30 In the present study, we chose to
conceptualize red cell "mass" as RBC in the belief that cell
"count" and "volume" variables more specifically
measure underlying physiological processes.
Although the contribution of the red cell mass to whole blood viscosity
can be thought of in terms of the hematocrit and although the
hematocrit is proportional to the product of MCVxRBC, the
rheological behavior of blood is sufficiently complicated to preclude
the expectation that a constant hematocrit implies a constant
viscosity. In fact, recent experimental work demonstrates significant
decreases in whole blood viscosity with decreasing MCV at a constant
hematocrit,33 thus indicating the need to consider both
MCV and RBC rather than only their product.
Hypothesis Proposed
Within the foregoing conceptual framework, the following model is
suggested by these results.
(1) Because essential hypertension is primarily a derangement of peripheral vascular resistance30 and because DBP is a more specific measure of overall resistance to blood flow than SBP, blood characteristics that influence viscosity will be more strongly related to DBP than to SBP.
(2) In general populations, there is a sufficiently high prevalence of and/or variation in health conditions that increase relative red cell mass to the point of affecting hemodynamic function.
(3) The impact of an increase in relative red cell mass is to increase whole blood viscosity, primarily by increasing the number of particles per unit volume of blood (RBC), and thereby increase peripheral resistance to blood flow.
(4) To maintain blood flow in the face of increased peripheral resistance, blood pressure increases.
(5) The deleterious consequence of increasing pressure, presumably to maintain blood flow, is partially compensated for by a concomitant decrease in red cell volume, thus attempting to counteract the viscous effects of a larger relative red cell mass (ie, count) with smaller cell size characteristics.
Because blood pressure level would appear to be a necessary
modulator in this hypothesis, an interaction is implied of pressure
regulation with counterregulatory relations between RBC and MCV. This
is the key implication of the results presented in Fig 3 and is
partially supported by laboratory-based research via rheological
mechanisms.33 The hypothesis attempts to integrate known
physiological processes linking blood pressure,
blood flow, and peripheral resistance to flow with known
relations involving fluid mechanics and viscosity of whole blood. It
does not purport to describe how viscosity characteristics, via red
cell mass, come to be altered, nor whether such alterations precede or
follow a derangement in blood pressure regulation.
Practical Implications
Clinical implications ensue from this model. Although early
hypertensive disease is associated with increased resistance to flow,
this appears to be primarily mediated by increases in blood viscosity
rather than vascular hindrance.30 However, in older men or
men with more severe hypertensive disease, both components contribute
to increased resistance, and, indeed, both could be linked as a
manifestation of perturbed pressure/flow regulation. Because of the
geriatric nature of this study group, variation in viscosity
characteristics may play a relatively more important role than vascular
hindrance in the observed relations with DBP.16 Vessel
geometry, vessel compliance, and end-arteriole reactivity may be
relatively static due to atherosclerotic processes and the consequences
of chronic hypertension in this elderly population compared with
hypertensive men 30 to 40 years younger. Thus, if the model implied by
this hypothesis is true, then maintenance of blood flow to
critical organ systems may be better served by factors that decrease
blood viscosity with little compromise of oxygen-carrying capacity
than by factors that alter vessel hindrance.
The model also conveys public health implications. The results suggest that when there is a sufficiently high prevalence of a pathophysiological process, some kind of regulatory interrelationship may be created, such as in this case among DBP, RBC, and MCV. One such example of a pathophysiological condition in an elderly population may be chronic obstructive lung disease and its possible sequel of polycythemia.7 Whether these interrelations would be manifest in other populations with different age, sex, and ethnic characteristics may depend on how such demographic characteristics are related to the existence and manifestation of similar disease processes affecting blood pressure control and the regulation of relative red cell mass. Longitudinal studies in particular may contribute unique understanding as to how derangements in these physiological systems coevolve and are related to the incidence of overt clinical disease.
|
Selected Abbreviations and Acronyms |
|---|
|
|
Acknowledgments |
|---|
This work was supported by contract N01–HC–05102 (to the Honolulu Heart Program, Kuakini Medical Center, Honolulu, Hawaii) from the National Heart, Lung, and Blood Institute; National Institutes of Health Research Grants HL–15722 and HL–48484 (Drs Meiselman and Fisher); and an award from the Wright Foundation, Los Angeles, Calif (Dr Fisher).
Received July 24, 1995; revision received October 23, 1995; accepted November 3, 1995.
|
References |
|---|
|
TopAbstractIntroductionMethodsResultsDiscussionReferences |
|---|
1. Bruschi G, Minari M, Bruschi ME, Tacinelli L, Milani B, Cavatorta A, Borghetti A. Similarities of essential and spontaneous hypertension: volume and number of blood cells. Hypertension. 1986;8:983-989.
2.
Postnov YV, Kravtsov GM, Orlov SN, Pokudin NI, Postnov
IY, Kotelevtsev YV. Effect of protein kinase C activation on
cytoskeleton and cation transport in human erythrocytes:
reproduction of some membrane abnormalities revealed in
essential hypertension. Hypertension. 1988;12:267-273.
3. Strazzullo P, Cappuccio FP, Iacoviello L, Cipollaro M, Varriale V, Giorgione N, Farinaro E, Mancini M. Erythrocyte volume and blood pressure in a cross-sectional population-based study. J Hypertens. 1990;8:179-183. [Medline] [Order article via Infotrieve]
4. Cirillo M, Laurenzi M. Erythrocyte and platelet volume in human hypertension. J Hypertens. 1989;7(suppl 6):S168-S169.
5. Gaisböck F. Die Bedeutung der Blutdruck-messung für die ärztliche Praxis. Deutsch Arch Klin Med. 1905;83:363-409.
6. Pseudopolycythaemia. Lancet. 1987;2:603-604. Editorial. [Medline] [Order article via Infotrieve]
7. Isbister JP. The contracted plasma volume syndromes (relative polycythaemias) and their haemorheological significance. Baillieres Clin Haematol. 1987;1:665-693. [Medline] [Order article via Infotrieve]
8. Tibblin G, Aurell E, Hjortzberg-Nordlund H, Paulin S, Risholm L, Sanne H, Wilhelmsen, Werkö L. A general health-examination of a random sample of 50-year men in Göteborg. Acta Med Scand. 1965;177:739-749. [Medline] [Order article via Infotrieve]
9. Tibblin G, Bergentz SE, Bjure J, Wilhelmsen L. Hematocrit, plasma protein, plasma volume, and viscosity in early hypertensive disease. Am Heart J.. 1966;72:165-176. [Medline] [Order article via Infotrieve]
10. McDonough JR, Hames CG, Garrison GE, Stulb SC, Lichtman MA, Hefelfinger DC. The relationship of hematocrit to cardiovascular states of health in the Negro and white population of Evans County, Georgia. J Chron Dis. 1965;18:243-257. [Medline] [Order article via Infotrieve]
11.
Harlan WR, Hull AL, Schmouder RL, Landis JR, Thompson
FE, Larkin FA. Blood pressure and nutrition in adults: the
National Health and Nutrition Examination Survey. Am J
Epidemiol. 1984;120:17-28.
12. Bao W, Dalferes ER, Srinivasan SR, Webber LS, Berenson GS. Normative distribution of complete blood count from early childhood through adolescence: the Bogalusa Heart Study. Prevent Med. 1993;22:825-837. [Medline] [Order article via Infotrieve]
13. Lowik MR, Odink J, Kok FJ, Ockhuizen T. Hematocrit and cardiovascular risk factors among elderly men and women (Dutch Nutrition Surveillance System). Gerontology. 1992;38:205-213. [Medline] [Order article via Infotrieve]
14.
Havlik RJ, Garrison RJ, Feinleib M, Padgett S, Castelli
WP, McNamara PM. Evidence for additional blood pressure
correlates in adults 20–56 years old.
Circulation. 1980;61:710-715.
15. Shimakawa T, Bild DE. Relationship between hemoglobin and cardiovascular risk factors in young adults. J Clin Epidemiol. 1993;46:1257-1266. [Medline] [Order article via Infotrieve]
16.
Fowkes FHR, Lowe GDO, Rumley A, Lennie SE, Smith FB,
Donnan PT. The relationship between blood viscosity and blood
pressure in a random sample of the population aged 55 to 74
years. Eur Heart J. 1993;14:597-601.
17. Sharp DS, Bath PMW, Martin JF, Beswick AD, Sweetnam PM. Platelet and erythrocyte volume and count: epidemiological predictors of impedance measured ADP-induced platelet aggregation in whole blood. Platelets. 1994;5:252-257.
18.
Yano K, Reed DM, Mcgee DL. Ten–year
incidence of coronary heart disease in the Honolulu Heart
Program: relationship to biologic and lifestyle
characteristics. Am J Epidemiol. 1984;119:653-666.
19. Worth RM, Kagan A. Ascertainment of men of Japanese ancestry in Hawaii through World War II Selective Service registration. J Chron Dis. 1970;23:389-397. [Medline] [Order article via Infotrieve]
20.
Cirillo M, Laurenzi M, Trevisan M, Stamler J.
Hematocrit, blood pressure, and hypertension: the Gubbio population
study. Hypertension. 1992;20:319-326.
21.
Leth A. Changes in plasma and extracellular
fluid volumes in patients with essential hypertension during
long–term treatment with
hydrochlorothiazide.
Circulation. 1970;42:479-485.
22. SAS Institute Inc. SAS Companion for the Microsoft Windows Environment, version 6. 1st ed. Cary, NC: SAS Institute Inc; 1993:356.
23. Lund–Johansen P, Omvik P. Hemodynamic patterns of untreated hypertensive disease. In: Laragh JH, Brenner BM, eds. Hypertension: Pathophysiology, Diagnosis, and Management. New York, NY: Raven Press Ltd; 1990:305-327.
24. Smith WCS, Lowe GDO, Lee AJ, Tunstall-Pedoe H. Rheological determinants of blood pressure in a Scottish adult population. J Hypertens. 1992;10:467-472. [Medline] [Order article via Infotrieve]
25.
de Simone G, Devereux RB, Chien S, Alderman MH, Atlas
SA, Laragh JH. Relation of blood viscosity to demographic and
physiologic variables and to cardiovascular risk
factors in apparently normal adults.
Circulation. 1990;81:107-117.
26. Harrison BDW, Stokes TC. Secondary polycythaemia: its causes, effects and treatment. Br J Dis Chest. 1982;76:313-340. [Medline] [Order article via Infotrieve]
27.
Letcher RL, Chien S, Pickering TG, Laragh JH.
Elevated blood viscosity in patients with borderline essential
hypertension. Hypertension. 1983;5:757-762.
28. Letcher RL, Chien S, Pickering TG, Sealey JE, Laragh JH. Direct relationship between blood pressure and blood viscosity in normal and hypertensive subjects. Am J Med. 1981;70:1195-1202. [Medline] [Order article via Infotrieve]
29. Berne RM, Levy MN. Cardiovascular Physiology. New York, NY: Mosby-Year Book; 1992:120.
30. Chabanel A, Chien S. Blood viscosity as a factor in human hypertension. In: Laragh JH, Brenner BM, eds. Hypertension: Pathophysiology, Diagnosis, and Management. New York, NY: Raven Press Ltd; 1990:329-337.
31. Van Holde KE. Physical Biochemistry. Englewood Cliffs, NJ: Prentice–Hall Inc; 1971:145.
32. Lowe GDO. Clinical Blood Rheology. Boca Raton, Fla: CRC Press; 1988:27.
33. Chen D, Kaul DK. Rheologic and hemodynamic characteristics of red cells of mouse, rat, and human. Biorheology. 1994;31:103-113.[Medline] [Order article via Infotrieve]
This article has been cited by other articles:
 |
|
 |
|
  D. L. Mann and M. R. Bristow Mechanisms and Models in Heart Failure: The Biomechanical Model and Beyond Circulation, May 31, 2005; 111(21): 2837 - 2849. [Full Text] [PDF]
|
|
|
|
 |
|
 G. de Simone, R. B. Devereux, M. Chinali, L. G. Best, E. T. Lee, T. K. Welty, and for the Strong Heart Study Investigators Association of Blood Pressure With Blood Viscosity in American Indians: The Strong Heart Study Hypertension, April 1, 2005; 45(4): 625 - 630. [Abstract] [Full Text] [PDF]
|
|
|
|
|
|
D. L. Mann Mechanisms and Models in Heart Failure : A Combinatorial Approach Circulation, August 31, 1999; 100(9): 999 - 1008. [Full Text] [PDF]
|
|
| ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||