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Examining possible causes for age-related blood pressure elevations in 107 females volunteering for a weight loss study.


A gradual elevation of systolic blood pressure (SBP) is commonly associated with aging and is generally recognized as being unhealthful. Accordingly, it would be most important if the major cause(s) behind this deleterious, age-related phenomenon were elucidated in order to develop sound regimens for prevention and treatment. As a first approximation, we examined SBP and many other parameters over a wide spectrum of age in 107 healthy females volunteering for a weight loss study. Since several observers have previously associated age-related SBP elevations to a corresponding fat accumulation, this report was also prompted by initial data showing that in older subjects when compared to the younger, fat mass did not seem relatively increased despite higher SBP readings. Therefore, we correlated much of our data via linear regression analysis to determine which of the other measured parameters could be responsible for the age-related augmentation in SBP. Body weight, BM1, fat mass, percent body fat, free fatty mass, cardiac rate, fasting blood sugar, insulin concentrations and HbAlC correlated positively with SBP. In contrast, circulating levels of Vitamin [D.sub.3] correlated negatively with SBP. Of the various parameters scrutinized, only FBS and HbAIC showed a significant positive rise with age and could be responsible, at least in part, with the age-related increase in SBP in the present study.


It is generally accepted that a prolonged elevation of systolic blood pressure (SBP) is deleterious to cardiovascular health. (1-4) This is unfortunate, because the common trend is for a gradual rise in SBP with aging in the United States and many other Western nations. (5), (6) A popular theory is that increased body mass (especially fat mass) that occurs frequently during aging is largely responsible. (7), (12) Recently, we carried out a clinical "weight-loss" study using 107 healthy female volunteers. In this group, we noted by initial observation a significant elevation of SBP with aging despite no increased fat mass and/or body weight. Because at baseline each of the subjects had received a number of other evaluations, we believed, as a first approximation, it would be valuable to determine which of these additional parameters correlated with the age-related SBP elevations--if not excess fat accumulation.


Study Design

To carry out the original "weight loss study," all participants gave written informed consent that was in compliance with the Helsinki Declaration as approved by the researchers' ethics committee. Most volunteers were overweight or obese with a group average BMI of 28.7 kg/[m.sup.2] [+ or -] 1.1 (SEM) (range 16.9 kg/[m.sup.2] to 50.6 kg/[m.sup.2]). The average age was 56.0 years [+ or -] 1.2 (SEM) (range 29 years to 80 years).

After reviewing the study with a research technician, subjects were provided with a copy of the study's informed consent (1C) and were asked to review it with their personal physicians to ensure they had no medical conditions that would preclude their participation. After fasting for at least 12 hours, subjects returned to the research center and completed the test battery described below. All 107 subjects completed a baseline test battery that included: total-body DXA measures of body composition, blood pressure and resting heart-rate, and a 43-blood chemistry blood test panel. Blood chemistries were drawn at a Lab Corps Service Center of the subject's choice (

Specific Testing

Body Composition. In contrast to scale weight readings, which reflect how much not what kind of weight is lost, DEXA measurements provide for assessment of the kind of weight lost--fat, fat-free mass (FFM) and bone mineral density (BMD). The DEXA test provides a three-compartment model of body composition: fat, fat free mass (FFM), and bone mineral density (BMD). Measurements were made using a constant potential energy source at 78 kVp and a K-edge filler (cerium) to achieve a congruent, stable, dual-energy beam with effective energies of 40 and 70 keV. The unit performs a series of transverse scans moving from head to toe at one mm intervals; the scan area was approximately 60 cm x 200 cm. Data were collected for about 120 pixel elements (5 x 10 mm) per transverse. Total body measurements were typically completed in -10 minutes with a scan speed of 16 cm/sec or in -20 minutes with a scan speed of eight cm/sec. The R-value (ratio of low to high-energy attenuation in soft tissue) ranged from 1.20 to 1.47.

Blood Chemistries. After lasting for 12 hours, subjects had venous blood samples drawn at a local drawing station of their choice. Blood samples were collected in EDTA (one mg per milliliter) and were centrifuged within four hours, the plasma was separated, and the plasma sample shipped at 4 [degrees] C to a central laboratory. Analyses were made by routine clinical procedures.

Statistical Analyses

All linear regression statistical analyses were earned out with KaleidaGraph graphing and data analysis. Version 3.6, Synergy Software, Reading PA. A p < 0.05 determined by using a table of correlation coefficients (r value) was considered to be statistically significant.


Correlations of SBP and DBP with Age (Fig. 1)


When SBP and diastolic blood pressure (DBP) were correlated with age as depicted in Fig. 1, a significant linear correlation was found for SBP (r=0.33; p < 0.01). At 30 years of age, the average SBP of our volunteers was around 112 mm Hg and climbed gradually to around 128 mm Hg by age 80. Five of the subjects had an initial SBP reading at or above 140 mm Hg with the highest reading being 155 mm Hg in a 79 year old. In contrast, the overall DBP readings did not lit a linear regression curve well, so a polynomial plot was used as depicted in Fig. I. In our volunteers, DBP seemed to rise gradually in the younger age group but somewhere around age 45-60 leveled off and then began to decline after that.

Correlation of Structural Parameters

There was a statistically significant correlation of body weight to body mass index (BMI) derived from consideration of both weight and height (r=0.93, p < 0.01). Examining the relation of BMI to other "structural" parameters, the following statistically significant correlations could be found: Fat Mass r=0.92, Per Cent Fat r= 0.78, Free Fatty Mass (FFM) r = 0.66, tone Mineral Density (BMD) r = 0.47. When these same structural parameters were compared to age, no significant positive correlations were found.

Correlations of SBP With Varied Measured Parameters (Table 1)

SBP correlated significantly with many of the structural parameters as depicted in Table 1-scale weight, BMI, Fat Mass, % Fat, and FFM. "No correlation existed with BMD, although there was a significant negative correlation of SBP with circulating levels of vitamin [D.sub.3]. Examining the glucose-insulin system showed a significant positive correlation of SBP with FBS, HbAlC, and insulin levels in the circulation. Blood urea nitrogen (BUN) and circulating creatinine levels had no significant correlations with SBP.

Correlations of Age with Varied Measured Parameters (Table 2)

Of all the significant correlations with SBP noted above, when it came to age, only a correlation of FBS and HbAlC was found in these volunteers (Table 2). Unexpectedly, when structural parameters were compared to age, no significant correlations, with a single exception, were found. FFM that had correlated positively with SBP showed a significant but negative correlation with aging. The circulating levels of BUN and creatinine displayed a positive correlation with aging but did not show any correlation with SBP.
Table 2 CORRELATIONS WITH AGE (108 Females)
Parameter r Correlation Coefficient P value

Weight     .1 55        NS

BMI         .100        NS

Fat Mass    .038        NS

Fat %       .072        NS

FFM         .245      <.05

BMD         .325      <.01

D3          .082        NS

SBP         .332      <.01

DBP         .094        NS

Card Rate   .074        NS

FBS         .267      <.01

Insulin     .022        NS

AIC         .256      <.01

BUN         .425      <.01

Cr          .206      <.05

BUN/Cr      .279      <.01

For n= 100,.195 is p <.05..254 is p<.01


Certain important health parameters change adversely with age. Concerning structure, body weight on average increases because of an excess accumulation of fat that exceeds loss of muscle mass and decreased bone mineral density.12 Since SBP has also been reported to increase with age,"'6 many believe that increased fat mass directly or indirectly plays an important role in SBP elevations that progress during aging. (10), (11)

Recently, we recruited 107 relatively healthy female subjects for a "weight loss study" and noted initially among the volunteers a significant linear correlation of augmented systolic (SBP) with increased age, but no similar correlation between fat accumulation and aging. This suggested to us that something other than excess fat accumulation was largely responsible for the increasing pressure over time in our subjects. Since baseline measurements for our study included DXA examinations as well as certain important blood chemistries, we were able to examine correlations among many parameters to determine the potential mechanisms behind the age-related changes in SBP in our study group.

The data in Table 1 show the following significant positive correlations with SBP elevations: body weight, BMI, fat mass, % fat, fat free mass (FFM), cardiac rate, fasting blood sugar, insulin, and glycosylated hemoglobin (HbAlC). It is not surprising that each of the first five parameters listed in table 1 (structural) all correlated positively with SBP, since all of them correlated with each other. Because SBP shows a significant positive correlation with age, our premise was that the factors involved with this age-associated rise in SBP should correlate positively with age-just as SBP did. However, when examining structure with age, none of the parameters showed a positive correlation-FFM actually showed a negative correlation. Thus, the previously mention correlation between FFM and SBP depicted in Table 1 like the other structural parameters could not be a principle factor in the rising SBP seen here.

Parameter r Correlation Coefficient P value

Weight           .397  < 0.01

BMI              .457  < 0.01

Fat Mass         .410  < 0.01

Fat %            .388  < 0.01

FFM              .253   < 0.5

BMD              .155     NS

D3         .214 (neg)  < 0.05

Card Rate        .362  < 0.01

FBS              .345   < .01

Insulin          .359  < 0.01

AIC              .329   < .01

BUN              .094      NS

Cr               .023      NS

BUN/Cr           .089      NS

For n=100,.195 is p < .05,.254 is p< .01

It is a well-recognized fact that fat accumulation generally occurs during aging. (12) What happened in this study? We rationalized that the major thrust for recruitment was to obtain overweight people. Accordingly, for the most part, only fat-ladened younger individuals enrolled to mollify the difference seen normally in the aging process. Under usual circumstances, fat accumulation in the elderly may be in part responsible for age-related high blood pressure, but not here. Were we indeed examining a "fat group"? Over the entire range of age in the volunteers, the average percentage fat was about 42-44%. Much higher than the desired female value of 20-25%.

Even though fat accumulation did not appear to play a role in the higher pressure among the older individuals, still SBP rose significantly with advancing age. This emphasized the need to look elsewhere. Among our examined parameters, this left the correlation of fasting blood sugar and HbA1C both of which rose with age, as potential major causes for age-associated SBP elevations. It has long been noted that insulin resistance can be involved in hypertension. We found that FBS, HbAlC, and circulating insulin levels significantly correlated with the SBP and that FBS and HbAlC concentrations rose significantly during aging. Our data suggest that preventing insulin resistance with the rise in circulating glucose levels might prevent, or at least ameliorate some portion of age-related hypertension.(13), (14) In summary, our data indicate that factors other than fat accumulation could have a prominent role in SBP elevations with aging. The latter conclusion may be very important, because a number of safe, natural dietary supplements that can overcome the high levels of circulating glucose and insulin that exist with aging (15-19)

In closing, we should mention that we did not perform extensive analysis on DBP correlations. Over the years, it has become obvious that SBP is the sounder prognosticator of cardiovascular disorders, i.e., SBP is a more severe perturbation that elevated DBP. (1-3) Also, the usual scenario is for DBP to increase early on in life but decrease in later periods of the life span, whereas SBP continues to increase throughout the life span (5), (6) (Fig. I).

ACKNOWLEDGMENTS: Doctors Preuss and Kaats have no conflicts of interest.


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(15.) Perricone NV, Bagchi D, Echard B, Preuss HG: Long-term metabolic effects of different doses of niacin-bound chromium on Sprague-Dawley rats. Molecular and Cellular Biochemistry 338:91-103, 2009.

(16.) Preuss 1IG, Echard B, Bagchi D, Perricone NV: Maitake mushroom extracts ameliorate progressive hypertension and other chronic metabolic perturbations in aging female rats. Int J Med Sei 7:169-180, 2010.

(17.) Preuss HG, Echard B, Clouatre D, Bagchi D, Perricone NV: Niacin-bound chromium (NBC) increases life span in Zucker rats. J Inorg Chcm 10.1016/j.jinorgbio.201 1.01.005.

(18.) Preuss HG, Echard MT, Bagchi D, Perricone NV: Effects of astaxanthin on blood preussure and insulin sensitivity are not directly interdependent. Int J Med Sci 8:126-138, 2011.

(19.) Clouatre D, Echard B, Preuss HG: Effects of bitter melon extracts in diabetic and normal rats on blood glucose and blood pressure regulation. J Med Foods 14:1-9, 2011.

by: Harry G. Preuss MD (1) & Gilbert Kaats PhD (2)

(1.) Georgetown University Medical Center Department of Biochemistry/Physiology Washington, D.C. 20057

(2.) Health and Research Foundation San Antonio, Texas 78209
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Author:Pram, Harry G.; Kaals, Gilbert
Publication:Original Internist
Article Type:Report
Geographic Code:1USA
Date:Sep 1, 2011
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