Abstract
Blood pressure (BP) variability (BPV) contributes to target organ damage independent of BP. The authors examined the effect of a 1‐year multidisciplinary intervention on BPV in patients with the metabolic syndrome (MetS) as defined by criteria from the Third Report of the Adult Treatment Panel. Forty‐four nondiabetic patients underwent clinical and biochemical profiling, 24‐hour ambulatory BP monitoring (ABPM), body composition, carotid intima‐media thickness, and carotid‐femoral pulse wave velocity (PWV). The intervention targeted all MetS components. BPV was assessed by the standard deviation of daytime systolic BP derived from ABPM. Patients with low and high BPV (lower or higher than the median daytime standard deviation of 11.6 mm Hg) did not differ in regards to systolic and diastolic BP, age, fasting glucose, glycated hemoglobin, and body mass index, but the high‐variability group had higher values of low‐density lipoprotein and leg fat. The 1‐year intervention resulted in weight reduction but not BP‐lowering. BPV declined in the high‐variability group in association with lowering of PWV, C‐reactive protein, glycated hemoglobin, alanine aminotransferase, asymmetric dimethylarginine, and increased high‐density lipoprotein cholesterol. A multidisciplinary intervention independent of BP‐lowering normalized BPV, lowered PWV, and enhanced metabolic control.
Blood pressure (BP) is characterized by marked short‐term fluctuations such as beat‐to‐beat, minute‐to‐minute, hour‐to‐hour, and day‐to‐night changes. Twenty‐four–hour ambulatory BP monitoring (ABPM) is the most widely available tool to assess short‐term BP variability (BPV) and its wide use in the practice and research of hypertension allows meaningful insight into BPV's patterns, clinical significance, and underlying mechanisms. It is well‐accepted that short‐term (within 24 hours) variations are affected by sympathetic activation, peripheral resistance (caused by arterial elastic properties),1, 2, 3 blood viscosity, vasoconstrictors effects, and emotional and behavioral factors. There is also growing appreciation that BPV contributes to cardiovascular (CV) complications such that increased variability amplifies the damage caused by high BP per se. BPV likely comprises an independent predictor of CV mortality in the general population, as well as among hypertensive patients.4, 5, 6 Interestingly, little is known about the relationship between the metabolic syndrome (MetS) in nondiabetic patients and BPV. Although the MetS is common in patients with hypertension, and hypertension is a key component of the MetS, certain obesity‐related features of the MetS are not an essential part of the hypertensive phenotype in the general population. Furthermore, the MetS embodies one example of hypertension, in which the treatment of high BP does not necessarily comprise the major therapeutic target, but is rather one of several concomitant interventions to curb overall risk factor control. From an investigational point of view, multicomponent treatment of the MetS also offers an opportunity to assess how such a joint approach affects BPV. We undertook the present study to assess the effect on BPV of 1‐year treatment of MetS provided by a multidisciplinary intervention that included specialists in hypertension and endocrinology/metabolism, a dietician, and a physiotherapist.
Patients and Methods
Study participants were recruited at the Institute of Endocrinology, Metabolism and Hypertension (TASMC, Tel Aviv, Israel) through local advertising and referral of consecutive patients diagnosed with the MetS. The entry period was 2009 to 2013. The study was approved by the institutional review board of TASMC, and written informed consent was obtained from all of participants. Inclusion criteria included patients aged 18 to 75 years who fulfilled criteria from the Third Report of the Adult Treatment Panel (ATP III),7 with minor adjustments––impaired fasting glucose was considered a glucose level ≥100 mg%,8 patients with type 2 diabetes were not included in this trial. Exclusion criteria were current or recent pregnancy or intention to conceive within the trial's period, chronic renal or liver disease, and past bariatric surgery with ongoing weight loss. The intervention targeted all risk factors through frequent interactions with a multidisciplinary team including an endocrinologist, hypertension specialist, and a dietician.
Dietary Intervention
The target for weight loss was ≤5% within the first 6 months and a total of 10% within 12 months. Briefly, the recommended Mediterranean diet was rich in olive oil, legumes, fish, chicken, nuts, white milk products, fruits, and vegetables, and was low in artificial sugars, commercial sweets, pastries, butter, margarine, and red meat. Calorie consumption was set as 25% to 30% less than calories needed for resting metabolic rate. Specifically, the food group consumption rates were set as following: protein, >0.8 g/kg/d; carbohydrates, 40% of total calories at medium/low glycemic index; fat, 30% of total calories (≥10% monounsaturated fatty acid, ≤7% saturated fatty acid, no trans fats, and 1.6 g omega‐3 for men and 1.1 g omega‐3 for women); and finally dietary fiber, ≥25 g.9, 10
Personalized physical training was outlined by a physiotherapist with expertise in exercise physiology. All exercise sessions integrated aerobic and resistance training into each session. Patients were required to exercise at least three times a week beginning at the first week for at least 30 minutes per session. Participants were then instructed to keep training frequency to at least four times a week for the first 6 months and then no more than five times per week for a maximum of 60 minutes per session. Personal adjustments were made according to age, general status, and specific limitations, particularly degenerative joint disease, a common condition in patients with MetS/obesity. Patients were seen by a physician and/or a dietician every 2 weeks during the first 2 months and every month thereafter. Compliance with dietary requirements and physical activity was actively encouraged and recorded through personal interviews at each encounter with the trial's team and telephone communications (every 2 weeks) during the 10 months in the course of which patients were seen only monthly. If needed, patients were medicated to control hypertension and dyslipidemia. Baseline assessment included medical history, physical examination, biochemical profiling, body composition with dual‐energy X‐ray absorptiometry (Lunar iDXA; GE Healthcare, Wauwatosa, WI), femoral‐carotid pulse wave velocity (PWV), and carotid intima‐media thickness (IMT).
IMT of the left and right common carotid arteries was measured prior to the active initiation of the program with a high‐resolution B‐mode ultrasound system using a 7.5‐MHz linear array transducer (Aloka ProSound 4000, Tokyo, Japan) and analyzed offline by automated wall tracking software (MedicaSoft IMT Lab, Creteil, France). At least six measurements were taken over a 1‐cm length of each common carotid artery segment on both sides and averaged to obtain the mean IMT. All measurements were performed by a single investigator (M.Y.). Intraobserver reliability coefficient for IMT was 0.90.
PWV was assessed with the aid of the Complior device (Alam Medical, Paris, France) as previously described and extensively validated.11 In essence, the more rigid the arteries, the greater the speed of spread of the pressure wave across the arterial compartment under examination. Waveforms were recorded transcutaneously over the right common carotid artery and the right femoral artery. PWV was calculated from the measurements of the pulse transit time and the actual distance.12, 13
Ambulatory BP Monitoring
All patients underwent 24‐hour ABPM with a fully automatic device (SpaceLabs 90207; Spacelabs Healthcare, Snoqualmie, WA). Readings were obtained every 20 to 30 minutes for daytime and nighttime respectively. Participants were told to continue normal daily activities during measurements but momentarily withhold movement during the measurement itself. BPV was assessed by standard deviation (SD) of daytime systolic BP derived from the ABPM records. We also calculated a second index for BPV, variation independent of mean (VIM), an index that is independent of mean BP.14 This was done in light of studies suggesting that VIM is a powerful predictor of stroke and coronary heart disease outcomes.15 VIM was calculated as the daytime SD divided by the mean individual day systolic BP to the power of x, then multiplied by the population systolic BP mean to the power of x. In this equation a and x were calculated based on the model: SD=a (individual mean BP) x, in which they were derived from the linear regression of ln(SD)=ln(a)+xln(individual mean BP).14
Biochemical Analysis
Serum chemistry was measured by routine commercial automated assays (Centaur, Roche, Indianapolis, IN). Serum arginine and asymmetric dimethylarginine (ADMA) were determined by HPLC (Jasco FP 2020 PLUS, Essex, UK) with a fluorescent detector, following initial derivatization with ortho‐phthalaldehyde as described.16, 17 The mobile phase contained acetate buffer and methanol at a ratio of 70:30. Excitation was at 445 nm and emission at 340 nm. Recovery was 80% to 85% for arginine and 90% to 95% for ADMA.
Statistical Analysis
To analyze the differences in metabolic and vascular parameters before and after the 1‐year intervention, data were compared by means of analysis of variance with repeated measures, where the within‐group factor was the intervention (preintervention and postintervention) and the between‐group factor was the level of variability (high or low). These tests were followed by an Unequal N HSD post hoc test. When tested parameters deviated significantly from normal distribution, as verified by a Lilliefors test, nonparametric Friedman test was performed. To test whether the intervention‐associated changes in daytime BPV in the high‐ and low‐variability groups reflect true changes or merely a phenomenon of regression to the mean, analysis of covariance was performed. Significance was determined at P<.05. All statistical analysis was performed using STATISTICA version 6.0 (StatSoft, Tulsa, OK). Data is presented as mean plus/minus standard error of the mean (±SEM).
Results
Initial Assessment
We studied 44 nondiabetic patients (mean age, 51 years; 21 men with an average age of 50 years and 23 women with an average age of 51 years) and characterized them in terms of daytime systolic BP SD and VIM. Notably, values of these two parameters were almost identical: the median values of daytime SD and VIM, respectively, were 11.61 mm Hg and 11.56 mm Hg, respectively, with an SEM of 0.27 for both indices. This also resulted in a very close correlation between daytime SD and VIM values (r=0.99, P<.0001).
Upon study entry and after 12 months, patients underwent ABPM as well as blood and body composition tests. During the initial evaluation in the 44 participants, the median value of the daytime SD was 11.61 mm Hg, and our cohort was subdivided into those with SD >11.61 mm Hg (low variability [LV]) and those with SD that exceeded 11.61 mm Hg (high variability [HV]).
The clinical and biochemical characteristics of the LV and HV groups are listed in Table 1. Of critical importance is the fact that the two groups did not differ in terms of age, BMI, systolic and diastolic BP, pulse wave velocity, fasting glucose, glycated hemoglobin (HbA1C) and insulin, ADMA, triglycerides, IMT, and C‐reactive protein (CRP) (Table 1). Overall, approximately 50% of patients received antihypertensive medications prior to their enrollment in this study. There were no differences in terms of the overall number of users of antihypertensive medications and statins between the LV and HV groups. However, in spite of the overall between‐group similarity, the HV group had somewhat higher levels of low‐density lipoprotein cholesterol (LDL‐C). In addition, despite similar BMI, the HV group had a higher percentage of fat in the legs in the absence of other discernible fat/lean mass distribution features (Table 1).
Table 1.
Baseline Levels of Tested Parameters of the Low‐ and High‐Variability Subpopulations
| Low Variability | High Variability | P Value | |
|---|---|---|---|
| Age, y | 49±3 | 52±4 | NS |
| BMI, kg/m2 | 30.3±0.8 | 29.5±0.5 | NS |
| Body weight, kg | 97.1±3.0 | 88.9±3.1 | .07 |
| Systolic BP, mm Hg | 125.6±2.6 | 126.8±2.2 | NS |
| Diastolic BP, mm Hg | 76.5±1.5 | 76.8±1.9 | NS |
| Fasting glucose, mmol/L | 4.8±0.2 | 4.8±0.1 | NS |
| Glycated hemoglobin, % | 5.8±0.1 | 6.0±0.1 | NS |
| Insulin, pmol/L | 192.4±46.7 | 200.6±40.1 | NS |
| ADMA, μmol/L | 0.63±0.1 | 0.6±0.0 | NS |
| PWV, m/s | 9.7±0.9 | 10.3±0.6 | NS |
| Intima‐media thickness, μm | 733.8±23.3 | 773.3±33.3 | NS |
| CRP, mg% | 1.5±0.5 | 4.5±2.4 | NS |
| Triglycerides, mmol/L | 2.5±0.3 | 2.6±0.2 | NS |
| HDL‐C, mmol/L | 1.2±0.1 | 1.1±0.1 | NS |
| aLDL‐C, mmol/L | 2.7±0.3 | 3.0±0.2 | .05 |
| Leg fat, % | 34.2±2.2 | 39.6±1.8 | .06 |
Abbreviations: ADMA, asymmetric dimethylarginine; BMI, body mass index; BP, blood pressure; CRP, C‐reactive protein; HDL‐C, high‐density lipoprotein cholesterol; LDL‐C, low‐density lipoprotein cholesterol; NS, not significant; PWV, pulse wave velocity. Data are presented as standard error of the mean. aA non parametric statistical test was performed as data did not distribute normally.
Effects of Intervention
One year of intervention resulted in a significant reduction in weight, BMI, percentage of fat in several regions, cholesterol, and triglycerides in both group (Table 2). Yet, there was no reduction in 24‐hour mean of systolic and diastolic BP or day/night systolic/diastolic BP in both the HV and LV groups (Table 3).
Table 2.
Effect of 1‐Year Combined Intervention on Weight‐ and Fat‐Related Parameters that Significantly Changed in Both Groups
| Low‐Variability Group | High‐Variability Group | |||||
|---|---|---|---|---|---|---|
| Before | After | P Value | Before | After | P Value | |
| Total lean, % | 59.4±1.8 | 64.0±1.7 | .01 | 56.9±1.5 | 61.5±2.7 | <.01 |
| Total fat, % | 39.4±1.7 | 35.2±1.6 | .01 | 41.8±1.4 | 37.3±2.6 | <.01 |
| Fat in legs, % | 34.2±2.2 | 28.7±2.4 | <.05 | 39.6±1.8 | 34.8±2.8 | <.05 |
| Fat in gynecoid, % | 39.8±1.8 | 35.6±1.6 | <.05 | 43.8±1.6 | 41.4±1.8 | <.05 |
| Fat in android, % | 49.9±1.3 | 44.2±1.5 | <.01 | 49.2±1.3 | 42.5±3.0 | <.01 |
| Body weight, kg | 97.1±3.0 | 87.7±2.9 | <.01 | 88.9±3.1 | 83.0±3.6 | <.05 |
| Cholesterol, mmol/L | 5.1±0.2 | 4.6±0.2 | <.05 | 5.0±0.2 | 4.7±0.2 | .05 |
| Triglycerides, mmol/L | 2.5±0.3 | 1.6±0.2 | <.001 | 2.3±0.2 | 1.6±0.1 | <.01 |
Data are presented as mean±standard error of the mean.
Table 3.
BP Parameters That Were Not Significantly Affected by 1 Year of Combined Intervention
| BP, mm Hg | Low‐Variability Group | High‐Variability Group | ||
|---|---|---|---|---|
| Before | After | Before | After | |
| 24‐h mean systolic BP, mm Hg | 125.6±2.6 | 122.4±2.6 | 126.8±2.2 | 123.5±2.0 |
| 24‐h mean diastolic BP, mm Hg | 76.5±1. 5 | 74.2±1.5 | 76.8±1.9 | 75.4±1.2 |
| Daytime systolic BP, mm Hg | 128.9±2.7 | 126.6±2.5 | 130.7±2.1 | 128.3±2.3 |
| Nighttime systolic BP, mm Hg | 118.3±2.8 | 114.2±3.0 | 117.5±2.9 | 112.1±3.0 |
| Daytime diastolic BP, mm Hg | 79.3±1.5 | 77.9±1.6 | 80.0±1.9 | 79.4±1.3 |
| Nighttime diastolic BP, mm Hg | 69.9±1.6 | 66.6±1.7 | 69.2±2.2 | 66.5±1.3 |
Abbreviation: BP, blood pressure. Data are presented as mean± standard error of the mean.
Despite the lack of significant changes in BP in the course of the year's program, reduction in BPV as assessed by daytime SD and daytime VIM were seen only in the HV group but not in the LV group (Table 4). This intervention also resulted in favorable metabolic outcomes, which attained statistical significance exclusively in the HV group. Specifically, there was a significant reduction in HbA1C, alanine aminotransferase and ADMA, and CRP, as well as a significant elevation in high‐density lipoprotein cholesterol (HDL‐C) levels. In terms of body composition, the intervention beneficially affected both the LV and HV groups. Finally, PWV significantly declined in the HV group only, in the absence of change in any BP features except for the variability measures.
Table 4.
Parameters in Both Groups After 1 Year of Intervention
| Low‐Variability Group | High‐Variability Group | |||||
|---|---|---|---|---|---|---|
| Before | After | P Value | Before | After | P Value | |
| Daytime SD | 9.4±0.3 | 10.6±0.5 | NS | 13.4±0.3 | 11.1±0.6 | <.05 |
| Daytime VIM | 9.3±0.5 | 10.1±0.5 | NS | 13.0±0.4 | 11.1±0.6 | <.05 |
| PWV, m/s | 9.7±0.9 | 8.9±0.7 | NS | 10.3±0.5 | 9.2±0.6 | <.05 |
| CRP, mg% | 1.5±0.5 | 1.2±0.6 | NS | 4.5±2.4 | 2.2±1.3 | <.05 |
| Glycated hemoglobin | 5.8±0.1 | 5.8±0.1 | NS | 5.8±0.1 | 5.6±0.1 | <.05 |
| HDL‐C, mmol/L | 1.2±0.1 | 1.2±0.1 | NS | 1.1±0.1 | 1.26±0.1 | <.05 |
| ALT, U/L | 32.0±3.0 | 24.6±2.0 | NS | 39.6±5.5 | 28.8±2.5 | <.05 |
| ADMA, μmol/L | 0.6±0.1 | 0.6±0.2 | NS | 0.6±0.0 | 0.5±0.0 | <.05 |
| Arginine/ADMA | 75.9±6.7 | 96.3±12.7 | NS | 82.2±9.5 | 117.4±15.6 | .07 |
Abbreviations: ADMA, asymmetric dimethylarginine; ALT, alanine aminotransferase; HDL‐C, high‐density lipoprotein cholesterol; NS, not significant; SD, standard deviation; VIM, variation independent of mean. Data are presented as average±standard error of the mean.
Discussion
We examined BPV in a group of patients with MetS. Care was taken to exclude overt diabetes from this cohort such that participants' profile was rather typical for the majority of individuals with MetS in the general population: central obesity with dysglycemia and/or dyslipidemia with or without hypertension, not yet complicated by diabetes. Another feature of this study's cohort was that patients were not naive to treatment of their multicomponent condition, again representing a real‐life feature of MetS patients in Western countries in whom the MetS remains uncured over years despite repeat interventions, particularly those targeting weight and the progression of glycemia with time. Finally, this MetS cohort was not, on average, hypertensive at the initiation of the intervention owing to the use of antihypertensive drugs in 50% of the patients. On that background, the study group was subjected to an intensified, balanced, and multidisciplinary intervention that was neither gluco‐centric nor pressure‐centric. Rather, it offered individually structured pharmacologic and lifestyle modification as indicated in existing guidelines for hypertensive, prediabetic, obese, or dyslipidemic patients, attempting to comply with best‐practice principles as published. Additionally, in applying nutritional and physical activity recommendations, careful consideration was given to age, general status, and any preexisting physical impediments.
It is notable that dichotomization of the MetS cohort to patients with high and low BPV did not disclose differences in most metabolic, body composition, and vascular measures. Age, male/female ratio, glycemic control, and BP characteristics other than variability were likewise similar. The only discernible difference noted in the HV group was a somewhat higher LDL‐C level and increased leg fat. The association of lower body fatness with HV is somewhat surprising but may reflect excessive presence of fat in lower extremity muscles, potentially interfering with normal skeletal muscle function.
One year of a multidisciplinary approach offering multiple forms of therapy, encompassing better diet, exercise, weight loss, and the liberal use of medications to lower lipids and improve BP control, resulted in an overall decline in weight, fat mass at several “compartments” (such as android, lower body), and serum lipids, but not in BP. Of note is the observation that in terms of preintervention and postintervention features, there was no significant difference between groups in weight or BMI at the baseline assessment or following 1 year of intervention. The beneficial changes listed here are all in line with the expected results for an intensive and comprehensive program such as that offered to the study's participants. The new finding in this study is that high basal BPV could be lowered in the course of 1 year of treatment in association with identifiable metabolic and CV changes that were not clearly discernible with the same type of intervention in MetS patients with low BPV: a significant increase in HDL‐C along with lowering of LDL‐C, HbA1C, and alanine aminotransferase, the latter possibly reflecting hepatic fatty infiltration. Likewise, a decline in serum ADMA, a competitive endogenous inhibitor of endothelial nitric oxide synthase, in association with a resultant rise in the arginine/ADMA ratio was seen only in the HV group. These changes suggest the possibility that lowering ADMA, which has been linked to better endothelial capacity to generate nitric oxide18 may have contributed to, or perhaps resulted from, the lesser BPV. A previous study in African Americans found that high 24‐hour BPV was associated with impaired endothelial function.19 A favorable change in the arginine/ADMA ratio as attained in our HV patients during the 1‐year treatment can then either reflect or facilitate improvement in endothelial function.20 It is notable that these changes took place without an actual reduction in the mean 24‐hour ABPM. Additionally, elevated ADMA and LDL levels were found to increase arterial stiffness as measured by PWV.21, 22 Concordant with these reports we show that the intervention offered in the present study resulted in reduced PWV in the group of people with high BPV in association with a concomitant reduction in LDL and ADMA levels.
In the only study we could retrieve from existing literature on the treatment effects on BP as assessed by ABPM in patients with MetS, the influence of a single therapeutic modality, rapid weight loss induced by a very low‐calorie diet (800 kcal/d), was examined in a mixed cohort of patients with the MetS, which included patients receiving treatment for overt diabetes and hypertension. The initially normal mean BP by 24‐hour ABPM declined considerably within 6 weeks but was not accompanied by an overall change in BPV. By 1 year, although most weight loss was maintained, no overall appreciable change in BP or BPV was seen.23 While this study did not clarify whether optimization of other aspects of the MetS with other means such as initiation of physical activity or drugs were allowed during the 1‐year duration of the trial, its outcome suggested that weight loss alone was likely insufficient to reduce BPV.
Study Strengths
To our knowledge, the findings presented here comprise the first evidence that reduction in high BPV in patients with MetS is linked to concomitant reduction not only in large arterial properties, namely lowering of PWV, but also to better metabolic response attained through an identical protocol and a similar degree of achieved weight reduction. In addition, in response to a multi‐target comprehensive intervention, a cluster of subtle favorable metabolic changes in HbA1C, HDL‐C, alanine aminotransferase, CRP, and ADMA was seen in the HV group along with reduction in BPV and PWV. Perhaps more significantly, this is also the first suggestion that in patients with MetS, intense and structured multidisciplinary intervention as laid out in current guidelines, in combination with modification of drug treatment as needed, can achieve lowering of BPV in the absence of BP reduction.
Study Limitations
There are several limitations to the present study. We were unable to point out the “driving force” affording the clustering of reduction in BPV along with several dysmetabolic parameters in the HV group, as all patients received essentially the same type of intervention and attained similar weight reduction. In addition, because of the simultaneous application of several different measures (diet, exercise, and medications), the separate contribution of each of the interventions to the achieved reduction in BPV could not be assessed. The possibility cannot be excluded that for some patients, the assurance given by the close association with the multidisciplinary team may, in itself, nonspecifically reduce BPV.
Conclusions
The finding that improvement in BPV is, indeed, linked to better metabolic outcome and improvement in a measure of large arterial function (PWV) supports the possibility that improvement in dysmetabolism may be linked to reduction in BPV. This concept is intriguing but clearly requires confirmation and further study.
Source of Funding
The Sagol Foundation for the Metabolic Syndrome Research Center.
Disclosures
The authors have no conflicts of interest to disclose.
J Clin Hypertens (Greenwich). 2016;18:19–24. DOI: 10.1111/jch.12685 © 2015 Wiley Periodicals, Inc.
The first three authors contributed equally to this article.
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