Secondary Logo

Journal Logo

Original Articles

Visceral fat reduction and increase of intracellular fluid in weight loss participants on antihypertension medication

Dembrowski, Gerald C.a; Barnes, Jessica W.b

Author Information
Cardiovascular Endocrinology & Metabolism: March 2021 - Volume 10 - Issue 1 - p 31-36
doi: 10.1097/XCE.0000000000000222
  • Free

Abstract

Introduction

Hypertension and obesity have a multifaceted relationship with complicated underlying pathophysiologic factors. Rarely are overweight and obese adults found without comorbid conditions. Statistics show ~103 million Americans have hypertension [1–3], over 110 million Americans have type 2 diabetes (T2D) or are insulin resistant (prediabetic) [4] and 95 million adult Americans have dyslipidemia [5]. Metabolic syndrome (MetS), defined as a cluster of metabolic abnormalities including visceral adiposity (VA), insulin resistance, hypertension and dyslipidemia, now affects more than a third of adults in the United States [5]. These complex physiological interactions contribute to and perpetuate a heightened morbidity and mortality in this population. Interrelated mechanisms that have been directly or indirectly implicated include insulin resistance, inflammation (systemic and neuroinflammation), the gut microbiome, oxidative stress, visceral adipose tissue (also called visceral fat and VA) and adipokines, the renin-angiotensin aldosterone system and the sympathetic nervous system [1–3]. The effects of one or more of these factors can result in endothelial dysfunction, disrupt hemodynamics throughout the body and increase blood pressure as commonly observed in obesity.

A thorough literature review (Pubmed, Scopus, Google Scholar) was undertaken using search terms including but not limited to hypertension treatment, antihypertensive, hypertension medication, blood pressure medication, diet, calorie-restricted diet, very low-calorie diet (VLCD), weight loss, BMI, body fat, visceral fat, visceral adipose tissue and abdominal adiposity. We identified many studies evaluating the relationship between obesity and hypertension and the potential role of weight loss in the treatment of hypertension, but we found only one study from 1992 looking at differences in weight loss outcomes between subjects taking prescription antihypertensive medication (HT) and other participants [4]. Interestingly, this study reported that HT resulted in both higher (chlorthalidone) and lower (atenolol) weight loss than a placebo control in relatively small groups (<100 each). Further, authors noted the atenolol ‘drug effect was marked enough so that only (bodyweight of) the atenolol group was above baseline’ at study completion. This phenomenon is supported by an additional study focused not on weight loss, but on T2D [6]. This larger study (350–400 participants per arm) comparing the efficacy of a beta-blocker (atenolol) versus angiotensin converting enzyme inhibitor (captopril) in prevention of the macrovascular and microvascular complications of T2D found that patients randomized to atenolol gained more weight (3.4 kg) than those on captopril (1.6 kg) over a 9-year period (P = 0.020). The increasing prevalence of obesity, hypertension and T2D over the past ~30 years only serves to make the original question posed by Davis et al. more relevant, and we again asked whether antihypertensive medications affect the ability of participants to achieve the same level of body composition improvements as other participants.

In this study, we investigated whether prescription treatment for hypertension impacted participant outcomes in a 9-week intensive weight reduction program focused on lowering subcutaneous and VA by assessing changes in bodyweight, BMI, VA, body fat % and intracellular fluid (ICF) in an effort to identify any advantage or disadvantage in participants taking HT.

Materials and methods

Subject and program overview

This was a retrospective review of data from 2200 participants of the 20Lighter program (20L, Cheyenne, WY). This study was conducted with informed consent under a protocol reviewed and approved by a third-party Institutional Review Board. 20L, a commercially available, expert supervised 3-phase program included a loading day (no dietary restrictions) followed by ~6 weeks of a proprietary structured, nutritionally complete, VLCD (510–1000 kcal/day) without prepackaged foods or liquid meal replacements and a ~3 week structured transition back to a normal dietary intake (~1800 kcal/day) [7]. VCLD did not permit white table and sea salt, but encouraged the use of Himalayan pink salt and/or Redmond unrefined mineral salt (Heber City, UT). Participants engaged in once daily home weigh-ins, daily texting with the supervising provider, proprietary vitamin/mineral supplementation, daily journaling, and at least three body composition analyses (initial baseline, ~days 18–22, ~days 36–40 and ~days 60–65) using a bioelectrical impedance device (see below). Participants were encouraged to engage in light physical activity (walking, etc.) but to avoid beginning highly strenuous exercise until they completed the structured VLCD and had begun the third phase (dietary transition period) of the program (weeks 6–9). Management of prescription medications was handled by each participant’s primary care physician (PCP).

Body composition analysis

20L measured body composition via an FDA-cleared Class 2 medical device with bioelectrical impedance analysis (BIA) via bipolar foot electrodes (Tanita Corporation) to monitor participant progress. BIA is a widely accepted and highly accurate means of body composition analysis. Each participant used the same device for repeated measures, and participants were encouraged to at roughly the same time each day in the same attire. Numerous peer-reviewed publications and industry white papers have established the bona fides of BIA as an accurate and reproducible means of assessing body composition [8–10]. Endpoints of interest assessed included bodyweight, BMI, visceral fat rating (VFR) (a proprietary measure of VA), body fat % and body water % (a gauge of ICF). These endpoints were calculated using the proprietary Health Edge Software (Tanita Corporation).

Comparison of groups

In addition to the calculation of the mean at baseline and at the 60-day endpoint in both the HT and non-HT groups, we also compared the mean change over 60 days between groups. We did this additional comparison to minimize the impact of a higher proportion of males in the HT group that may affect the overt magnitude of improvements (e.g., a man who is 280 pounds at baseline is likely to lose more weight than a woman who is 200 pounds at baseline). We assessed the change over 60 days as a % improvement (change/baseline value × 100). This allows a comparison of improvements between the groups in a way that avoids a bias in favor of the non-HT group that had a higher proportion of male participants.

Statistical analysis

Baseline demographic values (age and BMI) are reported as median ± SD. All outcome data are shown as mean ± SEM. To assess for significance of each outcome from baseline to 60 days, a Wilcoxon matched-pairs signed rank test was employed. To assess significance between groups, a D’Agostino and Pearson (DAP) normality test was used to show the presence of normality in the population of means. If the population of means passed the DAP normality test (parametric), subsequent statistical analysis was done via an unpaired t-test with Welch’s Correction. If the means failed the DAP normality test (nonparametric), subsequent statistical analysis was done via a Mann–Whitney U-test. In all cases, the statistical significance threshold was P < 0.05.

Results

Baseline demographics

Age, BMI, comorbidities, history and prescription medications of 2200 participants are presented in Table 1. At the start of 20L program, 23.7% of participants reported no comorbidities, 35.9% reported one comorbidity, 22.1% reported two comorbidities and 18.3% reported three or more comorbidities. Of the 2200 participants, 726 (33%) reported taking at least one prescription medication for hypertension, an additional 241 (10.9%) reported they declined to begin HT or their PCP had indicated if body composition and blood pressure levels did not improve HT would be prescribed. Comorbidities included dyslipidemia or triglyceridemia, T2D, depression, previous treatment for cancer, at least one previous heart attack, nonalcoholic fatty liver, joint replacement or reconstructive surgery, arthritis, gout, epilepsy, angina, atrial fibrillation, sleep apnea requiring a CPAP machine, among others. Baseline age (HT: 52.5 ± 9.0, non-HT: 54.8 ± 9.3), BMI (HT: 35.2 ± 6.1, non-HT: 33.5 ± 6.7), comorbidities, history, prescription medications and other characteristics were similar between groups, with the exception of concomitant lipid-lowering medications (~3× more common) and diabetes medications (~2.5× more common) and a higher level of multiple comorbidities in the HT group as compared to the non-HT group or participants as whole.

Table 1 - Baseline characteristics
All (n = 2200) non-HT (n = 1474) HT (n = 726)
Age, years 54.0 ± 9.5 54.8 ± 9.3 52.5 ± 9.0
Gender male, n (%) 1269 (57.7) 753 (51.1) 516 (71.1)
BMI 34.1 ± 6.1 33.5 ± 6.7 35.2 ± 6.1
Prescription medications, n (%)
 Antihypertensive 726 (33.0) 0 (0) 726 (100)
 Lipid-lowering 594 (27.0) 212 (14.4) 382 (52.6)
 Type 1 or 2 diabetes 270 (12.3) 120 (8.1) 150 (20.7)
 Depression 514 (23.4) 391 (26.5) 123 (16.9)
 Gout 139 (6.3) 85 (5.8) 54 (7.4)
 Arthritis 79 (3.6) 44 (3.0) 35 (4.8)
 Other 424 (19.3) 231 (15.7) 193 (26.6)
Comorbidities, n (%)
 ≥3 403 (18.3) 87 (5.9) 316 (43.5)
 2 486 (22.1) 246 (16.7) 240 (33.1)
 1 790 (35.9) 620 (42.1) 170 (23.4)
 0 521 (23.7) 521 (35.3) 0 (0.0)
HT participants taking 1 or >1 prescription medication, n (%)
 1 380 (52.3)
 >1 346 (47.7)
Data presented as median ± SD or number (%).
Comorbidities included hypertension, dyslipidemia/triglyceridemia, type 2 diabetes, previous treatment for cancer, at least 1 previous heart attack, joint replacement or reconstructive surgery, arthritis, gout, epilepsy, angina, atrial fibrillation, sleep apnea requiring a CPAP machine, among others.

Overview of outcomes for HT and non-HT groups

From baseline to 60 days both HT and non-HT groups showed similar clinically relevant and statistically significant changes in the most basic weight loss outcome measurements (bodyweight % and BMI reduction). The HT group’s weight was reduced from a baseline of 240.3 ± 4.32 lbs to 208.8 ± 3.64 lbs at 60 days (P < 0.0001). The non-HT group’s bodyweight was reduced from a baseline of 238.7 ± 2.81 lbs to 207.7 ± 2.35 lbs at 60 days (P < 0.0001) (Fig. 1a).

Fig. 1
Fig. 1:
Within-group change from baseline to 60 days for HT and non-HT. We assessed and compared the mean at baseline and 60 days for each outcome to test for significant improvement in each outcome during 20L in both HT and non-HT groups; ***P < 0.0001.

BMI, a standardized measure of height and weight, was reduced for both groups with the HT group at baseline 35.4 ± 0.569 kg/m2 and 30.6 ± 0.528 kg/m2 at 60 days (P < 0.0001). The non-HT group was 33.2 ± 0.287 kg/m2 at baseline and 28.8 ± 0.246 kg/m2 at 60 days (P < 0.0001) (Fig. 1b).

As we looked into more complex body composition changes over 60 days, we continued to see significant improvements. The measure of VA, calculated by a proprietary Tanita Corporation algorithm as VFR (range 1–59), showed reductions for both groups. HT VFR was reduced from 21.2 ± 0.940 pts to 15.75 ± 0.923 pts (P < 0.0001) and non-HT was reduced from 19.61 ± 0.513 pts to 14.74 ± 0.745 pts (P < 0.0001) (Fig. 1c). Body fat % (the percentage of body weight that is fat), in the HT group dropped from 41.90 ± 0.620% to 35.32 ± 0.602% (P < 0.0001) and the non-HT group saw a reduction from 40.33 ± 0.540% to 34.09 ± 0.513% at 60 days (P < 0.0001) (Fig. 1d).

More nuanced and less often reported body water % represents ICF [11]. The HT group showed an increase of ICF% from 39.81 ± 0.411% to 42.99 ± 0.392% (P < 0.0001) and the non-HT increased from 40.60 ± 0.301% to 43.76 ± 0.252% (P < 0.0001) (Fig. 1e).

Comparison of HT and non-HT groups

To assess for any advantage or disadvantage in either group from baseline to 60-days, we compared the mean percentage change in bodyweight, BMI, VA, body fat, and body water between the HT and non-HT groups. The % of bodyweight lost during the study did not differ between groups. The HT group lost a mean 13.1 ± 0.15% and the non-HT group lost a mean 13.0 ± 0.12%, (P = 0.6185) (Fig. 2a). The % of BMI reduction was the same between groups. The mean % reduction in BMI for HT group was 13.5 ± 0.06 % versus 13.2 ± 0.18% in the non-HT group (P = 0.2486) (Fig. 2b).

Fig. 2
Fig. 2:
Comparison of between-group change from baseline to 60 days. To minimize the impact of baseline values between groups, we next directly compared the mean change from baseline to 60 days outcomes as a % improvement to assess any advantage or disadvantage between those taking and not taking HT.

Similar to bodyweight and BMI, VA (as measured by VFR) and body fat reductions did not differ between groups. The % VA decrease in the HT group was 25.7 ± 0.51% versus 24.8 ± 0.37% in the non-HT group (P = 0.1580) (Fig. 2c). Percentage reduction of body fat in the HT group was 15.7 ± 0.23%, slightly more than the 15.4 ± 0.41% reduction of the non-HT group (P = 0.6207) (Fig. 2d).

No statistical significance was found between the groups for % improvement in ICF. The mean increase in ICF in the HT group was 8.1 ± 0.24% and 7.8 ± 0.22% for the non-HT group (Fig. 2e).

While the % change analysis between groups was done to minimize the impact of a higher percentage of male participants in the HT group (71% in HT versus 51% in non-HT), we also assessed for significance between genders (% improvements in HT-male versus HT-female sub-cohorts and non-HT-male versus non-HT-female subcohorts) and found no statistically significant difference between the mean % reductions of bodyweight, BMI, VA or body fat and the % increase of ICF (Barnes and Dembrowski, unpublished data).

Discussion

As of 2017, nearly half of all adults in the US had hypertension, and ~70% were overweight or obese (BMI > 25) [12]. There is an intimate link between hypertension and obesity, and also a critical need to identify effective interventions for an ever-growing subset of the adult (and unfortunately adolescent) population at risk for serious long-term cardiovascular health issues [13]. Our aim was to evaluate if improvements in body composition metrics were lower, or showed a different pattern of response, in weight loss program participants taking HT than those who were not taking HT. Data show both statistically significant and clinically meaningful changes in all outcome measures for both groups. The presence of HT medications did not prevent successful weight loss, reduction of VA, improvement in ICF, and did not preclude favorable changes in body composition. The data show changes for each group independently were impactful.

To our knowledge, this is the first large-scale study assessing body composition changes beyond bodyweight and BMI between weight loss participants taking and not taking HT, and also the first to demonstrate a clinically relevant improvement in ICF in weight loss participants taking HT. While reduction of bodyweight is important, bodyweight alone is not an adequate measure of reduction in disease risk and improvement in overall health [14,15]. VA, specifically referring to fat surrounding organs in the abdomen, thoracic cavity and neck, is a well-characterized direct marker of cardiovascular and metabolic disease risk [2,14,16]. While the role of VA in cardiovascular and metabolic disease is well documented, its specific association with hypertension is also known [1,2,17].

Abdominal adipose tissue (AAT) depots (omental, mesenteric, etc.) release an array of pro-inflammatory cytokines and adipokines into the circulation and locally onto organs including the liver. In response to the systemic and local release of IL-6, the liver produces C-reactive protein (CRP) and other mediators of systemic inflammation [2]. The link between systemic inflammation (including its mediators) and the development of hypertension is widely accepted. Additionally, the role of immune cell infiltration (particularly monocyte/macrophage-dependent inflammatory pathways) and immune response has also been studied as a link between AAT and cardiovascular diseases (CVD) including hypertension [18].

Beyond the major role of AAT, other adipose tissue depots particularly those in the thoracic cavity associated with the heart and major vessels (epicardial, perivascular, etc.) have also been implicated in cardiovascular disease and hypertension [19]. Indeed, the recent uptick in cardiovascular morbidity and mortality in normal weight women without obvious abdominal obesity [20] suggest the role of heart and major vessel-associated adipose depots may be as important, if not more important than abdominal adiposity. This is supported by many individuals (men and women) in the HT group of our study that did not show evidence of dramatic abdominal obesity (high waist circumference, ‘beer belly’ or apple body shape) yet exhibited a high amount of visceral fat with BIA analysis. The proximity of perivascular and epicardial adipose tissue to the vascular wall and heart tissue, differential release of adipokines and cytokines, and infiltration by a different profile of immune cells versus AAT likely contribute to its particularly detrimental effect [18]. Therefore, it is of significant interest to identify weight loss interventions that reduce VA in both the abdomen and thoracic cavity, as AAT reduction is only part of the VA pathology picture.

With our current data showing a significant reduction in VA in individuals taking HT, future efforts will be focused on investigating if VA reduction results in quantitative improvements of blood pressure and reduction of medication in 20L program participants. While we have anecdotal evidence of medication reduction and discontinuation (Dembrowski and Barnes, article [21]), we did not have access to medical records allowing quantitative assessment in changes during and after 20L in all participants.

Although our study did not directly measure inflammatory markers, we did quantify ICF, a major player in osmotic stress balance that is integrally tied to both acute and chronic inflammation [22]. Studies [22–24] have noted a strong association between inflammation, microenvironmental hypertonicity (water flux out of the cell into the interstitial space triggering cell shrinkage and intracellular dehydration), hypertension and obesity. Herein, we found both groups, HT and non-HT, showed an increase of ICF over the course of 20L, and it would be interesting to also assess for a reduction in other more traditional inflammatory markers, IL-6, and CRP for example, in future studies.

VA has a clearly established role in the pathology of hypertension, yet the only weight loss intervention for obese individuals known to reduce VA currently is bariatric surgery. There is a dire need for interventions that overweight and obese individuals diagnosed with or in danger of hypertension can adopt to reduce VA in a safe, timely manner. Additionally, while waist circumference may represent a reduction in AAT, it is also critical to gauge VA reduction in populations that reflect a higher thoracic than abdominal adiposity such as women. This is of particular importance in light of reports showing increasing cardiovascular morbidity and mortality in younger women with ‘hidden obesity’ [20], defined as accumulation of visceral fat but not classified as overweight or obese. The data herein show 20L, a VLCD-based program, produces reductions in VA and other body composition metrics as measured by BIA, which is a convenient and easy method for individuals to gauge changes in VA in the abdomen and thoracic cavity. In totality, our data demonstrate that a safe nonpharmacologic, nonsurgical complementary therapeutic approach capable of producing clinically meaningful improvements in body composition endpoints, including those linked to hypertension, CVD and inflammation, is equally effective for adults taking prescription HT as it is for those participants who are not.

Acknowledgements

20Lighter is a commercial weight loss and metabolic health program, participants were not compensated for participation, and no outside funding was used in this study. The authors thank Linda Tighe, Maria Lee, Cindy Tervalon and Krista Curry for their help in study data collection, and Dr. Leonard Lomax and Steven Scesa for feedback on the article. The results and views of the current study do not constitute endorsement by Cardiovascular Endocrinology & Metabolism.

Conflicts of interest

Gerald C. Dembrowski and Jessica W. Barnes report ownership interest in an organization that may gain or lose financially through this publication.

References

1. DeMarco VG, Aroor AR, Sowers JR. The pathophysiology of hypertension in patients with obesity. Nat Rev Endocrinol. 2014; 10:364–376.
2. Mathieu P, Poirier P, Pibarot P, Lemieux I, Després JP. Visceral obesity: the link among inflammation, hypertension, and cardiovascular disease. Hypertension. 2009; 53:577–584.
3. Chamarthi B, Williams GH, Ricchiuti V, Srikumar N, Hopkins PN, Luther JM, et al. Inflammation and hypertension: the interplay of interleukin-6, dietary sodium, and the renin-angiotensin system in humans. Am J Hypertens. 2011; 24:1143–1148.
4. Davis BR, Oberman A, Blaufox MD, et al. Effect of antihypertensive therapy on weight loss. Hypertension. 1992; 19:393–399.
5. Saklayen MG. The global epidemic of the metabolic syndrome. Curr Hypertens Rep. 2018; 20:12.
6. UK Prospective Diabetes Study Group. Efficacy of atenolol and captopril in reducing risk of macrovascular and microvascular complications in type 2 diabetes: UKPDS 39. UK Prospective Diabetes Study Group. BMJ. 1998; 317:713–720.
7. Dembrowski GC, Barnes JW. Prescription thyroid replacement does not affect outcomes in an intensive weight reduction program. Transl J Am Coll Sports Med. 2019; 4:179–184.
8. Fernandes RA, Rosa CS, Buonani C, Oliveira AR, Freitas Júnior IF. The use of bioelectrical impedance to detect excess visceral and subcutaneous fat. J Pediatr (Rio J). 2007; 83:529–534.
9. Unno M, Furusyo N, Mukae H, Koga T, Eiraku K, Hayashi J. The utility of visceral fat level by bioelectrical impedance analysis in the screening of metabolic syndrome - the results of the kyushu and okinawa population study (KOPS). J Atheroscler Thromb. 2012; 19:462–470.
10. Demura S, Sato S. Prediction of visceral fat area at the umbilicus level using fat mass of the trunk: the validity of bioelectrical impedance analysis. J Sports Sci. 2007; 25:823–833.
11. Earthman C, Traughber D, Dobratz J, Howell W. Bioimpedance spectroscopy for clinical assessment of fluid distribution and body cell mass. Nutr Clin Pract. 2007; 22:389–405.
    12. Flegal KM, Kruszon-Moran D, Carroll MD, Fryar CD, Ogden CL. Trends in obesity among adults in the United States, 2005 to 2014. JAMA. 2016; 315:2284–2291.
    13. Centers for Disease Control and Prevention (CDC). Hypertension Cascade: Hypertension Prevalence, Treatment and Control Estimates Among US Adults Aged 18 Years and Older Applying the Criteria From the American College of Cardiology and American Heart Association’s 2017 Hypertension Guideline—NHANES 2013–2016. Atlanta, GA: US Department of Health and Human Services; 2019.
    14. Després JP. Body fat distribution and risk of cardiovascular disease: an update. Circulation. 2012; 126:1301–1313.
    15. Després JP, Moorjani S, Lupien PJ, Tremblay A, Nadeau A, Bouchard C. Regional distribution of body fat, plasma lipoproteins, and cardiovascular disease. Arteriosclerosis. 1990; 10:497–511.
    16. Goran MI, Gower BA. Relation between visceral fat and disease risk in children and adolescents. Am J Clin Nutr. 1999; 70:149S–156S.
    17. Holecki M, Duława J, Chudek J. Resistant hypertension in visceral obesity. Eur J Intern Med. 2012; 23:643–648.
    18. Rodriguez-Iturbe B, Pons H, Johnson RJ. Role of the immune system in hypertension. Physiol Rev. 2017; 97:1127–1164.
    19. Mahabadi AA, Rassaf T. Thoracic adipose tissue density as a novel marker of increased cardiovascular risk. Atherosclerosis. 2018; 279:91–92.
    20. Sun Y, Liu B, Snetselaar LG, Wallace RB, Caan BJ, Rohan TE, et al. Association of normal-weight central obesity with all-cause and cause-specific mortality among postmenopausal women. JAMA Netw Open. 2019; 2:e197337.
    21. Dembrowski GC, Barnes JW, et al. Resolution of Metabolic syndrome with reduction of visceral adipose tissue in a 47 year old patient with Type 2 Diabetes Mellitus. Diabetes Metab Syndr. 2020 Sep-Oct 14(5); 1001–1004.
    22. Brocker C, Thompson DC, Vasiliou V. The role of hyperosmotic stress in inflammation and disease. Biomol Concepts. 2012; 3:345–364.
    23. Stookey JD, Barclay D, Arieff A, Popkin BM. The altered fluid distribution in obesity may reflect plasma hypertonicity. Eur J Clin Nutr. 2007; 61:190–199.
    24. Toney GM, Stocker SD. Hyperosmotic activation of CNS sympathetic drive: implications for cardiovascular disease. J Physiol. 2010; 588:3375–3384.
      Keywords:

      antihypertensive medication; body composition; hypertension; intracellular fluid; very low-calorie diet; visceral fat

      Copyright © 2020 Wolters Kluwer Health, Inc. All rights reserved.