Impact of a Family History of Hypertension and Physical Activity on Left Ventricular Mass
Conditions: Genetic Predisposition, Genetic Hypertension
Sponsor: Montclair State University

Impact of a Family History of Hypertension and Physical Activity on Left Ventricular Mass 
 
NCT05334355 
 
3/14/2023 
 
 
 

Participants:  
The experimental protocols and the process for obtaining informed consent conformed with the 
Declaration of Helsinki and were approved by the Institutional Review Board of Montclair State 
University. Informed consent was obtained from all participants included in the study prior to the start 
of data collection. All participants were recruited in and around the Department of Exercise Science and 
Physical Education. Participants were separated into two groups dependent on their self-reported FHH 
status. Participants also self-reported physical activity behavior. Physical activity was reported as the 
number of days per week performing moderate and/or vigorous physical activity for at least 10 minutes 
for recreation. Participants were excluded from the study if they reported any prior cardiovascular 
diagnoses.  
Experimental Protocol 
Participants were asked to fast (water allowed) for 4hr, abstain from caffeine for 12hr, and avoid 
alcohol, over-the-counter drugs, and exercise 24hrs prior to data collection. During this visit, BP, heart 
rate (HR), and mean arterial pressure (MAP) were recorded (Omron BP785N Blood pressure monitor, 
Lake Forest, IL, USA). The average of three measurements was recorded after ≥5 minutes of rest in the 
supine position. Height and weight were collected (Detectco, Webb City, MO, USA) and used to calculate 
BSA; BSA = 0.007184 x weightkg0.425 x heightcm0.725 (Du Bois, 1916). 
Echocardiographic assessments were made while participants rested in the left lateral decubitus 
position. All measurements were made using a GE Vivid i Ultrasound (GE healthcare, Jiangsu, China) with 
a 2-5-MHz cardiac transducer. Participants underwent an echocardiogram using the parasternal long 
axis view, apical four chamber, and apical two chamber views according to the American Society of 
Echocardiography [2,3]. Briefly, the parasternal long axis view was done with the probe placed near the 
3rd intercostal space adjacent to the sternum. Linear measurements of wall thicknesses and ventricular 
chamber diameter were measured using two-dimensional brightness mode ultrasound and were 
assessed just below the level of the mitral valve leaflet tips perpendicular to the LV long axis. End-
diastole was defined as the first frame after the mitral valve closes. End systole was defined as the last 
frame before the mitral valve opened. LVM was calculated at end-diastole as LVM = 0.8 x 1.04 x [(IVS + 
LVID + PWT)3 – LVID3] + 0.6; where IVS is interventricular septum, PWT is posterior wall thickness, and 
LVID is left ventricular internal diameter [3]. Relative wall thickness (RWT) at end-diastole was calculated 
as RWT = (2 x PWT) / LVID [3]. Percentage fractional shortening (FS) was calculated as 100 x [(LVIDDiastole 

– LVIDSystole) / LVIDDiastole] [3]. Aortic diameter was measured at the aortic annulus during peak systole in 
the parasternal long axis view and was used to estimate aortic area using the following formula: CSA = 
D2 x 0.785 [2]. Apical views were done with the probe placed near the 5th or 6th intercostal space on the 
body’s flank. Left ventricular volumes at end-diastole and end-systole were assessed using the modified 
Simpson’s method of biplane disk summation [3]. Ejection fraction (EF) of the left ventricle was 
calculated as EF = [(EDV – ESV) / EDV] x 100; where EDV is end-diastolic volume, and ESV is end-systolic 
volume [3]. Stroke volume (SV) was calculated as SV = EDV – ESV. Cardiac output (Q) was calculated as Q 
= SVL/min x HR. MAP was calculated as MAP = [(1/3) x SBP] + [(2/3) x DBP]; where SBP is systolic blood 
pressure, and DBP is diastolic blood pressure. Total peripheral resistance (TPR) was calculated as TPR = 
MAP / Q.  
Statistical Analysis 
Normality was tested using the Shapiro-Wilk test where significance (p<0.05) indicated a non-
normal distribution. Both LVM and LVM/BSA violated the Shapiro-Wilk test of normality. Simple 
bivariate comparisons between groups were made using unpaired t-tests for normally distributed 
variables, and Mann-Whitney tests when normality was violated. Effect sizes for bivariate comparisons 
were estimated using Cohen’s d with 95% confidence intervals. Spearman’s rank correlations coefficient 
(rho) was used to examine relationships within each group and for all participants and variables of 
interest vs. LVM and LVM/BSA. ANCOVA tests were used to examine LVM and LVM/BSA compared 
between groups while statistically controlling for covariates of interest. LVM and LVM/BSA were 
logarithmically transformed prior to the ANCOVA investigations. The ANCOVA models were as follows. 
In model 1, age, SBP and sex were selected as common participant characteristic covariates that impact 
LVM and LVM/BSA. Model 2 accounted for the days per week of moderate-intensity exercise. Model 3 
accounted for the days per week of vigorous-intensity exercise. Model 4 covariates included EDV and 
TPR as indices of preload and afterload. A significant probability value (p<0.05) within the ANCOVA 
model for FHH status was interpreted as finding between-group differences when statistically 
controlling for the covariate variables. A lack of FHH significance in the model was interpreted as FHH 
status does not impact LVM or LVM/BSA independently of the covariate variable(s) within the model. 
Data is expressed as mean±SD. The alpha level for significance was set at p<0.05. All statistical tests 
were performed using JASP version 0.14.1 (University of Amsterdam, Amsterdam, The Netherlands).  
Data Availability 

Data is available on the Montclair State University Digital Commons website at: 
https://digitalcommons.montclair.edu/data/10  
 
References 
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