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Original Investigation

Associations between Habitual Sedentary Behavior and Endothelial Cell Health

Duran, Andrea T.1,2; Garber, Carol Ewing1; Ensari, Ipek2,3; Shimbo, Daichi2; Diaz, Keith M.2

Author Information
Translational Journal of the ACSM: Fall 2020 - Volume 5 - Issue 12 - e000138
doi: 10.1249/TJX.0000000000000138

Abstract

INTRODUCTION

Prolonged sedentary time is associated with incident cardiovascular disease (CVD) and mortality, independent of moderate–vigorous physical activity (MVPA) (1,2). However, the mechanisms underlying these associations have not been elucidated. Endothelial dysfunction, an early pathogenic process underlying atherosclerosis, is a possible putative mechanism (3,4). The sitting posture (the primary sedentary posture) promotes muscle inactivity of the lower extremities and changes in the angles at which the femoral and popliteal arteries run, causing bends within the arterial tree (5). These physiological conditions elicit hemodynamic changes that include blood pooling in the legs, decreased thigh and calf blood flow, and augmented turbulent blood flow in the deformed arterial segments (5,6). For these reasons, it is thought that prolonged sitting may promote atherosclerosis and increased CVD risk by exposing the endothelium to a proatherogenic milieu, facilitating dysfunction of the endothelium over time (7,8).

Supportive of this hypothesis, experimental evidence has shown that prolonged sitting blights endothelial-dependent vasodilation (EDV) in the popliteal and femoral arteries in 1 to 6 h (9,10). This sitting-induced endothelial dysfunction, however, has shown to be restored with even light muscular activity (e.g., leg fidgeting), which brings into question the long-lasting effects of prolonged sitting on the vasculature outside the context of an acute laboratory setting (10,11). Moreover, the laboratory-based models used in existing studies are limited because 1) acute periods of sitting in the laboratory over a single day (or in most cases a few hours) is not indicative of chronic exposure to sitting and 2) the control condition (uninterrupted sitting for hours at a time) does not have real-world generalizability (12). Thus, it is unclear if chronic exposure to such conditions with prolonged sitting contributes to endothelial dysfunction.

Studies have defined endothelial dysfunction solely as an impairment in EDV. This narrow focus provides insight concerning only one aspect of endothelial function. Laboratory-based investigations have elucidated cellular measures of endothelial dysfunction, including endothelial cell (EC) injury and diminished EC reparative capacity. Cellular measures include circulating endothelial microparticles (EMP), a measure of EC injury, and circulating endothelial progenitor cells (EPC), a measure of EC reparative capacity (13). The purpose of the current study was to comprehensively examine whether habitual sedentary time is associated with markers of endothelial function, including EDV, circulating levels of EMP, and circulating levels of EPC, in a cohort of healthy adults. We hypothesized that participants with greater sedentary time would exhibit worse EC health (i.e., lower EDV, higher circulating EMP, and lower circulating EPC).

MATERIALS AND METHODS

Study Participants

Healthy adult participants were enrolled into the Putative Mechanisms Underlying Myocardial Infarction Onset and Emotions (PUME) study, a laboratory-based, single-blind, randomized controlled experimental study conducted from August 2013 to May 2017 (N = 280). As described elsewhere in detail, PUME was designed to examine the impact of negative emotion (i.e., anger, anxiety, and sadness) induction tasks on EC health (14). Inclusion criteria included adults ≥18 yr of age. Exclusion criteria included individuals with any of the following: (a) chronic medical condition, including prevalent CVD and traditional CVD risk factors including history of hypertension, diabetes, and dyslipidemia; (b) active smoking; (c) medication use, including over-the-counter drugs and herbal medications; or (d) self-reported history of psychosis, mood disorders, or personality disorder diagnoses.

Instrumented measures of sedentary behavior were collected in a subsample of PUME participants from September 2014 to June 2017. All active PUME participants were invited to complete a 7-d accelerometer protocol: 163 were invited of whom 94 consented to participate and were able to be scheduled. Excluding those with missing data (n = 3) or with nonadherent accelerometer wear time (<3 d with ≥10 h of wear; n = 8), useable data were available from 83 participants. Characteristics of PUME participants included and those excluded in the present analyses are presented in the supplemental content (see Table 1, Supplemental Digital Content 1, http://links.lww.com/TJACSM/A113, which demonstrates characteristics of participants included and excluded from the current study). The PUME study protocol was approved by the institutional review board at Columbia University Medical Center. All participants provided written informed consent.

TABLE 1
TABLE 1:
Characteristics of Participants in the Low and High Total Sedentary Time Groups (N = 83).

Procedures

Participants came into the laboratory on two occasions. The first visit entailed collection/measurement of endothelial markers, for which the participants were instructed to arrive at 8:30 am after a fast from the previous midnight, and to refrain from any strenuous exercise in the 12 h before their visit. Upon arrival, they were escorted to a temperature-controlled room and seated in a comfortable chair. A 20-gauge intravenous catheter was inserted into an antecubital vein of the dominant arm. Afterward, the participant was instrumented with the EndoPAT2000™ device and instructed to relax for 30 min. Following this rest, EDV assessment was completed. Blood was then drawn into collection tubes. One citrated tube was used to measure circulating EMPs, and one EDTA tube was used to measure EPCs. EDV and blood draws were collected at five different time points; the current study only analyzed the baseline measures (time point 1) collected before the negative emotion induction task.

A second visit was scheduled 7–14 d after the initial laboratory visit. At this visit, participants were fitted with the activPAL (version 3; PAL Technologies, Glasgow, UK), a thigh-worn triaxial accelerometer, and inclinometer that has been validated for determining physical activity intensities, posture (sitting/lying, standing, or stepping), and sedentary time in healthy adults (15–18). Participants were instructed to wear the device continuously for 7 d and to not remove the monitor unless it was to be fully submerged in water (e.g., swimming and bath). Participants were also asked to complete a sleep and wear time log sheet to record daily sleep (“lights out”) and wake times, and times when the device was removed (if any).

Accelerometer Processing

Time-stamped 15-s epoch data files were exported using the activPAL software for subsequent processing and analysis in SAS 9.4. Nonwear and sleep time recorded in the logs were excluded from analyses. For each participant, minutes of sedentary time, standing time, light-intensity physical activity (LIPA, defined as 1.5–2.99 metabolic equivalents [METs] derived from stepping cadence), and MVPA (defined as ≥3 METs derived from stepping cadence) were summed for each day and averaged across the number of valid days (≥10 h of wear) to derive “per day” values (15). Sedentary and MVPA bouts were also quantified. A sedentary bout was defined as consecutive epochs in which the activPAL registered no standing or stepping events of any length. An MVPA bout was defined as any stepping period of ≥10 min for which each consecutive epoch had a stepping cadence assigned an activity intensity of ≥3 METs. We corrected for the influence of variation in wear time by standardizing sedentary time using the residuals obtained when regressing sedentary time on wear time (19,20). As a result, sedentary time is expressed as the mean predicted sedentary time given a wear time of 16 h·d−1.

EC Health Measures

EDV was determined using the reactive hyperemia index (RHI, unitless), which is measured as the transient increase in blood flow after a brief period of arterial occlusion. RHI was assessed using the EndoPAT2000™, a validated peripheral arterial tonometry device (21–23). EC injury and repair were assessed by measuring circulating EMPs and EPCs, respectively. Blood samples were prepared and processed using flow cytometry (BD FACS Calibur) and analyzed using previously published protocols (24–26). Two phenotypes of EMP were selected for analysis; those expressing CD62E+, which are phenotypic for EC activation, and those expressing CD31+, which are indicative of EC apoptosis (27). Similarly, two phenotypes of EPC were selected for analysis: those expressing CD34+/CD133+/KDR+ and those expressing CD34+/KDR+. Data were gated on the mononuclear lymphocytic population, and 500,000 events are collected in the gated region for each sample. Data were expressed as percentages of the mononuclear lymphocytic populations that consist of CD34+/CD133+/KDR+ cells, and separately, CD34+/KDR+ cells. Details on EDV, EMP, and EPC measurements are available in the supplemental content (see Methods, Supplemental Digital Content 1, http://links.lww.com/TJACSM/A113, which provides detailed information on EDV, EMP, and EPC measurements).

Statistical Analyses

Participants were classified into high and low total sedentary time groups by a median split of 589 min·d−1 of sedentary time. Descriptive statistics were computed to characterize the high and low sedentary time groups. For each EC variable, outliers were winsorized and thereafter transformed when appropriate. EMP data were natural log transformed. EPC data were square root transformed because zero was a possible value.

Multivariable regression models were used to compare the levels of each EC variable (EDV, EMP, and EPC) between high and low sedentary time groups. Unadjusted models were first conducted. Subsequent models were adjusted for age, sex, race, ethnicity, and education (model 1) and further adjusted for MVPA (model 2) and body mass index (model 3). As a sensitivity analysis, all analyses were repeated with sedentary time expressed as a continuous variable in hours per day.

As some evidence suggests that prolonged, uninterrupted sedentary bouts (e.g., sitting for hours at a time) may potentially be the most hazardous form of sedentary behavior (19,28,29), the above analyses were repeated examining mean sedentary bout duration (a measure of overall prolonged, uninterrupted sedentary behavior that has been linked to mortality) as the exposure variable (28). Participants were classified into high and low sedentary bout groups by a median split of 17.2 min per sedentary bout. All analyses were conducted using SAS, version 9.4 (SAS Institute, Cary, NC).

RESULTS

Participant Characteristics

In the overall sample (N = 83), sedentary behavior accounted for 61.7% ± 10.2% of wear time, equivalent to 9.9 ± 1.7 h·d−1 over a 16-h waking day. The mean ± SD sedentary bout duration was 18.7 ± 7.4 min per bout. LIPA and MVPA accounted for 31.6% ± 9.3% and 6.7% ± 2.9% of wear time, respectively, equivalent to 306.6 ± 95.8 and 64.5 ± 28.0 min·d−1. Table 1 presents the characteristics of participants classified into the high and low sedentary time groups according to total sedentary time. Participants in the high sedentary group were more likely to be male and engaged in lower levels of standing, LIPA, and MVPA. Characteristics of participants classified into high and low sedentary bout groups according to mean sedentary bout duration are shown in the supplemental content (see Table 2, Supplemental Digital Content 1, http://links.lww.com/TJACSM/A113, which demonstrates characteristics of participants classified into high and low sedentary bout groups according to mean sedentary bout duration).

TABLE 2
TABLE 2:
EDV, EMP, and EPC by Total Sedentary Time Groups (N = 83).

Sedentary Behavior and EC Health

Differences in the markers of EC health between the high and the low total sedentary time groups are shown in Table 2. In unadjusted and adjusted models, there were no significant differences between high and low total sedentary time groups in EDV as indicated by the RHI. There were also no significant differences in circulating levels of EMPs (CD62E+ and CD31+/CD42−) and EPCs (CD34+/KDR+ and CD34+/CD133+/KDR+) in unadjusted and adjusted models. Similarly, when high and low sedentary groups were defined according to accumulation of sedentary time in prolonged, uninterrupted sedentary bouts (e.g., mean sedentary bout duration), there were no significant differences between the high and the low groups for any of the endothelial measures (Table 3). In sensitivity analyses expressing total sedentary time and mean sedentary bout duration as continuous variables, there were no significant associations observed for any of the EC variables (see Tables 3 and 4, Supplemental Digital Content 1, http://links.lww.com/TJACSM/A113, which demonstrates results from the sensitivity analyses).

TABLE 3
TABLE 3:
EDV, EMP, and EPC by Median Split of Mean Sedentary Bout Duration (N = 83).

DISCUSSION

In this study of healthy adults, we evaluated several measures of EC health to examine the relation between ecological, habitual sedentary time, and endothelial dysfunction. We hypothesized that participants with greater sedentary time would exhibit poorer EC health (i.e., lower EDV, higher circulating EMP, and lower circulating EPC). Contrary to our hypothesis, we found that there were no statistically significant differences in measures of EDV, EC injury, or EC reparative capacity in participants with high compared with low volumes of accelerometer-measured sedentary time among a sample of healthy adults. These findings suggest that habitual sedentary behavior may not incur CVD risk, in part, through endothelial dysfunction.

The contention that sedentary behavior induces CVD risk partially through vascular dysfunction is premised on experimental evidence, which has demonstrated that acute prolonged bouts of sitting elicits impairments in EDV, particularly of the legs (9). For example, Thosar and colleagues (10) found that 3 h of uninterrupted sitting impaired EDV and decreased mean and antegrade shear rates in the superficial femoral artery. Similarly, Restaino et al. (5) found that 6 h of prolonged, uninterrupted sitting impaired both microvascular dilator function (i.e., blood flow and velocity) and macrovascular dilator function (i.e., flow-mediated dilation) of the popliteal artery. Despite promising laboratory-based findings, the lack of real-world applicability (e.g., in some studies participants were carried from a chair to an exam table for EDV testing) and evidence that even small amounts of fidgeting can offset sitting-induced EDV are limitations of this current evidence and necessitate a need for testing of the sedentary behavior–endothelial function link under ecological conditions (10,11). The present study addresses this evidence gap and provides some of the first data evaluating the associations between habitual levels of sedentary behavior and a panel of endothelial biomarkers.

Contrary to existing experimental evidence, our findings do not support a link between ecological sedentary behavior and endothelial dysfunction. Reasons for the discrepancy are unclear but could be attributed to several factors. First, the mean sedentary bout duration was only ~19 min per bout in the present observational study, far less than the 1- to 6-h sedentary bout durations used in laboratory-based studies. Second, we evaluated EDV in the upper extremities because of its strong correlation with EDV of the coronary arteries and demonstrated prognostic utility (30–32), characteristics not established with EDV in the commonly measuredlower extremities. Thus, differences between the present observational study and the previous laboratory-based studies could also be a result of upper extremity versus lower extremity differences, albeit our EDV results are supported by our cellular measures of EC injury (EMPs) and repair (EPCs). Finally, differences may be attributed to study design (cross-sectional vs acute induction of inactivity, wherein it is difficult to ascertain whether the observed effects are the result of increases in sedentary behavior or reductions in MVPA), inclusion of women (only men were studied in the previous experimental studies), and differences in the processing and analyzing of EMP and EPC (which widely vary from investigator to investigator).

There are several strengths to our study. First, the current study used both EDV and cellular measures of endothelial function. Measuring EMP and EPC, in addition to EDV, enabled us to complete a comprehensive evaluation of EC health, which is essential to unveil the complex processes that underlie endothelial dysfunction (e.g., EC injury, repair, and regeneration). Second, the activPAL was used for measuring habitual sedentary behavior. This device is widely considered the gold standard measure of sedentary behavior because it is extremely accurate (≥96%) and is one of the only devices capable of distinguishing motionless standing from sedentary time, thus allowing us to adhere to the consensus sedentary behavior definition, which includes both intensity of activity (≤1.5 METs) and position (sitting or reclining) (33). Finally, apparently healthy adults are an ideal population to study the effects of sitting on endothelial function as this population is generally free of overt chronic disease that could confound associations (e.g., those with multimorbidities have poor physical function and are thus more sedentary) (13).

Limitations must be acknowledged when interpreting our study findings. First, this was a cross-sectional study, which limits our ability to evaluate the effect of sedentary time on endothelial function, as causation cannot be implied. Second, this is a small, single-center study, which may limit the generalizability of our findings and statistical power to detect significant differences between high and low sedentary groups. Thus, caution is warranted when interpreting our study findings given the possibility of a type II error.

In conclusion, this study demonstrated that there were no statistically significant differences in a comprehensive battery of endothelial function measures, including measures of EDV, EC injury, and EC reparative capacity, when comparing healthy adults that accumulated higher and lower levels of habitual sedentary behavior (both the total volume and accumulation in prolonged, uninterrupted bouts). These findings suggest that sedentary behavior accrued in ecological settings may not detrimentally influence systemic endothelial function in healthy adults.

This work was supported by the National Heart, Lung, and Blood Institute (NHLBI) at the National Institutes of Health under grant nos. R01-HL116470, K24-HL125704, R01-HL116470-02S1, and R01-HL134985.

The authors report no conflict of interest. The results of the present study do not constitute endorsement by the American College of Sports Medicine.

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Supplemental Digital Content

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