Young users of electronic cigarettes exhibit reduced cardiorespiratory fitness

Abstract

Electronic nicotine delivery systems, often referred to as e-cigarettes, are popular tobacco products frequently advertised as safer alternatives to traditional cigarettes despite preliminary data suggesting a potential negative cardiovascular impact. Cardiorespiratory fitness is a critical cardiovascular health marker that is diminished in individuals who consume traditional tobacco products. Whether the use of e-cigarettes impacts cardiorespiratory fitness is currently unknown. Thus, the purpose of this study was to investigate the impact of regular e-cigarette use on cardiorespiratory fitness in young healthy adults. Twenty-six users of e-cigarettes (ECU, 13 males, and 13 females; age: 24 ± 3 yr; e-cigarette usage 4 ± 2 yr) and 16 demographically matched nonusers (NU, 6 males, and 10 females; age: 23 ± 3 yr) participated in this study. Cardiorespiratory fitness was measured by peak oxygen consumption (V̇o_2peak) during a cardiopulmonary exercise test. Measurements of chronotropic response, hemodynamic, oxygen extraction, and utilization were also evaluated. Our results suggest that regular users of e-cigarettes exhibited significantly lower peak oxygen consumption when compared with nonusers, even when controlled by fat-free mass and lean body mass. Hemodynamic changes were not different between both groups during exercise, whereas lower chronotropic responses and skeletal muscle oxygen utilization were observed in users of e-cigarettes. Results from the present study demonstrate that young, apparently healthy, regular users of e-cigarettes exhibit significantly reduced cardiorespiratory fitness, lower chronotropic response, and impaired skeletal muscle oxygen utilization during exercise. Overall, our findings contribute to the growing body of evidence that supports adverse effects of regular e-cigarette use on cardiovascular health.

NEW & NOTEWORTHY E-cigarettes are tobacco products frequently used by youth and young adults. Little is known about the long-term health effects of their prolonged use. Results from the present study demonstrate that young, apparently healthy, regular users of e-cigarettes exhibit significantly reduced cardiorespiratory fitness, a marker of cardiovascular health and a predictor of all-cause mortality. We also identified that the young users of e-cigarettes present with lower chronotropic response and impaired skeletal muscle oxygen utilization during exercise.

INTRODUCTION

Traditional cigarette smoking is a major risk factor for cardiovascular disease (CVD) development (1). With more than 4,000 different constituents, traditional tobacco damages vascular structure and integrity (2, 3), increases oxidative stress (4, 5), triggers an inflammatory response (6, 7), and disrupts normal autonomic regulation (8, 9), contributing to worse cardiovascular health. Extensive public health campaigns have successfully reduced the prevalence of traditional tobacco users (10, 11). Some switched to newly available products such as electronic nicotine delivery systems, commonly called e-cigarettes, which are battery-powered devices that heat a nicotine-containing “e-liquid,” creating an aerosol that users inhale. In addition to nicotine, “e-liquid” is also comprised of solvents (propylene glycol, vegetable glycerin) and various flavoring additives (12), and, therefore, e-cigarettes are classified as tobacco products by regulatory agencies (13). E-cigarettes are increasingly popular tobacco products, especially among the younger population (14), with almost 8% of middle and high school students (15), and 11% of young adults (16) reporting frequent use of these products. Furthermore, e-cigarettes are commonly viewed as healthier alternatives to traditional cigarettes (17, 18). Although traditional combustible cigarettes and e-cigarettes share some aspects of chemical composition (i.e., nicotine, acrolein), e-cigarettes exclusively contain a number of unique substances that have raised multiple health concerns (19–21). For example, propylene glycol, a commonly used solvent in e-cigarette liquids (22) has been shown to cause respiratory irritation (23). Recent results support that acute exposure to e-cigarettes may increase heart rate (24), blood pressure (25), arterial stiffness (26, 27), and decrease vascular function (28, 29), all prognostic markers of future cardiovascular events. Some epidemiological studies have associated e-cigarette usage with higher odds of reporting pulmonary (30–33) and cardiovascular (34–36) disease symptomatology. However, the health effects of regular e-cigarette use, particularly among young adults, remain unknown.

Cardiorespiratory fitness (CRF) represents the ability of respiratory, cardiovascular, and muscular systems to efficiently deliver and use oxygen during exercise (37) and is considered an established marker of cardiovascular health (38). CRF, measured through oxygen consumption (V̇o₂), is an independent predictor of all-cause morbidity and mortality (39, 40), and it is inversely associated with CVD risk (41, 42). It is currently known that chronic users of traditional cigarettes across different age ranges present with a reduced CRF (43–45), and that second-hand smoke exposure alone reduces maximal oxygen consumption (46).

Primary mechanisms proposed to contribute to lower consumption of those who smoke cigarettes have been related to respiratory (e.g., impaired gas exchange, pulmonary microvascular disease, airflow limitation), cardiovascular (e.g., left ventricular dysfunction, micro- and macrovascular impairments, heart rate response abnormalities), and/or skeletal muscle abnormalities (e.g., attenuated muscle mass, muscle wasting, reduced oxidative capacity), as well as their complex interactions (47).

Despite the popularity of e-cigarettes, there is a lack of knowledge about the potential impact of their long-term use on cardiorespiratory fitness and, therefore, on cardiovascular health (48). Thus, the purpose of the present study was to examine cardiorespiratory fitness in regular users of e-cigarettes. We hypothesized that regular users of e-cigarettes, who are otherwise healthy young adults, will exhibit lower CRF when compared with demographically matched nonusers.

METHODS

Experimental Design

A total of 42 participants from the Richmond Greater Region reported to the Vascular and Integrative Physiology (VIP) Laboratory at Virginia Commonwealth University. Participants completed an initial preliminary visit during which written informed consent was obtained, followed by collecting medical, physical, and sociodemographic information. Afterward, participants completed an experimental visit following an overnight fast of at least 8 h and ad libitum water. Participants were asked to abstain from exercise and tobacco product consumption for at least 12 h and from vitamin intake for 72 h prior to the experimental visit. Upon arrival, a venous blood sample was obtained, and participants completed a cardiorespiratory exercise test. The study protocol was approved by the Virginia Commonwealth University Institutional Review Board, and it followed the principles of the Declaration of Helsinki.

Participants

A total of 26 regular users of e-cigarettes (ECU) and 16 demographically matched, considering age, sex, and body mass index, nonusers (NU), all 21 yr of age or older, completed this study. The ECU group included current users of e-cigarette products for ≥3 times/wk and for ≥3 mo that primarily started using these products either during adolescence or very early young adulthood (49). Participants were excluded from both groups if they used cigarettes, other tobacco products (cigars, hookahs, smokeless), and any illicit or prescription drugs for nonmedical reasons weekly or more frequently in the past 60 days. Participants with evidence of cardiovascular, pulmonary, renal, hepatic, metabolic, and cerebral diseases or who were currently pregnant or nursing were also excluded from the study after an in-detailed screening and assessment of traditional health markers. Of 26 regular users of e-cigarettes, 25 self-identified as sole users of e-cigarettes, never smokers, and all 16 nonusers self-identified as never-smokers, never users of e-cigarettes.

Demographic Characteristics and Clinical Laboratory Values

Baseline anthropometric measurements of height, weight, calculated body mass index (BMI), and body composition using bioelectrical impedance analysis (BIA; Quantum V Segmental, RJL Systems) were obtained in all participants minus two due to technical issues. Resting systolic and diastolic blood pressures were evaluated in triplicate using Omron HEM705 (Omron, Lake Forest, IL), and the average of three assessments was used to calculate mean arterial pressure. Information regarding e-cigarette patterns of use (50, 51) and other lifestyle behaviors, including sleep, diet, and physical activity, were collected via self-reported questionnaires.

Assessment of standard clinical laboratory values was completed from a venous blood sample collected following an overnight fast. Hemoglobin and hematocrit values were obtained using the HemoPoint H2 analyzer (Stanbio Laboratory, Boerne, TX). Concentrations of standard biochemical values for lipids [total cholesterol (TC), high-density lipoproteins (HDL), low-density lipoproteins (LDL), and triglycerides] and glucose concentrations were obtained using the Cholestech LDX point-of-care analyzer (Alere, Providence, RI). Concentrations of high-sensitivity C-reactive protein (hsCRP), hemoglobin A_1c (HbA_1c), serum nicotine, and cotinine levels were obtained from standard core laboratory techniques (Laboratory Corporation of America Holdings, Burlington, NC).

Cardiopulmonary Exercise Testing

A maximal exercise test using the Godfrey protocol on a cycle ergometer was conducted in all participants, following the recommendations and guidelines from the American College of Sports Medicine (52). Expired gases were analyzed in the mixing chamber of a TruOne 2400 metabolic cart (Parvo Medics, Sandy, UT), and 30-s averages were used to obtain the volume of oxygen consumed (V̇o₂), respiratory exchange ratio (RER), and minute ventilation (V̇e). The ventilatory threshold (VT) was determined using the v-slope method (53). V̇o_2peak was scaled for body weight, fat-free mass (FFM), and lean mass (LM: FFM minus bone mineral content). The predicted relative peak V̇o₂ (% predicted) was calculated via the Wasserman-Hansen (54) and FRIEND (55) equations for each participant. Further ventilatory parameters were obtained from the exercise tests, including V̇e/V̇co₂ slope, V̇e/V̇o_2peak, and V̇e/V̇co_2peak. During the test, heart rate (Polar, Lake Success, NY), oxygen saturation (WristO_x2, Nonin Medical, MI), blood pressure (First Aid Only, WA), and self-perceived exertion using the Borg Rating of Perceived Exertion (RPE) scale were monitored. A test was considered maximal (_max) if the subject met three of the four following criteria: 1) a plateau in V̇o₂, 2) achieving >85% of predicted maximal heart rate (HR_max) (calculated using 220 minus age), 3) an RER > 1.10, and 4) volitional fatigue (>17 for a rating of perceived exertion [RPE] on the 6–20 Borg Scale). If three of four criteria were not met, oxygen consumption was designated as peak (V̇o_2peak).

The physiological age (Age_P) of the participants tested in the current study was estimated using the maximal values achieved during the cardiopulmonary exercise test (V̇o_2peak and HR_peak) (56). The following equations, previously derived from the fitness registry and the importance of exercise national database (FRIEND) (57) were used where A and B were defined in Table 1.

$${\text{Age}}_{\text{p}}=\frac{\left(A+{\dot{\text{V}}\text{O}}_{2\text{peak}}\right)}{B};{\text{Age}}_{\text{p}}=\frac{\left(A+{\text{HR}}_{\text{peak}}\right)}{B}$$

Table 1.

Physiological age equation variables

	Agep V̇o2peak		Agep HRPeak
	A	B	A	B
Male	−4.0968	−0.033	−200.11	0.9207
Female	−2.5605	−0.0211	−198.57	−0.8731

HR, heart rate.

Hemodynamic and Chronotropic Responses

A noninvasive signal morphology impedance cardiography device (PhysioFlow, Ebersviller, France) was used to assess hemodynamic parameters during rest and continuously during the exercise test in a subset of 33 participants (22 users of e-cigarettes and 11 nonusers). Specifically, stroke volume (SV), stroke volume index (SVI), cardiac output (CO), cardiac output index (CTI), early diastolic filling ratio (EDFR), and systemic vascular resistance (SVR) were attained.

Chronotropic response to exercise was evaluated in this study using a chronotropic response index (CRI), and incompetence was defined as CRI < 0.8 (58). CRI was calculated accounting for resting heart rate (HR_rest), maximal heart rate achieved during exercise test (HR_peak), and age-predicted maximal heart rate (HR_APM), using the following equation:

$$\mathrm{CRI}=\frac{\left({\mathrm{HR}}_{\text{peak}}-{\mathrm{HR}}_{\text{rest}}\right)}{\left({\mathrm{HR}}_{\text{APM}}-{\mathrm{HR}}_{\text{rest}}\right)}$$

Peripheral Oxygen Content

Arterial O₂ content ($\text{S}{\text{a}}_{{\text{O}}_2}$) was indirectly evaluated from highly representative peripheral O₂ saturation ($\text{S}{\text{p}}_{{\text{O}}_2}$) using a pulse oximeter (WristO_x2, Nonin Medical, MI) during rest and maximal exercise test. Mixed venous O₂ saturation ($\text{S}{\overline{\text{v}}}_{{\text{O}}_2}$) was calculated using a derivation of the Fick equation, considering cardiac output (CO) and hemoglobin (Hb) values (59):

$$\text{S}{\overline{\text{v}}}_{{\mathrm{O}}_2}=\text{S}{\text{p}}_{{\mathrm{O}}_2}-\left(\frac{\dot{\mathrm{V}}{\mathrm{o}}_2}{13.9\times \mathrm{C}\mathrm{O}\times \mathrm{H}\mathrm{b}}\right)$$

The oxygen extraction ratio (O₂ER) was also estimated based on the difference between $\text{S}{\text{p}}_{{\text{O}}_2}$ and $\text{S}{\overline{\text{v}}}_{{\text{O}}_2}$.

Statistical Analysis

All statistical analyses were performed using SPSS version 27 (SPSS Inc., Chicago, IL). Significance was set at P < 0.05. Data are presented as means ± standard deviation (SD) throughout the text and tables, as noted, while standard error of the mean (SE) was used for a visual representation of the data. The Shapiro–Wilk test was used to assess the normality of data distribution. The differences in demographics and clinical laboratory values between regular users of e-cigarettes and nonusers were compared using independent group t tests for parametric or Mann–Whitney U test for nonparametric data. A repeated-measures ANOVA (group: ECU vs. NU; time: rest vs. peak) was used to evaluate differences in cardiopulmonary response, hemodynamics, chronotropic responses, and oxygen extraction across the cardiopulmonary exercise test. When a significant group × time interaction was detected, between-group differences were examined using appropriate post hoc analysis. Single-time cardiopulmonary response variables were compared using independent group t tests for parametric or Mann–Whitney U test for nonparametric data. The magnitude of the differences was determined via effect size (Cohen’s d) for single-time variables and partial eta squared (${\eta }_{\text{p}}^2$) for repeated measures, to identify small (Cohen’s d = 0.2; ${\eta }_{\text{p}}^2$ = 0.01), medium (Cohen’s d = 0.5; ${\eta }_{\text{p}}^2$ = 0.06), and large (Cohen’s d = 0.8; ${\eta }_{\text{p}}^2$ = 0.13) effect sizes (60). Pearson or Spearman rank correlation coefficients were used to identify relationships between oxygen consumption and 1) cotinine levels; 2) e-cigarette use length; and 3) cardiac output, heart rate, and oxygen extraction ratio.

RESULTS

Participant Characteristics

Participant demographic characteristics and clinical laboratory values are presented in Table 2. No differences (P ≥ 0.090) were identified between groups in age, height, weight, lipid panel, resting heart rate, and blood pressure. Per the study design, serum nicotine and cotinine levels were significantly higher (P ≥ 0.001) in regular users of e-cigarettes when compared with nonusers. Moderate to vigorous physical activity levels and body composition, including fat mass, fat-free mass, and lean mass, were not different (P ≥ 0.378) between the groups. No statistical differences were identified between the biological sexes (male vs. female).

Table 2.

Participant characteristics and laboratory values in users of e-cigarette and nonusers

Variable	Users of E-Cigarettes	Nonusers	P value
Demographic characteristic
n	26	16
Sex (M/F)	13/13	6/10	0.575
Age, yr	22 (21–25)	22 (21–24)	0.868
Height, cm	172 (10)	170 (8)	0.462
Weight, kg	74 (21)	68 (12)	0.303
HR, beats/min	63 (7)	65 (8)	0.521
SBP, mmHg	114 (8)	114 (8)	0.930
DBP, mmHg	74 (5)	71 (7)	0.090
MVPA, min/wk	113 (0–248)	110 (8–259)	0.917
E-cigarette usage, day/wk	7 (7–7)	0 (0–0)	<0.001
E-cigarette usage, yr	4 (2–6)	0 (0–0)	<0.001
Nicotine, ng/mL	2.7 (0.0–6.5)	0.0 (0.0–0.0)	<0.001
Cotinine, ng/mL	96 (23–281)	0 (0–0)	<0.001
Body composition
BMI, kg/m2	24.8 (5.1)	23.6 (2.8)	0.378
Fat mass index, kg/m2	7.0 (5.4–9.2)	7.4 (5.7–8.2)	0.864
Fat mass, %	29 (7)	27 (6)	0.431
Fat-free mass index, kg/m2	17.4 (2.9)	17.0 (1.6)	0.629
Fat-free mass, %	71 (7)	72 (6)	0.431
Lean mass index, kg/m2	16.2 (2.7)	15.9 (1.6)	0.773
Lean mass, %	66 (62–71)	66 (63–72)	0.721
Clinical laboratory values
TC, mg/dL	168 (40)	167 (25)	0.979
HDL, mg/dL	53 (15)	54 (10)	0.891
LDL, mg/dL	89 (32)	82 (24)	0.605
Triglycerides, mg/dL	80 (52–99)	110 (8–170)	0.287
Glucose, mg/dL	90 (9)	90 (7)	0.898
HbA1c, %	5.2 (0.3)	5.1 (0.3)	0.322
hsCRP, mg/L	0.8 (0.4–1.9)	0.6 (0.3–1.0)	0.133
Hemoglobin, g/dL	14.3 (1.6)	14.3 (1.5)	0.960
Hematocrit, %	43 (5)	43 (4)	0.832
CO2, mmol/L	22 (2)	20 (3)	0.091

Data are presented as means (SD), or median (interquartile range). Bold font indicates statistical significance (P < 0.05). BMI, body mass index; CO₂, carbon dioxide; DBP, diastolic blood pressure; HbA_1c, hemoglobin A_1c; HDL, high-density lipoproteins; HR, heart rate; hsCRP, high sensitive C-reactive protein; LDL, low density lipoproteins; MVPA, moderate to vigorous physical activity; SBP, systolic blood pressure; TC, total cholesterol.

Cardiopulmonary Exercise Test

Cardiopulmonary exercise data for regular users of e-cigarettes and demographically matched nonusers are summarized in Table 3 and Fig. 1. Following the American College of Sports Medicine maximal exercise test criteria (52), 39 of 42 subjects reached a maximal test, and since three participants did not reach maximal classification, data are expressed as peak. Oxygen consumption during peak exercise was significantly (P ≤ 0.005; ${\eta }_{\text{p}}^2$ ≥ 0.183) lower when considering body weight (Fig. 1A), fat-free mass (Fig. 1B), and lean mass (Fig. 1C) in regular users of e-cigarettes when compared with nonusers. Per the American College of Sports Medicine cardiorespiratory fitness normative values (52), male users of e-cigarettes and nonusers are classified as “poor” cardiorespiratory fitness, whereas female participants of both groups are classified as “fair.” In addition, the oxygen consumption predicted calculated by the Wasserman-Hansen (ECU: 78 ± 15 vs. NU: 91 ± 16% predicted; P = 0.011, Cohen’s d = 0.86) (Fig. 1D) and FRIEND (ECU: 65 ± 13 vs. NU: 74 ± 12% predicted; P = 0.033, Cohen’s d = 0.72) equations were also significantly reduced in the users of e-cigarettes when compared with nonusers even when the effect of group or the effect of time were considered. Users of e-cigarettes also reached significantly (P = 0.011; Cohen’s d = 0.84) lower energetic expenditure (METs) than nonusers (ECU: 8 ± 1 vs. NU: 9 ± 2).

Table 3.

Cardiopulmonary response, hemodynamics, chronotropic response, and oxygen content and utilization at rest and during peak exercise in users of e-cigarettes and nonusers

	Users of E-Cigarettes		Nonusers
Variable	Rest	Peak Exercise	Rest	Peak Exercise	P value
V̇o2, L/min	0.5 ± 0.1	2.0 ± 0.5	0.5 ± 0.1	2.2 ± 0.5	0.173
V̇o2, mL/kg/min	7.2 ± 1.7	27.9 ± 4.9	6.8 ± 1.1	32.3 ± 5.5	0.005
V̇o2, mL/kg FFM/min	10.0 ± 2.2	39.0 ± 5.1	9.2 ± 1.4	43.7 ± 5.2	0.005
V̇o2, mL/kg LM/min	10.7 ± 2.3	42.0 ± 5.4	9.9 ± 1.6	46.9 ± 5.5	0.005
V̇e, L/min	14 ± 3	75 ± 20*	14 ± 3	91 ± 21	0.014
RER	0.76 ± 0.08	1.26 ± 0.13	0.80 ± 0.08	1.26 ± 0.93	0.773
CO, L/min	6.3 ± 1.1	18.5 ± 3.6	6.7 ± 1.7	16.8 ± 3.3	0.090
CI, L/min/m2	3.5 ± 0.8	10.0 ± 1.8	3.8 ± 0.8	9.7 ± 1.2	0.233
SV, mL	80 ± 17	106 ± 19	76 ± 15	93 ± 15	0.114
SVI, mL/m2	44 ± 10	58 ± 9	44 ± 6	54 ± 5	0.206
EDFR, %	51 ± 18	64 ± 24	47 ± 8	56 ± 16	0.625
SVRi, dyn·s/cm5·m2	2,227 ± 617	929 ± 185	1867 ± 283	919 ± 100	0.046
SVR, dyn·s/cm5	1,213 ± 322	510 ± 105	1,094 ± 208	536 ± 62	0.131
SBP, mmHg	120 ± 10	173 ± 23	118 ± 9	169 ± 14	0.649
DBP, mmHg	79 ± 8	85 ± 10	80 ± 8	86 ± 9	0.227
MAP, mmHg	95 ± 5	116 ± 11	94 ± 10	116 ± 10	0.222
HR, beats/min	78 ± 12	175 ± 12	86 ± 16	182 ± 9	0.976
$\text{S}{\text{p}}_{{\text{O}}_2}$, %	97 ± 1	96 ± 3	98 ± 1	97 ± 2	0.724
$\text{S}{\overline{\text{v}}}_{{\text{O}}_2}$, %	58 ± 11	43 ± 10	62 ± 7	36 ± 9	0.006
O2ER, %	37 ± 8	53 ± 11	36 ± 7	61 ± 10	0.005

Values are means ± standard deviation (SD). Bold font indicates statistical significance (P < 0.05). APMHR, age-predicted maximal heart rate achieved; CI, cardiac index; CO, cardiac output; CRI, chronotropic response index; DBP, diastolic blood pressure; EDFR, end-diastolic filling ratio; FFM, fat-free mass; HR, heart rate; LM, lean mass; MAP, mean arterial pressure; O₂ER, peripheral oxygen extraction ratio; RER: respiratory exchange ratio; SBP, systolic blood pressure; $\text{S}{\text{p}}_{{\text{O}}_2}$, peripheral oxygen saturation; SV, stroke volume; SVI, stroke volume index; $\text{S}{\overline{\text{v}}}_{{\text{O}}_2}$, mixed venous oxygen saturation; SVRi, systemic vascular resistance index; V̇e, ventilation; V̇o₂, oxygen consumption.

Figure 1.

Cardiorespiratory fitness evaluated through a maximal exercise test in individuals who use e-cigarettes (ECU, n = 26) and nonusers (NU, n = 16) and represented: weight relative (V̇o_{2peak/body weight}) (A); fat-free mass relative (V̇o_2peak/FFM) (B); lean mass relative (V̇o_2peak/LM) (C); percent predicted calculated via Wasserman-Hansen equation (V̇o_2peak % predicted) (D). Values are means ± SE. Significantly different between regular users of e-cigarettes and nonusers when *P < 0.05. **P < 0.01.

Peak work achieved during the exercise test was not different (ECU: 165 ± 40 vs. NU: 175 ± 26 W; P = 0.379) between the groups. Peak ventilation was significantly reduced (P = 0.014; ${\eta }_{\text{p}}^2$ = 0.14), while the V̇e/V̇co₂ slope was significantly lower (ECU: 27 ± 4 vs. NU: 30 ± 3; P = 0.012; Cohen’s d = 0.78) in the users of e-cigarettes when compared with the nonusers. RER response was not different (P = 0.773) between the groups. To note, peak oxygen consumption was not associated with e-cigarette nicotine usage (circulating cotinine, r ≤ −0.032; P ≥ 0.068) or length of use (years, r ≤ 0.033; P ≥ 0.068) even when scaled to body weight, fat-free mass, or lean mass.

Hemodynamic and Chronotropic Responses

Hemodynamic variables and chronotropic response at rest and maximal exercise are presented in Table 3. Resting and peak exercise central hemodynamics were not different (P ≥ 0.090; ${\eta }_{\text{p}}^2$ ≤ 0.09) between the groups, besides the systemic vascular resistance index, which was significantly (P = 0.046; ${\eta }_{\text{p}}^2$ = 0.12) different in users of e-cigarettes, particularly when the effect of time was considered. The observed response is likely due to elevated systemic vascular resistance index at baseline in the ECU group. Furthermore, no statistical differences (P ≥ 0.222) were observed between users of e-cigarettes and nonusers in blood pressure. Heart rate response from rest to peak exercise was not different (P = 0.967; ${\eta }_{\text{p}}^2$ = 0.01) between the groups; however, those who use e-cigarettes reached a significantly lower age-predicted maximal heart rate (APMHR) percentage during the exercise test than those who do not (ECU: 89 ± 6 vs. NU: 92 ± 5%; P = 0.043; Cohen’s d = 0.65). When evaluating the chronotropic response at maximal exercise, a lower change (ECU: 0.81 ± 0.9 vs. NU: 0.87 ± 0.7; P = 0.052, Cohen’s d = 0.62) was observed in users of e-cigarettes when compared with nonusers, with 9 (35%) regular users of e-cigarettes and 3 (18%) nonusers exhibiting chronotropic incompetence (CRI < 0.8).

Oxygen Content and Utilization

Peripheral capillary O₂ saturation and mixed venous O₂ content data are also summarized in Table 3. No differences between the groups were identified in $\text{S}{\text{p}}_{{\text{O}}_2}$ response to exercise (P = 0.724; ${\eta }_{\text{p}}^2$ = 0.127). Significantly (P = 0.006; ${\eta }_{\text{p}}^2$ = 0.23) different $\text{S}{\overline{\text{v}}}_{{\text{O}}_2}$ response to exercise was identified between groups when group by time interaction was evaluated, lower in those who use e-cigarettes (Δ$\text{S}{\overline{\text{v}}}_{{\text{O}}_2}$; ECU = 17 ± 9 vs. NU = 27 ± 10%; P = 0.006, Cohen’s d = 1.13), with a significant time effect. Similarly, O₂ extraction response to exercise was significantly (P = 0.005, ${\eta }_{\text{p}}^2$ = 0.24) lower in ECU when compared with NU when group by time interaction was considered, with a significant time effect. In addition, a significantly lower change in O₂ extraction from rest to peak exercise (ΔO₂ER; ECU = 15 ± 9 vs. NU = 26 ± 9%; P = 0.005, Cohen’s d = 1.15) was identified in users of e-cigarettes.

Reserve Capacity

The reserve capacity of oxygen consumption and its subcomponents (chronotropic, hemodynamic, and oxygen utilization) were evaluated as fold change from rest to exercise and are illustrated in Fig. 2. Nonusers showed a significantly higher fold increase in oxygen consumption (V̇o₂, ECU:3.1 ± 0.9 vs. NU:3.8 ± 0.9 fold change; P = 0.022; Cohen’s d = 0.76) when compared with users of e-cigarettes. No differences between the groups were identified in fold changes in chronotropic (HR; P = 0.466) and hemodynamic (CO; P = 0.106) responses. Nevertheless, significantly (P = 0.007; Cohen’s d = 1.01) lower oxygen extraction ratio fold change was identified in the users of e-cigarettes (0.4 ± 0.3 fold change) compared with nonusers (0.8 ± 0.3 fold change). To further investigate reserve capacity, we examined correlations between oxygen consumption (V̇o_2peak), peak heart rate, cardiac output, and O₂ extraction. Among all participants, we identified a strong positive association between peak O₂ consumption and O₂ extraction (r = 0.526; P = 0.002), whereas no associations were described with peak CO (r = 0.045; P = 0.807) or peak HR (r = 0.129; P = 0.414). A similar relationship has been identified just in the e-cigarette group, with a moderate relationship between peak O₂ consumption and O₂ extraction (r = 0.439; P = 0.047).

Figure 2.

Evaluation of reserve capacity during exercise in individuals who use e-cigarettes (ECU) and nonusers (NU). A: fold increases in oxygen consumption (V̇o_2peak) and each of its components, including: heart rate (HR, B), cardiac output (CO, C), and O₂ extraction (O₂ER, D) from rest to peak exercise. Values are means ± SE. Significantly different between regular users of e-cigarettes and nonusers when *P < 0.05.

Physiological Age

Biological age was not different (P = 0.868) between users of e-cigarettes and nonusers, with both groups’ median age being 22 yr old. On the other hand, we identified higher physiological age based on peak O₂ consumption (ECU: 37 vs. NU: 25 yr; P = 0.033, Cohen’s d = 0.72) and based on peak heart rate (ECU: 28 vs. NU: 20 yr; P = 0.051, Cohen’s d = 0.64) in individuals that use e-cigarettes when compared with those that do not. On average, regular users of e-cigarettes were 13 yr older (based on V̇o_2peak) or 4 yr older (based on HR_peak) than their biological age. On the other hand, nonusers were, on average, 2 yr older (based on V̇o_2peak) and 3 yr younger (based on HR_peak) than their biological age.

DISCUSSION

The long-term health consequences of regular e-cigarette usage and their potential impact on cardiovascular function are largely unknown. Our findings support that regular users of e-cigarettes, who are otherwise young, apparently healthy adults, exhibit reduced cardiorespiratory fitness, a marker of cardiovascular health and predictor of mortality when compared with demographically matched nonusers. In addition, at peak exercise, habitual users of e-cigarettes presented with functional hemodynamic responses but lower chronotropic responses and reduced O₂ extraction and utilization. When investigating contributors to reduced peak oxygen consumption, we identified oxygen extraction and utilization as the strongest limitation. Taken together, results from our study suggest that frequent e-cigarette use has adverse effects on users’ health through reduced cardiorespiratory fitness.

Cardiorespiratory Fitness in Users of E-Cigarettes

Cardiorespiratory fitness, evaluated through peak O₂ consumption, is an independent and strong predictor of all-cause (40, 41) and CVD (38) mortality. Several studies investigated the impact of traditional cigarette use on CRF, and most (45, 46, 61–63), but not all (64, 65), reported reduced O₂ consumption in those who smoke cigarettes, even in those exposed to passive cigarette smoke (46). An earlier study also described an association between smoking and worse cardiopulmonary fitness in teenagers who smoke following short cigarette usage (44). Currently, e-cigarettes and not traditional cigarettes are the most commonly used tobacco products among high schoolers and young adults (66, 67). Despite the large number of consumers of e-cigarettes, minimal information is available related to the potential effects of their long-term use on cardiopulmonary health (48). Our results reveal that regular users of e-cigarettes, who are otherwise young and apparently healthy adults, exhibit significantly lower cardiorespiratory fitness when compared with nonusers. Moreover, reduced CRF in the ECU group was observed even when adjusted for fat-free mass and lean mass, emphasizing that the observed differences were unrelated to lean mass. To put it in perspective, these young users of e-cigarettes present with average peak O₂ consumption levels similar to those previously reported in chronic users of cigarettes (46) and diseased populations, including patients with chronic obstructive pulmonary disease (68). In addition, we also observed a significantly lower energetic expenditure in users of e-cigarettes when compared with nonusers, with 1.23 lower METs despite both groups showing similar body composition. To note, differences of 1 MET have been associated with a 13% change in all-cause mortality and a 15% change in CVD-related mortality (41), emphasizing the potential long-term effects of e-cigarette usage.

Although chronological age is frequently associated with physiological dysfunctions, its use for predicting health outcomes is limited by its inability to account for multiple lifestyle behaviors. In contrast, physiological age is a more precise indicator, quantifying an individual’s age based on cellular and metabolic functions. This measure can greatly differ from chronological age, as it is significantly influenced by lifestyle behaviors (69, 70). In our study, we observed that users of e-cigarettes were, on average, 13 yr older (based on oxygen consumption) or 4 yr older (based on heart rate) than their biological age. Notably, users of e-cigarettes that participated in this study were young (21–30 yr) and apparently healthy when evaluating traditional CVD markers (i.e., blood pressure, lipids, glucose, hsCRP). However, our results indicate that they may present with possible accelerated physiological aging, frequently associated with worse cardiovascular health (71, 72). The present results are aligned with prevailing observations that have associated daily e-cigarette usage with increased odds of myocardial infarction (73) and stroke (35) and emphasize the potential risks associated with e-cigarette usage that may predispose young adults to worse and premature long-term CVD outcomes.

Physiological Mechanisms Limiting Cardiorespiratory Fitness

Oxygen consumption during high energetic demand relies on the integration of pulmonary, cardiovascular, and musculoskeletal systems. Thus, impairment in one or more of those systems can lead to a reduction in cardiorespiratory fitness. According to the Fick equation, peak oxygen consumption is determined by balancing central and peripheral factors.

Central limiting factors.

During exercise, central mechanisms, including the lungs and heart, play a critical role in oxygen content and supply. Arterial O₂ saturation reflects the amount of oxygen transported bound to hemoglobin. In a healthy individual, arterial O₂ saturation decreases with exertion but maintains adequate O₂ delivery. We did not identify differences in arterial oxygenation between regular users of e-cigarettes and nonusers during rest and exercise, inferring sufficient O₂ content during maximal exertion. Moreover, our findings suggest reduced ventilation at peak exercise in the users of e-cigarettes, as previously observed in individuals who actively smoke (74). Reduced ventilation could be related to a possible inefficient CO₂ elimination and, therefore, acidosis (75), which can also result from e-cigarette emission of CO₂ (76) and high levels of e-liquid solvent consumption (77, 78). Despite the ameliorated ventilation during peak exercise, arterial saturation was able to be sustained during maximal effort to similar levels between both groups. These results are also emphasized by the ventilatory efficiency slope response observed during exercise, which, despite being lower in the users of the e-cigarette than in the nonusers, both cohorts exhibit responses within normal ranges for young adults (79). It is possible that the discrepancies between groups could be driven by a combination of increased circulating CO₂ as well as lower peak ventilation. However, the current study only evaluated CO₂ at rest and not during exercise. Thus, future studies are warranted to assess ventilation response and CO₂ elimination during exercise to further explore this hypothesis.

Hemodynamic and chronotropic changes, also considered central limiting factors, play a significant role in O₂ transport and delivery during high energetic demand. In the present study, we observed that both regular users of e-cigarettes and nonusers did not show different hemodynamic responses at rest and during peak exercise, similar to what was expected for young adults (80). Of note, we have observed a different systemic vascular resistance between both groups, likely due to elevated systemic vascular resistance at baseline in the users of e-cigarettes indicative of overall higher vasoconstriction, as previously identified in this population (81, 82). Heart rate responses during exercise were not different between the groups, however, users of e-cigarettes achieved lower age-related peak heart rates during exercise than the response observed in nonusers. Indeed, 35% of individuals in the ECU group (compared with 18% of NU) exhibited a CRI lower than 0.8, which could be described as chronotropic incompetence (58). Multiple reports have described increased heart rate responses to acute e-cigarette use (25, 28, 83), associated primarily with nicotine content (84, 85), as well as in responses to exercise in chronic combustible cigarette users (86). Thus, although no information has been described in regular users of e-cigarettes in response to exercise, it is not surprising to identify a reduced chronotropic response in this population. To note, chronotropic incompetence is predictive of coronary heart disease incidence and all-cause mortality (87), and specifically in those who consume traditional tobacco products daily, it has been associated with worse 15-yr survival (88).

Peripheral limiting factors.

Adequate oxygen delivery, diffusion, and utilization during exertion are controlled by peripheral mechanisms, which include vasculature and skeletal muscle. Among those, vascular function is a critical component to maintaining adequate O₂ delivery during exercise. Recent information has supported that habitual users of e-cigarettes exhibit vascular dysfunction (81, 82, 89), and acute exposure to e-cigarettes also impaired vascular dilatory capacity (29, 90). Another common cause of reduced O₂ delivery to the skeletal muscle during exercise in users of traditional cigarettes is the high affinity of hemoglobin to carbon monoxide (91). To note, the formation of carboxyhemoglobin can contribute to reductions in peak O₂ consumption (92). Preliminary studies demonstrated that acute e-cigarette use might increase carboxyhemoglobin to similar levels as traditional cigarettes (93). However, in our study, users of e-cigarettes were instructed not to use their e-cigarettes for 12 h prior to testing, and exhaled carbon monoxide was similar between groups, minimizing any potential effect of carboxyhemoglobin during exercise testing.

Venous O₂ saturation is an indirect measurement of oxygen exchange between the microcirculation and skeletal muscle fibers. Resting $\text{S}{\overline{\text{v}}}_{{\text{O}}_2}$ typically range between 65 and 75% (94, 95), whereas during exercise, $\text{S}{\overline{\text{v}}}_{{\text{O}}_2}$ decreases due to O₂ utilization by the skeletal muscle (96). In the present study, a reduced response was observed during exercise in the users of e-cigarettes, along with a significantly reduced oxygen extraction in regular users of e-cigarettes during maximal exercise, inferring a possible mismatch between O₂ delivery and O₂ utilization. Decreased O₂ utilization can arise for several reasons, including poor skeletal muscle mitochondrial function, which can be diminished by nicotine consumption (97). Loss of skeletal muscle oxidative capacity is also another potential contributing factor that has been identified in users of traditional cigarettes (98). Muscle atrophy (99), wasting (100), and reduced muscle capillarization (101) are also common results of chronic traditional smoking and can have an impact on O₂ extraction. The effects of e-cigarette use on muscle function have yet to be investigated; however, animal studies exposed to e-cigarette aerosol suggest impairments in muscle force (102) and reduction in muscle glycogen stores (103). In the present study, no differences were identified in lean body mass and self-reported physical activity between both groups. However, further investigation is needed to evaluate if skeletal muscle composition and functionality are playing a role in the cardiopulmonary health of users of e-cigarettes.

Reserve Capacity

Evaluation of reserve capacity provides insight into potential factors that limit cardiorespiratory fitness. In the present study, we investigated reserve capacity as the change in oxygen consumption and its subcomponents from rest to peak exercise. We observed a significantly lower fold change in O₂ consumption in those who use e-cigarettes regularly than those who do not. Our results also revealed that reduced cardiorespiratory fitness in users of e-cigarettes was primarily driven by poor O₂ extraction and utilization and not hemodynamic or chronotropic responses. Interestingly, despite the higher rate of chronotropic incompetence and lower peak heart rate achieved by users of e-cigarettes, central mechanisms do not seem to be the primary limiting factors. These results are also supported by a strong positive association identified between peak O₂ consumption and O₂ extraction, emphasizing the role of peripheral oxygen utilization as a limiting factor in users of e-cigarettes.

Study Limitations

Although the present study provides novel findings in the field, several limitations should be considered.

The ever-evolving e-cigarette market is a unique limitation of investigating long-term e-cigarette exposure in humans (104). Users of e-cigarettes have access to a wide variety of product brands, devices, and e-liquid composition, which have been estimated to represent more than 20,000 different types of e-liquids (105), all of which could have a distinct impact on cardiorespiratory fitness outcomes, potentially different than the ones observed in the present study.

As in any cross-sectional study, lifestyle behaviors, including diet, sleep, or substance use, may also play a role in the observed response. The present study did not identify differences in physical activity levels, dietary intake, or sleep patterns between groups. For substance use, information was collected using a brief questionnaire. Although e-cigarette usage is often concurrently with other substances (106, 107), and several cross-sectional studies have described similar cardiorespiratory fitness in users of specific substances than nonusers [i.e., cannabis (108–110)], the self-reported nature of the data collected as well as the lack of response from a group of participants does not allow us to fully explore the role of those factors within the observed responses. Thus, we cannot exclude that some of these lifestyle choices or other factors not measured could influence the primary outcomes of the present study. In addition, we have not identified statistical differences in the primary outcomes between groups when evaluating the role of biological sex or the length of use. Nonetheless, it is possible that the present study is not adequately powered to detect potential differences in cardiorespiratory fitness when accounting for those two variables, and future studies should evaluate this question.

Another consideration is related to the time of data collection. To minimize the acute effects of e-cigarette use, participants were instructed to abstain from using their devices for 12 h before the visit, however, we cannot rule out the possibility that some participants may not have adhered to the protocol and that observed effects are, in part, mediated by the acute use rather than long-term use. Nevertheless, we can ensure that, at the time of cardiopulmonary exercise testing, all participants had abstained from e-cigarette use between 180 and 240 min while in our laboratory. In addition, we did not observe any significant correlations between the circulating nicotine or cotinine levels and cardiorespiratory outcomes, suggesting our results may be independent of acute nicotine exposure, as others have also suggested for different cardiovascular variables (111–113).

Finally, it is also important to mention potential limitations regarding the equipment used. All exercise tests were performed under the same testing conditions, time of day, equipment, and protocol to minimize the chances of malfunction and inaccuracies. In addition, hemodynamic parameters and peripheral oxygen content were evaluated noninvasively, which, while validated, could lead to testing inaccuracies. However, since the same protocol and equipment were used in all our participants and the team was blinded to the group allocation (ECU vs. NU), we are confident that the differences observed are not related to equipment inaccuracy.

Conclusion

In conclusion, for the first time, the present study has identified that regular users of e-cigarettes, who are otherwise young, apparently healthy adults, exhibit reduced cardiorespiratory fitness, a marker of cardiovascular health and predictor of mortality when compared with demographically matched nonusers. Our results also identified that an inadequate oxygen delivery by the vasculature and/or an inadequate oxygen utilization by the skeletal muscle may play a major role in the observed reduced cardiorespiratory fitness in young adults that use e-cigarettes. Taken together, these findings provide critical information to users, health professionals, and regulatory authorities about the potential public health implications of using e-cigarettes and raise concerns specifically in relation to the alarming number of young individuals choosing to consume these products.

DATA AVAILABILITY

Data will be made available upon reasonable request.

GRANTS

This research is supported in part by a Rapid Response Project (to P.R.-M.) awarded via the National Institute on Drug Abuse of the National Institutes of Health and the Center for Tobacco Products of the U.S. Food and Drug Administration under Award Number U54DA036105, an American Heart Association Predoctoral Fellowship and DC Women’s Board (to T.S.). The content is solely the responsibility of the authors and does not necessarily represent the official views of the NIH or the Food and Drug Administration.

DISCLOSURES

No conflicts of interest, financial or otherwise, are declared by the authors.

AUTHOR CONTRIBUTIONS

R.G., A.B., C.O.C., P.N.-S. and P.R.-M. conceived and designed research; T.S., C.M., K.C., A.H., C.T., M.C., E.T., H.B., H.S., S.I.A., S.C., R.G., and P.R.-M. performed experiments; T.S., C.M., E.T., and P.R.-M. analyzed data; T.S. and P.R.-M. interpreted results of experiments; T.S. and P.R.-M. prepared figures; T.S. and P.R.-M. drafted manuscript; T.S., C.M., K.C., A.H., C.T., M.C., E.T., H.B., H.S., S.I.A., S.C., R.G., A.B., C.O.C., P.N.-S., P.R.-M., edited and revised manuscript; T.S., C.M., K.C., A.H., C.T., M.C., E.T., H.B., H.S., S.I.A., S.C., R.G., A.B., C.O.C., P.N.-S., P.R.-M. approved final version of manuscript.