Regular Use of Cannabis in Female Athletes Is Associated With a Reduction in Early Anaerobic Power Production

Abstract

Lisano, JK, Flores, VA, Kisiolek, JN, and Stewart, LK. Regular use of cannabis in female athletes is associated with a reduction in early anaerobic power production. J Strength Cond Res 37(3): 616–622, 2023—Despite a growing number of claims related to the ability of cannabis use to affect health and performance, there is limited research available, especially in female athletes. This cross-sectional study aimed to determine whether chronic cannabis use in physically active female athletes is related to altered health and performance. Healthy, physically active, female cannabis users (CU: n = 12) and noncannabis users (NU: n = 12) with an average age of 23.8 ± 3.7 years and 19.3 ± 4.2% body fat completed athletic performance and health assessments. Significance was set at alpha = 0.05. The age of onset of regular cannabis use was 20.1 ± 2.8 years in CU with an average duration of cannabis use of 5.8 ± 3.1 years. There were no differences between groups with respect to body size, body composition, pulmonary function, cardiorespiratory function, or muscular strength. Cannabis users produced significantly less power in the first 2 stages of the Wingate assessment, but CU experienced significantly less anaerobic fatigue. Although body composition and cardiovascular fitness were comparable, average C-reactive protein concentration classified CU with higher risk for cardiovascular disease (CVD). Athletes and coaches who rely heavily on anaerobic performance should consider these findings because they indicate that regular cannabis use may affect early power production and CVD risk.

Introduction

Since 2014, there has been an increase in the availability of recreational cannabis across North America. In 2019, approximately 12% of adults older than 18 years reported using some form of cannabis within the past month which was significantly higher compared with 2018 (³³). In addition, evidence is emerging that athletes are also using cannabis products. It was reported that of 46,202 surveyed athletes, 1 in 4 reported the use of cannabis (⁶). Other research exploring cannabis use in combination with physical activity observed that 78.1% of surveyed individuals were using cannabis at least once per week (¹⁶). Most (77%) of the subjects reported that cannabis positively affected their performance through improved focus, energy, relaxation, and recovery after a workout (¹⁶). Despite a growing number of athletes using cannabis and claims of cannabis improving performance, there is still limited research exploring how the use of these products affects performance. This is especially true with respect to female athletes.

Phytocannabinoids, or cannabinoids, are the primary active components within cannabis products. Although there are more than 140 identified cannabinoids, 2 of the most well-studied are delta-9-tetrahydrocannabinol (Δ⁹-THC) and cannabidiol (CBD). Both cannabinoids mimic the endogenous cannabinoids (endocannabinoids) anandamide and 2-arachydonylglycerol (¹⁵). The cannabinoid Δ⁹-THC is a well-known agonist of cannabinoid 1 (CB1) receptor and is best known for its intoxicating effects. This is attributable to high expression of CB1 receptors on neuronal synapses within the central nervous system. On the other hand, CBD has no observed intoxicating effects but has a more promiscuous and less defined pharmacology. Cannabidiol has been observed to produce antagonistic effects on both CB1 and cannabinoid 2 (CB2) receptors in addition to interacting with a variety of receptors and channels such as G protein-coupled receptor 55 (GPR55), transient receptor potential cation, vanilloid subtype (TRPV) channels, and adenosine A2A receptors (¹⁵). All these receptors are expressed in tissues involved with physical activity and performance including skeletal muscle, the brain, and vasculature (^23,24).

Cannabis use is linked to alterations in both health and performance measures (^{5,8,11,12,22,27}). Acute consumption of Δ⁹-THC is associated with changes in systolic blood pressure (SBP) (^5,11), whereas diastolic blood pressure may decrease slightly (⁵). Direct inhalation of cannabis containing Δ⁹-THC has acute bronchodilatory effects (²²), which could account for previous findings observing cannabis-related increases in forced vital capacity (^8,12,27). Both CB1 and CB2 receptors are present in human skeletal muscle myotubes which gives Δ⁹-THC and CBD the potential to affect muscle structure and function (²³). Cannabis use is also associated with decreases in overall maximal oxygen consumption, peak work capacity, and maximal work duration (³⁶) as well as a reduced maximal strength and rate of force development during a 1 repetition maximum test when comparing cannabis users with nonusers. However, these findings excluded physically active female subjects (^7,29,36), do not specify acute or chronic cannabis use (^29,36), have too many confounding factors such as contaminant substance use (⁷), or have sample sizes as small as 3 subjects.

The control of inflammation is essential for optimal exercise performance and in maintaining health (¹⁴). C-reactive protein (CRP) is a biomarker of systemic inflammation and is routinely measured to ascertain immune status and risk for cardiovascular disease (CVD) (³⁰). Concentrations of CRP greater than 3 mg/L are associated with an increased risk of CVD (³⁵). In addition to the unclear effect of cannabis use on components of health-related fitness, it is unknown whether cannabis mediates inflammation in physically active female athletes.

This study aimed to determine whether physically active female athletes using cannabis have differences in anthropometric measures, pulmonary function, cardiorespiratory function, muscular strength, muscular power production, and circulating CRP concentrations when compared with equally physically active female athletes who are not currently using cannabis. It was hypothesized that there will be no difference in body size and composition between the groups. However, cannabis users were believed to have lower pulmonary function, cardiorespiratory function, and lower muscular strength and power production compared with nonusers. It was also predicted that cannabis users would have higher concentrations of CRP compared with nonusers.

Methods

Experimental Approach to the Problem

Female cannabis users and nonusers visited the laboratory 3 times and completed evaluations of cannabis use habits, pulmonary function, cardiovascular fitness, anaerobic power production, and circulating CRP. During the first visit, subjects completed written informed consent, medical history, Physical Activity Readiness Questionnaire (PAR-Q), International Physical Activity Questionnaire: Short Format (IPAQ), and the Marijuana Use Measure (MUM), followed by the collection of a venous blood sample. The subjects' second visit included measures of body height, body mass, body composition, pulmonary function, resting heart rate (HR) and blood pressure, and a treadmill V̇O₂max test. The third visit involved the completion of handgrip and Wingate anaerobic power assessments. Visits 1 and 2 were separated by 24 hours, with visit three 72 hours following visit 2. These rest periods were used to provide a period of recovery between visits. All subjects were instructed to maintain their usual dietary and hydration programs. All subjects also avoided vigorous exercise for 48 hours and alcohol, caffeine, and cannabis use for 12 hours before all testing visits.

Subjects

Current female cannabis users (CU: n = 12) and female noncannabis users (NU: n = 12) between 19 and 34 years with an average age of 23.8 ± 3.7 years were recruited from the Northern Colorado Area and nearby communities. Subjects were classified as CU if they used cannabis-derived products at least once per week for the past 6 months and NU if they had not consumed any cannabis-derived products within the past 12 months. Subjects were encouraged to maintain the regular use or nonuse habits for the duration of this study and to notify researchers whether their use habits changed over the duration of testing. All subjects met the American College of Sports Medicine (ACSM) guidelines for weekly physical activity (³⁸), 150 minutes of moderate or 75 minutes of vigorous physical activity, to participate in this study. Subjects were excluded from participation if they responded “yes” to any questions on the PAR-Q, did not meet the ACSM guidelines for weekly physical activity based on their responses to the IPAQ, were currently pregnant, or did not meet the study's cannabis use or nonuse requirements. Procedures for this study were approved by the University of Northern Colorado Institutional Review Board, and all subjects were provided with an explanation of the benefits and risks of this study. All subjects provided written informed consent before this study.

Procedures

Descriptive Measures

Questionnaires: Subjects completed a brief medical history questionnaire and the PAR-Q, IPAQ, and the MUM questionnaires. The MUM was used to evaluate cannabis use frequency, method, duration of use, and the onset of regular cannabis use (²⁶).

Body Size and Composition

Subjects were asked to remove their shoes and wear light workout clothes which included running shorts, a sports bra, and technical top for measures of body size and composition. Subjects' height and mass were collected using a stadiometer (Secca Precision for Health, Hamburg, Germany) and a digital platform scale (Detecto, Webb City, MO), respectively. Waist and hip measurements were collected by identifying the narrowest circumference between the xiphoid process and umbilicus (waist) and widest circumference below the umbilicus (hips) using a Gulick measurement tape. The waist-to-hip ratio was calculated by dividing the waist measurement by the hips measurement and multiplying by 100. Body fat percentage was determined using a standard 7-site skinfold assessment (pectoral, triceps, subscapular, midaxillary, abdominal, suprailliac, and thigh). A spring-loaded Lange Skinfold Caliper (Cambridge Scientific Industries, Inc, Cambridge, MA) was used to measure each site, in sequential order, a total of 2 times. If the first 2 measurements differed by more than 2 mm, a third measure was taken at that specific site. The average skinfold thickness for each site was used to calculate body density and body fat percentage (¹⁸).

Pulmonary FEV1

Subjects were instructed to exhale as forcefully, quickly, and completely as possible into a disposable turbine while wearing pulmonary nose clips. This process was completed a total of 3 times with 2 minutes of rest between trials. Predicted FEV₁ was calculated in the Spirolab-II spirometer (SDI Diagnostics, Easton, MA) based on subjects' age, height, body mass, ethnicity, and sex. Percent of predicted FEV₁ (FEV₁%) was calculated by dividing the measured FEV₁ by the predicted FEV₁ and multiplying by 100.

V̇O2max and Blood Lactate Assessment

Before performance testing and to ensure a controlled performance evaluation, hydration status was evaluated using a PAL-10S (4410) refractometer (ATAGO, Tokyo, Japan). Subjects were then fitted with a Polar HR monitor (Polar Electro Inc, Bethpage, NY) and asked to sit quietly for 5 minutes. Resting blood pressure was obtained before the assessment. After a 5-minute warmup at 1.7 miles per hour and 0 percent grade, the Bruce Ramp Protocol (⁴) and a TrueOne 2,400 metabolic cart (Parvomedics, Model: MMS-2400; Sandy, UT) were used to obtain subject's maximal oxygen consumption (V̇O₂max) on a treadmill (Trackmaster, Model: TMX425CP, Full Vision Inc, Newton, KS). In the final 30 seconds of each stage and immediately on the termination of exercise, blood lactate (mmol/L) and rate of perceived exertion (RPE) were obtained. Blood lactate measures were collected after a finger stick in which capillary blood was analyzed using a Lactate Plus Meter (Nova Biomedical, Waltham MA). The rate of perceived exertion was reported on the 0–10 Modified Borg Scale (³).

Grip Strength and Wingate Anaerobic Cycle Assessment

Upper-body strength was evaluated using a handgrip dynamometer (Grip-D T.K.K. 5101; Takei, Niigata, Japan). Subjects were instructed to squeeze the dynamometer by their side with the elbow extended, alternating each hand for adequate recovery until a total of 3 trials were obtained for both the left and right hands. A combined handgrip score was determined by using the best attempt from each hand.

Subjects were fitted to a Monark Cycle Ergometer 894-E (Monark Ergomedic, Vansbro, Sweden) per the manufacturer guidelines and asked to complete two 5-minute warm-up trials before administration of the assessment. After a 3-minute active recovery between the warm-up trials and the assessment, the cycle ergometer was loaded with resistance equal to 7.5% of the subject's body mass. After the 30-second assessment, the number of revolutions completed every 5 seconds was used to calculate power output (²). The Wingate assessment was performed after at least 72 hours of rest after the V̇O₂max assessment.

Blood Collection and C-reactive Protein Analysis

Subjects confirmed that they had refrained from strenuous physical activity for at least 48 hours, adhered to a 12-hour fast, and restrained from caffeine, alcohol, cannabis, and any nonprescription drug use before venous blood sample collection. Blood samples (10 ml) were collected by a certified phlebotomist in serum separation tube vacutainers between the hours of 7:00 and 9:00 am. After collection, blood samples were allowed to clot for 15 minutes at room temperature and then centrifuged for 10 minutes at 2,000 rpm. Serum was aspirated and stored at −80° C. An enzyme-linked immunosorbent assay (ELISA) was used for the analysis of CRP concentration (Alpco Diagnostics, Salem, NH). The 96-well plate was analyzed at a wavelength of 450 nm with a BioTek microplate reader (Model ELx800; BioTek Instruments, Winooski, VT). Concentrations of CRP were determined using a 4-parameter parametric standard curve.

Statistical Analyses

The mean and standard deviation (SD) were calculated for all variables using SPSS (version 24; IBM Analytics, Armonk NY). Alpha was set at 0.05. Before statistical analysis, all variables were tested for normal distribution and transformed if necessary. Intergroup comparisons were made using a Student t test or an analysis of covariance as necessary, and Pearson's r correlation was used to assess whether any significant relationships were present between variables. Cohen's d effect size (d) was calculated for each variable using pooled standard deviation to determine whether any meaningful differences were present (³⁷). Effect size threshold was set at 0.20 for small, 0.50 for medium, and 0.80 for large.

Results

Subjects' Characteristics and Cannabis Use

All subjects were between the ages of 19–34 years and were of mixed aerobic and resistance training backgrounds. There was no difference between groups for self-reported days (3.91 ± 1.85; p = 0.51, d = 0.30) or hours per session (1.11 ± 0.84; p = 0.62, d = 0.21) of engaging in vigorous physical activity. A total of 22 subjects were of Caucasian descent, while the remaining 2 were of Asian descent. There were no significant differences between CU and NU with respect to age, body mass, height, BMI, body fat percentage, waist-to-hip ratio, or blood pressure (Table 1).

Table 1 - Descriptive Characteristics.^*†

	Overall (N = 24)	CU (n = 12)	NU (n = 12)	p	d
Age (y)	23.8 ± 3.7	23.2 ± 3.4	24.3 ± 4.0	0.45	0.32
Body mass (kg)	59.9 ± 7.7	57.2 ± 7.5	62.6 ± 7.4	0.08	0.75
Height (cm)	167.6 ± 7.8	165.1 ± 8.4	170.0 ± 6.5	0.13	0.66
BMI (kg/m2)	21.3 ± 1.7	20.9 ± 1.8	21.6 ± 1.7	0.35	0.40
Body fat (%)	19.3 ± 4.2	18.3 ± 4.5	20.3 ± 3.8	0.85	0.48
Waist-to-hip ratio	0.74 ± 0.03	0.74 ± 0.02	0.74 ± 0.05	0.26	0.11
Resting SBP (mm Hg)	115.3 ± 11.7	111 ± 13.3	119.7 ± 8.3	0.07	0.80
Resting DBP (mm Hg)	71.3 ± 6.8	70.3 ± 7.4	72.3 ± 6.4	0.50	0.29

^*CU = cannabis users; NU = noncannabis users.

^†Data are presented as mean ± SD. Effect size represented by Cohen's D (d). No significant differences between NU and CU were present at α = 0.05.

Most (91.7%) of the cannabis users were inhaling the product, and 83% had used cannabis within the past 7 days. Patterns of cannabis use including last cannabis use and frequency of cannabis use and data related to the duration of cannabis use are presented in Table 2. None of the subjects in the CU group reported the co-use of tobacco with their cannabis intake.

Table 2 - Patterns of cannabis use.^*

Last use of cannabis
Within past few days (<7 d)	n = 10
Within past 2 wk (8–14 d)	n = 12
Frequency of cannabis use
Average use over past 30 d	15.0 ± 10.5 d
Average use per day	1.5 ± 0.7 times per day
Age of onset and use
Age of first-time use (y)	17.3 ± 1.97
Average age of onset of regular use (using more than once per week)	20.1 ± 2.8 y
Average duration of cannabis use (current age—age of onset)	5.8 ± 3.1 y
Duration of regular cannabis use (current age—onset of regular use)	3.1 ± 2.4 y
Primary method of consumption
Inhalation only	11
Oral edibles only	1

^*Data are presented as mean ± SD, based on n = 12 cannabis users.

Pulmonary Function

There were no observed significant differences with respect to pulmonary function between CU and NU. Overall, FEV₁max for both groups was 3.42 ± 0.51 L·s⁻¹ (p = 0.14, d = 0.64) and ranged from 2.41 to 4.22 L·s⁻¹ in CU and from 2.62 to 4.00 L·s⁻¹ in NU. Percent predicted FEV₁ (measured FEV₁max as a percentage of predicted FEV₁) was 96.44 ± 12.09% in CU and 100.53 ± 10.26% in NU and was not significantly different between groups (p = 0.38, d = 0.37). No subject had an FEV₁% lower than 80.06%. There were no significant correlations between any pulmonary function variables and cannabis use habits in CU.

V̇O₂max and Lactate Assessment

Absolute V̇O₂max was significantly higher in NU; however, relative V̇O₂max ranged from 40.72 to 75.19 ml·kg⁻¹·min⁻¹ in NU and 36.63 to 55.03 ml·kg⁻¹·min⁻¹ in CU and was not different between groups. There were no significant differences with respect to blood lactate concentration (mmol·L⁻¹), threshold, or onset of blood lactate accumulation (OBLA) (Table 3).

Table 3 - V̇O₂max and lactate test results.^*†

	Overall (N = 24)	CU (n = 12)	NU (n = 12)	p	d
Absolute V̇O2max (L·min−1)	3.1 ± 0.6	2.8 ± 0.6	3.4 ± 0.6	0.01	1.11
Relative V̇O2max (ml·kg−1·min−1)	51.5 ± 8.6	48.6 ± 6.4	54.3 ± 10.3	0.11	0.69
Blood lactate concentration (mmol·L−1)	10.8 ± 2.6	10.2 ± 2.6	11.3 ± 2.5	0.29	0.47
Lactate threshold (% of V̇O2max)	63.7 ± 12.0	61.2 ± 14.0	66.2 ± 9.7	0.34	0.43
OBLA (% of V̇O2max)	78.7 ± 12.2	76.6 ± 15.2	80.9 ± 8.5	0.42	0.36
RPE at termination (modified borg)	9.1 ± 0.6	9 ± 0.4	9.1 ± 0.7	0.59	0.23

^*CU = cannabis users; NU = noncannabis users.

^†Data are presented as mean ± SD. Effect size represented by Cohen's D (d). No significant differences between NU and CU were present at α = 0.05.

Strength and Power Assessment

Combined handgrip strength was not significantly different between groups, and the overall average of both groups was 62.83 ± 8.72 (p = 0.17, d = 0.64). The anaerobic power output of NU was significantly greater in stages 1 (p = 0.048, d = 0.92) and 2 (p = 0.026, d = 1.05) of the Wingate but did not differ in the subsequent stages (Figure 1). Over the duration of the Wingate assessment, anaerobic fatigue was significantly lower in CU (51.0 ± 9.0%) compared with NU (61.0 ± 11.0%) (p = 0.035, d = 0.99) (Figure 2). Total anaerobic work was not significantly different between CU and NU (11.01 ± 2.04 kJ; p = 0.14, d = 0.68) nor was mean power output (367.24 ± 67.90; p = 0.14, d = 0.68). Anaerobic fatigue was positively correlated with age of regular cannabis use (r = 0.608, n = 11, p = 0.047).

Figure 1.: Anaerobic power output during the 30-second Wingate assessment between cannabis user (CU) and nonuser (NU) groups. *Indicates a significant difference p < 0.05 in power output between stages.

Figure 2.: Anaerobic fatigue percent during the 30-second Wingate assessment between cannabis user (CU) and nonuser (NU) groups. *Indicates a significant difference p < 0.05 in anaerobic fatigue between groups.

C-reactive Protein Concentrations

Average CRP concentrations were 1.47 ± 2.50 mg·L⁻¹ in CU and 0.50 ± 0.39 in NU, and there were no significant differences between groups (p = 0.20, ES = 0.55). Analysis of covariance of CRP concentrations determined that there were no significant differences between CU or NU when controlling for BMI or body fat percentage, respectively (F(1,21) = 0.380, p = 0.54, and F(1,21) = 0.607, p = 0.45). However, concentrations of CRP were significantly greater in CU when controlling for age (F(1,21) = 6.28, p = 0.02). Serum CRP was negatively correlated with the age of onset of regular cannabis use (r = −0.597, n = 11, p = 0.04). Concentrations of CRP in CU did not correlate with any other measures of cannabis use.

Discussion

This cross-sectional study found that female athletes who are regularly using cannabis are similar to nonusing female athletes with respect to most of health and athletic performance measures. The subjects in this study had been using cannabis for an average of 5.8 ± 3.1 years, and the results suggest that regular cannabis use may not immediately affect health or athletic performance outcomes. This may be related to the overall good health and regular physical activity status of many of the study subjects. The average body fat value for all study subjects was 19.3 ± 4.2%, placing them in the 65^th percentile, or “Good” ACSM category. Average V̇O₂max values for all study subjects was 51.5 ± 8.6 ml/kg/min, placing them in the “Superior” category (³⁸). This status may have resulted in the potential to resist either the harmful or health-promoting effects of cannabis. This phenomenon was often observed in early studies exploring the effects of exercise on tobacco smoking (²⁰).

Although differences between NU and CU were not readily apparent in this study, it is important to continue expanding this area of research. Importantly, our data suggest that the chronic use of cannabis in female athletes may significantly lower their ability to generate power at the onset of activities that rely heavily on anaerobic power production. This was illustrated by 17.6% lower power output by CU in stage 1 (NU = 605 ± 142 W; CU = 498 ± 87 W, p = 0.048) and 20.1% lower power output of CU in stage 2 (NU = 491 ± 110 W; CU = 392 ± 79 W, p = 0.026) of the Wingate assessment when compared with NU. Both Δ⁹-THC and CBD have been observed to interact with peroxisome proliferator–activated receptor alpha (PPARα), a nuclear receptor present in skeletal muscle with distinct roles in lipid and glucose metabolism (²¹). Gene variants of PPARα are associated with explosive strength in speed and power athletes (²⁵). It is possible that the regular exposure of PPARα in skeletal muscle to phytocannabinoids such as Δ⁹-THC and CBD altered the function of key metabolic pathways that contribute to short-term power production. Although the initial power output of CU was lower than that of NU, CU experienced significantly less anaerobic fatigue compared with NU. This finding may suggest that, although CU had lower power output early on, they were able to better maintain their power output over the duration of the test. This is an excellent example of an instance where overall athletic performance seems to be similar between groups, and differences were revealed only after exploring the individual phases of the test. This early phase difference in power production is important for both coaches and athletes to consider whether the athlete's performance relies heavily on short-term power production.

Most of CU subjects in this study were inhaling combustible cannabis products. This method is the most commonly used method of cannabis consumption in adults older than 18 years (^28,32,34). Given this method of cannabis use, it was imperative that this study evaluated cardiorespiratory fitness and pulmonary function. Cannabis users had significantly lower mean absolute V̇O₂max values compared with NU (p = 0.018); however, this difference did not persist when these values were relativized to subjects' body mass. The lack of a difference between relative V̇O₂max in CU and NU is consistent with previous findings comparing female and male cannabis users and nonusers (³⁹) and male cannabis users and nonusers (^16,17,19). Similarly, pulmonary function was not different between groups with respect to FEV₁max or FEV₁%. Interestingly, no subject in this study had an observed FEV₁% below 80%, suggesting that no restrictive or obstructive pulmonary disorders were present (¹³). These results were similar to our previous study with male cannabis users (¹⁷). Although it is evident that acute use of cannabis products alters pulmonary function (^8,29), it does not seem that the chronic use of cannabis products through inhalation in young adults significantly alters pulmonary function or cardiorespiratory fitness.

Controlling inflammation in the body is essential for maintaining optimal health and athletic performance (¹⁴). C-reactive protein is a global biomarker of inflammation, and high concentrations are considered a risk factor for CVD (³⁰). The pooled average of all study subjects for circulating CRP was 0.98 ± 1.82 mg/L, which places the study population in the low-risk category for CVD. Although initial analysis of CRP did not reveal a significant difference between circulating concentrations in CU or NU, average CRP concentrations placed NU and CU in low-risk and moderate-risk categories for CVD, respectively. These altered CVD risk findings are consistent with previous studies (^16,28), and this pattern may suggest some initial perturbations in immune system function. This study found that serum CRP was negatively correlated with age of onset of regular cannabis use. It is possible that initiation of regular cannabis use earlier in adolescence may be linked to increased concentrations of CRP. These findings are consistent with previous research in which an inverse association between cannabis use and CRP was observed in subjects followed from adolescence to middle age (¹). Concentrations of CRP are positively associated with increasing age (³¹). Interestingly, when controlling for age, CU in this study had significantly greater (35%) CRP concentrations when compared with NU.

Although this study presents novel findings related to chronic cannabis use, performance, and health in physically active female athletes, there are limitations. This study was cross-sectional in design, and cannabis use or nonuse status was self-reported. In addition, there was variation in frequency of cannabis use in CU subjects, and the cannabinoid content of the products they were using was not known or standardized. It is highly likely that the concentration of Δ⁹-THC and CBD in the products used by subjects varied widely in both concentration and dose. Finally, all study subjects met ACSM's minimum requirements for weekly physical activity and were regularly engaging in resistance and cardiovascular training; however, subject method of training was not standardized.

Practical Applications

Chronic cannabis use was not associated with significant positive or negative alterations of aerobic performance, pulmonary function, or muscular strength in younger, athletic female athletes. This may lead these individuals to think that cannabis use may not affect their performance. It is possible that it may take longer for the effects of regularly using cannabis to appear. Chronic use of cannabis in physically active female athletes may be linked to lower initial power output and higher risk for CVD as defined by CRP. This study is important in that it provides a glimpse into where cannabis may begin to influence the health and athletic performance in young adults. The authors would like to emphasize that the use of cannabis products containing Δ⁹-THC or any other cannabinoid is explicitly prohibited by the World Anti-Doping Agency (WADA). The only exception to this is that WADA does permit athletes to use products containing pure CBD. The use of any other cannabinoid by an athlete could result in serious consequences including suspension.