BackgroundCannabis dependence is a significant public health problem. Because there are no approved medications for this condition, treatment must rely on behavioral approaches empirically complemented by such lifestyle change as exercise.AimsTo examine the effects of moderate aerobic exercise on cannabis craving and use in cannabis dependent adults under normal living conditions.DesignParticipants attended 10 supervised 30-min treadmill exercise sessions standardized using heart rate (HR) monitoring (60–70% HR reserve) over 2 weeks. Exercise sessions were conducted by exercise physiologists under medical oversight.ParticipantsSedentary or minimally active non-treatment seeking cannabis-dependent adults (n = 12, age 25±3 years, 8 females) met criteria for primary cannabis dependence using the Substance Abuse module of the Structured Clinical Interview for DSM-IV (SCID).MeasurementsSelf-reported drug use was assessed for 1-week before, during, and 2-weeks after the study. Participants viewed visual cannabis cues before and after exercise in conjunction with assessment of subjective cannabis craving using the Marijuana Craving Questionnaire (MCQ-SF).FindingsDaily cannabis use within the run-in period was 5.9 joints per day (SD = 3.1, range 1.8–10.9). Average cannabis use levels within the exercise (2.8 joints, SD = 1.6, range 0.9–5.4) and follow-up (4.1 joints, SD = 2.5, range 1.1–9.5) periods were lower than during the run-in period (both P<.005). Average MCQ factor scores for the pre- and post-exercise craving assessments were reduced for compulsivity (P  = .006), emotionality (P  = .002), expectancy (P  = .002), and purposefulness (P  = .002).ConclusionsThe findings of this pilot study warrant larger, adequately powered controlled trials to test the efficacy of prescribed moderate aerobic exercise as a component of cannabis dependence treatment. The neurobiological mechanisms that account for these beneficial effects on cannabis use may lead to understanding of the physical and emotional underpinnings of cannabis dependence and recovery from this disorder.Trial RegistrationClinicalTrials.gov NCT00838448]

PURPOSE-To validate a two-regression model for predicting energy expenditure (EE) from ActiGraph GT1M accelerometer generated activity counts using a whole-room indirect calorimeter and the doubly-labeled water (DLW) technique. We also investigated if a low-pass filter (LPF) approach would improve the model's accuracy in the minute-to-minute EE prediction.METHODS-Thirty-four healthy volunteers (age 20-67 yrs, BMI-19.3-52.1 kg/m 2 ) spent ~24-h in a room calorimeter while wearing a GT1M monitor and performed structured and self-selected activities followed by overnight sleep. The EE predicted by the models and expressed in metabolic equivalents (MET-min) during waking times was compared to the room calorimeter measured EE. A subset of volunteers (n=22) completed a 14-day DLW protocol in free-living while wearing an ActiGraph. The average daily EE predicted by the models (MET-min) was compared to the DLW. RESULTS-Comparedto the room calorimeter, the two-regression model over-predicted EE by 10.2±11.4% (1,282±125 and 1,174 ± 152 MET-min, p<0.001) and time spent in moderate physical activity (PA) by 36.9 ± 46.0 min while underestimating the time spent in light PA by -48.3 ± 55.0 min (p<0.05). The LPF reduced the squared and mean absolute error in the EE prediction (p<0.05), but not the prediction error in time spent in moderate or light PA (both p>0.05). The EE measured by DLW (2,108±358 MET-min/day) and predicted by both filtered and unfiltered models (2,104 ± 218 and 2,192 ± 228 MET-min/day, respectively) were similar (p>0.05). CONCLUSIONS-The two-regression model with LPF showed good agreement with total EE measured using room calorimeter and DLW. However, the individual variability in assessing time spent in sedentary, low, and moderate PA intensities and related EE remains significant.