Maciej S. Buchowski

Amount of Time Spent in Sedentary Behaviors in the United States, 2003–2004

Sedentary behaviors are linked to adverse health outcomes, but the total amount of time spent in these behaviors in the United States has not been objectively quantified. The authors evaluated participants from the 2003-2004 National Health and Nutrition Examination Survey aged >/=6 years who wore an activity monitor for up to 7 days. Among 6,329 participants with at least one 10-hour day of monitor wear, the average monitor-wearing time was 13.9 hours/day (standard deviation, 1.9). Overall, participants spent 54.9% of their monitored time, or 7.7 hours/day, in sedentary behaviors. The most sedentary groups in the United States were older adolescents and adults aged >/=60 years, and they spent about 60% of their waking time in sedentary pursuits. Females were more sedentary than males before age 30 years, but this pattern was reversed after age 60 years. Mexican-American adults were significantly less sedentary than other US adults, and White and Black females were similarly sedentary after age 12 years. These data provide the first objective measure of the amount of time spent in sedentary behavior in the US population and indicate that Americans spend the majority of their time in behaviors that expend very little energy.

Validation of Accelerometer Wear and Nonwear Time Classification Algorithm

INTRODUCTION the use of movement monitors (accelerometers) for measuring physical activity (PA) in intervention and population-based studies is becoming a standard methodology for the objective measurement of sedentary and active behaviors and for the validation of subjective PA self-reports. A vital step in PA measurement is the classification of daily time into accelerometer wear and nonwear intervals using its recordings (counts) and an accelerometer-specific algorithm. PURPOSE the purpose of this study was to validate and improve a commonly used algorithm for classifying accelerometer wear and nonwear time intervals using objective movement data obtained in the whole-room indirect calorimeter. METHODS we conducted a validation study of a wear or nonwear automatic algorithm using data obtained from 49 adults and 76 youth wearing accelerometers during a strictly monitored 24-h stay in a room calorimeter. The accelerometer wear and nonwear time classified by the algorithm was compared with actual wearing time. Potential improvements to the algorithm were examined using the minimum classification error as an optimization target. RESULTS the recommended elements in the new algorithm are as follows: 1) zero-count threshold during a nonwear time interval, 2) 90-min time window for consecutive zero or nonzero counts, and 3) allowance of 2-min interval of nonzero counts with the upstream or downstream 30-min consecutive zero-count window for detection of artifactual movements. Compared with the true wearing status, improvements to the algorithm decreased nonwear time misclassification during the waking and the 24-h periods (all P values < 0.001). CONCLUSIONS the accelerometer wear or nonwear time algorithm improvements may lead to more accurate estimation of time spent in sedentary and active behaviors.

Comparing Diabetes Prevalence Between African Americans and Whites of Similar Socioeconomic Status

OBJECTIVES We investigated whether racial disparities in the prevalence of type 2 diabetes exist beyond what may be attributable to differences in socioeconomic status (SES) and other modifiable risk factors. METHODS We analyzed data from 34331 African American and 9491 White adults aged 40 to 79 years recruited into the ongoing Southern Community Cohort Study. Participants were enrolled at community health centers and had similar socioeconomic circumstances and risk factor profiles. We used logistic regression to estimate the association between race and prevalence of self-reported diabetes after taking into account age, SES, health insurance coverage, body mass index, physical activity, and hypertension. RESULTS Multivariate analyses accounting for several diabetes risk factors did not provide strong support for higher diabetes prevalence rates among African Americans than among Whites (men: odds ratio [OR]=1.07; 95% confidence interval [CI]=0.95, 1.20); women: OR=1.13, 95% CI=1.04, 1.22). CONCLUSIONS Our findings suggest that major differences in diabetes prevalence between African Americans and Whites may simply reflect differences in established risk factors for the disease, such as SES, that typically vary according to race.

Assessment of Wear/Nonwear Time Classification Algorithms for Triaxial Accelerometer

PURPOSE The objective of this study is to assess the performance of existing wear/nonwear time classification algorithms for accelerometry data collected in the free-living environment using a wrist-worn triaxial accelerometer and a waist-worn uniaxial accelerometer in older adults. METHODS Twenty-nine adults age 76 to 96 yr wore wrist accelerometers for approximately 24 h per day and waist accelerometers during waking for approximately 7 d of free living. Wear and nonwear times were classified by existing algorithms (Alg([ActiLife]), Alg([Troiano]), and Alg([Choi])) and compared with wear and nonwear times identified by data plots and diary records. With the use of bias and probability of correct classification, the performance of the algorithms, two time windows (60 and 90 min), and vector magnitude (VM) versus vertical axis (V) counts from a triaxial accelerometer were compared. RESULTS Automated algorithms (Alg([Choi]) and Alg([Troiano])) classified wear/nonwear time intervals more accurately from VM than V counts. The use of the 90-min time window improved wear/nonwear classification accuracy when compared with the 60-min window. The Alg([Choi]) and Alg([Troiano]) performed better than the manufacturer-provided algorithm (Alg([ActiLife])), and the Alg([Choi]) performed better than the Alg([Troiano]) for wear/nonwear time classification using the data collected by both accelerometers. CONCLUSIONS Triaxial wrist-worn accelerometer can be used for an accurate wear/nonwear time classification in free-living older adults. The use of the 90-min window and the VM counts improves the performance of commonly used algorithms for wear/nonwear classification for both uniaxial and triaxial accelerometers.

Predicting Energy Expenditure of Physical Activity Using Hip- and Wrist-Worn Accelerometers

To investigate the association between physical activity and health, we need accurate and detailed free-living physical activity measurements. The determination of energy expenditure of activity (EEACT) may also be useful in the treatment and maintenance of nutritional diseases such as diabetes mellitus. Minute-to-minute energy expenditure during a 24-h period was measured in 60 sedentary normal female volunteers (35.4 +/- 9.0 years, body mass index 30.0 +/- 5.9 kg/m2), using a state-of-the-art whole-room indirect calorimeter. The activities ranged from sedentary deskwork to walking and stepping at different intensities. Body movements were simultaneously measured using a hip-worn triaxial accelerometer (Tritrac-R3D, Hemokentics, Inc., Madison, Wisconsin) and a wrist-worn uniaxial accelerometer (ActiWatch AW64, MiniMitter Co., Sunriver, Oregon) on the dominant arm. Movement data from the accelerometers were used to develop nonlinear prediction models (separately and combined) to estimate EEACT and compared for accuracy. In a subgroup (n=12), a second 24-h study period was repeated for cross-validation of the combined model. The combined model, using Tritrac-R3D and ActiWatch, accurately estimated total EEACT (97.7 +/- 3.2% of the measured values, p=0.781), as compared with using ActiWatch (86.0 +/- 4.7%, p<0.001) or Tritrac-R3D (90.0 +/- 4.6%, p<0.001) alone. This model was also accurate for all intensity categories during various physical activities. The subgroup cross-validation also showed accurate and reproducible predictions by the combination model. In this study, we demonstrated that movement measured using accelerometers at the hip and wrist could be used to accurately predict EEACT of various types and intensity of activities. This concept can be extended to develop valid models for the accurate measurement of free-living energy metabolism in clinical populations.

Effects of obesity and height on prostate-specific antigen (PSA) and percentage of free PSA levels among African-American and Caucasian men

Prior studies suggest that obese men have lower prostate‐specific antigen (PSA) levels than leaner men. Caucasian (CA) men also may have lower PSA levels than African‐American (AA) men, but the relevance of body size to racial disparities in PSA levels is unclear. The association between body mass index (BMI) and height on PSA and percentage of free PSA (%fPSA) was investigated within AA and CA men without a prior prostate cancer diagnosis.

Dietary Calcium Intake in Lactose Maldigesting Intolerant and Tolerant African-American Women

Background: The relationship between lactose maldigestion, lactose intolerance, and calcium intake in premenopausal African American women is unknown. Objective: To determine how intolerance of lactose and dairy products affects intake of calcium in lactose maldigesting premenopausal African American women. Design: Dietary intake of calcium was assessed in 50 premenopausal lactose maldigesting African American women as determined by the breath hydrogen test. Twenty-six women were lactose intolerant and 24 were lactose tolerant by self-reports. Results: The average intake of calcium in lactose maldigesting and intolerant women was significantly lower than in lactose tolerant women (388 ± 150 mg/day vs. 763 ± 333 mg/day, p < 0.0001, t test). Neither group reached the newly established Dietary Reference Intake (DRI) for calcium (1,000 mg/day). Major source of dietary calcium in lactose tolerant women were milk and dairy products (45%), and mixed foods containing calcium from non-dairy sources (30%). In lactose intolerant women, 46% of calcium was from mixed foods and only 12% was from milk and dairy products. Lactose intolerant women had higher body mass index (BMI) than lactose tolerant women (p = 0.008, t test), and calcium intake was negatively associated with BMI (R2 = 0.470). Conclusions: In African American premenopausal women, lactose tolerance facilitates the dietary intake of calcium when compared with their lactose intolerant counterparts. Low calcium intake is associated with higher BMI.

Body composition and energy metabolism following Roux-en-Y gastric bypass surgery.

Roux‐en‐Y gastric bypass (RYGB) surgery has become an accepted treatment for excessive obesity. We conducted a longitudinal study to assess regional body composition, muscle proteolysis, and energy expenditure before RYGB, and 6 and 12 months after RYGB. Whole‐body and regional fat mass (FM) and lean mass (LM) were assessed via dual energy X‐ray absorptiometry (DXA), and myofibrillar protein degradation was estimated by urinary 3‐methylhistidine (3‐MeH) in 29 subjects. Energy expenditure and substrate oxidation were also determined using a whole‐room, indirect calorimeter in 12 of these subjects. LM loss constituted 27.8 ± 10.2% of total weight loss achieved 12 months postoperatively, with the majority of LM loss (18 ± 6% of initial LM) occurring in the first 6 months following RYGB. During this period, the trunk region contributed 66% of whole‐body LM loss. LM loss occurred in the first 6 months after RYGB despite decreased muscle protein breakdown, as indicated by a decrease in 3‐MeH concentrations and muscle fractional breakdown rates. Sleep energy expenditure (SEE) decreased from 2,092 ± 342 kcal/d at baseline to 1,495 ± 190 kcal/day at 6 months after RYGB (P < 0.0001). Changes in both LM and FM had an effect on the reduction in SEE (P < 0.001 and P = 0.005, respectively). These studies suggest that loss of LM after RYGB is significant and strategies to maintain LM after surgery should be explored.

Energy expenditure, inflammation, and oxidative stress in steady-state adolescents with sickle cell anemia.

Sickle cell anemia (HbSS) is characterized by hypermetabolism, chronic inflammation, and increased oxidative stress, but the relationship between these factors is undefined. In this study, we examined indicators of inflammatory process and markers of oxidative damage and their impact on resting energy expenditure (REE) in stable HbSS adolescents (n = 35) and healthy controls carrying normal hemoglobin genotype (HbAA) (n = 39). C-reactive protein (CRP), white blood cell (WBC) count, and proinflammatory cytokines were measured as markers of inflammation and 2,3-dinor-5,6-dihydro-15-F2t-isoprostane (F2-IsoPM) as a marker of oxidative stress. REE was measured by indirect calorimetry. WBC counts (11.90 ± 5.3 ×103/μL versus 5.6 ± 1.9 ×103/μL; p < 0.001), serum CRP (9.1 ± 11.0 μg/mL versus 0.4 ± 0.7 μg/mL; p < 0.001) and serum IL-8 (7.5 ± 4.4 pg/mL versus 5.5 ± 4.8 pg/mL; p = 0.011) were higher in HbSS than HbAA, suggesting an anti-inflammatory response in HbSS. Higher urinary F2-IsoPM in HbSS (1.2 ± 0.4 versus 0.7 ± 0.3 ng/mg creatinine; p < 0.001) indicates increased oxidative stress. Fat free mass (FFM), hemoglobin (Hgb), interleukin (IL)-8, and F2-IsoPM were independent predictors of REE in HbSS (overall r2 = 0.778; p < 0.001). Low-grade inflammation and increased oxidative stress are present in adolescents with HbSS in the absence of acute crisis, and their markers are correlated with elevated REE.

Aerobic exercise training reduces cannabis craving and use in non-treatment seeking cannabis-dependent adults.

Background Cannabis 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. Aims To examine the effects of moderate aerobic exercise on cannabis craving and use in cannabis dependent adults under normal living conditions. Design Participants 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. Participants Sedentary 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). Measurements Self-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). Findings Daily 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). Conclusions The 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 Registration ClinicalTrials.gov NCT00838448]