11289373
Quality Control Methods in Accelerometer Data Processing: Identifying Extreme Counts
Background Accelerometers are designed to measure plausible human activity, however extremely high count values (EHCV) have been recorded in large-scale studies. Using population data, we develop methodological principles for establishing an EHCV threshold, propose a threshold to define EHCV in the ActiGraph GT1M, determine occurrences of EHCV in a large-scale study, identify device-specific error values, and investigate the influence of varying EHCV thresholds on daily vigorous PA (VPA). Methods We estimated quantiles to analyse the distribution of all accelerometer positive count values obtained from 9005 seven-year old children participating in the UK Millennium Cohort Study. A threshold to identify EHCV was derived by differentiating the quantile function. Data were screened for device-specific error count values and EHCV, and a sensitivity analysis conducted to compare daily VPA estimates using three approaches to accounting for EHCV. Results Using our proposed threshold of ≥ 11,715 counts/minute to identify EHCV, we found that only 0.7% of all non-zero counts measured in MCS children were EHCV; in 99.7% of these children, EHCV comprised < 1% of total non-zero counts. Only 11 MCS children (0.12% of sample) returned accelerometers that contained negative counts; out of 237 such values, 211 counts were equal to −32,768 in one child. The medians of daily minutes spent in VPA obtained without excluding EHCV, and when using a higher threshold (≥19,442 counts/minute) were, respectively, 6.2% and 4.6% higher than when using our threshold (6.5 minutes; p<0.0001). Conclusions Quality control processes should be undertaken during accelerometer fieldwork and prior to analysing data to identify monitors recording error values and EHCV. The proposed threshold will improve the validity of VPA estimates in children’s studies using the ActiGraph GT1M by ensuring only plausible data are analysed. These methods can be applied to define appropriate EHCV thresholds for different accelerometer models.
5913864
Compliance with physical activity guidelines: prevalence in a population of children and youth.
PURPOSE
To use objective monitoring of physical activity to determine the percentages of children and youth in a population that met physical activity guidelines.


METHODS
A total of 375 students in grades 1-12 wore an accelerometer (CSA 7164) for seven consecutive days. Bouts of continuous activity and accumulation of minutes spent in physical activity at various intensities were calculated to determine how many students met three physical activity guidelines.


RESULTS
Over 90% of students met Healthy People 2010, Objective 22.6 and nearly 70% met the United Kingdom Expert Consensus Group guideline, both of which recommend daily accumulation of moderate physical activity. Less than 3% met Healthy People 2010, Objective 22.7, which calls for bouts of continuous vigorous physical activity. For the United Kingdom Expert Consensus Group guideline, compliance decreased markedly with age, but gender differences were not statistically significant.


CONCLUSIONS
Prevalence estimates for compliance with national physical activity guidelines varied markedly for the three guidelines examined. Objective monitoring of physical activity in youth appears to be feasible and may provide more accurate prevalence rates than self-report measures.
24117286
Physical Activity Assessment With Accelerometers: An Evaluation Against Doubly Labeled Water
This review focuses on the ability of different accelerometers to assess daily physical activity as compared with the doubly labeled water (DLW) technique, which is considered the gold standard for measuring energy expenditure under free‐living conditions. The PubMed Central database (U.S. NIH free digital archive of biomedical and life sciences journal literature) was searched using the following key words: doubly or double labeled or labeled water in combination with accelerometer, accelerometry, motion sensor, or activity monitor. In total, 41 articles were identified, and screening the articles’ references resulted in one extra article. Of these, 28 contained sufficient and new data. Eight different accelerometers were identified: 3 uniaxial (the Lifecorder, the Caltrac, and the CSA/MTI/Actigraph), one biaxial (the Actiwatch AW16), 2 triaxial (the Tritrac‐R3D and the Tracmor), one device based on two position sensors and two motion sensors (ActiReg), and the foot‐ground contact pedometer. Many studies showed poor results. Only a few mentioned partial correlations for accelerometer counts or the increase in R2 caused by the accelerometer. The correlation between the two methods was often driven by subject characteristics such as body weight. In addition, standard errors or limits of agreement were often large or not presented. The CSA/MTI/Actigraph and the Tracmor were the two most extensively validated accelerometers. The best results were found for the Tracmor; however, this accelerometer is not yet commercially available. Of those commercially available, only the CSA/MTI/Actigraph has been proven to correlate reasonably with DLW‐derived energy expenditure.
1778482
Predictive validity of three ActiGraph energy expenditure equations for children.
PURPOSE
This study evaluated the predictive validity of three previously published ActiGraph energy expenditure (EE) prediction equations developed for children and adolescents.


METHODS
A total of 45 healthy children and adolescents (mean age: 13.7 +/- 2.6 yr) completed four 5-min activity trials (normal walking, brisk walking, easy running, and fast running) in an indoor exercise facility. During each trial, participants wore an ActiGraph accelerometer on the right hip. EE was monitored breath by breath using the Cosmed K4b portable indirect calorimetry system. Differences and associations between measured and predicted EE were assessed using dependent t-tests and Pearson correlations, respectively. Classification accuracy was assessed using percent agreement, sensitivity, specificity, and area under the receiver operating characteristic (ROC) curve.


RESULTS
None of the equations accurately predicted mean energy expenditure during each of the four activity trials. Each equation, however, accurately predicted mean EE in at least one activity trial. The Puyau equation accurately predicted EE during slow walking. The Trost equation accurately predicted EE during slow running. The Freedson equation accurately predicted EE during fast running. None of the three equations accurately predicted EE during brisk walking. The equations exhibited fair to excellent classification accuracy with respect to activity intensity, with the Trost equation exhibiting the highest classification accuracy and the Puyau equation exhibiting the lowest.


CONCLUSIONS
These data suggest that the three accelerometer prediction equations do not accurately predict EE on a minute-by-minute basis in children and adolescents during overground walking and running. The equations maybe useful, however, for estimating participation in moderate and vigorous activity.
24115381
Physical activity in the United States measured by accelerometer.
PURPOSE
To describe physical activity levels of children (6-11 yr), adolescents (12-19 yr), and adults (20+ yr), using objective data obtained with accelerometers from a representative sample of the U.S. population.


METHODS
These results were obtained from the 2003-2004 National Health and Nutritional Examination Survey (NHANES), a cross-sectional study of a complex, multistage probability sample of the civilian, noninstitutionalized U.S. population in the United States. Data are described from 6329 participants who provided at least 1 d of accelerometer data and from 4867 participants who provided four or more days of accelerometer data.


RESULTS
Males are more physically active than females. Physical activity declines dramatically across age groups between childhood and adolescence and continues to decline with age. For example, 42% of children ages 6-11 yr obtain the recommended 60 min x d(-1) of physical activity, whereas only 8% of adolescents achieve this goal. Among adults, adherence to the recommendation to obtain 30 min x d(-1) of physical activity is less than 5%.


CONCLUSIONS
Objective and subjective measures of physical activity give qualitatively similar results regarding gender and age patterns of activity. However, adherence to physical activity recommendations according to accelerometer-measured activity is substantially lower than according to self-report. Great care must be taken when interpreting self-reported physical activity in clinical practice, public health program design and evaluation, and epidemiological research.
2960208
Independent mobility in relation to weekday and weekend physical activity in children aged 10–11 years: The PEACH Project
BackgroundChildren's independent mobility has fallen in recent years and may in part explain reported declines in physical activity in young people. This cross-sectional study investigated whether independent mobility in boys and girls was related to objectively measured physical activity.MethodsThirteen hundred and seven 10–11 year old boys and girls from 23 schools in a large UK city took part. Measures included objectively recorded physical activity (accelerometer (Actigraph GT1M)), height (m) and weight (kg), a newly developed scale for local (Local-IM) and area independent mobility (Area-IM), minutes of daylight after school, level of neighbourhood deprivation and pubertal status.ResultsBoys had greater Local-IM, Area-IM and physical activity (average weekday and weekend counts per minute) compared to girls. In linear regression analyses (adjusting for minutes of daylight after school, neighbourhood deprivation, pubertal status and body mass index) higher scores for Local-IM and Area-IM were significantly (p < 0.01) related to higher levels of physical activity on weekdays for boys and girls. For weekend physical activity, only Local-IM in girls remained significant (p < 0.05) in the model.ConclusionIndependent mobility appears to be an important independent correlate of weekday physical activity for both boys and girls.
13804744
Physical activity and dietary behaviour in a population-based sample of British 10-year old children: the SPEEDY study (Sport, Physical activity and Eating behaviour: Environmental Determinants in Young people)
BackgroundThe SPEEDY study was set up to quantify levels of physical activity (PA) and dietary habits and the association with potential correlates in 9–10 year old British school children. We present here the analyses of the PA, dietary and anthropometry data.MethodsIn a cross-sectional study of 2064 children (926 boys, 1138 girls) in Norfolk, England, we collected anthropometry data at school using standardised procedures. Body mass index (BMI) was used to define obesity status. PA was assessed with the Actigraph accelerometer over 7 days. A cut-off of ≥ 2000 activity counts was used to define minutes of moderate-to-vigorous PA (MVPA). Dietary habits were assessed using the Health Behaviour in School Children food questionnaire. Weight status was defined using published international cut-offs (Cole, 2000). Differences between groups were assessed using independent t-tests for continuous data and chi-squared tests for categorical data.ResultsValid PA data (>500 minutes per day on ≥ 3 days) was available for 1888 children. Mean (± SD) activity counts per minute among boys and girls were 716.5 ± 220.2 and 635.6 ± 210.6, respectively (p < 0.001). Boys spent an average of 84.1 ± 25.9 minutes in MVPA per day compared to 66.1 ± 20.8 among girls (p < 0.001), with an average of 69.1% of children accumulating 60 minutes each day. The proportion of children classified as overweight and obese was 15.0% and 4.1% for boys and 19.3% and 6.6% for girls, respectively (p = 0.001). Daily consumption of at least one portion of fruit and of vegetables was 56.8% and 49.9% respectively, with higher daily consumption in girls than boys and in children from higher socioeconomic backgrounds.ConclusionResults indicate that almost 70% of children meet national PA guidelines, indicating that a prevention of decline, rather than increasing physical activity levels, might be an appropriate intervention target. Promotion of daily fruit and vegetable intake in this age group is also warranted, possibly focussing on children from lower socioeconomic backgrounds.
70549093
Objective measurement of levels and patterns of physical activity
Objective measurement of levels and patterns of physical activity . Riddoch C.J., Mattocks C., Deere K., Saunders J., Kirkby J., Tilling K., Leary S.D., Blair S.N. & Ness A.R. ( 2007 ) Archives of Disease in Childhood , 92 , 963 – 969 . DOI: 10.1136/adc.2006.112136. 
 
 
 
Objective  To measure the levels and patterns of physical activity, using accelerometers, of 11-year-old children participating in the Avon Longitudinal Study of Parents and Children (ALSPAC). 
 
 
 
Design  Cross-sectional analysis. 
 
 
 
Setting  The ALSPAC is a birth cohort study located in the former county of Avon, in the south-west of England. This study used data collected when the children were 11 years old. 
 
 
 
Participants  A total of 5595 children (2662 boys, 2933 girls). The children are the offspring of women recruited to a birth cohort study during 1991–1992. The median age (95% CI) of the children is now 11.8 (11.6–11.9) years. 
 
 
 
Methods  Physical activity was measured over a maximum of seven consecutive days using the MTI Actigraph accelerometer. 
 
 
 
Main outcome measures  Level and pattern of physical activity. 
 
 
 
Results  The median physical activity level was 580 counts/min. Boys were more active than girls [median (IQR) 644 (528–772) counts/min vs. 529 (444–638) counts/min, respectively]. Only 2.5% (95% CI 2.1% to 2.9%) of children [boys 5.1% (95% CI 4.3% to 6.0%), girls 0.4% (95% CI 0.2% to 0.7%)] met current internationally recognized recommendations for physical activity. Children were most active in summer and least active in winter (difference = 108 counts/min). Both the mother and partner's education level were inversely associated with activity level [P for trend <0.001 (both mother and partner)]. The association was lost for mother's education (P for trend = 0.07) and attenuated for partner's education (P for trend = 0.02), after adjustment for age, sex, season, maternal age and social class. 
 
 
 
Conclusions  A large majority of children are insufficiently active, according to current recommended levels for health.
129120626
Standardizing and Optimizing the Use of Accelerometer Data for Free-Living Physical Activity Monitoring
The unequivocal link between physical activity and health has prompted researchers and public health officials to search for valid, reliable, and logistically feasible tools to measure and quantify free-living physical activity. Accelerometers hold promise in this regard. Recent technological advances have led to decreases in both the size and cost of accelerometers while increasing functionality (e.g., greater memory, waterproofing). A lack of common data reduction and standardized reporting procedures dramatically limit their potential, however. The purpose of this article is to expand on the utility of accelerometers for measuring free-living physical activity. A detailed example profile of physical activity is presented to highlight the potential richness of accelerometer data. Specific recommendations for optimizing and standardizing the use of accelerometer data are provided with support from specific examples. This descriptive article is intended to advance and ignite scholarly dialogue and debate ...
13945944
International children's accelerometry database (ICAD): Design and methods
BackgroundOver the past decade, accelerometers have increased in popularity as an objective measure of physical activity in free-living individuals. Evidence suggests that objective measures, rather than subjective tools such as questionnaires, are more likely to detect associations between physical activity and health in children. To date, a number of studies of children and adolescents across diverse cultures around the globe have collected accelerometer measures of physical activity accompanied by a broad range of predictor variables and associated health outcomes. The International Children's Accelerometry Database (ICAD) project pooled and reduced raw accelerometer data using standardized methods to create comparable outcome variables across studies. Such data pooling has the potential to improve our knowledge regarding the strength of relationships between physical activity and health. This manuscript describes the contributing studies, outlines the standardized methods used to process the accelerometer data and provides the initial questions which will be addressed using this novel data repository.MethodsBetween September 2008 and May 2010 46,131 raw Actigraph data files and accompanying anthropometric, demographic and health data collected on children (aged 3-18 years) were obtained from 20 studies worldwide and data was reduced using standardized analytical methods.ResultsWhen using ≥ 8, ≥ 10 and ≥ 12 hrs of wear per day as a criterion, 96%, 93.5% and 86.2% of the males, respectively, and 96.3%, 93.7% and 86% of the females, respectively, had at least one valid day of data.ConclusionsPooling raw accelerometer data and accompanying phenotypic data from a number of studies has the potential to: a) increase statistical power due to a large sample size, b) create a more heterogeneous and potentially more representative sample, c) standardize and optimize the analytical methods used in the generation of outcome variables, and d) provide a means to study the causes of inter-study variability in physical activity. Methodological challenges include inflated variability in accelerometry measurements and the wide variation in tools and methods used to collect non-accelerometer data.
9172267
Comparison of four ActiGraph accelerometers during walking and running.
UNLABELLED
Currently, researchers can use the ActiGraph 7164 or one of three different versions of the ActiGraph GT1M to objectively measure physical activity.


PURPOSE
To determine whether differences exist between activity counts from the ActiGraph 7164 and the three versions of the GT1M at given walking and running speeds.


METHODS
Ten male participants (23.6 +/- 2.7 yr) completed treadmill walking and running at 10 different speeds (3-min stages) while wearing the ActiGraph 7164 and the latest GT1M (GT1M-V3) or the GT1M version one (GT1M-V1) and the GT1M version two (GT1M-V2). Participants walked at 3, 5, and 7 km x h(-1) followed by running at 8, 10, 12, 14, 16, 18, and 20 km x h(-1). The accelerometers were worn on an elastic belt around the waist over the left and right sides of the hip. Testing was performed on different days using a counterbalanced within-subjects design to account for potential differences attributable to accelerometer placement. At each speed, a one-way repeated-measures ANOVA was used to examine differences between activity counts in counts per minute (cpm). Post hoc pairwise comparisons with Bonferroni adjustments were used where appropriate.


RESULTS
There were no significant differences between activity counts at any given walking or running speed (P < 0.05). At all running speeds, activity counts from the ActiGraph 7164 and GT1M-V2 displayed the lowest and highest values, respectively. Output from all accelerometers peaked at 14 km x h(-1) (mean range = 8974 +/- 677 to 9412 +/- 982 cpm) and then gradually declined at higher speeds. The mean difference score at peak output between the ActiGraph 7164 and GT1M-V2 was 439 +/- 565 cpm.


CONCLUSIONS
There were no statistically significant differences between outputs from all the accelerometers, indicating that researchers can select any of the four ActiGraph accelerometers in doing research.
2124018
Ethnic and gender differences in physical activity levels among 9-10-year-old children of white European, South Asian and African-Caribbean origin: the Child Heart Health Study in England (CHASE Study).
BACKGROUND
Ethnic differences in physical activity in children in the UK have not been accurately assessed. We made objective measurements of physical activity in 9-10-year-old British children of South Asian, black African-Caribbean and white European origin.


METHODS
Cross-sectional study of urban primary school children (2006-07). Actigraph-GT1M activity monitors were worn by 2071 children during waking hours on at least 1 full day. Ethnic differences in mean daily activity [counts, counts per minute of registered time (CPM) and steps] were adjusted for age, gender, day of week and month. Multilevel modelling allowed for repeated days within individual and clustering within school.


RESULTS
In white Europeans, mean daily counts, CPM and mean daily steps were 394,785, 498 and 10,220, respectively. South Asian and black Caribbean children recorded more registered time per day than white Europeans (34 and 36 min, respectively). Compared with white Europeans, South Asians recorded 18 789 fewer counts [95% confidence interval (CI) 6390-31 187], 41 fewer CPM 95% CI 26-57) and 905 fewer steps (95% CI 624-1187). Black African-Caribbeans recorded 25 359 more counts (95% CI 14 273-36 445), and similar CPM, but fewer steps than white Europeans. Girls recorded less activity than boys in all ethnic groups, with 74 782 fewer counts (95% CI 66 665-82 899), 84 fewer CPM (95% CI 74-95) and 1484 fewer steps (95% CI 1301-1668).


CONCLUSION
British South Asian children have lower objectively measured physical activity levels than European whites and black African-Caribbeans.
13788071
Best practices for using physical activity monitors in population-based research.
The use of physical activity monitors in population-based research has increased dramatically in the past decade. In this report, we review the major purpose for using physical activity monitors in different types of population-based studies (i.e., surveillance, intervention, association studies) and discuss the strengths and weaknesses for the various behavioral outcomes derived from monitors for each study type. We also update and extend previous recommendations for use of these instruments in large-scale studies, particularly with respect to selecting monitor systems in the context of technological advances that have occurred in recent years. The current state of the science with respect to optimal measurement schedules for use of physical activity monitors is also discussed. A checklist and flowchart are provided so that investigators have more guidance when reporting key elements of monitor use in their studies.
37926145
Features of the metabolic syndrome are associated with objectively measured physical activity and fitness in Danish children: the European Youth Heart Study (EYHS).
OBJECTIVE
Features of the metabolic syndrome are becoming increasingly evident in children. Decreased physical activity is likely to be an important etiological factor, as shown previously for subjective measures of physical activity in selected groups. The purpose of this study was to examine the relationship between the metabolic syndrome and objectively measured physical activity and whether fitness modified this relationship.


RESEARCH DESIGN AND METHODS
A total of 589 Danish children (310 girls, 279 boys, mean [+/-SD] age 9.6 +/- 0.44 years, mean weight 33.6 +/- 6.4 kg, mean height 1.39 +/- 0.06 m) were randomly selected. Physical activity was measured with the uni-axial Computer Science & Applications accelerometer (MTI actigraph) worn at the hip for at least 3 days (>/=10 h/day) and fitness with a maximal bike test. As outcomes, we measured sitting systolic and diastolic blood pressure, degree of adiposity (sum of four skinfolds), and, finally, insulin, glucose, triglicerides, and HDL cholesterol in fasting blood samples. The outcome variables were statistically normalized and expressed as the number of SDs from the mean. (i.e., Z scores). A metabolic syndrome risk score was computed as the mean of these Z scores. Multiple linear regression was used to test the association between physical activity and metabolic risk, adjusted primarily for age, sex, sexual maturation, ethnicity, parental smoking, socioeconomic factors, and the Computer Science & Applications unit, as well as for fitness. Robust SEs were computed by clustering on school.


RESULTS
All children were in the nondiabetic range of fasting glucose. Metabolic risk was inversely related to physical activity (P = 0.008). The relationship was weakened after adjustment for fitness, but there was a significantly positive interaction between physical activity and fitness.


CONCLUSIONS
Physical activity is inversely associated with metabolic risk, independently of potential confounders. The interaction between physical activity and fitness suggests that the potential beneficial effect of activity may be greatest in children with lower cardiorespiratory fitness.
17757982
Use of accelerometers in a large field-based study of children: protocols, design issues, and effects on precision.
BACKGROUND
Objective methods can improve accuracy of physical activity measurement in field studies but uncertainties remain about their use.


METHODS
Children age 11 years from the Avon Longitudinal Study of Parents and Children (ALSPAC), were asked to wear a uni-axial accelerometer (MTI Actigraph) for 7 days.


RESULTS
Of 7159 children who attended for assessment, 5595 (78%) provided valid measures. The reliability coefficient for 3 days of recording was .7 and the power to detect a difference of 0.07 SDs (P<or=.05) was > 90%. Measures tended to be higher on the first day of recording (17 counts/min; 95% CI, 10-24) and if children wore the monitor for fewer days, but these differences were small. The children who provided valid measures of activity were different from those who did not, but the differences were modest.


CONCLUSION
Objective measures of physical activity can be incorporated into large longitudinal studies of children.
22432604
Conquering childhood inactivity: is the answer in the past?
PURPOSE
The primary purpose of this study was to compare the health-related physical fitness and physical activity behaviors of Old Order Mennonite children to both rural and urban-dwelling children living a contemporary Canadian lifestyle.


METHODS
A cross-sectional study design was used to compare the physical fitness and physical activity characteristics of three groups of children between the ages of 8-13 yr. A total of 124 Old Order Mennonite children (OOM) from Ontario, Canada, were compared with contemporary living children from urban (USK, N = 110) and rural (RSK, N = 165) Saskatchewan, Canada. Fitness was assessed using measures of height, weight, triceps skinfold, grip strength, push-ups, partial curl-ups, and aerobic fitness. Physical activity levels were directly measured for seven consecutive days using a MTI Actigraph accelerometer model 7164.


RESULTS
After controlling for maturational age, analyses revealed that OOM children had a smaller triceps skinfold than USK children (P < 0.01), a greater aerobic fitness score than RSK children (P < 0.05), and greater grip strength than both RSK and USK children (P < 0.001). The OOM children also accumulated more minutes of MVPA per day than RSK or USK groups (P < 0.001).


CONCLUSION
This research demonstrates that OOM children tend to be leaner, stronger and more active than urban and rural dwelling children living a contemporary Canadian lifestyle despite having no physical education, no institutionalized sport, and low socioeconomic status. These findings support the notion that that contemporary living may facilitate a decline in fitness and physical activity among some Canadian children.
25038212
Objectively measured physical activity correlates with indices of insulin resistance in Danish children.
OBJECTIVE: To explore the association between measures of insulin resistance with objectively assessed physical activity.DESIGN: School-based, cross-sectional study.SUBJECTS: A randomly selected sample of 589 children (310 girls, 279 boys, mean (standard deviations, s.d.) age=9.7 (0.44) y, weight=33.6 (6.4) kg, height=1.39 (0.06) m) from Denmark.METHODS: Fasting blood samples were analysed for serum insulin and glucose. Physical activity was measured with the uniaxial Computer Science and Applications (CSA) model 7164 accelerometer, worn for at least 3 days (≥10 h day−1). Adiposity was assessed by the sum of four skinfolds. Multiple linear regression were performed to model insulin and glucose from average CSA output, adjusted for age, gender, puberty, ethnicity, birth weight, parental smoking, socioeconomic group, and CSA unit. In addition, we adjusted for skinfold thickness.RESULTS: Mean fasting serum glucose ranged from 4.1 to 6.5 mmol l−1 with a mean (s.d.) of 5.1 (0.37) mmol l−1. Fasting insulin was negatively correlated with CSA output on levels of adjustment. Fasting glucose was not significantly associated with physical activity. However, in girls both indices of insulin resistance were significantly related to activity, whereas in boys none of the associations were significant.CONCLUSION: Physical activity is inversely associated with fasting insulin in the nondiabetic range of fasting glucose. The relationship was stronger for insulin than for glucose, indicating compensatory action by the β cells. Our data emphasise the importance of physical activity in children for the maintenance of metabolic control.
28722080
Accelerometer data reduction: a comparison of four reduction algorithms on select outcome variables.
PURPOSE
Accelerometers are recognized as a valid and objective tool to assess free-living physical activity. Despite the widespread use of accelerometers, there is no standardized way to process and summarize data from them, which limits our ability to compare results across studies. This paper a) reviews decision rules researchers have used in the past, b) compares the impact of using different decision rules on a common data set, and c) identifies issues to consider for accelerometer data reduction.


METHODS
The methods sections of studies published in 2003 and 2004 were reviewed to determine what decision rules previous researchers have used to identify wearing period, minimal wear requirement for a valid day, spurious data, number of days used to calculate the outcome variables, and extract bouts of moderate to vigorous physical activity (MVPA). For this study, four data reduction algorithms that employ different decision rules were used to analyze the same data set.


RESULTS
The review showed that among studies that reported their decision rules, much variability was observed. Overall, the analyses suggested that using different algorithms impacted several important outcome variables. The most stringent algorithm yielded significantly lower wearing time, the lowest activity counts per minute and counts per day, and fewer minutes of MVPA per day. An exploratory sensitivity analysis revealed that the most stringent inclusion criterion had an impact on sample size and wearing time, which in turn affected many outcome variables.


CONCLUSIONS
These findings suggest that the decision rules employed to process accelerometer data have a significant impact on important outcome variables. Until guidelines are developed, it will remain difficult to compare findings across studies.
39452003
The Millennium Cohort Study.
The Millennium Cohort Study is the latest in the line of British birth cohort studies. MCS resembles its predecessors which follow people born in 1946, 1958 and 1970 in the intention to become multi-purpose longitudinal data resource charting many aspects of individual's lives over time. The families of a sample of around 20,000 babies are being interviewed during 2001-02, when eligible babies reach 9 months, to establish the conditions from which they set out in life. The survey contrasts with the previous cohort studies in various ways. Instead of taking all births in one week, the sample of births is spread over a year; the births are from a selection of electoral wards, thereby enabling eventual analysis by neighbourhood characteristics; it also over samples children living in deprived areas, wards with high ethnic minority populations and samples have been boosted in Scotland, Wales and Northern Ireland. The latter UK country has not been covered by the other studies. It interviews fathers as well as mothers, and given that its initial funding comes via the ESRC, puts a greater emphasis on socio-economic data than in early parts of the other studies. MCS has been enhanced by additional Government funding. The research team, based at the Institute of Education, aims to deposit a multi-purpose dataset for public use at the ESRC data Archive in the Spring of 2003.
3837216
Actigraph Accelerometer-Defined Boundaries for Sedentary Behaviour and Physical Activity Intensities in 7 Year Old Children
Background Accurate objective assessment of sedentary and physical activity behaviours during childhood is integral to the understanding of their relation to later health outcomes, as well as to documenting the frequency and distribution of physical activity within a population. Purpose To calibrate the Actigraph GT1M accelerometer, using energy expenditure (EE) as the criterion measure, to define thresholds for sedentary behaviour and physical activity categories suitable for use in a large scale epidemiological study in young children. Methods Accelerometer-based assessments of physical activity (counts per minute) were calibrated against EE measures (kcal.kg−1.hr−1) obtained over a range of exercise intensities using a COSMED K4b2 portable metabolic unit in 53 seven-year-old children. Children performed seven activities: lying down viewing television, sitting upright playing a computer game, slow walking, brisk walking, jogging, hopscotch and basketball. Threshold count values were established to identify sedentary behaviour and light, moderate and vigorous physical activity using linear discriminant analysis (LDA) and evaluated using receiver operating characteristic (ROC) curve analysis. Results EE was significantly associated with counts for all non-sedentary activities with the exception of jogging. Threshold values for accelerometer counts (counts.minute−1) were <100 for sedentary behaviour and ≤2240, ≤3840 and ≥3841 for light, moderate and vigorous physical activity respectively. The area under the ROC curves for discrimination of sedentary behaviour and vigorous activity were 0.98. Boundaries for light and moderate physical activity were less well defined (0.61 and 0.60 respectively). Sensitivity and specificity were higher for sedentary (99% and 97%) and vigorous (95% and 91%) than for light (60% and 83%) and moderate (61% and 76%) thresholds. Conclusion The accelerometer cut points established in this study can be used to classify sedentary behaviour and to distinguish between light, moderate and vigorous physical activity in children of this age.
121958493
On Jonckheere's k-Sample Test Against Ordered Alternatives
In this paper a k-sample non-parametric test for trend is considered. Given a sample of size ni , i = 1, …, k respectively from each of k populations, the test rejects the hypothesis that the k populations are identical if S = Σ k i=2 Si ≥ Si . Here Si is the Mann-Whitney statistic computed when each observation in the i-th sample is compared with the combined observations from the first (i – 1) populations. A recurrence formula is derived for computing the exact distribution of S. Tables of exact probabilities and critical values are given for nominal values of α = 0.5, 0.2, 0.1, 0.05, 0.025, 0.01, and 0.005 for k = 3 and all possible sample sizes from 2 to 8, and for equal sample sizes for values of n = 2(1)6, k = 4(1)6.
7696063
Multiple Hypothesis Testing
INTRODUCTION ..................................................................................................................... 561 ORGANIZING CO CEPTS ..................................................................................................... 564 Primary Hypotheses, Closure, Hierarchical Sets, and Minimal Hypotheses ...................... 564 Families ................................................................................................................................ 565 Type 1 Error Control ............................................................................................................ 566 Power ................................................................................................................................... 567 P-Values and Adjusted P-Values ......................................................................................... 568 Closed Test Procedures ....................................................................................................... 569 METHODS BA ED ON ORDERED P-VALUES ................................................................... 569 Methods Based on the First-Order Bonferroni Inequality .................................................. 569 Methods Based on the Simes Equality ................................................................................. 570 Modifications for Logically Related Hypotheses ................................................................. 571 Methods Controlling the False Discovery Rate ................................................................... 572 COMPARING NORMALLY DISTRIBUTED M ANS ......................................................... 573 OTHER ISSUES ........................................................................................................................ 575 Tests vs Confidence I tervals ............................................................................................... 575 Directional vs Nondirectional Inference ............................................................................. 576 Robustness ............................................................................................................................ 577 Others ........................................................................ ....................................................... 578 CONCLUSION .......................................................................................................................... 580
15368740
Comparison of the ActiGraph 7164 and the ActiGraph GT1M during self-paced locomotion.
PURPOSE
This study compared the ActiGraph accelerometer model 7164 (AM1) with the ActiGraph GT1M (AM2) during self-paced locomotion.


METHODS
Participants (n = 116, aged 18-73 yr, mean body mass index = 26.1 kg x m(-2)) walked at self-selected slow, medium, and fast speeds around an indoor circular hallway (0.47 km). Both activity monitors were attached to a belt secured to the hip and simultaneously collected data in 60-s epochs. To compare differences between monitors, the average difference (bias) in count output and steps output was computed at each speed. Time spent in different activity intensities (light, moderate, and vigorous) based on the cut points of Freedson et al. was compared for each minute.


RESULTS
The mean +/- SD walking speed was 0.7 +/- 0.22 m x s(-1) for the slow speed, 1.3 +/- 0.17 m x s(-1) for medium, and 2.1 +/- 0.61 m x s(-1) for fast speeds. Ninety-five percent confidence intervals (95% CI) were used to determine significance. Across all speeds, step output was significantly higher for the AM1 (bias = 19.8%, 95% CI = -23.2% to -16.4%) because of the large differences in step output at slow speed. The count output from AM2 was a significantly higher (2.7%, 95% CI = 0.8%-4.7%) than that from AM1. Overall, 96.1% of the minutes were classified into the same MET intensity category by both monitors.


CONCLUSIONS
The step output between models was not comparable at slow speeds, and comparisons of step data collected with both models should be interpreted with caution. The count output from AM2 was slightly but significantly higher than that from AM1 during the self-paced locomotion, but this difference did not result in meaningful differences in activity intensity classifications. Thus, data collected with AM1 should be comparable to AM2 across studies for estimating habitual activity levels.
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Independent associations of physical activity and cardiorespiratory fitness with metabolic risk factors in children: the European youth heart study
Aims/hypothesisHigh levels of cardiorespiratory fitness (CRF) and physical activity (PA) are associated with a favourable metabolic risk profile. However, there has been no thorough exploration of the independent contributions of cardiorespiratory fitness and subcomponents of activity (total PA, time spent sedentary, and time spent in light, moderate and vigorous intensity PA) to metabolic risk factors in children and the relative importance of these factors.MethodsWe performed a population-based, cross-sectional study in 9- to 10- and 15- to 16-year-old boys and girls from three regions of Europe (n = 1709). We examined the independent associations of subcomponents of PA and CRF with metabolic risk factors (waist circumference, BP, fasting glucose, insulin, triacylglycerol and HDL-cholesterol levels). Clustered metabolic risk was expressed as a continuously distributed score calculated as the average of the standardised values of the six subcomponents.ResultsCRF (standardised β = −0.09, 95% CI −0.12, −0.06), total PA (standardised β = −0.08, 95% CI −0.10, −0.05) and all other subcomponents of PA were significantly associated with clustered metabolic risk. After excluding waist circumference from the summary score and further adjustment for waist circumference as a confounding factor, the magnitude of the association between CRF and clustered metabolic risk was attenuated (standardised β = −0.05, 95% CI −0.08, −0.02), whereas the association with total PA was unchanged (standardised β = −0.08 95% CI −0.10, −0.05).Conclusions/interpretationPA and CRF are separately and independently associated with individual and clustered metabolic risk factors in children. The association between CRF and clustered risk is partly mediated or confounded by adiposity, whereas the association between activity and clustered risk is independent of adiposity. Our results suggest that fitness and activity affect metabolic risk through different pathways.