Reliability and Validity of the Computer Science and Applications Accelerometer in a Mechanical Setting

Brage, Sören; Brage, Niels; Wedderkopp, Niels; Fröberg, Karsten

doi:10.1207/s15327841mpee0702_4

Cited by 82 publications

(78 citation statements)

References 16 publications

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“…). 2 This protocol is analogous to testing all the pedometers on a single mechanical calibration rig 7,26 and is in agreement with the 'longevity' protocol of McKenzie et al 24 that used one subject walking on a treadmill, over a number of trials.…”

supporting

confidence: 57%

“…2 Data reported as 2 mean (SD) and 3 median (interquartile range). 4 Significantly different from all other speeds for the same pedometer brand (p < 0.02), 5 MTI > NL, DW, KL, VT (p < 0.03), 6 DW < KL (p < 0.02), 7 MTI > KL (p < 0.04), 8 (DW, MTI, NL, VT) detected ~100% of the actual steps ( Fig. 2A-D , pedometers brands differed significantly over the same speed (p < 0.05) but not above 5.64 km.hr -1 (Table I).…”

Section: Partmentioning

confidence: 92%

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Pedometer step counting in South Africa: tools or trinkets?

Cook¹

2006

S. Afr. j. sports med.

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Design. One hundred instruments (20 instruments/brand) were tested at five level walking speeds on a motorised treadmill (3.24, 4.02, 4.80, 5.64, 6.42 km.hr -1 ) and during motor vehicle travel on tarred roads (62.9 km).results. The KL was highly variable across all speeds, while the VT tended to be variable at the lowest speed. The DW, NL and VT significantly underestimated steps below 4.80km.hr -1 (41 -94%, p < 0.02) but accuracy improved at speeds ≥ 4.80 km.hr -1 (98 -102%). The KL displayed the highest variability (60% inter-instrument variance) followed by the VT (10% inter-instrument variance). The research-grade pedometers were the least variable (0 -1% inter-instrument variance). At 4.80 km.hr -1 , all research-grade pedometers measured within a 10% margin of error compared with the 90% of VT units and 42% of KL units. The VT was significantly more resistant to nonambulatory signals than the DW (p < 0.01). The KL was the most variable in its response to non-ambulatory signals while the NL was the most consistent. The MTI detected the most non-ambulatory signals (p < 0.05).conclusions. The KL should not be used as a promotional pedometer. The VT achieved the minimum standards required of a promotional pedometer.

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supporting

confidence: 57%

Section: Partmentioning

confidence: 92%

Pedometer step counting in South Africa: tools or trinkets?

Cook¹

2006

S. Afr. j. sports med.

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“…CSA output is related to acceleration but not in a linear manner, as it also depends on movement frequency. 20 Step frequency therefore influences validity of the CSA as a measure of intensity in running and to a lesser extent in walking. [24][25][26] Even so, CSA output is highly correlated with intensity within the walking-jogging range, although accelerometry generally underestimates higher running intensities due to biomechanical limitations.…”

Section: Discussionmentioning

confidence: 99%

“…The CSA is a uniaxial piezoelectric accelerometer with a dynamic range of 72.13g and a frequency-dependent bandwidth filter, which can be regarded as a mathematical weighting function. 19,20 The CSA samples acceleration at 10 Hz and Relationship between physical activity and insulin resistance in Danish children S Brage et al integrates this over the user-defined epoch. In this study, the CSA was mailed to the children, preprogrammed to start at 0800 the following morning.…”

Section: Data Collectionmentioning

confidence: 99%

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Objectively measured physical activity correlates with indices of insulin resistance in Danish children.

et al. 2004

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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 ¼ 9.7 (0.44) y, weight ¼ 33.6 (6.4) kg, height ¼ 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 (Z10 h day À1 ). 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 À1 with a mean (s.d.) of 5.1 (0.37) mmol l À1 . 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 b cells. Our data emphasise the importance of physical activity in children for the maintenance of metabolic control.

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Physical Activity Awareness of British Adolescents

Corder¹

2011

Arch Pediatr Adolesc Med

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Objective To assess adolescent PA awareness and investigate associations with biological and psychosocial factors. Design Cross-sectional from November 2005 to July 2007 (ROOTS study). Setting Population-based sample recruited via Cambridgeshire and Suffolk schools (UK). Participants N=799 (44% male, 14.5±0.5 years). Main Exposures Self-rated PA perception, self-reported psychosocial factors, measured anthropometry. Outcome Measure PA measured using accelerometry over five days. ‘Inactive’ defined as accelerometry-measured <60 min/day of at least moderate PA (MVPA). Associations between awareness (agreement between self-rated and accelerometry-measured active/inactive) and potential correlates investigated using multinomial logistic regression. Results 70% of adolescents were inactive (81% of girls, 56% of boys, OR(95% CI) 3.41(2.41, 4.82)). 53% of all girls (63% of inactive girls) and 34% of all boys (60% of inactive boys) inaccurately rated themselves as active (over-estimators). Compared to girls accurately describing themselves as inactive (29%), girl over-estimators had lower fat mass (OR(95% CI) 0.84(0.70, 0.99)), higher SES (high vs. low 2.4(1.07, 5.32)), reported more parent-support (1.57(1.12, 2.22)) and better family relationships (0.25(0.09, 0.67)). Amongst boys accurately describing themselves as inactive (22%), over-estimators had lower fat mass (0.86(0.77, 0.96)) reported more peer-support (1.75(1.32, 2.30)) and less teasing (0.75(0.61, 0.92)). Conclusions A substantial number of adolescents believe themselves to be more physically active than they really are. They maybe unaware of potential health risks, and may be unlikely to participate in PA promotion programs. Increasing information of PA health benefits beyond weight control might help encourage behavior change.

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Reliability and Validity of the Computer Science and Applications Accelerometer in a Mechanical Setting

Cited by 82 publications

References 16 publications

Pedometer step counting in South Africa: tools or trinkets?

Pedometer step counting in South Africa: tools or trinkets?

Objectively measured physical activity correlates with indices of insulin resistance in Danish children.

Physical Activity Awareness of British Adolescents

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