Urs Mäder

Reactivity to accelerometer measurement of children and adolescents

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Differences in weight status and energy-balance related behaviors among schoolchildren in German-speaking Switzerland compared to seven countries in Europe

BackgroundOverweight in children and adolescents have increased significantly and are a major public health problem. To allow international comparisons, Switzerland joined the European study ‘ENERGY’ cross sectional survey consortium that investigated the prevalence of overweight and obesity as well as selected dietary, physical and sedentary behaviors of 10–12 years old pupils across seven other countries in Europe. The aims of the present study was to compare body composition and energy-balance related behaviors of Swiss schoolchildren to those of the seven European ENERGY-countries and to analyze overweight and energy-balance related behaviors of Swiss children according to socio-demographic factors.MethodsA school-based cross-sectional study among 10–12 year old children was conducted in Switzerland and seven other European countries using a standardized protocol. Body height, weight and waist-circumference were measured by trained research assistants. Energy-balance related behaviors –i.e. selected dietary, physical activity and screen-viewing behaviors were assessed by questionnaires. Weight status and behaviors in Switzerland were compared to the seven European ENERGY countries. Within the Swiss sample, analyses stratified by gender, parental education and ethnicity were performed.ResultsData of 546 Swiss children (mean age 11.6±0.8y, 48% girls) were obtained and compared to the ENERGY- results (N=7.148; mean age 11.5±0.8y, 48% girls). In Switzerland significantly less children were overweight (13.9%) or obese (2.3%) compared to the average across the ENERGY-countries (23.7% and 4.7%, respectively), and were even somewhat lower than the ENERGY countries with the lowest prevalence. Sugar sweetened beverage intakes and breakfast habits of Swiss children did not differ significantly from those of ENERGY. However, the mean time devoted by Swiss children to walking or cycling to school and attending sports activities was significantly higher and screen time significantly lower compared to the other ENERGY-countries. Within the Swiss, sample relatively large and consistent differences were observed between children from native and non-native ethnicity.ConclusionsThe prevalence of overweight and obesity among Swiss children are substantial but significantly lower compared to all other European ENERGY-Partners, probably due to the fact that Swiss children were found to be more active and less sedentary comparing to the rest of the European sample.

Regional differences of physical activity and sedentary behaviour in Swiss children are not explained by socio-demographics or the built environment

ObjectiveWe evaluated whether regional differences in physical activity (PA) and sedentary behaviour (SB) existed along language boundaries within Switzerland and whether potential differences would be explained by socio-demographics or environmental characteristics.MethodsWe combined data of 611 children aged 4 to 7 years from four regional studies. PA and SB were assessed by accelerometers. Information about the socio-demographic background was obtained by questionnaires. Objective neighbourhood attributes could be linked to home addresses. Multivariate regression models were used to test associations between PA and SB and socio-demographic characteristics and neighbourhood attributes.ResultsChildren from the German compared to the French-speaking region were more physically active and less sedentary (by 10–15xa0%, pxa0<xa00.01). Although German-speaking children lived in a more favourable environment and a higher socioeconomic neighbourhood (differences pxa0<xa00.001), these characteristics did not explain the differences in PA behaviour between French and German speaking.ConclusionsFactors related to the language region, which might be culturally rooted were among the strongest correlates of PA and SB among Swiss children, independent of individual, social and environmental factors.

Neural network versus activity-specific prediction equations for energy expenditure estimation in children

The aim of this study was to compare the energy expenditure (EE) estimations of activity-specific prediction equations (ASPE) and of an artificial neural network (ANNEE) based on accelerometry with measured EE. Forty-three children (age: 9.8 ± 2.4 yr) performed eight different activities. They were equipped with one tri-axial accelerometer that collected data in 1-s epochs and a portable gas analyzer. The ASPE and the ANNEE were trained to estimate the EE by including accelerometry, age, gender, and weight of the participants. To provide the activity-specific information, a decision tree was trained to recognize the type of activity through accelerometer data. The ASPE were applied to the activity-type-specific data recognized by the tree (Tree-ASPE). The Tree-ASPE precisely estimated the EE of all activities except cycling [bias: -1.13 ± 1.33 metabolic equivalent (MET)] and walking (bias: 0.29 ± 0.64 MET; P < 0.05). The ANNEE overestimated the EE of stationary activities (bias: 0.31 ± 0.47 MET) and walking (bias: 0.61 ± 0.72 MET) and underestimated the EE of cycling (bias: -0.90 ± 1.18 MET; P < 0.05). Biases of EE in stationary activities (ANNEE: 0.31 ± 0.47 MET, Tree-ASPE: 0.08 ± 0.21 MET) and walking (ANNEE 0.61 ± 0.72 MET, Tree-ASPE: 0.29 ± 0.64 MET) were significantly smaller in the Tree-ASPE than in the ANNEE (P < 0.05). The Tree-ASPE was more precise in estimating the EE than the ANNEE. The use of activity-type-specific information for subsequent EE prediction equations might be a promising approach for future studies.

Relationship between the objectively-assessed neighborhood area and activity behavior in Swiss youth

Background Neighborhood attributes are modifiable determinants of physical activity (PA) and sedentary behavior (SB). We tested whether the objectively-assessed built and social environment was associated with PA and SB in Swiss youth and whether sex, age and the socioeconomic position (Swiss-SEP) modified such associations. Methods We combined data of 1742 youth (ages 4 to 17) from seven studies conducted within Switzerland between 2005–2010. All youth provided accelerometer data and a home address, which was linked to objective environmental data and the Swiss-SEP-index. Associations between neighborhood attributes and PA were analyzed by multivariable multilevel regression analyses. Results The extent of green areas and building density was positively associated with PA in the total sample (p < 0.05). Factors representing centrally located areas, and more schoolchildren living nearby tended to increase PA in secondary schoolchildren, boys and those from lower-ranked socioeconomic areas. In primary schoolchildren, the extent of green areas was positively associated with PA (p = 0.05). Associations between neighborhood attributes and PA were more pronounced in youth from low socioeconomic areas. Conclusions The results indicate that some associations between neighborhood attributes and PA differ by age, sex and socioeconomic area. This should be taken into account when planning interventions to increase childhood PA.

Comparing the Validity and Output of the GT1M and GT3X Accelerometer in 5- to 9-Year-Old Children

The purpose of this study was to compare the validity and output of the biaxial ActiGraph GT1M and the triaxial GT3X (ActiGraph, LLC, Pensacola, FL, USA) accelerometer in 5- to 9-year-old children. Thirty-two children wore the two monitors while their energy expenditure was measured with indirect calorimetry. They performed four locomotor and four play activities in an exercise laboratory and were further measured during 12 minutes of a sports lesson. Validity evidence in relation to indirect calorimetry was examined with linear regression equations applied to the laboratory data. During the sports lessons predicted energy expenditure according to the regression equations was compared to measured energy expenditure with the Wilcoxon-signed rank test and the Spearman correlation. To compare the output, agreement between counts of the two monitors during the laboratory activities was assessed with Bland-Altman plots. The evidence of validity was similar for both monitors. Agreement between the output of the two monitors was good for vertical counts (mean bias =u2009−14 ± 22 counts) but not for horizontal counts (−17 ± 32 counts). The current results indicate that the two accelerometer models are able to estimate energy expenditure of a range of physical activities equally well in young children. However, they show output differences for movement in the horizontal direction.

Metabolic Thresholds and Validated Accelerometer Cutoff Points for the Actigraph GT1M in Young Children Based on Measurements of Locomotion and Play Activities

The purpose of the current study was to determine metabolic thresholds and subsequent activity intensity cutoff points for the ActiGraph GT1M with various epochs spanning from 5 to 60 sec in young children. Twenty-two children, aged 4 to 9 years, performed 10 different activities including locomotion and play activities. Energy expenditure was measured with indirect calorimetry. Thresholds and cutoff points were determined through receiver operating characteristic curves. The lower metabolic threshold was 6.19 kcal·kg−1·h−1 for moderate and 9.28 kcal·kg−1·h−1 for vigorous intensity. The cutoff points for the GT1M accelerometer appear to be lower than those for the previous model (7164). For 5-sec epochs, a cutoff point of 143 counts resulted for moderate intensity and of 208 counts for vigorous intensity activity. Whether short or long epochs were chosen when collecting data to determine cutoff points, does not appear to have an influence on the resulting cutoff values. Similarly, comparable results are seen when analyses are based on locomotion only as opposed to a wide range of activities including childrens play.