Sanne I. de Vries

Validity and Reproducibility of Motion Sensors in Youth: A Systematic Update

PURPOSE To review recently published studies on the reproducibility, validity, and feasibility of motion sensors used to assess physical activity in healthy children and adolescents (2-18 yr). METHODS On October 2004, a systematic literature search in PubMed, EMBASE, and PsycINFO was performed. This search has been updated on October 2007. In this update, the clinimetric quality of three pedometers (Digi-Walker, Walk4Life, and Sun TrekLINQ) and nine accelerometers (ActiGraph, BioTrainer, StepWatch Activity Monitor, Actiwatch, Actical, Tritrac-R3D, RT3, ActivTracer, and Mini-Motionlogger) has been evaluated and compared using a checklist. RESULTS Thirty-two recently published clinimetric studies have been reviewed. All 12 motion sensors have been validated in youth in one or more studies. There is strong evidence for moderate validity of the StepWatch in children and adolescents (4-18 yr) and moderate to good validity of the ActiGraph in preschool children and young children (2-8 yr). There is less evidence for the reproducibility and feasibility of the 12 motion sensors. Strong evidence exists for good reproducibility of the ActiGraph in preschool children (2-4 yr). CONCLUSION Compared to the review performed in 2004, there is increased evidence for the clinimetric quality of pedometers and accelerometers in youth. Most motion sensors seem reproducible, valid, and feasible in assessing physical activity in youth.

Determinants of activity-friendly neighborhoods for children: results from the SPACE study

Purpose. To examine the association between childrens physical activity and factors of the built environment. Design. Cross-sectional study. Setting. Ten neighborhoods in six cities in the Netherlands. Subjects. Four hundred twenty-two children (age range, 6–11 years; 49% male). Measures. Physical activity diary, neighborhood observations, and anthropometric measures. Analysis. Univariate and multivariate linear regression analyses. Results. According to univariate analyses adjusted for age, sex, body mass index, and highest level of maternal education, physical activity (≥ 3 metabolic equivalents) was significantly (p < .05) associated with the proportion of green space, with the residential density, with the general impression of activity-friendliness of the neighborhood, and with the frequency of certain types of residences (e.g., terraced houses), sports fields, water, dog waste, heavy traffic, and safe walking and cycling conditions (e.g., cycle tracks and 30-km speed zones) in the neighborhood. According to adjusted multivariate analyses, physical activity was best predicted by the frequency of parallel parking spaces in the neighborhood and by the general impression of activity-friendliness of the neighborhood (R2 = 0.193). Conclusions. Childrens physical activity is associated with certain modifiable factors of the built environment. Longitudinal studies should examine whether there is a causal relationship.

Association between parenting practices and children's dietary intake, activity behavior and development of body mass index: the KOALA Birth Cohort Study.

BackgroundInsights into the effects of energy balance-related parenting practices on childrens diet and activity behavior at an early age is warranted to determine which practices should be recommended and to whom. The purpose of this study was to examine child and parent background correlates of energy balance-related parenting practices at age 5, as well as the associations of these practices with childrens diet, activity behavior, and body mass index (BMI) development.MethodsQuestionnaire data originated from the KOALA Birth Cohort Study for ages 5 (N = 2026) and 7 (N = 1819). Linear regression analyses were used to examine the association of child and parent background characteristics with parenting practices (i.e., diet- and activity-related restriction, monitoring and stimulation), and to examine the associations between these parenting practices and childrens diet (in terms of energy intake, dietary fiber intake, and added sugar intake) and activity behavior (i.e., physical activity and sedentary time) at age 5, as well as BMI development from age 5 to age 7. Moderation analyses were used to examine whether the associations between the parenting practices and child behavior depended on child characteristics.ResultsSeveral child and parent background characteristics were associated with the parenting practices. Dietary monitoring, stimulation of healthy intake and stimulation of physical activity were associated with desirable energy balance-related behaviors (i.e., dietary intake and/or activity behavior) and desirable BMI development, whereas restriction of sedentary time showed associations with undesirable behaviors and BMI development. Child eating style and weight status, but not child gender or activity style, moderated the associations between parenting practices and behavior. Dietary restriction and monitoring showed weaker, or even undesirable associations for children with a deviant eating style, whereas these practices showed associations with desirable behavior for normal eaters. By contrast, stimulation to eat healthy worked particularly well for children with a deviant eating style or a high BMI.ConclusionAlthough most energy balance-related parenting practices were associated with desirable behaviors, some practices showed associations with undesirable child behavior and weight outcomes. Only parental stimulation showed desirable associations with regard to both diet and activity behavior. The interaction between parenting and child characteristics in the association with behavior calls for parenting that is tailored to the individual child.

Built environmental correlates of walking and cycling in dutch urban children: Results from the SPACE study

This study examined built environmental correlates of children’s walking and cycling behavior. Four hundred and forty-eight children from 10 Dutch neighborhoods completed a seven-day physical activity diary in which the number of walking and cycling trips for transportation, to school, and for recreation were assessed. The associations between observed built environmental characteristics and children’s walking and cycling behavior were examined with multivariate linear regression analyses. The results showed that built environmental correlates of children’s walking and cycling behavior differ by purpose and by commuting mode implying a behavior-specific approach for interventions and for future, preferably prospective, studies.

Evaluation of Neural Networks to Identify Types of Activity Using Accelerometers

PURPOSE To develop and evaluate two artificial neural network (ANN) models based on single-sensor accelerometer data and an ANN model based on the data of two accelerometers for the identification of types of physical activity in adults. METHODS Forty-nine subjects (21 men and 28 women; age range = 22-62 yr) performed a controlled sequence of activities: sitting, standing, using the stairs, and walking and cycling at two self-paced speeds. All subjects wore an ActiGraph accelerometer on the hip and the ankle. In the ANN models, the following accelerometer signal characteristics were used: 10th, 25th, 75th, and 90th percentiles, absolute deviation, coefficient of variability, and lag-one autocorrelation. RESULTS The model based on the hip accelerometer data and the model based on the ankle accelerometer data correctly classified the five activities 80.4% and 77.7% of the time, respectively, whereas the model based on the data from both sensors achieved a percentage of 83.0%. The hip model produced a better classification of the activities cycling, using the stairs, and sitting, whereas the ankle model was better able to correctly classify the activities walking and standing still. All three models often misclassified using the stairs and standing still. The accuracy of the models significantly decreased when a distinction was made between regular versus brisk walking or cycling and between going up and going down the stairs. CONCLUSIONS Relatively simple ANN models perform well in identifying the type but not the speed of the activity of adults from accelerometer data.

Schoolyard physical activity of 6-11 year old children assessed by GPS and accelerometry.

BackgroundChildren’s current physical activity levels are disturbingly low when compared to recommended levels. This may be changed by intervening in the school environment. However, at present, it is unclear to what extent schoolyard physical activity contributes towards reaching the daily physical activity guideline. The aim of this study was to examine how long and at what intensity children are physically active at the schoolyard during different time segments of the day. Moreover, the contribution of schoolyard physical activity towards achieving the recommended guideline for daily physical activity was investigated.MethodsChildren (n=76) between the age of 6–11 years were recruited in six different schools in five cities (>70.000 residents) in the Netherlands. During the weekdays of a regular school week, childrens’ physical activity and location were measured with ActiGraph accelerometers and Travelrecorder GPS receivers. Data was collected from December 2008 to April 2009. From the data, the amount of moderate to vigorous physical activity (MVPA) on and outside the schoolyard was established. Moreover, the percentage of MVPA on the schoolyard was compared between the following segments of the day: pre-school, school, school recess, lunch break and post-school. Differences between boys and girls were compared using linear and logistic mixed-effects models.ResultsOn average, children spent 40.1 minutes/day on the schoolyard. During this time, boys were more active on the schoolyard, with 27.3% of their time spent as MVPA compared to 16.7% among girls (OR=2.11 [95% CI 1.54 - 2.90]). The children were most active on the schoolyard during school recess, during which boys recorded 39.5% and girls recorded 23.4% of the time as MVPA (OR=2.55 [95% CI: 1.69 - 3.85]). Although children were only present at the schoolyard for 6.1% of the total reported time, this time contributed towards 17.5% and 16.8% of boys’ and girls’ minutes of MVPA.ConclusionsOn the schoolyard, children’s physical activity levels are higher than on average over the whole day. Physical activity levels are particularly high during school recess. The school environment seems to be an important setting for improving children’s physical activity levels. Further research on the facilitators of these high activity levels may provide targets for further promotion of physical activity among children.

Correlates of physical activity in 2-year-old toddlers: the generation R study.

OBJECTIVE To describe and identify correlates of objectively measured physical activity and sedentary behavior in 2-year-old toddlers. STUDY DESIGN A total of 347 children participating in a birth cohort study wore a unaxial ActiGraph accelerometer during 1 weekday and 1 weekend day. Information on potential correlates was assessed by parent-reported questionnaires, delivery reports, and regular visits to child health centers. Univariate and multivariable linear regression analyses were conducted to examine the associations between potential correlates and the following physical activity outcomes: percentage of time spent in sedentary behavior, percentage of time spent in moderate-to-vigorous physical activity, and mean counts per minute. RESULTS A high percentage of monitored time was spent in sedentary behavior; 85.6% on weekdays and 84.5% on weekend days. Four correlates were significantly associated with at least 1 physical activity outcome in the multivariable regression models: childs sex, childs age, number of siblings, and season of measurement. The associations of gross motor development with moderate-to-vigorous physical activity and mean counts per minute approached significance. Associations of socioeconomic variables and childs body mass index z-score with physical activity outcomes were not significant. CONCLUSION Two-year-old toddlers spend most of their time in sedentary behavior. No modifiable correlates were identified. Further research on physical activity and associated health benefits among very young children is warranted.

The value of (pre)school playgrounds for children's physical activity level: A systematic review

The (pre)school environment is an important setting to improve children’s health. Especially, the (pre)school playground provides a major opportunity to intervene. This review presents an overview of the existing evidence on the value of both school and preschool playgrounds on children’s health in terms of physical activity, cognitive and social outcomes. In addition, we aimed to identify which playground characteristics are the strongest correlates of beneficial effects and for which subgroups of children effects are most distinct. In total, 13 experimental and 17 observational studies have been summarized of which 10 (77%) and 16 (94%) demonstrated moderate to high methodological quality, respectively. Nearly all experimental studies (n = 11) evaluated intervention effects on time spent in different levels of physical activity during recess. Research on the effects of (pre)school playgrounds on cognitive and social outcomes is scarce (n = 2). The experimental studies generated moderate evidence for an effect of the provision of play equipment, inconclusive evidence for an effect of the use of playground markings, allocating play space and for multi-component interventions, and no evidence for an effect of decreasing playground density, the promotion of physical activity by staff and increasing recess duration on children’s health. In line with this, observational studies showed positive associations between play equipment and children’s physical activity level. In contrast to experimental studies, significant associations were also found between children’s physical activity and a decreased playground density and increased recess duration. To confirm the findings of this review, researchers are advised to conduct more experimental studies with a randomized controlled design and to incorporate the assessment of implementation strategies and process evaluations to reveal which intervention strategies and playground characteristics are most effective.

Outdoor play among children in relation to neighborhood characteristics: a cross-sectional neighborhood observation study

BackgroundAlthough environmental characteristics as perceived by parents are known to be related to children’s outdoor play behavior, less is known about the relation between independently measured neighborhood characteristics and outdoor play among children. The purpose of this study was to identify quantitative as well as qualitative neighborhood characteristics related to outdoor play by means of neighborhood observations.MethodsQuestionnaires including questions on outdoor play behavior of the child were distributed among 3,651 parents of primary school children (aged 4–12 years). Furthermore, neighborhood observations were conducted in 33 Dutch neighborhoods to map neighborhood characteristics such as buildings, formal outdoor play facilities, public space, street pattern, traffic safety, social neighborhood characteristics, and general impression. Data of the questionnaires and the neighborhood observations were coupled via postal code of the respondents. Multilevel GEE analyses were performed to quantify the correlation between outdoor play and independently measured neighborhood characteristics.ResultsParental education was negatively associated with outdoor play among children. Neither the presence nor the overall quality of formal outdoor play facilities were (positively) related to outdoor play among children in this study. Rather, informal play areas such as the presence of sidewalks were related to children’s outdoor play. Also, traffic safety was an important characteristic associated with outdoor play.ConclusionsThis study showed that, apart from individual factors such as parental education level, certain modifiable characteristics in the neighborhood environment (as measured by neighborhood observations) were associated with outdoor play among boys and girls of different age groups in The Netherlands. Local policy makers from different sectors can use these research findings in creating more activity-friendly neighborhoods for children.

Identification of children's activity type with accelerometer-based neural networks

PURPOSE The studys purpose was to identify childrens physical activity type using artificial neural network (ANN) models based on uniaxial or triaxial accelerometer data from the hip or the ankle. METHODS Fifty-eight children (31 boys and 27 girls, age range = 9-12 yr) performed the following activities in a field setting: sitting, standing, walking, running, rope skipping, playing soccer, and cycling. All children wore uniaxial and triaxial ActiGraph accelerometers on both the hip and the ankle. Four ANN models were developed using the following accelerometer signal characteristics: 10th, 25th, 75th, and 90th percentiles; absolute deviation; coefficient of variability; and lag-one autocorrelation. The accuracy of the models was evaluated by leave-one-subject-out cross-validation. RESULTS The models based on hip accelerometer data correctly classified the activities 72% and 77% of the time using uniaxial and triaxial accelerometer data, respectively, whereas the models based on ankle accelerometer data achieved a percentage of 57% and 68%. The hip models were better able to correctly classify the activities walking, rope skipping, and running, whereas the ankle models performed better when classifying sitting. The models based on triaxial accelerometer data produced a better classification of the activities standing, running, rope skipping, playing soccer, and cycling than its uniaxial counterparts. CONCLUSIONS Applying ANN models to processing accelerometer data from children is promising for classifying common physical activities. The highest percentage of correctly classified activities was achieved when using triaxial accelerometer data from the hip.