Effect of a general school-based physical activity intervention on bone mineral content and density: A cluster-randomized controlled trial.

Background: Specific physical loading leads to enhanced bone development during childhood. A general physical activity program mimicking a real-life situation was successful at increasing general physical health in children. Yet, it is not clear whether it can equally increase bone mineral mass. We performed a cluster-randomized controlled trial in children of both gender and different pubertal stages to determine whether a school-based physical activity (PA) program during one school-year influences bone mineral content (BMC) and density (BMD), irrespective of gender.Methods: Twenty-eight 1st and 5th grade (6-7 and 11-12 year-old) classes were cluster randomized to an intervention (INT, 16 classes, n = 297) and control (CON; 12 classes, n = 205) group. The intervention consisted of a multi-component PA intervention including daily physical education with at least 10 min of jumping or strength training exercises of various intensities. Measurements included anthropometry, and BMC and BMD of total body, femoral neck, total hip and lumbar spine using dual-energy X-ray absorptiometry (DXA). PA was assessed by accelerometers and Tanner stages by questionnaires. Analyses were performed by a regression model adjusted for gender, baseline height and weight, baseline PA, post-intervention pubertal stage, baseline BMC, and cluster.Results: 275 (72%) of 380 children who initially agreed to have DXA measurements had also post-intervention DXA and PA data. Mean age of prepubertal and pubertal children at baseline was 8.7 +/- 2.1 and 11.1 +/- 0.6 years, respectively. Compared to CON, children in INT showed statistically significant increases in BMC of total body, femoral neck, and lumbar spine by 5.5%, 5.4% and 4.7% (all p < 0.05), respectively, and BMD of total body and lumbar spine by 8.4% and 7.3% (both p < 0.01), respectively. There was no gender*group, but a pubertal stage*group interaction consistently favoring prepubertal children.Conclusion: A general school-based PA intervention can increase bone health in elementary school children of both genders, particularly before puberty. (C) 2010 Elsevier Inc. All rights reserved.

BMI group-related differences in physical fitness and physical activity in preschool-age children: a cross-sectional analysis.

In the Ballabeina study, we investigated age- and BMI-group-related differences in aerobic fitness (20 m shuttle run), agility (obstacle course), dynamic (balance beam) and static balance (balance platform), and physical activity (PA, accelerometers) in 613 children (M age = 5.1 years, SD = 0.6). Normal weight (NW) children performed better than overweight (OW) children in aerobic fitness, agility, and dynamic balance (all p <.001), while OWchildren had a better static balance (p < .001). BMI-group-related differences in aerobic fitness and agility were larger in older children (p for interaction with age = .01) in favor of the NW children. PA did not differ between NW and OW (p > or = .1), but did differ between NW and obese children (p < .05). BMI-group-related differences in physical fitness can already be present in preschool-age children.

Physical activity, bodyweight, health and fear of negative evaluation in primary school children.

Fear of negative evaluation (FNE) is regarded as being the core feature of social anxiety. The present study examined how FNE is associated with physical activity (PA), body mass index (BMI) and perceived physical health (PPH) in children. Data were collected in a sample of 502 primary school children in first and fifth grades taking part in a randomized-controlled trial ("Kinder-Sportstudie KISS") aimed at increasing PA and health. PA was assessed by accelerometry over 7 days, PPH by the Child Health Questionnaire and FNE by the Social Anxiety Scale for Children--Revised. BMI z-scores were calculated based on Swiss norms. Cross-sectional analyses indicated that children high in FNE exercised less, reported lower levels of PPH and had higher BMI z-scores (P&lt;0.01). Using mixed linear models, the school-based PA intervention did not manage to reduce FNE scores. Overweight children demonstrated a greater increase in FNE (P&lt;0.05) indicating that enhanced weight may be a risk factor for FNE. In conclusion, the associations among high FNE, low PA and increased BMI should be considered when promoting an active lifestyle in children.

Assessment of Physical Activity and Energy Expenditure by GPS Combined With Accelerometry in Real-Life Conditions.

Background: Physical activity (PA) and related energy expenditure (EE) is often assessed by means of a single technique. Because of inherent limitations, single techniques may not allow for an accurate assessment both PA and related EE. The aim of this study was to develop a model to accurately assess common PA types and durations and thus EE in free-living conditions, combining data from global positioning system (GPS) and 2 accelerometers. Methods: Forty-one volunteers participated in the study. First, a model was developed and adjusted to measured EE with a first group of subjects (Protocol I, n = 12) who performed 6 structured and supervised PA. Then, the model was validated over 2 experimental phases with 2 groups (n = 12 and n = 17) performing scheduled (Protocol I) and spontaneous common activities in real-life condition (Protocol II). Predicted EE was compared with actual EE as measured by portable indirect calorimetry. Results: In protocol I, performed PA types could be recognized with little error. The duration of each PA type could be predicted with an accuracy below 1 minute. Measured and predicted EE were strongly associated (r = .97, P < .001). Conclusion: Combining GPS and 2 accelerometers allows for an accurate assessment of PA and EE in free-living situations.

Don't stop, don't stop: physical activity and adolescence.

The aim was to assess whether physical activity decreases during adolescence, whether this decrease depends on the gender, whether physical activity is related to personal, family, and school factors, and whether it is associated to healthy behaviors in a sample of adolescents. Data were drawn from a survey carried out in 2001 among in-school Catalan adolescents aged 14-19 years. Subjects were divided in two groups: physical activity (N=4,185, 43.5% females) and no-physical activity (N=2,743; 68.9% females). Personal, family, school and lifestyles' variables were compared. Chi-square and Odds Ratio were used to compare qualitative variables and Student's t to compare quantitative variables. For the multivariate analysis, all statistically significant variables in the univariate analysis in each of the four groups of variables (plus age) were introduced in a non-conditioned multiple regression. Analysis was performed separately by gender. Physical activity was significantly more frequent among males and decreased with age. Globally, physically active youth perceived themselves as healthier and happier with their body image, they showed a better relationship with their parents, were better connected to school, and exhibited healthier lifestyles. As physical activity has important benefits on health, health professionals dealing with adolescents should encourage adolescents to keep practicing. This message must be specially directed to females.

Validity of four short physical activity questionnaires in middle-aged persons.

PURPOSE: Self-administered questionnaires continue to be the most widely used type of physical activity assessment in epidemiological studies. However, test-retest reliability and validity of physical activity questionnaires have to be determined. In this study, three short physical activity questionnaires already used in Switzerland and the International Physical Activity Questionnaire (IPAQ) were validated. METHODS: Test-retest reliability was assessed by repeated administration of all questionnaires within 3 wk in 178 volunteers (77 women, 46.1+/-14.8 yr; 101 men 46.8+/-13.2 yr). Validity of categorical and continuous data was studied in a subsample of 35 persons in relation to 7-d accelerometer readings, percent body fat, and cardiorespiratory fitness. RESULTS: Reliability was fair to good with a Spearman correlation coefficient range of 0.43-0.68 for measures of continuous data and moderate to fair with Kappa values between 0.32 and 0.46 for dichotomous measures active/inactive. Total physical activity reported in the IPAQ and the Office in Motion Questionnaire (OIMQ) correlated with accelerometry readings (r=0.39 and 0.44, respectively). In contrast, correlations of self-reported physical data with percent body fat and cardiorespiratory fitness were low (r=-0.26-0.29). Participants categorized as active by the Swiss HEPA Survey 1999 instrument (HEPA99) accumulated significantly more days of the recommended physical activities than their inactive counterparts (4.4 and 2.7 d.wk, respectively, P<0.05). However, compared with accelerometer data, vigorous physical activities were overreported in investigated questionnaires. CONCLUSION: Collecting valid data on physical activity remains a challenging issue for questionnaire surveys. The IPAQ and the three other questionnaires are characterized to inform decisions about their appropriate use.

A model for physical activity, bahaviour and energy expenditure assessment in real-life condition

RésuméL'origine de l'obésité, qui atteint des proportions épidémiques, est complexe. Elle est liée au mode de vie et au comportement des individus par rapport à l'activité physique, expression des choix individuels et de l'interaction avec l'environnement. Les mesures du comportement au niveau de l'activité physique des individus face à leur environnement, la répartition des types d'activité physique, la durée, la fréquence, l'intensité, et la dépense énergétique sont d'une grande importance. Aujourd'hui, il y a un manque de méthodes permettant une évaluation précise et objective de l'activité physique et du comportement des individus. Afin de compléter les recherches relatives à l'activité physique, à l'obésité et à certaines maladies, le premier objectif du travail de thèse était de développer un modèle pour l'identification objective des types d'activité physique dans des conditions de vie réelles et l'estimation de la dépense énergétique basée sur une combinaison de 2 accéléromètres et 1 GPS. Le modèle prend en compte qu'une activité donnée peut être accomplie de différentes façons dans la vie réelle. Les activités quotidiennes ont pu être classées en 8 catégories, de sédentaires à actives, avec une précision de 1 min. La dépense énergétique a pu peut être prédite avec précision par le modèle. Après validation du modèle, le comportement des individus de l'activité physique a été évalué dans une seconde étude. Nous avons émis l'hypothèse que, dans un environnement caractérisé par les pentes, les personnes obèses sont tentées d'éviter les pentes raides et de diminuer la vitesse de marche au cours d'une activité physique spontanée, ainsi que pendant les exercices prescrits et structurés. Nous avons donc caractérisé, par moyen du modèle développé, le comportement des individus obèses dans un environnement vallonné urbain. La façon dont on aborde un environnement valloné dans les déplacements quotidiens devrait également être considérée lors de la prescription de marche supplémentaire afin d'augmenter l'activité physique.SummaryOrigin of obesity, that reached epidemic proportion, is complex and may be linked to different lifestyle and physical activity behaviour. Measurement of physical activity behaviour of individuals towards their environment, the distribution of physical activity in terms of physical activity type, volume, duration, frequency, intensity, and energy expenditure is of great importance. Nowadays, there is a lack of methods for accurate and objective assessment of physical activity and of individuals' physical activity behaviour. In order to complement the research relating physical activity to obesity and related diseases, the first aim of the thesis work was to develop a model for objective identification of physical activity types in real-life condition and energy expenditure based on a combination of 2 accelerometers and 1 GPS device. The model takes into account that a given activity can be achieved in many different ways in real life condition. Daily activities could be classified in 8 categories, as sedentary to active physical activity, within 1 min accuracy, and physical activity patterns determined. The energy expenditure could be predicted accurately with an accuracy below 10%. Furthermore, individuals' physical activity behaviour is expression of individual choices and their interaction with the neighbourhood environment. In a second study, we hypothesized that, in an environment characterized by inclines, obese individuals are tempted to avoid steep positive slopes and to decrease walking speed during spontaneous outdoor physical activity, as well as during prescribed structured bouts of exercise. Finally, we characterized, by mean of the developed model, the physical activity behaviour of obese individuals in a hilly urban environment. Quantifying how one tackles hilly environment or avoids slope in their everyday displacements should be also considered while prescribing extra walking in free-living conditions in order to increase physical activity.

Change in physical activity after smoking cessation: the Coronary Artery Risk Development in Young Adults (CARDIA) study.

AIMS: To estimate physical activity trajectories for people who quit smoking, and compare them to what would have been expected had smoking continued. DESIGN, SETTING AND PARTICIPANTS: A total of 5115 participants in the Coronary Artery Risk Development in Young Adults Study (CARDIA) study, a population-based study of African American and European American people recruited at age 18-30 years in 1985/6 and followed over 25 years. MEASUREMENTS: Physical activity was self-reported during clinical examinations at baseline (1985/6) and at years 2, 5, 7, 10, 15, 20 and 25 (2010/11); smoking status was reported each year (at examinations or by telephone, and imputed where missing). We used mixed linear models to estimate trajectories of physical activity under varying smoking conditions, with adjustment for participant characteristics and secular trends. FINDINGS: We found significant interactions by race/sex (P = 0.02 for the interaction with cumulative years of smoking), hence we investigated the subgroups separately. Increasing years of smoking were associated with a decline in physical activity in black and white women and black men [e.g. coefficient for 10 years of smoking: -0.14; 95% confidence interval (CI) = -0.20 to -0.07, P < 0.001 for white women]. An increase in physical activity was associated with years since smoking cessation in white men (coefficient 0.06; 95% CI = 0 to 0.13, P = 0.05). The physical activity trajectory for people who quit diverged progressively towards higher physical activity from the expected trajectory had smoking continued. For example, physical activity was 34% higher (95% CI = 18 to 52%; P < 0.001) for white women 10 years after stopping compared with continuing smoking for those 10 years (P = 0.21 for race/sex differences). CONCLUSIONS: Smokers who quit have progressively higher levels of physical activity in the years after quitting compared with continuing smokers.