Physical Education or Playtime: which is more effective at promoting physical activity in primary school children?

Background School physical education (PE) and playtime provide important opportunities for physical activity (PA). However, little research has assessed PA during primary school PE using accelerometry or compared PA during different lesson types. There is also a lack of research comparing PA during PE and playtime, despite suggestions that playtime promotes more PA. The primary aim of this study was to determine which types of PE lesson are most facilitative of PA. The secondary aim was to determine whether children are more active during PE or playtime. Methods Descriptive and fitness data were assessed in 20 children aged 8-9years from a single school. Over eight consecutive weeks PA was assessed during PE lessons, which were classified as either team games or movement activities. At the mid-week of data collection playtime PA was also assessed. PA was assessed using accelerometry and the percentage of time spent in moderate to vigorous PA (MVPA) calculated. Paired t-tests were used to compare MVPA during movement lessons and team games lessons and during PE and playtime. Results Children spent 9.5% of PE lessons in MVPA and engaged in significantly more MVPA during team games (P < 0.001). MVPA was also significantly higher during PE than playtime (P < 0.01). Conclusions Children do not engage in sufficient PA during PE, but are most active during team games lessons; whilst PA during playtime is lower than PE. Interventions to increase PA during both PE and playtime are therefore required. PE interventions should target games lessons as they dominate the curriculum, encourage most PA and present the greatest potential for change. Playtime interventions should encourage participation in active games through the provision of playground equipment and markings.

Effect of school based physical activity programme (KISS) on fitness and adiposity in primary schoolchildren: cluster randomised controlled trial.

To assess the effectiveness of a school based physical activity programme during one school year on physical and psychological health in young schoolchildren. Cluster randomised controlled trial. 28 classes from 15 elementary schools in Switzerland randomly selected and assigned in a 4:3 ratio to an intervention (n=16) or control arm (n=12) after stratification for grade (first and fifth grade), from August 2005 to June 2006. 540 children, of whom 502 consented and presented at baseline. Children in the intervention arm (n=297) received a multi-component physical activity programme that included structuring the three existing physical education lessons each week and adding two additional lessons a week, daily short activity breaks, and physical activity homework. Children (n=205) and parents in the control group were not informed of an intervention group. For most outcome measures, the assessors were blinded. Primary outcome measures included body fat (sum of four skinfolds), aerobic fitness (shuttle run test), physical activity (accelerometry), and quality of life (questionnaires). Secondary outcome measures included body mass index and cardiovascular risk score (average z score of waist circumference, mean blood pressure, blood glucose, inverted high density lipoprotein cholesterol, and triglycerides). 498 children completed the baseline and follow-up assessments (mean age 6.9 (SD 0.3) years for first grade, 11.1 (0.5) years for fifth grade). After adjustment for grade, sex, baseline values, and clustering within classes, children in the intervention arm compared with controls showed more negative changes in the z score of the sum of four skinfolds (-0.12, 95 % confidence interval -0.21 to -0.03; P=0.009). Likewise, their z scores for aerobic fitness increased more favourably (0.17, 0.01 to 0.32; P=0.04), as did those for moderate-vigorous physical activity in school (1.19, 0.78 to 1.60; P<0.001), all day moderate-vigorous physical activity (0.44, 0.05 to 0.82; P=0.03), and total physical activity in school (0.92, 0.35 to 1.50; P=0.003). Z scores for overall daily physical activity (0.21, -0.21 to 0.63) and physical quality of life (0.42, -1.23 to 2.06) as well as psychological quality of life (0.59, -0.85 to 2.03) did not change significantly. A school based multi-component physical activity intervention including compulsory elements improved physical activity and fitness and reduced adiposity in children. Trial registration Current Controlled Trials ISRCTN15360785.

The International Physical Activity Questionnaire-long form overestimates self-reported physical activity of Brazilian adults

Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

Assessment of physical activity by accelerometer and IPAQ-short version in patients with chronic kidney disease undergoing hemodialysis

To compare the short version of International Physical Activity Questionnaire (IPAQ) and the accelerometer measurement of physical activity (PA) in patients undergoing hemodialysis. Sample consisted of 40 patients (19 men) aged 45 ± 16 years. Patients reported their PA using the IPAQ during a face-to-face interview, and wore an Actigraph GT3-X accelerometer for 1 week to obtain minutes per day of light PA, moderate-to-vigorous PA (MVPA) and total PA as well as raw counts per day (vector magnitude). All PA-related variables were significantly correlated among instruments (r = 0.34-0.47) when analyzed as a group. However, when analyzed separately by gender, the relationships were present for women only (r = 0.46-0.62). IPAQ significantly underestimated light PA (IPAQ vs. accelerometer: 180.0 vs. 251.1 min/day, p = 0.019), but no differences were found between methods for MVPA and total PA. Modest correlations were found between self-reported PA time by IPAQ (short version) and accelerometer, but only in women. However, the IPAQ may underestimate light PA, which is the main form of PA in this population.

Adiposity and age explain most of the association between physical activity and fitness in physically active men

[EN] BACKGROUND: To determine if there is an association between physical activity assessed by the short version of the International Physical Activity Questionnaire (IPAQ) and cardiorespiratory and muscular fitness. METHODOLOGY/PRINCIPAL FINDINGS: One hundred and eighty-two young males (age range: 20-55 years) completed the short form of the IPAQ to assess physical activity. Body composition (dual-energy X-Ray absorptiometry), muscular fitness (static and dynamic muscle force and power, vertical jump height, running speed [30 m sprint], anaerobic capacity [300 m running test]) and cardiorespiratory fitness (estimated VO(2)max: 20 m shuttle run test) were also determined in all subjects. Activity-related energy expenditure of moderate and vigorous intensity (EEPA(moderate) and EEPA(vigorous), respectively) was inversely associated with indices of adiposity (r = -0.21 to -0.37, P<0.05). Cardiorespiratory fitness (VO(2)max) was positively associated with LogEEPA(moderate) (r = 0.26, P<0.05) and LogEEPA(vigorous) (r = 0.27). However, no association between VO(2)max with LogEEPA(moderate), LogEPPA(vigorous) and LogEEPA(total) was observed after adjusting for the percentage of body fat. Multiple stepwise regression analysis to predict VO(2)max from LogEEPA(walking), LogEEPA(moderate), LogEEPA(vigorous), LogEEPA(total), age and percentage of body fat (%fat) showed that the %fat alone explained 62% of the variance in VO(2)max and that the age added another 10%, while the other variables did not add predictive value to the model [VO(2)max = 129.6-(25.1x Log %fat) - (34.0x Log age); SEE: 4.3 ml.kg(-1). min(-1); R(2) = 0.72 (P<0.05)]. No positive association between muscular fitness-related variables and physical activity was observed, even after adjusting for body fat or body fat and age. CONCLUSIONS/SIGNIFICANCE: Adiposity and age are the strongest predictors of VO(2)max in healthy men. The energy expended in moderate and vigorous physical activities is inversely associated with adiposity. Muscular fitness does not appear to be associated with physical activity as assessed by the IPAQ.

Domains of physical activity and all-cause mortality: systematic review and dose-response meta-analysis of cohort studies

Background The dose–response relation between physical activity and all-cause mortality is not well defined at present. We conducted a systematic review and meta-analysis to determine the association with all-cause mortality of different domains of physical activity and of defined increases in physical activity and energy expenditure. Methods MEDLINE, Embase and the Cochrane Library were searched up to September 2010 for cohort studies examining all-cause mortality across different domains and levels of physical activity in adult general populations. We estimated combined risk ratios (RRs) associated with defined increments and recommended levels, using random-effects meta-analysis and dose–response meta-regression models. Results Data from 80 studies with 1 338 143 participants (118 121 deaths) were included. Combined RRs comparing highest with lowest activity levels were 0.65 [95% confidence interval (95% CI) 0.60–0.71] for total activity, 0.74 (95% CI 0.70–0.77) for leisure activity, 0.64 (95% CI 0.55–0.75) for activities of daily living and 0.83 (95% CI 0.71–0.97) for occupational activity. RRs per 1-h increment per week were 0.91 (95% CI 0.87–0.94) for vigorous exercise and 0.96 (95% CI 0.93–0.98) for moderate-intensity activities of daily living. RRs corresponding to 150 and 300 min/week of moderate to vigorous activity were 0.86 (95% CI 0.80–0.92) and 0.74 (95% CI 0.65–0.85), respectively. Mortality reductions were more pronounced in women. Conclusion Higher levels of total and domain-specific physical activity were associated with reduced all-cause mortality. Risk reduction per unit of time increase was largest for vigorous exercise. Moderate-intensity activities of daily living were to a lesser extent beneficial in reducing mortality.

Physical activity intensity and surrogate markers for cardiovascular health in adolescents

We examined the impact of physical activity (PA) on surrogate markers of cardiovascular health in adolescents. 52 healthy students (28 females, mean age 14.5 ± 0.7 years) were investigated. Microvascular endothelial function was assessed by peripheral arterial tonometry to determine reactive hyperemic index (RHI). Vagal activity was measured using 24 h analysis of heart rate variability [root mean square of successive normal-to-normal intervals (rMSSD)]. Exercise testing was performed to determine peak oxygen uptake ([Formula: see text]) and maximum power output. PA was assessed by accelerometry. Linear regression models were performed and adjusted for age, sex, skinfolds, and pubertal status. The cohort was dichotomized into two equally sized activity groups (low vs. high) based on the daily time spent in moderate-to-vigorous PA (MVPA, 3,000-5,200 counts(.)min(-1), model 1) and vigorous PA (VPA, >5,200 counts(.)min(-1), model 2). MVPA was an independent predictor for rMSSD (β = 0.448, P = 0.010), and VPA was associated with maximum power output (β = 0.248, P = 0.016). In model 1, the high MVPA group exhibited a higher vagal tone (rMSSD 49.2 ± 13.6 vs. 38.1 ± 11.7 ms, P = 0.006) and a lower systolic blood pressure (107.3 ± 9.9 vs. 112.9 ± 8.1 mmHg, P = 0.046). In model 2, the high VPA group had higher maximum power output values (3.9 ± 0.5 vs. 3.4 ± 0.5 W kg(-1), P = 0.012). In both models, no significant differences were observed for RHI and [Formula: see text]. In conclusion, in healthy adolescents, PA was associated with beneficial intensity-dependent effects on vagal tone, systolic blood pressure, and exercise capacity, but not on microvascular endothelial function.

Community referral for promoting physical activity among primary care patients

Introduction. There is a need for physical activity interventions based in primary care clinics that take advantage of community resources. The purpose of this randomized controlled trial was to compare the effects of two physical activity interventions: (1) physical activity prescription by a primary care provider plus referral to community physical activity resources and (2) physical activity prescription only. ^ Methods. Sedentary adult patients recruited from a general medicine clinic were randomized to receive a physical activity prescription, delivered by the primary care provider, plus referral to community physical activity resources (n=38) or physical activity prescription only (n=32). Outcomes were use of community resources (exercise facility and personal trainers), physical activity levels (self-report questionnaire and pedometer), and attitudes regarding physical activity assessed at 8 weeks. ^ Results. Three of 38 (7.9%) subjects referred to the community resources and none of the 32 subjects in the prescription only group used the community resources during the 8 week trial. Sixteen of 32 subjects in the prescription plus referral group and 19 of 38 in the prescription group completed the self-report follow-up forms at 8 weeks. For minutes of moderate- or vigorous-intensity physical activity per week, there were no between-group differences at baseline, follow-up, or change from baseline to follow-up. However, for moderate- and vigorous-intensity physical activity, there were significant improvements from baseline to follow-up within each group. For attitudes related to physical activity, there were no between-group differences at baseline, follow-up, or change from baseline to follow-up; neither were there any within-group changes. ^ Discussion. Physical activity prescription delivered by a healthcare provider in the context of a routine primary care visit can improve physical activity levels, with no additional improvement gained by referring to community resources. The intervention was feasible for primary care providers to deliver, but only 50% of subjects returned the self-report physical activity questionnaire at the 8 week assessment. ^

Has the development of a New Urbanist community affected the physical activity levels of residents in surrounding neighborhoods?

Study Aims. The neighborhood environment has been shown to influence physical activity levels, but little is known about how far-reaching these effects are. This study sought to determine whether or not the development of a New Urbanist community in Austin, Texas affected the physical activity levels of residents in surrounding neighborhoods. The results were stratified by demographic characteristics, residential distance from the New Urbanist community, and type of physical activity to determine if any observed changes varied by these factors.^ Methods. Self-report questionnaires were mailed to a random sample of households located within one mile of the New Urbanist development. The questionnaire included questions about physical activity behaviors before and after the community was constructed in 2006. Changes in reported levels of physical activity between the two time points were examined.^ Results. The prevalence and average minutes per week of total physical activity did not change. Significant increases in the frequency and quantity of moderate-intensity leisure-time physical activity were observed. The amount of time spent walking and biking for recreation outside of the neighborhood increased significantly among those living close to Mueller. The weekly time spent in vigorous-intensity activity increased significantly, especially among those living closer to Mueller. There were significant decreases in the prevalence of and time spent walking for transport. The use of Mueller parks and trails was highest among participants living close to Mueller.^ Conclusions. The nearby Mueller development does not appear to have encouraged sedentary members of the surrounding population to become physically active, but might be associated with increased weekly physical activity among those who were already active. The increase in vigorous-intensity physical activity and recreational walking/biking outside of the neighborhood among those subjects living closer to Mueller may be attributed to the use of Mueller parks and trails, which was also considerably higher among this group. People may be substituting the time they spent walking for transport before the Mueller development with moderate-intensity leisure-time physical activity. Future research should seek to identify barriers that may be preventing more nearby residents from using Mueller facilities for physical activity. ^

Automatic physical activity pattern recognition and meal intake modelling in type 1 diabetes for their inclusion in artificial pancreas systems

La diabetes comprende un conjunto de enfermedades metabólicas que se caracterizan por concentraciones de glucosa en sangre anormalmente altas. En el caso de la diabetes tipo 1 (T1D, por sus siglas en inglés), esta situación es debida a una ausencia total de secreción endógena de insulina, lo que impide a la mayoría de tejidos usar la glucosa. En tales circunstancias, se hace necesario el suministro exógeno de insulina para preservar la vida del paciente; no obstante, siempre con la precaución de evitar caídas agudas de la glucemia por debajo de los niveles recomendados de seguridad. Además de la administración de insulina, las ingestas y la actividad física son factores fundamentales que influyen en la homeostasis de la glucosa. En consecuencia, una gestión apropiada de la T1D debería incorporar estos dos fenómenos fisiológicos, en base a una identificación y un modelado apropiado de los mismos y de sus sorrespondientes efectos en el balance glucosa-insulina. En particular, los sistemas de páncreas artificial –ideados para llevar a cabo un control automático de los niveles de glucemia del paciente– podrían beneficiarse de la integración de esta clase de información. La primera parte de esta tesis doctoral cubre la caracterización del efecto agudo de la actividad física en los perfiles de glucosa. Con este objetivo se ha llevado a cabo una revisión sistemática de la literatura y meta-análisis que determinen las respuestas ante varias modalidades de ejercicio para pacientes con T1D, abordando esta caracterización mediante unas magnitudes que cuantifican las tasas de cambio en la glucemia a lo largo del tiempo. Por otro lado, una identificación fiable de los periodos con actividad física es un requisito imprescindible para poder proveer de esa información a los sistemas de páncreas artificial en condiciones libres y ambulatorias. Por esta razón, la segunda parte de esta tesis está enfocada a la propuesta y evaluación de un sistema automático diseñado para reconocer periodos de actividad física, clasificando su nivel de intensidad (ligera, moderada o vigorosa); así como, en el caso de periodos vigorosos, identificando también la modalidad de ejercicio (aeróbica, mixta o de fuerza). En este sentido, ambos aspectos tienen una influencia específica en el mecanismo metabólico que suministra la energía para llevar a cabo el ejercicio y, por tanto, en las respuestas glucémicas en T1D. En este trabajo se aplican varias combinaciones de técnicas de aprendizaje máquina y reconocimiento de patrones sobre la fusión multimodal de señales de acelerometría y ritmo cardíaco, las cuales describen tanto aspectos mecánicos del movimiento como la respuesta fisiológica del sistema cardiovascular ante el ejercicio. Después del reconocimiento de patrones se incorpora también un módulo de filtrado temporal para sacar partido a la considerable coherencia temporal presente en los datos, una redundancia que se origina en el hecho de que en la práctica, las tendencias en cuanto a actividad física suelen mantenerse estables a lo largo de cierto tiempo, sin fluctuaciones rápidas y repetitivas. El tercer bloque de esta tesis doctoral aborda el tema de las ingestas en el ámbito de la T1D. En concreto, se propone una serie de modelos compartimentales y se evalúan éstos en función de su capacidad para describir matemáticamente el efecto remoto de las concetraciones plasmáticas de insulina exógena sobre las tasas de eleiminación de la glucosa atribuible a la ingesta; un aspecto hasta ahora no incorporado en los principales modelos de paciente para T1D existentes en la literatura. Los datos aquí utilizados se obtuvieron gracias a un experimento realizado por el Institute of Metabolic Science (Universidad de Cambridge, Reino Unido) con 16 pacientes jóvenes. En el experimento, de tipo ‘clamp’ con objetivo variable, se replicaron los perfiles individuales de glucosa, según lo observado durante una visita preliminar tras la ingesta de una cena con o bien alta carga glucémica, o bien baja. Los seis modelos mecanísticos evaluados constaban de: a) submodelos de doble compartimento para las masas de trazadores de glucosa, b) un submodelo de único compartimento para reflejar el efecto remoto de la insulina, c) dos tipos de activación de este mismo efecto remoto (bien lineal, bien con un punto de corte), y d) diversas condiciones iniciales. ABSTRACT Diabetes encompasses a series of metabolic diseases characterized by abnormally high blood glucose concentrations. In the case of type 1 diabetes (T1D), this situation is caused by a total absence of endogenous insulin secretion, which impedes the use of glucose by most tissues. In these circumstances, exogenous insulin supplies are necessary to maintain patient’s life; although caution is always needed to avoid acute decays in glycaemia below safe levels. In addition to insulin administrations, meal intakes and physical activity are fundamental factors influencing glucose homoeostasis. Consequently, a successful management of T1D should incorporate these two physiological phenomena, based on an appropriate identification and modelling of these events and their corresponding effect on the glucose-insulin balance. In particular, artificial pancreas systems –designed to perform an automated control of patient’s glycaemia levels– may benefit from the integration of this type of information. The first part of this PhD thesis covers the characterization of the acute effect of physical activity on glucose profiles. With this aim, a systematic review of literature and metaanalyses are conduced to determine responses to various exercise modalities in patients with T1D, assessed via rates-of-change magnitudes to quantify temporal variations in glycaemia. On the other hand, a reliable identification of physical activity periods is an essential prerequisite to feed artificial pancreas systems with information concerning exercise in ambulatory, free-living conditions. For this reason, the second part of this thesis focuses on the proposal and evaluation of an automatic system devised to recognize physical activity, classifying its intensity level (light, moderate or vigorous) and for vigorous periods, identifying also its exercise modality (aerobic, mixed or resistance); since both aspects have a distinctive influence on the predominant metabolic pathway involved in fuelling exercise, and therefore, in the glycaemic responses in T1D. Various combinations of machine learning and pattern recognition techniques are applied on the fusion of multi-modal signal sources, namely: accelerometry and heart rate measurements, which describe both mechanical aspects of movement and the physiological response of the cardiovascular system to exercise. An additional temporal filtering module is incorporated after recognition in order to exploit the considerable temporal coherence (i.e. redundancy) present in data, which stems from the fact that in practice, physical activity trends are often maintained stable along time, instead of fluctuating rapid and repeatedly. The third block of this PhD thesis addresses meal intakes in the context of T1D. In particular, a number of compartmental models are proposed and compared in terms of their ability to describe mathematically the remote effect of exogenous plasma insulin concentrations on the disposal rates of meal-attributable glucose, an aspect which had not yet been incorporated to the prevailing T1D patient models in literature. Data were acquired in an experiment conduced at the Institute of Metabolic Science (University of Cambridge, UK) on 16 young patients. A variable-target glucose clamp replicated their individual glucose profiles, observed during a preliminary visit after ingesting either a high glycaemic-load or a low glycaemic-load evening meal. The six mechanistic models under evaluation here comprised: a) two-compartmental submodels for glucose tracer masses, b) a single-compartmental submodel for insulin’s remote effect, c) two types of activations for this remote effect (either linear or with a ‘cut-off’ point), and d) diverse forms of initial conditions.

Assessment bias : physical activity questionnaire assessment inadvertently influences patients’ desire to be ‘more physically active’

Evaluating physical activity is important for public health population research and evaluating lifestyle interventions among targeted groups. Self-reported questionnaires are frequently used to evaluate physical activity in a variety of contexts where resource or pragmatic limitations prohibit the use of more sophisticated approaches. However, prior research in the use of other patient reported outcomes in healthcare settings has highlighted that simply completing a questionnaire may change a patients’ behaviour or responses to subsequent questions. This methodology study aimed to examine whether completing a standard physical activity questionnaire altered patients responses to two related questions a) whether they are ‘sufficiently physically active’ and b) whether they desire ‘to be more physically active.’

Averting uncertainty : a practical guide to physical activity research in Australian schools

Preventative health has become central to contemporary health care, identifying youth physical activity as a key factor in determining health and functioning. Schools offer a unique research setting due to distinctive methodological circumstances. However, school-based researchers face several obstacles in their endeavour to complete successful research investigations; often confronted with complex research designs and methodological procedures that are not easily amenable to school contexts. The purpose of this paper is to provide a practical guide for teachers (both teacher educators and teaching practitioners) seeking to conduct physical activity-based research in Australian school settings, as well as discuss research practices. The research enabling process has been divided into six phases: preparation; design; outcome measures; procedures; participants; and feedback. Careful planning and consideration must be undertaken prior to the commencement of, and during the research process, due to the complex nature of school settings and research processes that exist in the Australian context.

Promoting physical activity to older adults : a preliminary evaluation of three general practice-based strategies

The aim of this study was to explore the feasibility of an exercise scientist (ES) working in general practice to promote physical activity (PA) to 55 to 70 year old adults. Participants were randomised into one of three groups: either brief verbal and written advice from a general practitioner (GP) (G1, N=9); or individualised counselling and follow-up telephone calls from an ES, either with (G3, N=8) or without a pedometer (G2, N=11). PA levels were assessed at week 1, after the 12-wk intervention and again at 24 weeks. After the 12-wk intervention, the average increase in PA was 116 (SD=237) min/wk; N=28, p < 0.001. Although there were no statistically significant between-group differences, the average increases in PA among G2 and G3 participants were 195 (SD=207) and 138 (SD=315) min/wk respectively, compared with no change (0.36, SD=157) in G1. After 24 weeks, average PA levels remained 56 (SD=129) min/wk higher than in week 1. The small numbers of participants in this feasibility study limit the power to detect significant differences between groups, but it would appear that individualised counselling and follow-up contact from an ES, with or without a pedometer, can result in substantial changes in PA levels. A larger study is now planned to confirm these findings.

Comparison of three generations of ActiGraph (TM) activity monitors in children and adolescents

In this study, we evaluated agreement among three generations of ActiGraph (TM) accelerometers in children and adolescents. Twenty-nine participants (mean age = 14.2 +/- 3.0 years) completed two laboratory-based activity sessions, each lasting 60 min. During each session, participants concurrently wore three different models of the ActiGraph (TM) accelerometers (GT1M, GT3X, GT3X+). Agreement among the three models for vertical axis counts, vector magnitude counts, and time spent in moderate-to-vigorous physical exercise (MVPA) was evaluated by calculating intraclass correlation coefficients and Bland-Altman plots. The intraclass correlation coefficient for total vertical axis counts, total vector magnitude counts, and estimated MVPA was 0.994 (95% CI = 0.989-0.996), 0.981 (95% CI = 0.969-0.989), and 0.996 (95% CI = 0.989-0.998), respectively. Inter-monitor differences for total vertical axis and vector magnitude counts ranged from 0.3% to 1.5%, while inter-monitor differences for estimated MVPA were equal to or close to zero. On the basis of these findings, we conclude that there is strong agreement between the GT1M, GT3X, and GT3X+ activity monitors, thus making it acceptable for researchers and practitioners to use different ActiGraph (TM) models within a given study.

Effects of physical activity intervention in youth : a review

Effects of physical activity interventions in youth: A review. International SportMed Journal. Vol.2 No.5 2001. The purpose of this paper is to review the peer-reviewed literature pertinent to physical activity interventions for children and adolescents. In order to provide a more quantitative conclusion regarding the effectiveness of these interventions, a meta-analytic approach was utilized in which effect sizes (the efficacy of each intervention or magnitude of the intervention effect was expressed as a standardized effect size, which represents the influence of the treatment or intervention on the dependent variable) from each study are pooled to provide a global estimate of effectiveness. A search of the relevant peer-reviewed literature was conducted using several computer-based databases, including MEDLINE, PYSCHLIT, SOCIAL SCIENCE INDEX, and SPORTS DISCUS. Manual searches were also made using the reference lists from recovered articles. Applying strict criteria for quality of design and assessment of physical activity, 10 studies were located, yielding a total of 44 effect sizes. The mean effect size was 0.47 (95% C.I. 0.28 – 0.66) suggesting that interventions have produced moderate increases in physical activity behavior. Effect sizes ranged from –0.61 to 2.5. Interventions focusing on increasing the amount of physical activity performed during regular physical education were more effective than those targeting overall levels of physical activity. Interventions were almost entirely school-based. Accordingly, the development and evaluation of community-based approaches for promoting physical activity among young people, especially older adolescents, remains an urgent priority for future research.