Physical activity, energy balance and obesity

Obesity appears when energy intake exceeds energy expenditure. The most important variable compound of energy expenditure is physical activity. The global epidemics of obesity seem closely related to reduced physical activity and sedentariness widely increasing nowadays. Once obesity has developed, caloric intake becomes similar to energy expenditure. To lose weight, besides decreasing energy intake, energy expenditure must be increased. The promotion of physical activity is difficult and so the results of treatment of obesity are discouraging for doctors, other health professionals and patients. Proactive efforts from patients and health providers with an intensive feedback between them may be extremely helpful. Nevertheless, more studies are needed to provide better approaches on the role of physical activity for the prevention and treatment of obesity and for long-term weight-loss maintenance.

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.

Eleven-year physical activity trends in a Swiss urban area.

OBJECTIVE: Regular physical activity is a major health determinant. Little is known about physical activity trends. We evaluated whether adult physical activity levels are changing in a Swiss urban state (Geneva). METHOD: We analyzed 11-year trends of physical activity indicators, including 3+MET-minutes per week and physical activity outside working hours, in population representative adults (n=9320, aged 35-74years, 50% women), relating declared physical activity to socioeconomic status, lifestyle, and clinical and blood markers. RESULTS: Combining yearly cohorts from 1999 to 2009, we found a significant trend for increased physical activity levels. Weekly age and sex adjusted 3+MET-minutes per week increased from 3023 to 3752, between 1999 and 2009 (P=0.02). The increase also concerned physical activity outside working hours (+18kcal/day/year). There was a shift from low levels of physical activity levels towards higher activities. Physical activity indicators were associated with socioeconomic status, comorbidities, and biological and anthropometric measures. The trend for increased physical activity was more prominent over the latter 5years. CONCLUSION: We found that physical activity levels have increased in an urban Swiss state. The increase is significant but small, and further efforts to promote physical activity are therefore warranted.

Assessment of physical activity with a pedometer and its relationship with VO2max among adolescents in Switzerland.

OBJECTIVES: In the absence of a gold standard, the assessment of physical activity in children remains difficult. To record physical activity with a pedometer and to examine to what extent it is correlated with VO2max. METHODS: Survey on physical activity and fitness; 233 Swiss adolescents aged 11 to 15 carried a pedometer (Pedoboy) during seven consecutive days. VO2max was estimated through an endurance shuttle run test. RESULTS: The physical activity recorded by the pedometer did not vary from one day to the other (p > 0.05). The physical activity was higher among boys than among girls (p < 0.001) and higher among younger adolescents (6th versus 8th grade; p < 0.001). The correlation between physical activity and estimated VO2max was 0.30 (p < 0.01). CONCLUSIONS: The use of a pedometer to assess physical activity over one entire week is feasible among adolescents. The record provided by the pedometer gives an objective measure of the usual physical activity and, as such, is relatively well correlated with aerobic capacity.

Unraveling dynamics of human physical activity patterns in chronic pain conditions.

Chronic pain is a complex disabling experience that negatively affects the cognitive, affective and physical functions as well as behavior. Although the interaction between chronic pain and physical functioning is a well-accepted paradigm in clinical research, the understanding of how pain affects individuals' daily life behavior remains a challenging task. Here we develop a methodological framework allowing to objectively document disruptive pain related interferences on real-life physical activity. The results reveal that meaningful information is contained in the temporal dynamics of activity patterns and an analytical model based on the theory of bivariate point processes can be used to describe physical activity behavior. The model parameters capture the dynamic interdependence between periods and events and determine a 'signature' of activity pattern. The study is likely to contribute to the clinical understanding of complex pain/disease-related behaviors and establish a unified mathematical framework to quantify the complex dynamics of various human activities.

Nonlinear analysis of human physical activity patterns in health and disease.

The reliable and objective assessment of chronic disease state has been and still is a very significant challenge in clinical medicine. An essential feature of human behavior related to the health status, the functional capacity, and the quality of life is the physical activity during daily life. A common way to assess physical activity is to measure the quantity of body movement. Since human activity is controlled by various factors both extrinsic and intrinsic to the body, quantitative parameters only provide a partial assessment and do not allow for a clear distinction between normal and abnormal activity. In this paper, we propose a methodology for the analysis of human activity pattern based on the definition of different physical activity time series with the appropriate analysis methods. The temporal pattern of postures, movements, and transitions between postures was quantified using fractal analysis and symbolic dynamics statistics. The derived nonlinear metrics were able to discriminate patterns of daily activity generated from healthy and chronic pain states.

The Effect of a Physical Activity Program on the Total Number of Primary Care Visits in Inactive Patients: A 15-Month Randomized Controlled Trial

Abstract Background: Effective promotion of exercise could result in substantial savings in healthcare cost expenses in terms of direct medical costs, such as the number of medical appointments. However, this is hampered by our limited knowledge of how to achieve sustained increases in physical activity. Objectives: To assess the effectiveness of a Primary Health Care (PHC) based physical activity program in reducing the total number of visits to the healthcare center among inactive patients, over a 15-month period. Research Design: Randomized controlled trial. Subjects: Three hundred and sixty-two (n = 362) inactive patients suffering from at least one chronic condition were included. One hundred and eighty-three patients (n = 183; mean (SD); 68.3 (8.8) years; 118 women) were randomly allocated to the physical activity program (IG). One hundred and seventy-nine patients (n = 179; 67.2 (9.1) years; 106 women) were allocated to the control group (CG). The IG went through a three-month standardized physical activity program led by physical activity specialists and linked to community resources. Measures: The total number of medical appointments to the PHC, during twelve months before and after the program, was registered. Self-reported health status (SF-12 version 2) was assessed at baseline (month 0), at the end of the intervention (month 3), and at 12 months follow-up after the end of the intervention (month 15). Results: The IG had a significantly reduced number of visits during the 12 months after the intervention: 14.8 (8.5). The CG remained about the same: 18.2 (11.1) (P = .002). Conclusions: Our findings indicate that a 3-month physical activity program linked to community resources is a shortduration, effective and sustainable intervention in inactive patients to decrease rates of PHC visits. Trial Registration: ClinicalTrials.gov NCT00714831

A comparison of indices of glucose metabolism in five black populations: data from modeling the epidemiologic transition study (METS).

BACKGROUND: Globally, Africans and African Americans experience a disproportionate burden of type 2 diabetes, compared to other race and ethnic groups. The aim of the study was to examine the association of plasma glucose with indices of glucose metabolism in young adults of African origin from 5 different countries. METHODS: We identified participants from the Modeling the Epidemiologic Transition Study, an international study of weight change and cardiovascular disease (CVD) risk in five populations of African origin: USA (US), Jamaica, Ghana, South Africa, and Seychelles. For the current study, we included 667 participants (34.8 ± 6.3 years), with measures of plasma glucose, insulin, leptin, and adiponectin, as well as moderate and vigorous physical activity (MVPA, minutes/day [min/day]), daily sedentary time (min/day), anthropometrics, and body composition. RESULTS: Among the 282 men, body mass index (BMI) ranged from 22.1 to 29.6 kg/m(2) in men and from 25.8 to 34.8 kg/m(2) in 385 women. MVPA ranged from 26.2 to 47.1 min/day in men, and from 14.3 to 27.3 min/day in women and correlated with adiposity (BMI, waist size, and % body fat) only among US males after controlling for age. Plasma glucose ranged from 4.6 ± 0.8 mmol/L in the South African men to 5.8 mmol/L US men, while the overall prevalence for diabetes was very low, except in the US men and women (6.7 and 12 %, respectively). Using multivariate linear regression, glucose was associated with BMI, age, sex, smoking hypertension, daily sedentary time but not daily MVPA. CONCLUSION: Obesity, metabolic risk, and other potential determinants vary significantly between populations at differing stages of the epidemiologic transition, requiring tailored public health policies to address local population characteristics.

Tracking of physical activity during adolescence: The 1993 Pelotas Birth Cohort, Brazil

Objective: To analyze physical activity during adolescence in participants of the 1993 Pelotas Birth Cohort Study, Brazil. Methods: Data on leisure time physical activity at 11, 15, and 18 years of age were analyzed. At each visit, a cut-off point of 300 min/week was used to classify adolescents as active or inactive. A total of 3,736 participants provided data on physical activity at each of the three age points. Results: A significant decline in the proportion of active adolescents was observed from 11 to 18 years of age, particularly among girls (from 32.9% to 21.7%). The proportions of girls and boys who were active at all three age points were 28.0% and 55.1%, respectively. After adjustment for sex, economic status, and skin color, participants who were active at 11 and 15 years of age were 58.0% more likely to be active at 18 years of age compared with those who were inactive at 11 and 15 years of age. Conclusions: Physical activity declined during adolescence and inactivity tended to track over time. Our findings reinforce the need to promote physical activity at early stages of life, because active behavior established early tends to be maintained over time.

Physical activity of children with developmental coordination disorder in the presence of attention deficit hyperactivity disorder : does gender matter?

Baerg, S., Cairney, J., Hay, J., Rempel, L. and Faught, B.E. (2009). Physical Activity of Children with Developmental Coordination Disorder in the Presence of Attention Deficit Hyperactivity Disorder: Does Gender Matter? Brock University, St. Catharines, Ontario, CANADA. Children with Developmental Coordination Disorder (DCD) have difficulties in motor coordination. Attention-deficit hyperactive disorder (ADHD) is considered the condition most co-morbid with DCD at approximately 50%. Children with DCD are generally less physically active (PA) than their peers, while children with ADHD are often considered more physically active. It is not known if the physical activity patterns of children with DCD-ADHD resemble those of children with primarily DCD or that of their healthy peers. The primary objective of this research was to contrast physical activity patterns between children with DCD, DCD-ADHD, and healthy controls. Since boys are generally reported as more physically active than girls, a secondary objective was to determine if gender moderated the association between groups and physical activity. A sample of males (n=66) and females (n=44) were recruited from the Physical Health Activity Study Team (PHAST) longitudinal study. The Movement Assessment Battery for Children (2nd Ed.) was used to identify probable cases of DCD, and Connor's Revised Parent Rating Scale- Short Version to identify ADHD. Subjects (mean age=12.8±.4 yrs) were allocated to three groups; DCD (n=32), DCD-ADHD (n=30) and control (n=48). Physical activity was monitored for seven days with the Actical® accelerometer (activity count, step count and energy expenditure). Children completed the Participation Questionnaire (PQ) during the in-school session of data collection for the PHAST study. Height, weight and body mass index (BMI) were also determined. Analysis of variance showed significant group differences for activity count (F(2,56)=5.36, p=.007) and PQ (F(2,44 )=6. 71, p=.003) in males, while a significant group difference for step count (F(2,37)=3.55, p=.04) was found in females. Post hoc comparison tests (Tukey) identified significantly lower PQ and activity count between males with OCD and controls (p=.004) and males with DCD-ADHD and controls (p=.003). Conversely, females with DCD-ADHD had significantly more step counts than their controls (p=.01). Analysis of covariance demonstrated a gender by DCD groups negative interaction for males (activity count) (F(2,92):;:3.11, p=.049) and a positive interaction for females (step count) (F(1,92)=4.92, p=.009). Hyperactivity in females with DCD-ADHD appears to contribute to more physical activity, whereas DCD may contribute to decreased activity in males with DCD and DCDADHD. Further research is needed to examine gender differences in physical activity within the context of DCD and ADHD.

The role of physical activity and perceived adequacy on cardiorespiratory fitness in children with developmental coordination disorder

Evidence suggests that children with developmental coordination disorder (DCD) have lower levels of cardiorespiratory fitness (CRF) compared to children without the condition. However, these studies were restricted to field-based methods in order to predict V02 peak in the determination of CRF. Such field tests have been criticised for their ability to provide a valid prediction of V02 peak and vulnerability to psychological aspects in children with DCD, such as low perceived adequacy toward physical activity. Moreover, the contribution of physical activity to the variance in V02 peak between the two groups is unknown. The purpose of our study was to determine the mediating role of physical activity and perceived adequacy towards physical activity on V02 peak in children with significant motor impairments. This prospective case-control design involved 122 (age 12-13 years) children with significant motor impairments (n=61) and healthy matched controls (n=61) based on age, gender and school location. Participants had been previously assessed for motor proficiency and classified as a probable DCD (p-DCD) or healthy control using the movement ABC test. V02 peak was measured by a progressive exercise test on a cycle ergometer. Perceived adequacy was measured using a 7 -item subscale from Children's Selfperception of Adequacy and Predilection for Physical Activity scale. Physical activity was monitored for seven days with the Actical® accelerometer. Children with p-DCD had significantly lower V02 peak (48.76±7.2 ml/ffm/min; p:50.05) compared to controls (53.12±8.2 ml/ffm/min), even after correcting for fat free mass. Regression analysis demonstrated that perceived adequacy and physical activity were significant mediators in the relationship between p-DCD and V02 peak. In conclusion, using a stringent laboratory assessment, the results of the current study verify the findings of earlier studies, adding low CRF to the list of health consequences associated with DCD. It seems that when testing for CRF in this population, there is a need to consider the psychological barriers associated with their condition. Moreover, strategies to increase physical activity in children with DCD may result in improvement in their CRF.

Developing Physical Activity Habit in Schools for Active Lifestyle Among Children and Adolescents

This study sought to identify and suggest ways to develop physical activity habits in school-aged children and adolescents that could help them continue healthy active practices throughout their lifespan. A systematic review of the literature identified 4 key factors that may influence school-based physical activity habit formation—motivation, enjoyment, commitment, and sustainment—and how each may be achieved in schools. The research paper begins by exploring the definitions and meaning of a habit, how it is developed, and its effect on a healthy active lifestyle. The study proposes a framework comprising 3 major components (i.e., programs, teachers, students) and offers practical strategies that support and nurture the development of students’ physical activity habits in schools. The study concludes by making recommendations for further study.

Development of the Physical Activity Interactive Recall (PAIR) for Aboriginal children

Affiliation: Margaret Cargo : Département de médecine sociale et préventive, Faculté de médecine, Université de Montréal

Bizzy Break! The effect of a classroom-based activity break on in-school physical activity levels of primary school children

The school has been identified as a key setting to promote physical activity. The purpose of this study was to evaluate the effect of a classroom-based activity break on in-school step counts of primary school children. Data for 90 children (49 boys, 41 girls, 9.3 ± 1.4 years) from three Irish primary schools is presented. In each school one class was randomly assigned as the intervention group and another as controls. Children's step counts were measured for five consecutive days during school hours at baseline and follow-up. Teachers of the intervention classes led a 10 min activity break in the classroom each day (Bizzy Break!). Mean daily in-school steps for the intervention at baseline and follow-up were 5351 and 5054. Corresponding values for the control group were 5469 and 4246. There was a significant difference in the change in daily steps from baseline to follow-up between groups (p < .05). There was no evidence that girls and boys responded differently to the intervention (p > .05). Children participating in a daily 10 min classroom-based activity break undertake more physical activity during school hours than controls.