Physical Activity and Snus: Is There a Link?

The study aimed at assessing the link between physical activity (PA), sports activity and snus use among young men in Switzerland. Data from the Cohort Study on Substance Use Risk Factors (C-SURF) were used to measure PA with the International Physical Activity Questionnaire and sports activity with a single item. Multivariate logistic regression analysis was conducted to measure the association between snus use, PA and sports activity. Similar models were run for smoking and snuff use. Snus use increased in a dose-response association with PA (high level: OR = 1.72; 95% CI 1.16-2.55) and with individuals exercising once a week or more often (OR = 1.65; 95% CI 1.26-2.16; p < 0.001) or almost every day (OR = 2.27; 95% CI 1.72-3.01; p < 0.001) in separate models. Entered simultaneously, only sports and exercise maintained a basically unchanged significant dose-response relationship, whereas PA became non-significant. A non-significant dose-response relation was found for cigarette smoking and snuff use, indicating that the association with sport is specific to snus and not to tobacco use in general or smokeless tobacco in particular. This study showed that the association between snus use and sports is not specific to Nordic countries.

Objectively measured physical activity and sedentary time in youth: the International children's accelerometry database (ICAD).

BACKGROUND: Physical activity and sedentary behaviour in youth have been reported to vary by sex, age, weight status and country. However, supporting data are often self-reported and/or do not encompass a wide range of ages or geographical locations. This study aimed to describe objectively-measured physical activity and sedentary time patterns in youth. METHODS: The International Children's Accelerometry Database (ICAD) consists of ActiGraph accelerometer data from 20 studies in ten countries, processed using common data reduction procedures. Analyses were conducted on 27,637 participants (2.8-18.4 years) who provided at least three days of valid accelerometer data. Linear regression was used to examine associations between age, sex, weight status, country and physical activity outcomes. RESULTS: Boys were less sedentary and more active than girls at all ages. After 5 years of age there was an average cross-sectional decrease of 4.2 % in total physical activity with each additional year of age, due mainly to lower levels of light-intensity physical activity and greater time spent sedentary. Physical activity did not differ by weight status in the youngest children, but from age seven onwards, overweight/obese participants were less active than their normal weight counterparts. Physical activity varied between samples from different countries, with a 15-20 % difference between the highest and lowest countries at age 9-10 and a 26-28 % difference at age 12-13. CONCLUSIONS: Physical activity differed between samples from different countries, but the associations between demographic characteristics and physical activity were consistently observed. Further research is needed to explore environmental and sociocultural explanations for these differences.

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

OBJECTIVE: We 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. METHODS: We 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. RESULTS: Children from the German compared to the French-speaking region were more physically active and less sedentary (by 10-15 %, p < 0.01). Although German-speaking children lived in a more favourable environment and a higher socioeconomic neighbourhood (differences p < 0.001), these characteristics did not explain the differences in PA behaviour between French and German speaking. CONCLUSIONS: Factors 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.

New measurements of energy expenditure and physical activity in chronic kidney disease.

The accurate estimation of total daily energy expenditure (TEE) in chronic kidney patients is essential to allow the provision of nutritional requirements; however, it remains a challenge to collect actual physical activity and resting energy expenditure in maintenance dialysis patients. The direct measurement of TEE by direct calorimetry or doubly labeled water cannot be used easily so that, in clinical practice, TEE is usually estimated from resting energy expenditure and physical activity. Prediction equations may also be used to estimate resting energy expenditure; however, their use has been poorly documented in dialysis patients. Recently, a new system called SenseWear Armband (BodyMedia, Pittsburgh, PA) was developed to assess TEE, but so far no data have been published in chronic kidney disease patients. The aim of this review is to describe new measurements of energy expenditure and physical activity in chronic kidney disease patients.

How does a hilly urban environment influence daily physical activity in obese individuals?

Background: Increases in physical activity (PA) are promoted by walking in an outdoor environment. Along with walking speed, slope is a major determinant of exercise intensity, and energy expenditure. The hypothesis was that in free-living conditions, a hilly environment diminishes PA to a greater extent in obese (OB) when compared with control (CO) individuals. Methods: To assess PA types and patterns, 28 CO (22 ± 2 kg/m2) and 14 OB (33 ± 4 kg/m2) individuals wore during an entire day 2 accelerometers and 1 GPS device, around respectively their waist, ankle and shoulder. They performed their usual PA and were asked to walk an additional 60 min per day. Results: The duration of inactivity and activity with OB individuals tended to be, respectively, higher and lower than that of CO individuals (P = .06). Both groups spent less time walking uphill/downhill than on the level (20%, 19%, vs. 61% of total walking duration, respectively, P < .001). However OB individuals spent less time walking uphill/downhill per day than CO (25 ± 15 and 38 ± 15 min/d, respectively, P < 0.05) and covered a shorter distance per day (3.8 km vs 5.2 km, P < 0.01). Conclusions: BMI and outdoor topography should also be considered when prescribing extra walking in free-living conditions.

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.

Reduced physical activity level and cardiorespiratory fitness in children with chronic diseases.

We aimed to compare physical activity level and cardiorespiratory fitness in children with different chronic diseases, such as type 1 diabetes mellitus (T1DM), obesity (OB) and juvenile idiopathic arthritis (JIA), with healthy controls (HC). We performed a cross-sectional study including 209 children: OB: n = 45, T1DM: n = 48, JIA: n = 31, and HC: n = 85. Physical activity level was assessed by accelerometer and cardiorespiratory fitness by a treadmill test. ANOVA, linear regressions and Pearson correlations were used. Children with chronic diseases had reduced total daily physical activity counts (T1DM 497 +/- 54 cpm, p = 0.003; JIA 518 +/- 28, p < 0.001, OB 590 +/- 25, p = 0.003) and cardiorespiratory fitness (JIA 39.3 +/- 1.7, p = 0.001, OB 41.7 +/- 1.2, p = 0.020) compared to HC (668 +/- 35 cpm; 45.3 +/- 0.9 ml kg(-1) min(-1), respectively). Only 60.4% of HC, 51.6% of OB, 38.1% of JIA and 38.5% of T1DM children met the recommended daily 60 min of moderate-to-vigorous physical activity. Low cardiorespiratory fitness was associated with female gender and low daily PA. Children with chronic diseases had reduced physical activity and cardiorespiratory fitness. As the benefits of PA on health have been well demonstrated during growth, it should be encouraged in those children to prevent a reduction of cardiorespiratory fitness and the development of comorbidities.

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.

Weight status and gender-related differences in motor skills and in child care - based physical activity in young children.

Over the last decades, a decline in motor skills and in physical activity and an increase in obesity has been observed in children. However, there is a lack of data in young children. We tested if differences in motor skills and in physical activity according to weight or gender were already present in 2- to 4-year-old children. Fifty-eight child care centers in the French part of Switzerland were randomly selected for the Youp'là bouge study. Motor skills were assessed by an obstacle course including 5 motor skills, derived from the Zurich Neuromotor Assessment test. Physical activity was measured with accelerometers (GT1M, Actigraph, Florida, USA) using age-adapted cut-offs. Weight status was assessed using the International Obesity Task Force criteria (healthy weight vs overweight) for body mass index (BMI). Of the 529 children (49% girls, 3.4 ± 0.6 years, BMI 16.2 ± 1.2 kg/m2), 13% were overweight. There were no significant weight status-related differences in the single skills of the obstacle course, but there was a trend (p = 0.059) for a lower performance of overweight children in the overall motor skills score. No significant weight status-related differences in child care-based physical activity were observed. No gender-related differences were found in the overall motor skills score, but boys performed better than girls in 2 of the 5 motor skills (p ≤ 0.04). Total physical activity as well as time spent in moderate-vigorous and in vigorous activity during child care were 12-25% higher and sedentary activity 5% lower in boys compared to girls (all p < 0.01). At this early age, there were no significant weight status- or gender-related differences in global motor skills. However, in accordance to data in older children, child care-based physical activity was higher in boys compared to girls. These results are important to consider when establishing physical activity recommendations or targeting health promotion interventions in young children.

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.

Physical activity level and health-related quality of life in the general adult population: a systematic review.

OBJECTIVE: Little is known regarding health-related quality of life and its relation with physical activity level in the general population. Our primary objective was to systematically review data examining this relationship. METHODS: We systematically searched MEDLINE, EMBASE, CINAHL, and PsycINFO for health-related quality of life and physical activity related keywords in titles, abstracts, or indexing fields. RESULTS: From 1426 retrieved references, 55 citations were judged to require further evaluation. Fourteen studies were retained for data extraction and analysis; seven were cross-sectional studies, two were cohort studies, four were randomized controlled trials and one used a combined cross sectional and longitudinal design. Thirteen different methods of physical activity assessment were used. Most health-related quality of life instruments related to the Medical Outcome Study SF-36 questionnaire. Cross-sectional studies showed a consistently positive association between self-reported physical activity and health-related quality of life. The largest cross-sectional study reported an adjusted odds ratio of "having 14 or more unhealthy days" during the previous month to be 0.40 (95% Confidence Interval 0.36-0.45) for those meeting recommended levels of physical activity compared to inactive subjects. Cohort studies and randomized controlled trials tended to show a positive effect of physical activity on health-related quality of life, but similar to the cross-sectional studies, had methodological limitations. CONCLUSION: Cross-sectional data showed a consistently positive association between physical activity level and health-related quality of life. Limited evidence from randomized controlled trials and cohort studies precludes a definitive statement about the nature of this association.

A new measurement of energy expenditure and physical activity in patients treated by maintenance hemodialysis

Purpose: The accurate estimation of total energy expenditure (TEE) is essential to allow the provision of nutritional requirements in patients treated by maintenance hemodialysis (MHD). The measurement of TEE and resting energy expenditure (REE) by direct or indirect calorimetry and doubly labeled water are complicated, timeconsuming and cumbersome in this population. Recently, a new system called SenseWear® armband (SWA) was developed to assess TEE, physical activity and REE. This device works by measurements of body acceleration in two axes, heat production and steps counts. REE measured by indirect calorimetry and SWA are well correlated. The aim of this study was to determine TEE, physical activity and REE on patients on MHD using this new device. Methods and materials: Daily TEE, REE, step count, activity time, intensity of activity and lying time were determined for 7 consecutive days in unselected stable patients on MHD and sex, age and weightmatched healthy controls (HC). Patients with malnutrition, cancer, use of immunosuppressive drugs, hypoalbumemia <35 g/L and those hospitalized in the last 3 months, were excluded. For MHD patients, separate analyses were conducted in dialysis and non-dialysis days. Relevant parameters known to affect REE, such as BMI, albumin, pre-albumin, hemoglobin, Kt/V, CRP, bicarbonate, PTH, TSH, were recorded. Results: Thirty patients on MHD and 30 HC were included. In MHD patients, there were 20 men and 10 women. Age was 60,13 years ± 14.97 (mean ± SD), BMI was 25.77 kg/m² ± 4.73 and body weight was 74.65 kg ± 16.16. There were no significant differences between the two groups. TEE was lower in MHD patients compared to HC (28.79 ± 5.51 SD versus 32.91 ± 5.75 SD kcal/kg/day; p <0.01). Activity time was significantly lower in patients on MHD (101.3 ± 12.6SD versus 50.7 ± 9.4 SD min; p = 0.0021). Energy expenditure during the time of activity was significantly lower in MHD patients. MHD patients walked 4543 ± 643 SD vs 8537 ± 744 SD steps per day (p <0.0001). Age was negatively correlated with TEE (r = -0.70) and intensity of activity (r = -0.61) in HC, but not in patients on MHD. TEE showed no difference between dialysis and non-dialysis days (29.92 ± 2.03 SD versus 28.44 ± 1.90 SD kcal/kg/day; p = NS), reflecting a lack of difference in activity (number of steps, time of physical activity) and REE. This finding was observed in MHD patients both older and younger than 60 years. However, age stratification appeared to have an influence on TEE, regardless of dialysis day, (29.92 ± 2.07 SD kcal/kg/day for <60 years-old versus 27.41 ± 1.04 SD kcal/kg/day for ≥60 years old), although failing to reach statistical significance. Conclusion: Using SWA, we have shown that stable patients on MHD have a lower TEE than matched HC. On average, a TEE of 28.79 kcal/kg/day, partially affected by age, was measured. This finding gives support to the clinical impression that it is difficult and probably unnecessary to provide an energy amount of 30-35 kcal/kg/day, as proposed by international guidelines for this population. In addition, we documented for the first time that MHD patients exert a reduced physical activity as compared to HC. There were surprisingly no differences in TEE, REE and physical activity parameters between dialysis and non-dialysis days. This observation might be due to the fact that patients on MHD produce a physical effort to reach the dialysis centre. Age per se did not influence physical activity in MHD patients, contrary to HC, reflecting the impact of co-morbidities on physical activity in this group of patients.

Constrained Total Energy Expenditure and Metabolic Adaptation to Physical Activity in Adult Humans.

Current obesity prevention strategies recommend increasing daily physical activity, assuming that increased activity will lead to corresponding increases in total energy expenditure and prevent or reverse energy imbalance and weight gain [1-3]. Such Additive total energy expenditure models are supported by exercise intervention and accelerometry studies reporting positive correlations between physical activity and total energy expenditure [4] but are challenged by ecological studies in humans and other species showing that more active populations do not have higher total energy expenditure [5-8]. Here we tested a Constrained total energy expenditure model, in which total energy expenditure increases with physical activity at low activity levels but plateaus at higher activity levels as the body adapts to maintain total energy expenditure within a narrow range. We compared total energy expenditure, measured using doubly labeled water, against physical activity, measured using accelerometry, for a large (n = 332) sample of adults living in five populations [9]. After adjusting for body size and composition, total energy expenditure was positively correlated with physical activity, but the relationship was markedly stronger over the lower range of physical activity. For subjects in the upper range of physical activity, total energy expenditure plateaued, supporting a Constrained total energy expenditure model. Body fat percentage and activity intensity appear to modulate the metabolic response to physical activity. Models of energy balance employed in public health [1-3] should be revised to better reflect the constrained nature of total energy expenditure and the complex effects of physical activity on metabolic physiology.