Continuous monitoring and quantification of multiple parameters of daily physical activity in ambulatory Duchenne muscular dystrophy patients.

Multiple motor function and strength assessment tools exist for the evaluation of neuromuscular diseases, but most do not directly assess functional ability in the patients' daily physical activity in their home environment. In this study our aim was to assess: 1) the feasibility and accuracy of physical activity monitoring during two days in a home environment of five DMD patients using a non-commercialized monitor containing a 3D accelerometer and a gyroscope, 2) if a difference in the physical activity parameters could be measured before and one month after starting prednisolone. We reliably quantified the time spend sitting, standing, lying, walking, the number of steps taken, the cadence, the number of walking episodes and their duration as well as how these were distributed over the day. Parameters possibly reflecting endurance, such as the duration of the walking episodes or the succession of two or three walking episodes lasting more than 30 s were the most improved after prednisolone treatment. This degree of detailed determination of physical activity in a home environment has not been previously reported in neuromuscular disorders to our knowledge and some of the reported parameters are potential new outcome measures in clinical trials.

Promotion of physical activity in the primary care setting : the situation in Switzerland

Although many harmful effects of a sedentary lifestyle on health are well known, we still need to better understand how regular physical activity in the general population can be promoted effectively. Among the currently explored strategies, screening for sedentary lifestyle and promoting physical activity in the primary care setting seem promising. Despite recommendations from governmental agencies and professional associations in favor of physical activity counseling, this approach has not been widely adopted so far. This article summarizes the steps taken in Switzerland with the aim of developing physical activity counseling in the primary care setting. It describes how the early implication of primary care physicians influenced in a concrete way the development of the project.

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.

Equating accelerometer estimates among youth: The Rosetta Stone 2.

OBJECTIVES: Different accelerometer cutpoints used by different researchers often yields vastly different estimates of moderate-to-vigorous intensity physical activity (MVPA). This is recognized as cutpoint non-equivalence (CNE), which reduces the ability to accurately compare youth MVPA across studies. The objective of this research is to develop a cutpoint conversion system that standardizes minutes of MVPA for six different sets of published cutpoints. DESIGN: Secondary data analysis. METHODS: Data from the International Children's Accelerometer Database (ICAD; Spring 2014) consisting of 43,112 Actigraph accelerometer data files from 21 worldwide studies (children 3-18 years, 61.5% female) were used to develop prediction equations for six sets of published cutpoints. Linear and non-linear modeling, using a leave one out cross-validation technique, was employed to develop equations to convert MVPA from one set of cutpoints into another. Bland Altman plots illustrate the agreement between actual MVPA and predicted MVPA values. RESULTS: Across the total sample, mean MVPA ranged from 29.7MVPAmind(-1) (Puyau) to 126.1MVPAmind(-1) (Freedson 3 METs). Across conversion equations, median absolute percent error was 12.6% (range: 1.3 to 30.1) and the proportion of variance explained ranged from 66.7% to 99.8%. Mean difference for the best performing prediction equation (VC from EV) was -0.110mind(-1) (limits of agreement (LOA), -2.623 to 2.402). The mean difference for the worst performing prediction equation (FR3 from PY) was 34.76mind(-1) (LOA, -60.392 to 129.910). CONCLUSIONS: For six different sets of published cutpoints, the use of this equating system can assist individuals attempting to synthesize the growing body of literature on Actigraph, accelerometry-derived MVPA.