993 resultados para Physical activity measurement


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With measurement of physical activity becoming more common in clinical practice, it is imperative that healthcare professionals become more knowledgeable about the different methods available to objectively measure physical activity behaviour. Objective measures do not rely on information provided by the patient, but instead measure and record the biomechanical or physiological consequences of performing physical activity, often in real time. As such, objective measures are not subject to the reporting bias or recall problems associated with self-report methods. The purpose of this article was to provide an overview of the different methods used to objectively measure physical activity in clinical practice. The review was delimited to heart rate monitoring, accelerometers and pedometers since their small size, low participant burden and relatively low cost make these objective measures appropriate for use in clinical practice settings. For each measure, strengths and weakness were discussed; and whenever possible, literature-based examples of implementation were provided.

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Background Interventions to promote physical activity (PA) in children attending family child care homes (FCCHs) require valid, yet practical, measurement tools. The aim of this study was to assess the validity of two proxy report instruments designed to measure PA in children attending FCCHs. Methods A sample of 37 FCCH providers completed the Burdette parent proxy report, modified for the family child care setting for 107 children 3.4±1.2 years of age. A second sample of 42 FCCH providers completed the Harro parent and teacher proxy report, modified for the family child care setting, for 131 children 3.8±1.3 years of age. Both proxy reports were assessed for validity using accelerometry as a criterion measure. Results Significant positive correlations were observed between provider-reported PA scores from the modified Burdette proxy report and objectively measured total PA (r=0.30; p<0.01) and moderate-to-vigorous PA (MVPA; r=0.34; p<0.01). Across levels of provider-reported PA, both total PA and MVPA increased significantly in a linear dose-response fashion. The modified Harro proxy report was not associated with objectively measured PA. Conclusion Proxy PA reports completed by family child care providers may be a valid assessment option in studies where more burdensome objective measures are not feasible.

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Accurate and detailed measurement of an individual's physical activity is a key requirement for helping researchers understand the relationship between physical activity and health. Accelerometers have become the method of choice for measuring physical activity due to their small size, low cost, convenience and their ability to provide objective information about physical activity. However, interpreting accelerometer data once it has been collected can be challenging. In this work, we applied machine learning algorithms to the task of physical activity recognition from triaxial accelerometer data. We employed a simple but effective approach of dividing the accelerometer data into short non-overlapping windows, converting each window into a feature vector, and treating each feature vector as an i.i.d training instance for a supervised learning algorithm. In addition, we improved on this simple approach with a multi-scale ensemble method that did not need to commit to a single window size and was able to leverage the fact that physical activities produced time series with repetitive patterns and discriminative features for physical activity occurred at different temporal scales.

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Background There are few theoretically derived questionnaires of physical activity determinants among youth, and the existing questionnaires have not been subjected to tests of factorial validity and invariance, The present study employed confirmatory factor analysis (CFA) to test the factorial validity and invariance of questionnaires designed to be unidimensional measures of attitudes, subjective norms, perceived behavioral control, and self-efficacy about physical activity. Methods Adolescent girls in eighth grade from two cohorts (N = 955 and 1,797) completed the questionnaires at baseline; participants from cohort 1 (N = 845) also completed the questionnaires in ninth grade (i.e., 1-year follow-up). Factorial validity and invariance were tested using CFA with full-information maximum likelihood estimation in AMOS 4.0, Initially, baseline data from cohort 1 were employed to test the fit and, when necessary, to modify the unidimensional models. The models were cross-validated using a multigroup analysis of factorial invariance on baseline data from cohorts 1 and 2, The models then were subjected to a longitudinal analysis of factorial invariance using baseline and follow-up data from cohort i, Results The CFAs supported the fit of unidimensional models to the four questionnaires, and the models were cross-validated, as indicated by evidence of multigroup factorial invariance, The models also possessed evidence of longitudinal factorial invariance. Conclusions Evidence was provided for the factorial validity and the invariance of the questionnaires designed to be unidimensional measures of attitudes, subjective norms, perceived behavioral control, and self-efficacy about physical activity among adolescent girls, (C) 2000 American Health Foundation and academic Press.

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Background The purposes of this study were 1) to establish accelerometer count cutoffs to categorize activity intensity of 3 to 5-y old-children and 2) to evaluate the accelerometer as a measure of children’s physical activity in preschool settings. Methods While wearing an ActiGraph accelerometer, 16 preschool children performed five, 3-min structured activities. Receiver Operating Characteristic (ROC) curve analyses identified count cutoffs for four physical activity intensities. In 9 preschools, 281 children wore an ActiGraph during observations performed by three trained observers (interobserver reli-ability = 0.91 to 0.98). Results Separate count cutoffs for 3, 4, and 5-y olds were established. Sensitivity and specificity for the count cutoffs ranged from 86.7% to 100.0% and 66.7% to 100.0%, respectively. ActiGraph counts/15 s were different among all activities (P < 0.05) except the two sitting activities. Correlations between observed and ActiGraph intensity categorizations at the preschools ranged from 0.46 to 0.70 (P < 0.001). Conclusions The ActiGraph count cutoffs established and validated in this study can be used to objectively categorize the time that preschool-age children spend in different physical activity intensity levels.

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Objective To compare the level of agreement in results obtained from four physical activity (PA) measurement instruments that are in use in Australia and around the world. Methods 1,280 randomly selected participants answered two sets of PA questions by telephone. 428 answered the Active Australia (AA) and National Health Surveys, 427 answered the AA and CDC Behavioural Risk Factor Surveillance System surveys (BRFSS), and 425 answered the AA survey and the short International Physical Activity Questionnaire (IPAQ). Results Among the three pairs of survey items, the difference in mean total PA time was lowest when the AA and NHS items were asked (difference=24) (SE:17) minutes, compared with 144 (SE:21) mins for AA/BRFSS and 406 (SE:27) mins for AA/IPAQ). Correspondingly, prevalence estimates for 'sufficiently active' were similar for AA and NHS (56% and 55% respectively), but about 10% higher when BRFSS data were used, and about 26% higher when the IPAQ items were used, compared with estimates from the AA survey. Conclusions The findings clearly demonstrate that there are large differences in reported PA times and hence in prevalence estimates of 'sufficient activity' from these four measures. Implications It is important to consistently use the same survey for population monitoring purposes. As the AA survey has now been used three times in national surveys, its continued use for population surveys is recommended so that trend data ever a longer period of time can be established.

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Background Multi-strategic community wide interventions for physical activity are increasingly popular but their ability to achieve population level improvements is unknown. Objectives To evaluate the effects of community wide, multi-strategic interventions upon population levels of physical activity. Search methods We searched the Cochrane Public Health Group Segment of the Cochrane Register of Studies,The Cochrane Library, MEDLINE, MEDLINE in Process, EMBASE, CINAHL, LILACS, PsycINFO, ASSIA, the British Nursing Index, Chinese CNKI databases, EPPI Centre (DoPHER, TRoPHI), ERIC, HMIC, Sociological Abstracts, SPORTDiscus, Transport Database and Web of Science (Science Citation Index, Social Sciences Citation Index, Conference Proceedings Citation Index). We also scanned websites of the EU Platform on Diet, Physical Activity and Health; Health-Evidence.org; the International Union for Health Promotion and Education; the NIHR Coordinating Centre for Health Technology (NCCHTA); the US Centre for Disease Control and Prevention (CDC) and NICE and SIGN guidelines. Reference lists of all relevant systematic reviews, guidelines and primary studies were searched and we contacted experts in the field. The searches were updated to 16 January 2014, unrestricted by language or publication status. Selection criteria Cluster randomised controlled trials, randomised controlled trials, quasi-experimental designs which used a control population for comparison, interrupted time-series studies, and prospective controlled cohort studies were included. Only studies with a minimum six-month follow up from the start of the intervention to measurement of outcomes were included. Community wide interventions had to comprise at least two broad strategies aimed at physical activity for the whole population. Studies which randomised individuals from the same community were excluded. Data collection and analysis At least two review authors independently extracted the data and assessed the risk of bias. Each study was assessed for the setting, the number of included components and their intensity. The primary outcome measures were grouped according to whether they were dichotomous (per cent physically active, per cent physically active during leisure time, and per cent physically inactive) or continuous (leisure time physical activity time (time spent)), walking (time spent), energy expenditure (as metabolic equivalents or METS)). For dichotomous measures we calculated the unadjusted and adjusted risk difference, and the unadjusted and adjusted relative risk. For continuous measures we calculated percentage change from baseline, unadjusted and adjusted. Main results After the selection process had been completed, 33 studies were included. A total of 267 communities were included in the review (populations between 500 and 1.9 million). Of the included studies, 25 were set in high income countries and eight were in low income countries. The interventions varied by the number of strategies included and their intensity. Almost all of the interventions included a component of building partnerships with local governments or non-governmental organisations (NGOs) (29 studies). None of the studies provided results by socio-economic disadvantage or other markers of equity. However, of those included studies undertaken in high income countries, 14 studies were described as being provided to deprived, disadvantaged or low socio-economic communities. Nineteen studies were identified as having a high risk of bias, 10 studies were unclear, and four studies had a low risk of bias. Selection bias was a major concern with these studies, with only five studies using randomisation to allocate communities. Four studies were judged as being at low risk of selection bias although 19 studies were considered to have an unclear risk of bias. Twelve studies had a high risk of detection bias, 13 an unclear risk and four a low risk of bias. Generally, the better designed studies showed no improvement in the primary outcome measure of physical activity at a population level. All four of the newly included, and judged to be at low risk of bias, studies (conducted in Japan, United Kingdom and USA) used randomisation to allocate the intervention to the communities. Three studies used a cluster randomised design and one study used a stepped wedge design. The approach to measuring the primary outcome of physical activity was better in these four studies than in many of the earlier studies. One study obtained objective population representative measurements of physical activity by accelerometers, while the remaining three low-risk studies used validated self-reported measures. The study using accelerometry, conducted in low income, high crime communities of USA, emphasised social marketing, partnership with police and environmental improvements. No change in the seven-day average daily minutes of moderate to vigorous physical activity was observed during the two years of operation. Some program level effect was observed with more people walking in the intervention community, however this result was not evident in the whole community. Similarly, the two studies conducted in the United Kingdom (one in rural villages and the other in urban London; both using communication, partnership and environmental strategies) found no improvement in the mean levels of energy expenditure per person per week, measured from one to four years from baseline. None of the three low risk studies reporting a dichotomous outcome of physical activity found improvements associated with the intervention. Overall, there was a noticeable absence of reporting of benefit in physical activity for community wide interventions in the included studies. However, as a group, the interventions undertaken in China appeared to have the greatest possibility of success with high participation rates reported. Reporting bias was evident with two studies failing to report physical activity measured at follow up. No adverse events were reported.The data pertaining to cost and sustainability of the interventions were limited and varied. Authors' conclusions Although numerous studies have been undertaken, there is a noticeable inconsistency of the findings in the available studies and this is confounded by serious methodological issues within the included studies. The body of evidence in this review does not support the hypothesis that the multi-component community wide interventions studied effectively increased physical activity for the population, although some studies with environmental components observed more people walking. Plain language summary Community wide interventions for increasing physical activity Not having enough physical activity leads to poorer health. Regular physical activity can reduce the risk of chronic disease and improve one's health and wellbeing. The lack of physical activity is a common and in some cases a growing health problem. To address this, 33 studies have used improvement activities directed at communities, using more than one approach in a single program. When we first looked at the available research in 2011 we observed that there was a lack of good studies which could show whether this approach was beneficial or not. Some studies claimed that community wide programs improved physical activities and other studies did not. In this update we found four new studies that were of good quality; however none of these four studies increased physical activity levels for the population. Some studies reported program level effects such as observing more people walking, however the population level of physical activity had not increased. This review found that community wide interventions are very difficult to undertake, and it appears that they usually fail to provide a measurable benefit in physical activity for a population. It is apparent that many of the interventions failed to reach a substantial portion of the community, and we speculate that some single strategies included in the combination may lack individual effectiveness. Laički sažetak Intervencije u zajednici za povećanje tjelesne aktivnosti Nedostatna tjelesna aktivnost povezana je s lošijim zdravljem.Redovita tjelesna aktivnost može umanjiti rizik od kroničnih bolesti te poboljšati zdravlje i kvalitetu života pojedinca.Manjak tjelesne aktivnosti čest je problem, a učestalost tog problema se povećava.Cochrane sustavni pregled je analizirao 33 studije koje su istražile programe za povećanje tjelesne aktivnosti u zajednici, u kojima se koristilo više od jednog pristupa.Kad su prvi put pregledani dokazi iz istraživanja koja su bila dostupna 2011. godine, utvrđeno je da nema dovoljno dobrih studija koje bi mogle pokazati je li takav pristup koristan ili ne.Primjerice, neke studije tvrde da programi za povećanje tjelesne aktivnosti u zajednici poboljšavaju tjelesnu aktivnost pojedinaca u zajednici, a druge studije tvrde suprotno.U ovom obnovljenom sustavnom pregledu pronađene su 4 nove studije koje su bile visoke kvalitete, ail nijedna od tih studija nije pokazala da je istraživana intervencija dovela do povećanja tjelesne aktivnosti u zajednici.Neke su studije opisale učinak na način da je opisano da je uočeno da više ljudi u zajednici hoda, međutim, ukupna razina tjelesne aktivnosti u promatranoj populaciji nije se povećala.Ovaj sustavni pregled je utvrdio da je intervencije za povećanje tjelesne aktivnosti u zajednici teško provesti i čini se da one obično ne uspijevaju u svojoj namjeri da na mjerljiv način povećaju tjelesnu aktivnost u populaciji.Čini se da mnoge intervencije nisu uspjele doseći veći broj stanovnika u zajednici pa se može smatrati da neke od strategija uključene u analizirane kombinacije nisu zasebno učinkovite.

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The provision of autonomy supportive environments that promote physical activity engagement have become popular in contemporary youth settings. However, questions remain about whether adolescent perceptions of their autonomy have implications for physical activity. The purpose of this investigation was to examine the association between adolescents’ self-reported physical activity and their perceived autonomy. Participants (n = 384 adolescents) aged between 12 and 15 years were recruited from six secondary schools in metropolitan Brisbane, Australia. Self-reported measures of physical activity and autonomy were obtained. Logistic regression with inverse probability weights were used to examine the association between autonomy and the odds of meeting youth physical activity guidelines. Autonomy (OR 0.61, 95% CI 0.49-0.76) and gender (OR 0.62, 95% CI 0.46-0.83) were negatively associated with meeting physical activity guidelines. However, the model explained only a small amount of the variation in whether youth in this sample met physical activity guidelines (R2 = 0.023). For every 1 unit decrease in autonomy (on an index from 1 to 5), participants were 1.64 times more likely to meet physical activity guidelines. The findings, which are at odds with several previous studies, suggest that interventions designed to facilitate youth physical activity should limit opportunities for youth to make independent decisions about their engagement. However, the small amount of variation explained by the predictors in the model is a caveat, and should be considered prior to applying such suggestions in practical settings. Future research should continue to examine a larger age range, longitudinal observational or intervention studies to examine assertions of causality, as well as objective measurement of physical activity.

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Background: Alterations in energy expenditure during activity post head injury has not been investigated due primarily to the difficulty of measurement. Objective: The aim of this study was to compare energy expenditure during activity and body composition of children following acquired brain injury (ABI) with data from a group of normal controls. Design: Energy expenditure was measured using the Cosmed K4b2 in a group of 15 children with ABI and a group of 67 normal children during rest and when walking and running. Mean number of steps taken per 3 min run was also recorded and body composition was measured. Results: The energy expended during walking was not significantly different between both groups. A significant difference was found between the two groups in the energy expended during running and also for the number of steps taken as children with ABI took significantly less steps than the normal controls during a 3 min run. Conclusions: Children with ABI exert more energy per activity than healthy controls when controlled for velocity or distance. However, they expend less energy to walk and run when they are free to choose their own desirable, comfortable pace than normal controls. © 2003 Elsevier Ltd. All rights reserved.

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Type 1 diabetes is associated with the risk for late diabetic complications which are divided into microvascular (retinopathy, nephropathy, and neuropathy) and macrovascular (cardiovascular disease, CVD) diseases. The risk for diabetic complication can be reduced by effective treatment, most importantly the glycaemic control. Glycaemia in type 1 diabetes is influenced by the interplay between insulin injections and lifestyle factors such as physical activity and diet. The effect of physical activity in patients with type 1 diabetes is not well known, however. The aim of this thesis was to investigate the physical activity and the physical fitness of patients with type 1 diabetes with special emphasis on glycaemic control and the diabetic complications. The patients included in the study were all part of the nationwide, multicenter Finnish Diabetic Nephropathy (FinnDiane) Study which aims to characterise genetic, clinical, and environmental factors that predispose to diabetic complications in patients with type 1 diabetes. In addition, subjects from the IDentification of EArly mechanisms in the pathogenesis of diabetic Late complications (IDEAL) Study were studied. Physical activity was assessed in the FinnDiane Study in 1945 patients by a validated questionnaire. Physical fitness was measured in the IDEAL Study by spiroergometry (cycle test with measurement of respiratory gases) in 86 young adults with type 1 diabetes and in 27 healthy controls. All patients underwent thorough clinical characterisation of their diabetic complication status. Four substudies were cross-sectional using baseline data and one study additionally used follow-up data. Physical activity, especially the intensity of activities, was reduced in patients affected by diabetic nephropathy, retinopathy, and CVD. Low physical activity was associated with poor glycaemic control, a finding most clear in women and evident also in patients with no signs of diabetic complications. Furthermore, low physical activity was associated with a higher HbA1c variability, which in turn was associated with the progression of renal disease and CVD during follow-up. A higher level of physical activity was also associated with better insulin sensitivity. The prevalence of the metabolic syndrome in type 1 diabetes was also lower the higher the physical activity. The aerobic physical fitness level of young adults with type 1 diabetes was reduced compared with healthy peers and in men an association between higher fitness level and lower HbA1c was observed. In patients with type 1 diabetes, a higher physical activity was associated with better glycaemic control and may thus be beneficial with respect to the prevention of diabetic complications.

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The prevalence of obesity worldwide has increased dramatically over the last few decades. Poor dietary habits and low levels of exercise in adolescence are often maintained into adulthood where they can impact on the incidence of obesity and chronic diseases. A 3-year longitudinal study of anthropometric, dietary and exercise parameters was carried out annually (2005 - 2007) in 3 Irish secondary schools. Anthropometric measurements were taken in each year and analysed longitudinally. Overweight and obesity were at relatively low levels in these adolescents. Height, weight, BMI, waist and hip circumferences and TST increased significantly over the 3 years. Waist-to-hip ratio (WHR) decreased significantly over time. Boys were significantly taller than girls across the 3 years. A 3-day weighed food diary was used to assess food intake by the adolescents. Analysis of dietary intake data was determined using WISP©. Mean daily energy and nutrient intakes were reported. Mean daily energy and macronutrient intakes were analysed longitudinally. The adolescents’ diet was characterised by relatively high saturated fat intakes and insufficient fruit and vegetable consumption. The dietary pattern did not change significantly over the 3 years. Boys consumed more energy than girls over the study period. A validated questionnaire was used to assess physical activity and sedentary activity levels. Boys were substantially more active and had higher energy expenditure estimates than girls throughout the study. A significant longitudinal decrease in physical activity levels among the adolescents was observed. Both genders spent more than the recommended amount of time (hrs/day) pursing sedentary activities. The dietary pattern in these Irish adolescents is relatively poor. Of additional concern is the overall longitudinal decrease in physical activity levels. Promoting consumption of a balanced diet and increased exercise levels among adolescents will help to reduce future public health care costs due to weight-related diseases.

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In this paper we present an Orientation Free Adaptive Step Detection (OFASD) algorithm for deployment in a smart phone for the purposes of physical activity monitoring. The OFASD algorithm detects individual steps and measures a user’s step counts using the smart phone’s in-built accelerometer. The algorithm considers both the variance of an individual’s walking pattern and the orientation of the smart phone. Experimental validation of the algorithm involved the collection of data from 10 participants using five phones (worn at five different body positions) whilst walking on a treadmill at a controlled speed for periods of 5 min. Results indicated that, for steps detected by the OFASD algorithm, there were no significant differences between where the phones were placed on the body (p > 0.05). The mean step detection accuracies ranged from 93.4 % to 96.4 %. Compared to measurements acquired using existing dedicated commercial devices, the results demonstrated that using a smart phone for monitoring physical activity is promising, as it adds value to an accepted everyday accessory, whilst imposing minimum interaction from the user. The algorithm can be used as the underlying component within an application deployed within a smart phone designed to promote self-management of chronic disease where activity measurement is a significant factor, as it provides a practical solution, with minimal requirements for user intervention and less constraints than current solutions.

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Background: Accurate assessment tools are required for the surveillance of physical activity (PA) levels and the assessment of the effect of interventions. In addition, increasing awareness of PA is often used as the first step in pragmatic behavioural interventions, as discrepancies between the amount of activity an individual perceives they do and the amount actually undertaken may act as a barrier to change. Previous research has demonstrated differences in the amount of activity individuals report doing, compared to their level of physical activity when measured with an accelerometer. Understanding the characteristics of those whose PA level is ranked differently when measured with either self-report or accelerometry is important as it may inform the choice of instrument for future research. The aim of this project was to determine which individual characteristics are associated with differences between self-reported and accelerometer measured physical activity.

Methods: Participant data from the 2009 wave of the Commuting and Health in Cambridge study were used. Quartiles of self-reported and accelerometer measured PA were derived by ranking each measure from lowest to highest. These quartiles were compared to determine whether individuals’ physical activity was ranked higher by either method. Multinomial logistic regression models were used to investigate the individual characteristics associated with different categories of mismatch.

Results: Data from 486 participants (70% female) were included in the analysis. In adjusted analyses, the physical activity of overweight or obese individuals was significantly more likely to be ranked higher by self-report than by accelerometer than that of normal-weight individuals (OR = 2.07, 95%CI = 1.28–3.34), particularly among women (OR = 3.97, 95%CI = 2.11–7.47).

Conclusions: There was a greater likelihood of mismatch between self-reported and accelerometer measured physical activity levels in overweight or obese adults. Future studies in overweight or obese adults should consider employing both methods of measurement.

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Background: Patient reported outcome measures (PROMs) are used to evaluate lifestyle interventions but littleis known about differences between patients returning valid and invalid responses, or of potential for bias inevaluations. We aimed to examine the characteristics of patients who returned valid responses to lifestylequestionnaires compared to those whose responses were invalid for evaluating lifestyle change. 
Methods: We conducted a secondary data analysis from the SPHERE Study, a trial of an intervention to improveoutcomes for patients with coronary heart disease in primary care. Postal questionnaires were used to assessphysical activity (Godin) and diet (DINE) among study participants at baseline and 18 month follow-up. Three binaryresponse variables were generated for analysis: (1) valid Godin score; (2) valid DINE Fibre score; and (3) validDINE Total Fat score. Multivariate analysis comprised generalised estimating equation regression to examine theassociation of patients’ characteristics with their return of valid responses at both timepoints. 
Results: Overall, 92.1% of participants (832/903) returned questionnaires at both baseline and 18 months. Relativelyfewer valid Godin scores were returned by those who left school aged <15 years (36.5%) than aged 18 and over(50.5%), manual workers (39.5%) than non-manual (49.5%) and those with an elevated cholesterol (>5 mmol)(34.7%) than those with a lower cholesterol (44.4%) but multivariate analysis identified that only school leaving age(p = 0.047) was of statistical significance.Relatively fewer valid DINE scores were returned by manual than non-manual workers (fibre: 80.8% v 86.8%;fat: 71.2% v 80.0%), smokers (fibre: 72.6% v 84.7%; fat: 67.5% v 76.9%), patients with diabetes (fibre: 75.9% v 82.9%;fat: 66.9% v 75.8%) and those with cholesterol >5 mmol (fat: 68.2% v 76.2%) but multivariate analysis showedstatistical significance only for smoking (fibre: p = 0.013; fat: p = 0.045), diabetes (fibre: p = 0.039; fat: p = 0.047), andcholesterol (fat: p = 0.039). 
Conclusions: Our findings illustrate the importance of detailed reporting of research methods, with clearinformation about response rates, respondents and valid outcome data. Outcome measures which are relevant to astudy population should be chosen carefully. The impact of methods of outcome measurement and valid responserates in evaluating healthcare requires further study.

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Background

The aim of this position statement was to inform the choice of physical activity tools for use within CF research and clinical settings.

Methods

A systematic review of physical activity tools to explore evidence for reliability, validity, and responsiveness. Narrative answers to “four key questions” on motion sensors, questionnaires and diaries were drafted by the core writing team and then discussed at the Exercise Working Group in ECFS Lisbon 2013.

Results and summary

Our current position is that activity monitors such as SenseWear or ActiGraph offer informed choices to facilitate a comprehensive assessment of physical activity, and should as a minimum report on dimensions of physical activity including energy expenditure, step count and time spent in different intensities and sedentary time. The DigiWalker pedometer offers an informed choice of a comparatively inexpensive method of obtaining some measurement of physical activity. The HAES represents an informed choice of questionnaire to assess physical activity. There is insufficient data to recommend the use of one diary over another. Future research should focus on providing additional evidence of clinimetric properties of these and new physical activity assessment tools, as well as further exploring the added value of physical activity assessment in CF.