Accurate assessment is required to assess current and changing physical activity levels, and to evaluate the effectiveness of interventions designed to increase activity levels. This study systematically reviewed the literature to determine the extent of agreement between subjectively (self-report e.g. questionnaire, diary) and objectively (directly measured; e.g. accelerometry, doubly labeled water) assessed physical activity in adults.
4 March 2020 in International Journal of Behavioral Nutrition and Physical Activity
Background: Sedentary behaviour (SB) is a risk factor for chronic disease and premature mortality. While many individual studies have examined the reliability and validity of various self-report measures for assessing SB, it is not clear, in general, how self-reported SB (e.g., questionnaires, logs, ecological momentary assessments (EMAs)) compares to device measures (e.g., accelerometers, inclinometers).Objective: The primary objective of this systematic review was to compare self-report versus device measures of SB in adults.Methods: Six bibliographic databases were searched to identify all studies which included a comparable self-report and device measure of SB in adults. Risk of bias within and across studies was assessed. Results were synthesized using meta-analyses.Results: The review included 185 unique studies. A total of 123 studies comprising 173 comparisons and data from 55,199 participants were used to examine general criterion validity. The average mean difference was -105.19 minutes/day (95% CI: -127.21, -83.17); self-report underestimated sedentary time by ~1.74 hours/day compared to device measures. Self-reported time spent sedentary at work was ~40 minutes higher than when assessed by devices. Single item measures performed more poorly than multi-item questionnaires, EMAs and logs/diaries. On average, when compared to inclinometers, multi-item questionnaires, EMAs and logs/diaries were not significantly different, but had substantial amount of variability (up to 6 hours/day within individual studies) with approximately half over-reporting and half under-reporting. A total of 54 studies provided an assessment of reliability of a self-report measure, on average the reliability was good (ICC = 0.66).Conclusions: Evidence from this review suggests that single-item self-report measures generally underestimate sedentary time when compared to device measures. For accuracy, multi-item questionnaires, EMAs and logs/diaries with a shorter recall period should be encouraged above single item questions and longer recall periods if sedentary time is a primary outcome of study. Users should also be aware of the high degree of variability between and within tools. Studies should exert caution when comparing associations between different self-report and device measures with health outcomes.Systematic review registration: PROSPERO CRD42019118755
Background. Accurate assessment of physical activity (PA) in children and adolescents is required to establish PA levels, monitor changes and inform public healthy policy. This study systematically reviews the literature to determine the extent of agreement between indirect (e.g., questionnaire) and direct (e.g., accelerometry) assessments of PA in pediatric populations (≤19 years). Methods. Literature was identified through searching electronic databases (e.g., MEDLINE, EMBASE), websites of relevant organizations and conference abstracts until April 2007. Studies were included if they collected indirect and direct measures of PA in pediatric populations and were reported in English. Quality of included studies was appraised using a modified Downs and Black tool. Results. A total of 83 studies were included; 24 describing comparable data and 59 including a correlation analysis. The majority of correlations reported between indirect and direct measures were low-to-moderate (range: −0.56–0.89). Overall, 72% of the indirect measures overestimated the directly measured values. Combined gender, as well as male- and female-only data comparing indirect measures to accelerometery, heart rate monitoring or direct observation, all reported an overestimation by indirect method. A similar trend was observed in combined gender data comparing indirect measures with doubly labelled water; however, the opposite trend was observed in the male- and female-only data with a slight underestimation by indirect measure. Conclusions. Substantial discrepancies and moderate correlations between indirect methods and direct measures of assessing PA in pediatric populations are of concern, especially when trying to establish relationships with health outcomes.
Summary: The objective of this study was to systematically review the literature and compare the effectiveness of controlled interventions with a focus on physical activity (PA) and/or sedentary behaviours (SBs) for reducing sedentary time in adults. Six electronic databases were searched to identify all studies that examined the effects of interventions that targeted PA and/or SBs and that reported on changes in SBs (sedentary, sitting or television time). A qualitative synthesis was performed for all studies, and meta‐analyses conducted among studies with mean differences (min/d) of sedentary time. PROSPERO: CRD42014006535. Sixty‐five controlled studies met inclusion criteria; 33 were used in the meta‐analyses. Interventions with a focus on PA or that included a PA and SB component produced less consistent findings and generally resulted in modest reductions in sedentary time (PA: standardized mean differences [SMD] = −0.22 [95% confidence interval {CI}: −0.35, −0.10], PA + SB: SMD = −0.37 [95% CI: −0.69, −0.05]). Moderate quality evidence from the randomized controlled trial meta‐analysis coupled with the qualitative synthesis provides consistent evidence that large and clinically meaningful reductions in sedentary time can be expected from interventions with a focus on reducing SBs (SMD = −1.28 [95% CI: −1.68, −0.87] ). There is evidence to support the need for interventions to include a component focused on reducing SBs in order to generate clinically meaningful reductions in sedentary time.
9 April 2024 in British Journal of Sports Medicine
Objective To examine and summarise evidence from meta-analyses of cohort studies that evaluated the predictive associations between baseline cardiorespiratory fitness (CRF) and health outcomes among adults. Design Overview of systematic reviews. Data source Five bibliographic databases were searched from January 2002 to March 2024. Results From the 9062 papers identified, we included 26 systematic reviews. We found eight meta-analyses that described five unique mortality outcomes among general populations. CRF had the largest risk reduction for all-cause mortality when comparing high versus low CRF (HR=0.47; 95% CI 0.39 to 0.56). A dose–response relationship for every 1-metabolic equivalent of task (MET) higher level of CRF was associated with a 11%–17% reduction in all-cause mortality (HR=0.89; 95% CI 0.86 to 0.92, and HR=0.83; 95% CI 0.78 to 0.88). For incident outcomes, nine meta-analyses described 12 unique outcomes. CRF was associated with the largest risk reduction in incident heart failure when comparing high versus low CRF (HR=0.31; 95% CI 0.19 to 0.49). A dose–response relationship for every 1-MET higher level of CRF was associated with a 18% reduction in heart failure (HR=0.82; 95% CI 0.79 to 0.84). Among those living with chronic conditions, nine meta-analyses described four unique outcomes in nine patient groups. CRF was associated with the largest risk reduction for cardiovascular mortality among those living with cardiovascular disease when comparing high versus low CRF (HR=0.27; 95% CI 0.16 to 0.48). The certainty of the evidence across all studies ranged from very low-to-moderate according to Grading of Recommendations, Assessment, Development and Evaluations. Conclusion We found consistent evidence that high CRF is strongly associated with lower risk for a variety of mortality and incident chronic conditions in general and clinical populations.
2 April 2019 in International Journal of Behavioral Nutrition and Physical Activity
With approximately 8 hours of one’s waking day spent at work, occupational tasks and environments are important influencers on an individual’s physical activity (PA) and sedentary behaviours. Little research has compared device-measured physical activity, sedentary behaviour and cardiometabolic outcomes between occupational groups. To compare device-measured movement (sedentary time [ST], light intensity physical activity [LPA], moderate-to-vigorous intensity physical activity [MVPA], and steps) across occupations. The secondary objective was to examine whether cardiometabolic and fitness outcomes differed by occupation. Five bibliographic databases were searched to identify all studies which included working age, employed adults from high-income countries, and reported on device-measured movement within occupations. Risk of bias within and across studies was assessed. Results were synthesized using meta-analyses and narrative syntheses. The review includes 132 unique studies with data from 15,619 participants. Working adults spent ~ 60% of their working and waking time engaged in sedentary behaviour; a very small proportion (~ 4%) of the day included MVPA. On average, workers accumulated 8124 steps/day. Office and call center workers’ steps/day were among the lowest, while those of postal delivery workers were highest. Office workers had the greatest ST and the lowest time in LPA both at work and during wakeful time. However, office workers had the greatest minutes sent in MVPA during wakeful hours. Laborers had the lowest ST and spent a significantly greater proportion of their work time in LPA and MVPA. Healthcare and protective services workers had higher levels of LPA at work compared to other occupations. Workers in driving-based occupations tended to have a higher body mass index and blood pressure. This review identifies that occupational and wakeful time PA and ST differed between occupations. Future studies are needed to assess whether patterns differ by age and sex, describe leisure-time movement and movement patterns, and the relationship with cardiometabolic health. PROSPERO CRD42017070448 .