Physical activity guidelines from around the world are typically expressed in terms of frequency, duration, and intensity parameters. Objective monitoring using pedometers and accelerometers offers a new opportunity to measure and communicate physical activity in terms of steps/day. Various step-based versions or translations of physical activity guidelines are emerging, reflecting public interest in such guidance. However, there appears to be a wide discrepancy in the exact values that are being communicated. It makes sense that step-based recommendations should be harmonious with existing evidence-based public health guidelines that recognize that "some physical activity is better than none" while maintaining a focus on time spent in moderate-to-vigorous physical activity (MVPA). Thus, the purpose of this review was to update our existing knowledge of "How many steps/day are enough?", and to inform step-based recommendations consistent with current physical activity guidelines. Normative data indicate that healthy adults typically take between 4,000 and 18,000 steps/day, and that 10,000 steps/day is reasonable for this population, although there are notable "low active populations." Interventions demonstrate incremental increases on the order of 2,000-2,500 steps/day. The results of seven different controlled studies demonstrate that there is a strong relationship between cadence and intensity. Further, despite some inter-individual variation, 100 steps/minute represents a reasonable floor value indicative of moderate intensity walking. Multiplying this cadence by 30 minutes (i.e., typical of a daily recommendation) produces a minimum of 3,000 steps that is best used as a heuristic (i.e., guiding) value, but these steps must be taken over and above habitual activity levels to be a true expression of free-living steps/day that also includes recommendations for minimal amounts of time in MVPA. Computed steps/day translations of time in MVPA that also include estimates of habitual activity levels equate to 7,100 to 11,000 steps/day. A direct estimate of minimal amounts of MVPA accumulated in the course of objectively monitored free-living behaviour is 7,000-8,000 steps/day. A scale that spans a wide range of incremental increases in steps/day and is congruent with public health recognition that "some physical activity is better than none," yet still incorporates step-based translations of recommended amounts of time in MVPA may be useful in research and practice. The full range of users (researchers to practitioners to the general public) of objective monitoring instruments that provide step-based outputs require good reference data and evidence-based recommendations to be able to design effective health messages congruent with public health physical activity guidelines, guide behaviour change, and ultimately measure, track, and interpret steps/day.

Background The World Health Organization’s ‘Global Recommendations on Physical Activity for Health’ state that adults should engage in regular moderate-to-vigorous intensity aerobic physical activity (MVPA; e.g. walking, running, cycling) and muscle-strengthening activity (MSA; e.g. strength/resistance training). However, assessment of both MVPA and MSA is rare in physical activity surveillance. The aim of this study is to describe the prevalence, correlates and chronic health conditions associated with meeting the combined MVPA-MSA guidelines among a population representative sample of U.S. adults. Methods In this cross-sectional study, data were drawn from the U.S. 2015 Behavioral Risk Factor Surveillance System. During telephone interviews, MVPA and MSA were assessed using validated questionnaires. We calculated the proportions meeting both the global MVPA and MSA physical activity guidelines (MVPA ≥150 min/week and MSA ≥2 sessions/week). Poisson regressions with a robust error variance were used to assess: (i) prevalence ratios (PR) for meeting both guidelines across sociodemographic factors (e.g. age, sex, education, income, race/ethnicity); and (ii) PRs of 12 common chronic health conditions (e.g. diabetes, coronary heart disease, hypertension, depression) across different categories of physical activity guideline adherence (met neither [reference]; MSA only; MVPA only; met both). Results Among 383,928 adults (aged 18–80 years), 23.5% (95% CI: 20.1, 20.6%) met the combined MVPA-MSA guidelines. Those with poorer self-rated health, older adults, women, lower education/income and current smokers were less likely to meet the combined guidelines. After adjustment for covariates (e.g. age, self-rated health, income, smoking) compared with meeting neither guidelines, MSA only and MVPA only, meeting the combined MVPA-MSA guidelines was associated with the lowest PRs for all health conditions (APR range: 0.44–0.76), and the clustering of ≥6 chronic health conditions (APR = 0.33; 95% CI: 0.31–0.35). Conclusions Eight out of ten U.S. adults do not meet the global physical activity guidelines. This study supports the need for comprehensive health promotion strategies to increase the uptake and adherence of MVPA-MSA among U.S. adults. Large-scale interventions should target specific population sub-groups including older adults, women, those with poorer health and lower education/income. Electronic supplementary material The online version of this article (10.1186/s12966-019-0797-2) contains supplementary material, which is available to authorized users.

Light-intensity physical activity could play a role in improving adult cardiometabolic health and reducing mortality risk. Frequent short bouts of light activity improve glycaemic control. Nevertheless, the modest volume of the prospective epidemiological evidence base and the moderate consistency between observational and laboratory evidence inhibits definitive conclusions.

BackgroundMobile technologies have great potential to promote an active lifestyle in lower educated working young adults, an underresearched target group at a high risk of low activity levels.ObjectiveThe objective of our study was to examine the effect and process evaluation of the newly developed evidence- and theory-based smartphone app “Active Coach” on the objectively measured total daily physical activity; self-reported, context-specific physical activity; and self-reported psychosocial variables among lower educated working young adults.MethodsWe recruited 130 lower educated working young adults in this 2-group cluster randomized controlled trial and assessed outcomes at baseline, posttest (baseline+9 weeks), and follow-up (posttest+3 months). Intervention participants (n=60) used the Active Coach app (for 9 weeks) combined with a Fitbit activity tracker. Personal goals, practical tips, and educational facts were provided to encourage physical activity. The control group received print-based generic physical activity information. Both groups wore accelerometers for objective measurement of physical activity, and individual interviews were conducted to assess the psychosocial variables and context-specific physical activity. Furthermore, intervention participants were asked process evaluation questions and generalized linear mixed models and descriptive statistics were applied.ResultsNo significant intervention effects were found for objectively measured physical activity, self-reported physical activity, and self-reported psychosocial variables (all P>.05). Intervention participants evaluated the Active Coach app and the combined use with the Fitbit wearable as self-explanatory (36/51, 70.6%), user friendly (40/51, 78.4%), and interesting (34/51, 66.7%). Throughout the intervention, we observed a decrease in the frequency of viewing graphical displays in the app (P<.001); reading the tips, facts, and goals (P<.05); and wearing the Fitbit wearable (P<.001). Few intervention participants found the tips and facts motivating (10/41, 24.4%), used them to be physically active (8/41, 19.6%), and thought they were tailored to their lifestyle (7/41, 17.1%).ConclusionsThe lack of significant intervention effects might be due to low continuous user engagement. Advice or feedback that was not perceived as adequately tailored and the difficulty to compete with many popular commercial apps on young people’s smartphones may be responsible for a decrease in the engagement. A stand-alone app does not seem sufficient to promote an active lifestyle among lower educated working young adults; therefore, multicomponent interventions (using both technological and human support), as well as context-specific sensing to provide tailored advice, might be needed in this population.Trial RegistrationClinicalTrials.gov NCT02948803; https://clinicaltrials.gov/ct2/show/results/NCT02948803 (Archived by WebCite at http://www.webcitation.org/71OPFwaoA)

BackgroundOccupational sitting can be the largest contributor to overall daily sitting time in white-collar workers. With adverse health effects in adults, intervention strategies to influence sedentary time on a working day are needed. Therefore, the present aim was to examine employees’ and executives’ reflections on occupational sitting and to examine the potential acceptability and feasibility of intervention strategies to reduce and interrupt sedentary time on a working day.MethodsSeven focus groups (four among employees, n = 34; three among executives, n = 21) were conducted in a convenience sample of three different companies in Flanders (Belgium), using a semi-structured questioning route in five themes [personal sitting patterns; intervention strategies during working hours, (lunch) breaks, commuting; and intervention approach]. The audiotaped interviews were verbatim transcribed, followed by a qualitative inductive content analysis in NVivo 10.ResultsThe majority of participants recognized they spend their working day mostly sitting and associated this mainly with musculoskeletal health problems. Participants suggested a variety of possible strategies, primarily for working hours (standing during phone calls/meetings, PC reminders, increasing bathroom use by drinking more water, active sitting furniture, standing desks, rearranging the office) and (lunch) breaks (physical activity, movement breaks, standing tables). However, several barriers were reported, including productivity concerns, impracticality, awkwardness of standing, and the habitual nature of sitting. Facilitating factors were raising awareness, providing alternatives for simply standing, making some strategies obligatory and workers taking some personal responsibility.ConclusionsThere are some strategies targeting sedentary time on a working day that are perceived to be realistic and useful. However several barriers emerged, which future trials and practical initiatives should take into account.

This current opinion provides an overview of the emerging discipline of muscle-strengthening exercise epidemiology. First, we define muscle-strengthening exercise, and discuss its recent addition into the global physical activity guidelines, which were historically mainly focused on aerobic physical activity (walking, running, cycling etc.). Second, we provide an overview of the current clinical and epidemiological evidence on the associations between muscle-strengthening exercise and health, showing a reduced mortality risk, and beneficial cardiometabolic, musculoskeletal, functional and mental health-related outcomes. Third, we describe the latest epidemiological research on the assessment, prevalence, trends and correlates of muscle-strengthening exercise. An overview of recent population estimates suggests that the proportion of adults meeting the current musclestrengthening exercise guideline (10-30%; ≥ 2 sessions/week) is far lower than adults reporting meeting the aerobic exercise guideline (~50%; ≥ 150 min/week). Fourth, we discuss the complexity of muscle-strengthening exercise promotion, highlighting the need for concurrent, coordinated, and multiple-level strategies to increase populationlevel uptake/adherence of this exercise modality. Last, we explore key research gaps and strategies that will advance the field of muscle-strengthening exercise epidemiology. Our objective is to provide a case for increased emphasis on the role of muscle-strengthening exercise for chronic disease prevention, and most importantly, stimulate more research in this currently understudied area of physical activity epidemiology.

BackgroundComputer-tailored physical activity (PA) interventions delivered through the Internet represent a promising and appealing method to promote PA at a population level. However, personalized advice is mostly provided based on subjectively measured PA, which is not very accurate and might result in the delivery of advice that is not credible or effective. Therefore, an innovative computer-tailored PA advice was developed, based on objectively pedometer-measured PA.ObjectiveThe study aim was to evaluate the effectiveness of a computer-tailored, pedometer-based PA intervention in working adults.MethodsParticipants (≥18 years) were recruited between May and December 2012 from eight Flemish workplaces. These workplaces were allocated randomly to an intervention or control group. Intervention group participants (n=137) received (1) a booklet with information on how to increase their steps, (2) a non-blinded pedometer, and (3) an Internet link to request computer-tailored step advice. Control group participants (n=137) did not receive any of the intervention components. Self-reported and pedometer-based PA were assessed at baseline (T0), and 1 month (T1) and 3 months (T2) months post baseline. Repeated measures analyses of covariance were used to examine intervention effects for both the total sample and the at-risk sample (ie, adults not reaching 10,000 steps a day at baseline).ResultsThe recruitment process resulted in 274 respondents (response rate of 15.1%) who agreed to participate, of whom 190 (69.3%) belonged to the at-risk sample. Between T0 and T1 (1-month post baseline), significant intervention effects were found for participants’ daily step counts in both the total sample (P=.004) and the at-risk sample (P=.001). In the at-risk sample, the intervention effects showed a daily step count increase of 1056 steps in the intervention group, compared to a decrease of 258 steps in the control group. Comparison of participants’ self-reported PA revealed a significant intervention effect for time spent walking in the at-risk sample (P=.02). Intervention effects were still significant 3 months post baseline for participants’ daily step counts in both the total sample (P=.03) and the at-risk sample (P=.02); however, self-reported PA differences were no longer significant.ConclusionsA computer-tailored, pedometer-based PA intervention was effective in increasing both pedometer-based and self-reported PA levels, mainly in the at-risk participants. However, more effort should be devoted to recruit and retain participants in order to improve the public health impact of the intervention.Trial RegistrationClinicalTrials.gov: NCT02080585; https://clinicaltrials.gov/ct2/show/NCT02080585 (Archived by WebCite at http://www.webcitation.org/6VvQnRQSy).

Objective: To describe self-reported physical activity (PA) patterns in the various domains (school, home, transport, leisure time) and intensity categories (walking, moderate PA, vigorous PA) in European adolescents. Furthermore, self-reported PA patterns were evaluated in relation to gender, age category, weight status category and socio-economic status (SES). Design: Cross-sectional study. Setting: Ten European cities. Subjects: In total, 3051 adolescents (47?6 % boys, mean age 14?8 (SD 1?2) years) completed an adolescent-adapted version of the validated International Physical Activity Questionnaire. Results: The total sample reported most PA during leisure time (485 min/week) and least PA at home (140 min/week). Boys reported significantly more school-based PA (P , 0?001), leisure-time PA (P 5 0?003), vigorous PA (P , 0?001) and total PA (P 5 0?002) than girls, while girls reported more home-based PA (P , 0?001) and walking (P 5 0?002) than boys. Self-reported PA at school (P , 0?001), moderate PA (P , 0?001), vigorous PA (P , 0?001) and total PA (P , 0?001) were significantly higher in younger age groups than in older groups. Groups based on weight status differed significantly only in leisure-time PA (P 5 0?004) and total PA (P 5 0?003), while groups based on SES differed in all PA domains and intensities except transport-related PA and total PA. Conclusions: The total sample of adolescents reported different scores for the different PA domains and intensity categories. Furthermore, patterns were different according the adolescents' gender, age, weight status and SES.