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.

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. 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). 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). 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.

Background: Healthy behaviors are crucial for maintaining a person’s health and well-being. The effects of health behavior interventions are mediated by individual and contextual factors that vary over time. Recently emerging smartphone-based ecological momentary interventions (EMIs) can use real-time user reports (ecological momentary assessments [EMAs]) to trigger appropriate support when needed in daily life. Objective: This systematic review aims to assess the characteristics of smartphone-delivered EMIs using self-reported EMAs in relation to their effects on health behaviors, user engagement, and user perspectives. Methods: We searched MEDLINE, Embase, PsycINFO, and CINAHL in June 2019 and updated the search in March 2020. We included experimental studies that incorporated EMIs based on EMAs delivered through smartphone apps to promote health behaviors in any health domain. Studies were independently screened. The PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) guidelines were followed. We performed a narrative synthesis of intervention effects, user perspectives and engagement, and intervention design and characteristics. Quality appraisal was conducted for all included studies. Results: We included 19 papers describing 17 unique studies and comprising 652 participants. Most studies were quasi-experimental (13/17, 76%), had small sample sizes, and great heterogeneity in intervention designs and measurements. EMIs were most popular in the mental health domain (8/17, 47%), followed by substance abuse (3/17, 18%), diet, weight loss, physical activity (4/17, 24%), and smoking (2/17, 12%). Of the 17 studies, the 4 (24%) included randomized controlled trials reported nonstatistically significant effects on health behaviors, and 4 (24%) quasi-experimental studies reported statistically significant pre-post improvements in self-reported primary outcomes, namely depressive (P<.001) and psychotic symptoms (P=.03), drinking frequency (P<.001), and eating patterns (P=.01). EMA was commonly used to capture subjective experiences as well as behaviors, whereas sensors were rarely used. Generally, users perceived EMIs to be helpful. Common suggestions for improvement included enhancing personalization, multimedia and interactive capabilities (eg, voice recording), and lowering the EMA reporting burden. EMI and EMA components were rarely reported and were not described in a standardized manner across studies, hampering progress in this field. A reporting checklist was developed to facilitate the interpretation and comparison of findings and enhance the transparency and replicability of future studies using EMAs and EMIs. Conclusions: The use of smartphone-delivered EMIs using self-reported EMAs to promote behavior change is an emerging area of research, with few studies evaluating efficacy. Such interventions could present an opportunity to enhance health but need further assessment in larger participant cohorts and well-designed evaluations following reporting checklists. Future research should explore combining self-reported EMAs of subjective experiences with objective data passively collected via sensors to promote personalization while minimizing user burden, as well as explore different EMA data collection methods (eg, chatbots). Trial Registration: PROSPERO CRD42019138739; https://www.crd.york.ac.uk/prospero/display_record.php?RecordID=138739

Occupational 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. Seven 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. The 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. There 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.

Reliable and valid measures of total sedentary time, context-specific sedentary behaviour (SB) and its potential correlates are useful for the development of future interventions. The purpose was to examine test-retest reliability and criterion validity of three newly developed questionnaires on total sedentary time, context-specific SB and its potential correlates in adolescents, adults and older adults. Reliability and validity was tested in six different samples of Flemish (Belgium) residents. For the reliability study, 20 adolescents, 22 adults and 20 older adults filled out the age-specific SB questionnaire twice. Test-retest reliability was analysed using Kappa coefficients, Intraclass Correlation Coefficients and/or percentage agreement, separately for the three age groups. For the validity study, data were retrieved from 62 adolescents, 33 adults and 33 older adults, with activPAL™ as criterion measure. Spearman correlations and Bland-Altman plots (or non-parametric approach) were used to analyse criterion validity, separately for the three age groups and for weekday, weekend day and average day. The test-retest reliability for self-reported total sedentary time indicated following values: ICC = 0.37-0.67 in adolescents; ICC = 0.73-0.77 in adults; ICC = 0.68-0.80 in older adults. Item-specific reliability results (e.g. context-specific SB and its potential correlates) showed good-to-excellent reliability in 67.94 %, 68.90 % and 66.38 % of the items in adolescents, adults and older adults respectively. All items belonging to sedentary-related equipment and simultaneous SB showed good reliability. The sections of the questionnaire with lowest reliability were: context-specific SB (adolescents), potential correlates of computer use (adults) and potential correlates of motorized transport (older adults). Spearman correlations between self-reported total sedentary time and the activPAL™ were different for each age group: ρ = 0.02-0.42 (adolescents), ρ = 0.06-0.52 (adults), ρ = 0.38-0.50 (older adults). Participants over-reported total sedentary time (except for weekend day in older adults) compared to the activPAL™, for weekday, weekend day and average day respectively by +57.05 %, +46.29 %, +53.34 % in adolescents; +40.40 %, +19.15 %, +32.89 % in adults; +10.10 %, −6.24 %, +4.11 % in older adults. The questionnaires showed acceptable test-retest reliability and criterion validity. However, over-reporting of total SB was noticeable in adolescents and adults. Nevertheless, these questionnaires will be useful in getting context-specific information on SB.