Worldwide, public health physical activity guidelines include special emphasis on populations of children (typically 6-11 years) and adolescents (typically 12-19 years). Existing guidelines are ...commonly expressed in terms of frequency, time, and intensity of behaviour. However, the simple step output from both accelerometers and pedometers is gaining increased credibility in research and practice as a reasonable approximation of daily ambulatory physical activity volume. Therefore, the purpose of this article is to review existing child and adolescent objectively monitored step-defined physical activity literature to provide researchers, practitioners, and lay people who use accelerometers and pedometers with evidence-based translations of these public health guidelines in terms of steps/day. In terms of normative data (i.e., expected values), the updated international literature indicates that we can expect 1) among children, boys to average 12,000 to 16,000 steps/day and girls to average 10,000 to 13,000 steps/day; and, 2) adolescents to steadily decrease steps/day until approximately 8,000-9,000 steps/day are observed in 18-year olds. Controlled studies of cadence show that continuous MVPA walking produces 3,300-3,500 steps in 30 minutes or 6,600-7,000 steps in 60 minutes in 10-15 year olds. Limited evidence suggests that a total daily physical activity volume of 10,000-14,000 steps/day is associated with 60-100 minutes of MVPA in preschool children (approximately 4-6 years of age). Across studies, 60 minutes of MVPA in primary/elementary school children appears to be achieved, on average, within a total volume of 13,000 to 15,000 steps/day in boys and 11,000 to 12,000 steps/day in girls. For adolescents (both boys and girls), 10,000 to 11,700 may be associated with 60 minutes of MVPA. Translations of time- and intensity-based guidelines may be higher than existing normative data (e.g., in adolescents) and therefore will be more difficult to achieve (but not impossible nor contraindicated). Recommendations are preliminary and further research is needed to confirm and extend values for measured cadences, associated speeds, and MET values in young people; continue to accumulate normative data (expected values) for both steps/day and MVPA across ages and populations; and, conduct longitudinal and intervention studies in children and adolescents required to inform the shape of step-defined physical activity dose-response curves associated with various health parameters.
Aging-related cognitive decline and cognitive impairment greatly impacts older adults' daily life. The worldwide ageing of the population and associated wave of dementia urgently calls for prevention ...strategies to reduce the risk of cognitive decline. Physical activity (PA) is known to improve cognitive function at older age through processes of neuroplasticity. Yet, emerging studies suggest that larger cognitive gains may be induced when PA interventions are combined with cognitive activity (CA). This meta-analysis evaluates these potential synergistic effects by comparing cognitive effects following combined PA + CA interventions to PA interventions (PA only), CA interventions (CA only) and control groups.
Pubmed, Embase, PsycInfo, CINAHL and Sportdiscus were searched for English peer-reviewed papers until April 2018. Data were extracted on cognition and factors potentially influencing the cognitive effects: mode of PA + CA combination (sequential or simultaneous), session frequency and duration, intervention length and study quality. Differences between older adults with and without mild cognitive impairments were also explored.
Forty-one studies were included. Relative to the control group, combined PA + CA intervention showed significantly larger gains in cognition (g = 0.316; 95% CI 0.188-0.443; p < .001). Studies that compared combined PA + CA with PA only, showed small but significantly greater cognitive improvement in favor of combined interventions (g = 0.160; 95% CI 0.041-0.279; p = .008). No significant difference was found between combined PA + CA and CA only interventions. Furthermore, cognitive effects tended to be more pronounced for studies using simultaneous designs (g = 0.385; 95%CI 0.214-0.555; p < .001) versus sequential designs (g = 0.114; 95%CI -0.102- 0.331, p = .301). Effects were not moderated by session frequency, session duration, intervention length or study quality. Also, no differences in effects were found between older adults with and without mild cognitive impairments.
Findings of the current meta-analysis suggest that PA programs for older adults could integrate challenging cognitive exercises to improve cognitive health. Combined PA + CA programs should be promoted as a modality for preventing as well as treating cognitive decline in older adults. Sufficient cognitive challenge seems more important to obtain cognitive effects than high doses of intervention sessions.
Positive associations between motor competence and physical activity have been identified by means of variable-centered analyses. To expand the understanding of these associations, this study used a ...person-centered approach to investigate whether different combinations (i.e., profiles) of actual and perceived motor competence exist (aim 1); and to examine differences in physical activity levels (aim 2) and weight status (aim 3) among children with different motor competence-based profiles.
Children's (N = 361; 180 boys = 50%; Mage = 9.50±1.24yrs) actual motor competence was measured with the Test of Gross Motor Development-2 and their perceived motor competence via the Self Perception Profile for Children. We assessed physical activity via accelerometers; height through stadiometers, and weight through scales. Cluster analyses (aim 1) and MANCOVAs (aim 2 & 3) were used to analyze the data.
The analysis generated two predictable groups: one group displaying relatively high levels of both actual (M TGMD-2 percentile = 42.54, SD = 2.33) and perceived motor competence (M = 3.42, SD = .37; high-high), and one group with relatively low levels of both (M percentile = 9.71, SD = 3.21; M PMC = 2.52, SD = .35; low-low). One additional group was also identified as having relatively low levels of actual motor competence (M percentile = 4.22, SD = 2.85) but relatively high levels of perceived motor competence (M = 3.52, SD = .30; low-high). The high-high group demonstrated higher daily physical activity (M = 48.39±2.03) and lower BMI (M = 18.13±.43) than the low-low group (MMVPA = 37.93±2.01; MBMI = 20.22±.42). The low-high group had similar physical activity-levels as the low-low group (M = 36.21±2.18) and did not significantly differ in BMI (M = 19.49±.46) from the other two groups.
A combination of high actual and perceived motor competence is related to higher physical activity and lower weight status. It is thus recommended to expand health interventions in children with components that foster the development of both actual and perceived motor competence. Health professionals should furthermore pay sufficient attention to endorsing children's actual and perceived motor competence.
The current study aimed to understand the perceptions and experiences of Iranian parents and principals of preschool children on weight management based on the PRECEDE-PROCEED Model (PPM), a ...comprehensive structure for assessing health needs for designing, implementing, and evaluating health promotion, and other public health programs. PRECEDE provides a structure for planning a targeted and focused public health program, and PROCEED provides a structure for implementing and evaluating the program. Data were gathered from 17 preschoolers’ parents and two principals using semi-structured interviews in the preschool setting in Tehran, the capital of Iran, in 2019. Data were analyzed manually through directed content analysis based on constructs in phases two and three of the PPM, simultaneously with data collection. This study identified genetic, behavioral (e.g., food preferences, physical activity, sedentary behaviors, the effect of parents’, peers’, principals’ and teachers’ behavior and also influence of grandparents’ and neighbors’ behaviors) and environmental (e.g., home, grandparents’ home and preschool) factors from the epidemiological construct. Also, predisposing (e.g., child’s attitude, parent’s and principals’ attitude, as well as parents’ knowledge and parents’ and principals’ beliefs), enabling (e.g., parental skills and skills of the principals and teachers, rules and laws in the preschools, and availability), and reinforcing (e.g., family support and influences, teachers’ encouragement and influences, and peers’ influences) factors were identified from the educational and ecological construct. Additionally, “quality of child-parent relationship” was determined as a new factor affecting preschoolers’ weight management promotion; however, it was not in the PPM. In the study, parents’ and principals’ experiences regarding preschoolers’ weight management promotion confirmed the genetic, behavioral, environmental, predisposing, enabling and reinforcing factors of the PPM. “Quality of child-parent relationship” factor may be related to the culture and family relationship type of Iranian people, which is suggested to be investigated in future studies.
The start of retirement is an important stage in an (older) adult's life and can affect physical activity (PA) and/or sedentary behaviors, making it an ideal period to implement health interventions. ...To identify the most optimal timing of such interventions it is important to determine how PA and sedentary behaviors change not only when making the transition to retirement, but also during the first years of retirement. The main study aim was to examine whether PA and sedentary behaviors change differently in retiring adults compared with recently retired adults. A second aim was to examine potential moderating effects of gender and educational level.
A longitudinal study was conducted in Ghent, Belgium. Baseline measurements took place in 2012-2013 and follow-up data were collected 2 years later. In total, 446 adults provided complete data at both time points. Of the participants 105 adults were not retired at baseline but retired between baseline and follow-up (i.e. retiring) and 341 were already retired at baseline (i.e. recently retired). All participants completed a questionnaire on PA, sedentary behaviors, socio-demographic factors and physical functioning. Repeated measures MANOVAs were conducted in SPSS 22.0. to analyze the data.
Leisure-time cycling increased over time in retiring adults, but decreased in recently retired adults (p < 0.01). (Voluntary) work-related walking and moderate-to-vigorous PA decreased strongly in retiring adults, while slight increases were found in recently retired adults (p < 0.001 and p < 0.01). Passive transport decreased more strongly in recently retired than in retiring adults (p < 0.05), and computer use increased more in retiring adults than in the recently retired group (p < 0.001). Low-educated recently retired adults had the strongest decrease in walking for transport (p < 0.05) and strongest increase in TV viewing time (p < 0.01) and computer use (p < 0.10). For gender, almost no moderating effects were found.
Future interventions should focus on PA and/or specific sedentary behaviors in retiring adults, but should definitely include long-term follow-up, as recently retired adults seem to be prone to lapse into an unhealthy lifestyle. Specific attention should be paid to low-educated adults as they are particularly susceptible to a decrease in PA and increased TV viewing time and computer use.
In July, 2019, the World Health Organization (WHO) commenced work to update the 2010 Global Recommendations on Physical Activity for Health and established a Guideline Development Group (GDG) ...comprising expert public health scientists and practitioners to inform the drafting of the 2020 Guidelines on Physical Activity and Sedentary Behavior. The overall task of the GDG was to review the scientific evidence and provide expert advice to the WHO on the amount of physical activity and sedentary behavior associated with optimal health in children and adolescents, adults, older adults (> 64 years), and also specifically in pregnant and postpartum women and people living with chronic conditions or disabilities.
The GDG reviewed the available evidence specific to each sub-population using systematic protocols and in doing so, identified a number of gaps in the existing literature. These proposed research gaps were discussed and verified by expert consensus among the entire GDG.
Evidence gaps across population sub-groups included a lack of information on: 1) the precise shape of the dose-response curve between physical activity and/or sedentary behavior and several of the health outcomes studied; 2) the health benefits of light-intensity physical activity and of breaking up sedentary time with light-intensity activity; 3) differences in the health effects of different types and domains of physical activity (leisure-time; occupational; transportation; household; education) and of sedentary behavior (occupational; screen time; television viewing); and 4) the joint association between physical activity and sedentary time with health outcomes across the life course. In addition, we acknowledge the need to conduct more population-based studies in low- and middle-income countries and in people living with disabilities and/or chronic disease, and to identify how various sociodemographic factors (age, sex, race/ethnicity, socioeconomic status) modify the health effects of physical activity, in order to address global health disparities.
Although the 2020 WHO Guidelines for Physical Activity and Sedentary Behavior were informed by the most up-to-date research on the health effects of physical activity and sedentary time, there is still substantial work to be done in advancing the global physical activity agenda.
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.
Sedentary behavior occurs largely subconsciously, and thus specific behavior change techniques are needed to increase conscious awareness of sedentary behavior. Chief amongst these behavior change ...techniques is self-monitoring of sedentary behavior. The aim of this systematic review and meta-analysis was to evaluate the short-term effectiveness of existing interventions using self-monitoring to reduce sedentary behavior in adults.
Four electronic databases (PubMed, Embase, Web of Science, and The Cochrane Library) and grey literature (Google Scholar and the International Clinical Trials Registry Platform) were searched to identify appropriate intervention studies. Only (cluster-)randomized controlled trials that 1) assessed the short-term effectiveness of an intervention aimed at the reduction of sedentary behavior, 2) used self-monitoring as a behavior change technique, and 3) were conducted in a sample of adults with an average age ≥ 18 years, were eligible for inclusion. Relevant data were extracted, and Hedge's g was used as the measure of effect sizes. Random effects models were performed to conduct the meta-analysis.
Nineteen intervention studies with a total of 2800 participants met the inclusion criteria. Results of the meta-analyses showed that interventions using self-monitoring significantly reduced total sedentary time (Hedges g = 0,32; 95% CI = 0,14 - 0,50; p = 0,001) and occupational sedentary time (Hedge's g = 0,56; 95% CI = 0,07 - 0,90; p = 0,02) on the short term. Subgroup analyses showed that significant intervention effects were only found if objective self-monitoring tools were used (g = 0,40; 95% CI = 0,19 - 0,60; p < 0,001), and if the intervention only targeted sedentary behavior (g = 0,45; 95% CI = 0,15-0,75; p = 0,004). No significant intervention effects were found on the number of breaks in sedentary behavior.
Despite the small sample sizes, and the large heterogeneity, results of the current meta-analysis suggested that interventions using self-monitoring as a behavior change technique have the potential to reduce sedentary behavior in adults. If future - preferably large-scale studies - can prove that the reductions in sedentary behavior are attributable to self-monitoring and can confirm the sustainability of this behavior change, multi-level interventions including self-monitoring may impact public health by reducing sedentary behavior.
Fathers are important in establishing healthy behaviors in their children, but are rarely engaged in lifestyle programs. Focusing on physical activity (PA) of both fathers and their children by ...engaging them together in PA (i.e. "co-PA") is therefore a promising novel strategy for interventions. The study aim was to investigate the effect of the 'Run Daddy Run' on co-PA and PA of fathers and their children, and secondary outcomes such as weight status and sedentary behaviour (SB).
This study is a non-randomized controlled trial (nRCT), including 98 fathers and one of their 6 to 8 years old children (intervention = 35, control = 63). The intervention was implemented over a 14-week period, and consisted of six (inter)active father-child sessions and an online component. Due to COVID-19, only 2/6 sessions could be implemented as planned, the remaining sessions were delivered online. In November 2019-January 2020 pre-test measurements took place, and post-test measurements in June 2020. Additional follow-up test was conducted in November 2020. PA (i.e. LPA, MPA, VPA and volume) of fathers and children were objectively measured using accelerometry, co-PA and the secondary outcomes were questioned using an online questionnaire.
Significant intervention effects were found for co-PA (+ 24 min./day in the intervention compared to the control group, p = 0.002), and MPA of the father (+ 17 min./day, p = 0.035). For children, a significant increase in LPA (+ 35 min./day, p < 0.001) was found. However, an inverse intervention effect was found for their MPA and VPA (-15 min./day, p = 0.005 and - 4 min./day, p = 0.002, respectively). Also decreases in fathers' and children's SB were found (-39 min./day, p = 0.022 and - 40 min./day, p = 0.003, respectively), but no changes in weight status, the father-child relationship, and the PA-family health climate (all p > 0.05).
The Run Daddy Run intervention was able to improve co-PA, MPA of fathers and LPA of children, and decreasing their SB. Inverse intervention effects were however found for MPA and VPA of children. These results are unique given their magnitude and clinical relevance. Targeting fathers together with their children might be a novel and potential intervention strategy to improve overall physical activity levels, however, further efforts should however be made to target children's MPA and VPA. Last, replicating these findings in a randomized controlled trial (RCT) is recommended for future research.
This study is registered as a clinical trial (clinicaltrials.gov, ID number: NCT04590755, date: 19/10/2020).
Abstract Objective To investigate whether neighborhood walkability (higher residential density, land use mix, street connectivity) is positively associated with physical activity in Belgian adults ...and whether this association is moderated by neighborhood SES. Methods The Belgian Environmental Physical Activity Study (BEPAS) was conducted in Ghent, Belgium. Data were collected between May 2007 and September 2008. Twenty-four neighborhoods were selected, stratified on GIS-based walkability and neighborhood SES. In total, 1200 adults (aged 20–65 years; 50 per neighborhood) completed the International Physical Activity Questionnaire and wore an accelerometer for seven days. After omitting participants with missing accelerometer data, the final sample consisted of 1166 adults. Results Living in a high-walkable neighborhood was associated with more accelerometer-based minutes of moderate-to-vigorous physical activity (38.6 vs. 31.8 min/day, p < 0.001), transportational walking and cycling, recreational walking, and less motorized transport (all p < 0.05). Low neighborhood SES was related to more cycling for transport and less motorized transport (all p < 0.05). No interactions between walkability and neighborhood SES were found. Conclusions The BEPAS results generally confirmed the findings from Australia and the US showing that, in Europe, walkability is also positively related to physical activity. As neighborhood SES was not a significant moderator, walkability appears beneficial for all economic strata.
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