Do community-wide interventions increase physical activity? S1TEP

Background Not getting enough physical activity leads to poorer health. Regular physical activity can reduce the risk of chronic disease and improve one’s health and well-being. The lack of physical activity is a common and growing problem in many countries. We sought to evaluate the effects of community wide, multi-strategic interventions upon the physical activity patterns of populations. Method We undertook a Cochrane Systematic Review which included an extensive search of databases, including studies which met pre-determined criteria, and conducted independent risk of bias assessment and data extraction. Results After the selection process, 25 studies were included in the review. The strategies varied by the number and type of components and their intensity. No studies were identified as low risk of bias. Sixteen studies were identified as having a high risk of bias and thus untrustworthy. Nine studies were of considered to have an unclear risk of bias and some studies held back data they collected. The effects reported were inconsistent across the studies and the measures. Some of the better designed studies showed no improvement in measures of physical activity. Interventions which have an environmental change component seemed to be a promising direction. Those interventions which were primarily a mass media campaign were less likely to be successful. Conclusions Although numerous studies have been undertaken, there is considerable inconsistency in the findings of the available studies and this is confounded by serious methodological issues within the included studies. Simply combining interventions does not necessarily result in increased physical activity as many such studies, including some long term programs, failed to demonstrate efficacy. There is a clear need for well-designed studies and these studies should focus on the quality of measurement of physical activity. The review is currently being updated with newer studies.

Objective measurement of physical activity in youth : current issues, future directions

Second-generation activity monitors have revolutionized the way in which we measure youth physical activity. Use of the monitors avoids the problems associated with self-report methods and allows for the estimation of physical activity patterns over time. This article examines important methodological issues related to the use of activity monitors in children and adolescents.

Activity patterns of preschool-aged children at risk for obesity

BACKGROUND Although the prevalence of obesity in young children highlights the importance of early interventions to promote physical activity (PA), there are limited data on activity patterns in this age group. The purpose of this study is to describe activity patterns in preschool-aged children and explore differences by weight status. METHODS Analyses use baseline data from Healthy Homes/Healthy Kids- Preschool, a pilot obesity prevention trial of preschool-aged children overweight or at risk for overweight. A modified parent-reported version of the previous-day PA recall was used to summarize types of activity. Accelerometry was used to summarize daily and hourly activity patterns. RESULTS "Playing with toys" accounted for the largest proportion of a child's previous day, followed by "meals and snacks", and "chores". Accelerometry-measured daily time spent in sedentary behavior, light PA, and moderate-to-vigorous PA (MVPA) was 412, 247, and 69 minutes, respectively. Percent of hourly time spent in MVPA ranged from 3% to 13%, peaking in the late morning and evening hours. There were no statistically significant MVPA differences by weight status. CONCLUSIONS This study extends our understanding of activity types, amounts, and patterns in preschool-age children and warrants further exploration of differences in physical activity patterns by weight status.

Analysis of physical activity in emmetropic and myopic university students during semester and holiday periods: A pilot study

Background Previous studies (mostly questionnaire-based in children) suggest that outdoor activity is protective against myopia. There are few studies on young adults investigating both the impact of simply being outdoors versus performing physical activity. The aim was to study the relationship between the refractive error of young adults and their physical activity patterns. Methods Twenty-seven university students, aged 18 to 25 years, wore a pedometer (Omron HJ720ITE) for seven days both during the semester and holiday periods. They simultaneously recorded the type of activity performed, its duration, the number of steps taken (from the pedometer) and their location (indoors/outdoors) in a logbook. Mean spherical refractive error was used to divide participants into three groups (emmetropes: +1.00 to -0.50 D, low myopes: -0.62 to -3.00 D, higher myopes: -3.12 D or greater myopia). Results There were no significant differences between the refractive groups during the semester or holiday periods; the average daily times spent outdoors, the duration of physical activity, the ratio of physical activity performed outdoors to indoors and amount of near work performed were similar. The peak exercise intensity was similar across all groups: approximately 100 steps perminute, a brisk walk. Up to one-third of all physical activity was performed outdoors. There were some significant differences in activities performed during semester and holiday times. For example, lowmyopes spent significantly less time outside (49 ± 47 versus 74 ± 41 minutes, p = 0.005) and performed less physical activity (6,388 ± 1,747 versus 6,779 ± 2,746 steps per day; p = 0.03) during the holidays compared to during semester. Conclusions The fact that all groups had similar low exercise intensity butmany were notmyopic suggests that physical activity levels are not critical. There were differences in the activity patterns of lowmyopes during semester and holiday periods. This study highlights the need for a larger longitudinal-based study with particular emphasis on how discretionary time is spent.

Learning from Outdoor Webcams: Surveillance of Physical Activity Across Environments

Abstract
Publicly available, outdoor webcams continuously view the world and share images. These cameras include traffic cams, campus cams, ski-resort cams, etc. The Archive of Many Outdoor Scenes (AMOS) is a project aiming to geolocate, annotate, archive, and visualize these cameras and images to serve as a resource for a wide variety of scientific applications. The AMOS dataset has archived over 750 million images of outdoor environments from 27,000 webcams since 2006. Our goal is to utilize the AMOS image dataset and crowdsourcing to develop reliable and valid tools to improve physical activity assessment via online, outdoor webcam capture of global physical activity patterns and urban built environment characteristics.
This project’s grand scale-up of capturing physical activity patterns and built environments is a methodological step forward in advancing a real-time, non-labor intensive assessment using webcams, crowdsourcing, and eventually machine learning. The combined use of webcams capturing outdoor scenes every 30 min and crowdsources providing the labor of annotating the scenes allows for accelerated public health surveillance related to physical activity across numerous built environments. The ultimate goal of this public health and computer vision collaboration is to develop machine learning algorithms that will automatically identify and calculate physical activity patterns.

Physical activity of children with developmental coordination disorder in the presence of attention deficit hyperactivity disorder : does gender matter?

Baerg, S., Cairney, J., Hay, J., Rempel, L. and Faught, B.E. (2009). Physical Activity of Children with Developmental Coordination Disorder in the Presence of Attention Deficit Hyperactivity Disorder: Does Gender Matter? Brock University, St. Catharines, Ontario, CANADA. Children with Developmental Coordination Disorder (DCD) have difficulties in motor coordination. Attention-deficit hyperactive disorder (ADHD) is considered the condition most co-morbid with DCD at approximately 50%. Children with DCD are generally less physically active (PA) than their peers, while children with ADHD are often considered more physically active. It is not known if the physical activity patterns of children with DCD-ADHD resemble those of children with primarily DCD or that of their healthy peers. The primary objective of this research was to contrast physical activity patterns between children with DCD, DCD-ADHD, and healthy controls. Since boys are generally reported as more physically active than girls, a secondary objective was to determine if gender moderated the association between groups and physical activity. A sample of males (n=66) and females (n=44) were recruited from the Physical Health Activity Study Team (PHAST) longitudinal study. The Movement Assessment Battery for Children (2nd Ed.) was used to identify probable cases of DCD, and Connor's Revised Parent Rating Scale- Short Version to identify ADHD. Subjects (mean age=12.8±.4 yrs) were allocated to three groups; DCD (n=32), DCD-ADHD (n=30) and control (n=48). Physical activity was monitored for seven days with the Actical® accelerometer (activity count, step count and energy expenditure). Children completed the Participation Questionnaire (PQ) during the in-school session of data collection for the PHAST study. Height, weight and body mass index (BMI) were also determined. Analysis of variance showed significant group differences for activity count (F(2,56)=5.36, p=.007) and PQ (F(2,44 )=6. 71, p=.003) in males, while a significant group difference for step count (F(2,37)=3.55, p=.04) was found in females. Post hoc comparison tests (Tukey) identified significantly lower PQ and activity count between males with OCD and controls (p=.004) and males with DCD-ADHD and controls (p=.003). Conversely, females with DCD-ADHD had significantly more step counts than their controls (p=.01). Analysis of covariance demonstrated a gender by DCD groups negative interaction for males (activity count) (F(2,92):;:3.11, p=.049) and a positive interaction for females (step count) (F(1,92)=4.92, p=.009). Hyperactivity in females with DCD-ADHD appears to contribute to more physical activity, whereas DCD may contribute to decreased activity in males with DCD and DCDADHD. Further research is needed to examine gender differences in physical activity within the context of DCD and ADHD.

Development of the Physical Activity Interactive Recall (PAIR) for Aboriginal children

Affiliation: Margaret Cargo : Département de médecine sociale et préventive, Faculté de médecine, Université de Montréal

Physical activity as a dimension of family life for lower primary school children

While questions of children's engagement in physical activity are being widely debated, little is known about how physical activity is valued and managed within families. This paper reports on qualitative data from a multi-method study on lower primary aged children. The focus of the broader study was to determine the relationships between young children's physical activity patterns, skills, and recreational interests, and their families' location, income, commitment to physical activity, and other responsibilities. Drawing on interviews with 12 purposively selected families, it was found that physical activity was highly valued across different family contexts, that children's engagement was shaped by their interests, friendships, and safety, and that issues such as income, family configuration, parental work commitments, and transport were potential barriers to further engagement.

Emerging adulthood and patterns of physical activity among young Australian women

The transition from adolescence to young adulthood is associated with a sharp decline in physical activity, particularly for women. This article explores the relations between physical activity status and change and status and change in four life domains: residential independence, employment status, relationship status, and motherhood. Two waves of survey data from a representative sample of 8,545 Australian women, aged 18-23 at Survey 1 and 22-27 at Survey 2, were analyzed. Cross-sectionally, physical inactivity was most strongly related to being a mother married, and not being in the labor force. Longitudinally, decreases in physical activity were most strongly associated with moving into a live-in relationship, with getting married, and with becoming a mother When considered in combination, women who were married with children and not employed outside the home were the most likely to be physically inactive. The data suggest that adoption of adult statuses, particularly traditional roles involving family relationships and motherhood, is associated with reductions in physical activity for these women, although it is possible that the effect is driven by socioeconomic factors associated with early transitions. The data suggest a need for interventions to promote continued physical activity among young women who cohabit or marry and among those not in the workforce, in addition to those supporting young mothers to be physically active.

Exploring the relationship between patterns of physical activity, sedentary behaviour and cardiometabolic health in middle-aged Irish adults

Background and Study Rationale Being physically active is a major contributor to both physical and mental health. More specifically, being physically active lowers risk of coronary heart disease, high blood pressure, stroke, metabolic syndrome (MetS), diabetes, certain cancers and depression, and increases cognitive function and wellbeing. The physiological mechanisms that occur in response to physical activity and the impact of total physical activity and sedentary behaviour on cardiometabolic health have been extensively studied. In contrast, limited data evaluating the specific effects of daily and weekly patterns of physical behaviour on cardiometabolic health exist. Additionally, no other study has examined interrelated patterns and minute-by-minute accumulation of physical behaviour throughout the day across week days in middle-aged adults. Study Aims The overarching aims of this thesis are firstly to describe patterns of behaviour throughout the day and week, and secondly to explore associations between these patterns and cardiometabolic health in a middle-aged population. The specific objectives are to: 1 Compare agreement between the International Physical Activity Questionnaire-Short Form (IPAQ-SF) and GENEActiv accelerometer-derived moderate-to-vigorous (MVPA) activity and secondly to compare their associations with a range of cardiometabolic and inflammatory markers in middle-aged adults. 2 Determine a suitable monitoring frame needed to reliably capture weekly, accelerometer-measured, activity in our population. 3 Identify groups of participants who have similar weekly patterns of physical behaviour, and determine if underlying patterns of cardiometabolic profiles exist among these groups. 4 Explore the variation of physical behaviour throughout the day to identify whether daily patterns of physical behaviour vary by cardiometabolic health. Methods All results in this thesis are based on data from a subsample of the Mitchelstown Cohort; 475 (46.1% males; mean aged 59.7±5.5 years) middle-aged Irish adults. Subjective physical activity levels were assessed using the IPAQ-SF. Participants wore the wrist GENEActiv accelerometer for 7 consecutive days. Data was collected at 100Hz and summarised into a signal magnitude vector using 60s epochs. Each time interval was categorised based on validated cut-offs. Data on cardiometabolic and inflammatory markers was collected according to standard protocol. Cardiometabolic outcomes (obesity, diabetes, hypertension and MetS) were defined according to internationally recognised definitions by World Health Organisation (WHO) and Irish Diabetes Federation (IDF). Results The results of the first chapter suggest that the IPAQ-SF lacks the sensitivity to assess patterning of activity and guideline adherence and assessing the relationship with cardiometabolic and inflammatory markers. Furthermore, GENEActiv accelerometer-derived MVPA appears to be better at detecting relationships with cardiometabolic and inflammatory markers. The second chapter examined variations in day-to-day physical behaviour levels between- and within-subjects. The main findings were that Sunday differed from all other days in the week for sedentary behaviour and light activity and that a large within-subject variation across days of the week for vigorous activity exists. Our data indicate that six days of monitoring, four weekdays plus Saturday and Sunday, are required to reliably estimate weekly habitual activity in all activity intensities. In the next chapter, latent profile analysis of weekly, interrelated patterns of physical behaviour identified four distinct physical behaviour patterns; Sedentary Group (15.9%), Sedentary; Lower Activity Group (28%), Sedentary; Higher Activity Group (44.2%) and a Physically Active Group (11.9%). Overall the Sedentary Group had poorer outcomes, characterised by unfavourable cardiometabolic and inflammatory profiles. The remaining classes were characterised by healthier cardiometabolic profiles with lower sedentary behaviour levels. The final chapter, which aimed to compare daily cumulative patterns of minute-by-minute physical behaviour intensities across those with and without MetS, revealed significant differences in weekday and weekend day MVPA. In particular, those with MetS start accumulating MVPA later in the day and for a shorted day period. Conclusion In conclusion, the results of this thesis add to the evidence base regards an optimal monitoring period for physical behaviour measurement to accurately capture weekly physical behaviour patterns. In addition, the results highlight whether weekly and daily distribution of activity is associated with cardiometabolic health and inflammatory profiles. The key findings of this thesis demonstrate the importance of daily and weekly physical behaviour patterning of activity intensity in the context of cardiometabolic health risk. In addition, these findings highlight the importance of using physical behaviour patterns of free-living adults observed in a population-based study to inform and aid health promotion activity programmes and primary care prevention and treatment strategies and development of future tailored physical activity based interventions.