Clinical use of objective measures of physical activity

With measurement of physical activity becoming more common in clinical practice, it is imperative that healthcare professionals become more knowledgeable about the different methods available to objectively measure physical activity behaviour. Objective measures do not rely on information provided by the patient, but instead measure and record the biomechanical or physiological consequences of performing physical activity, often in real time. As such, objective measures are not subject to the reporting bias or recall problems associated with self-report methods. The purpose of this article was to provide an overview of the different methods used to objectively measure physical activity in clinical practice. The review was delimited to heart rate monitoring, accelerometers and pedometers since their small size, low participant burden and relatively low cost make these objective measures appropriate for use in clinical practice settings. For each measure, strengths and weakness were discussed; and whenever possible, literature-based examples of implementation were provided.

Physical inactivity remains the greatest public health problem of the 21st century : evidence, improved methods and solutions using the '7 investments that work' as a framework

In 2009, BJSM's first editorial argued that ‘Physical inactivity is the greatest public health problem of the 21st century’.1 The data supporting that claim have not yet been challenged. Now, 5 years after BJSM published its first dedicated ‘Physical Activity is Medicine’ theme issue (http://bjsm.bmj.com/content/43/1.toc) we are pleased to highlight 23 new contributions from six countries. This issue contains an analysis of the cost of physical inactivity from the US Centre for Diseases Control.2 We also report the cost-effectiveness of one particular physical activity intervention for adults.3

Physical activity recognition from accelerometer data using a multi-scale ensemble method

Accurate and detailed measurement of an individual's physical activity is a key requirement for helping researchers understand the relationship between physical activity and health. Accelerometers have become the method of choice for measuring physical activity due to their small size, low cost, convenience and their ability to provide objective information about physical activity. However, interpreting accelerometer data once it has been collected can be challenging. In this work, we applied machine learning algorithms to the task of physical activity recognition from triaxial accelerometer data. We employed a simple but effective approach of dividing the accelerometer data into short non-overlapping windows, converting each window into a feature vector, and treating each feature vector as an i.i.d training instance for a supervised learning algorithm. In addition, we improved on this simple approach with a multi-scale ensemble method that did not need to commit to a single window size and was able to leverage the fact that physical activities produced time series with repetitive patterns and discriminative features for physical activity occurred at different temporal scales.

Physical activity patterns of inner-city elementary schoolchildren

Purpose This study aimed to objectively measure the physical activity (PA) characteristics of a racially and ethnically diverse sample of inner-city elementary schoolchildren and to examine the influence of sex, race/ethnicity, grade level, and weight status on PA. Methods A total of 470 students in grades 4-6 from six inner-city schools in Philadelphia wore an ActiGraph GT3X+ accelerometer (Actigraph, Pensacola, FL) for up to 7 d. The resultant data were uploaded to a customized Visual Basic EXCEL macro to determine the time spent in sedentary (SED), light-intensity PA (LPA), and moderate- to vigorous-intensity PA (MVPA). Results On average, students accumulated 48 min of MVPA daily. Expressed as a percentage of monitoring time, students were sedentary for 63% of the time, in LPA 31% of the time, and in MVPA 6% of the time. Across all race/ethnicity and grade level groups, boys exhibited significantly higher levels of MVPA than girls did; fifth-grade boys exhibited significantly lower MVPA levels than fourth-and sixth-grade boys did, and sixth-grade girls exhibited significantly lower MVPA levels than fourth-and fifth-grade girls did. Hispanic children exhibited lower levels of MVPA than children from other racial/ethnic groups did, and overweight and obese children exhibited significantly lower MVPA levels than children in the healthy weight range did. Across the entire sample, only 24.3% met the current public health guidelines for PA. Physical inactivity was significantly greater among females, Hispanics, and overweight and obese students. Conclusions Fewer than one in four inner-city schoolchildren accumulated the recommended 60 min of MVPA daily. These findings highlight the need for effective and sustainable programs to promote PA in inner-city youth.

Measuring and influencing physical activity with Smartphone technology : a systematic review

Background Rapid developments in technology have encouraged the use of smartphones in physical activity research, although little is known regarding their effectiveness as measurement and intervention tools. Objective This study systematically reviewed evidence on smartphones and their viability for measuring and influencing physical activity. Data Sources Research articles were identified in September 2013 by literature searches in Web of Knowledge, PubMed, PsycINFO, EBSCO, and ScienceDirect. Study Selection The search was restricted using the terms (physical activity OR exercise OR fitness) AND (smartphone* OR mobile phone* OR cell phone*) AND (measurement OR intervention). Reviewed articles were required to be published in international academic peer-reviewed journals, or in full text from international scientific conferences, and focused on measuring physical activity through smartphone processing data and influencing people to be more active through smartphone applications. Study Appraisal and Synthesis Methods Two reviewers independently performed the selection of articles and examined titles and abstracts to exclude those out of scope. Data on study characteristics, technologies used to objectively measure physical activity, strategies applied to influence activity; and the main study findings were extracted and reported. Results A total of 26 articles (with the first published in 2007) met inclusion criteria. All studies were conducted in highly economically advantaged countries; 12 articles focused on special populations (e.g. obese patients). Studies measured physical activity using native mobile features, and/or an external device linked to an application. Measurement accuracy ranged from 52 to 100 % (n = 10 studies). A total of 17 articles implemented and evaluated an intervention. Smartphone strategies to influence physical activity tended to be ad hoc, rather than theory-based approaches; physical activity profiles, goal setting, real-time feedback, social support networking, and online expert consultation were identified as the most useful strategies to encourage physical activity change. Only five studies assessed physical activity intervention effects; all used step counts as the outcome measure. Four studies (three pre–post and one comparative) reported physical activity increases (12–42 participants, 800–1,104 steps/day, 2 weeks–6 months), and one case-control study reported physical activity maintenance (n = 200 participants; >10,000 steps/day) over 3 months. Limitations Smartphone use is a relatively new field of study in physical activity research, and consequently the evidence base is emerging. Conclusions Few studies identified in this review considered the validity of phone-based assessment of physical activity. Those that did report on measurement properties found average-to-excellent levels of accuracy for different behaviors. The range of novel and engaging intervention strategies used by smartphones, and user perceptions on their usefulness and viability, highlights the potential such technology has for physical activity promotion. However, intervention effects reported in the extant literature are modest at best, and future studies need to utilize randomized controlled trial research designs, larger sample sizes, and longer study periods to better explore the physical activity measurement and intervention capabilities of smartphones.

Nutrition and physical activity policies and practices in family child care homes

Background Family child care homes (FCCHs) are the second-largest provider of nonrelative care in the U.S. However, despite providing care for nearly 1.9 million children aged <5 years, little is known about the nutrition and physical activity practices of FCCHs. Purpose To address this gap, this study aims to describe policies and practices related to nutrition and physical activity in a representative sample of FCCHs. Methods A stratified random sample of registered FCCHs operating in Kansas (N=297) completed the Nutrition and Physical Activity Self Assessment for Child Care (NAPSACC) instrument. Prevalence estimates and 95% CIs for meeting or exceeding accepted child care standards were calculated using SAS PROC SURVEYFREQ. Results Most providers either met or exceeded child care standards related to serving fruit and vegetables and provision of daily physical activity. Very few providers reported serving fried meats or vegetables or unhealthy snack foods on a regular basis. Areas of concern included infrequent servings of low-fat milk, frequent use of unhealthy foods for celebrations, widespread use of TV and video games throughout the day, restricting physical activity for children who misbehave, and lack of appropriate indoor spaces for physical activity. Only a small percentage of providers reported receiving regular training in nutrition or physical activity. Relatively few providers had written guidelines on nutrition or physical activity. Conclusions Some strengths were exhibited by FCCHs, but substantial weaknesses were shown with respect to meeting established child care standards for nutrition and physical activity. Interventions to promote healthy eating and regular physical activity in FCCHs are thus warranted.

Correlates of objectively measured physical activity in preadolescent youth

Objective The purpose of this study was to identify the psychosocial and environmental correlates of objectively measured physical activity behavior in a diverse sample of sixth-grade students. Design Cross-sectional. Participants and Setting One hundred ninety-eight sixth-grade students from 4 public middle schools in Columbia, South Carolina. The study group was 52.0% female, 55.1% African-American, with a mean age of 11.4 +/- 0.6 years. Main Outcome Measures Time spent in moderate physical activity (MPA) and vigorous physical activity (VPA) was assessed using a uniaxial accelerometer (CSA WAM 7164) (Computer Science and Applications Inc., Shalimar, FL). Determinant variables included: age, gender, race/ethnicity (demographic); physical activity self-efficacy, social norms related to physical activity, and beliefs regarding physical activity outcomes (psychosocial); and perceived physical activity habits of parents and peers, involvement in community physical activity organizations, involvement in community-based sports programs, access to fitness/sporting equipment at home, and self-reported hours spent watching television or playing video games (environmental). Results For boys, physical activity self-efficacy, social norms related to physical activity, and involvement in community physical activity organizations were salient predictors of MPA and VPA. Among girls, only physical activity self-efficacy emerged as a clear predictor of objectively measured physical activity. Conclusions These findings are consistent with previous studies using self-reported physical activity and suggest that interventions to increase physical. activity in preadolescent youth should endeavor to boost physical activity self-efficacy by offering a wide selection of enjoyable, developmentally-appropriate physical activity options.

Validation of a 24-h physical activity recall in indigenous and non-indigenous Australian adolescents

The purpose of this study was to evaluate the concurrent validity of a modified version of the widely used previous day physical activity recall (PDPAR24) self-report instrument in a diverse sample of Australian adolescents comprising Aboriginal and Torres Strait Islanders (A&TSI) and non-indigenous high school students. A sample of 63 A&TSI and 59 non-indigenous high school students (N = 122) from five public secondary schools participated in the study. Participants completed the PDPAR-24 after wearing a seated electronic pedometer on the previous day. Significant positive correlations were observed between the self-reported physical activity variables (mean MET level, blocks of vigorous activity, and blocks of moderate-to-vigorous physical activity) and 24-h step counts. Validity coefficients (rho) ranged from 0.29 to 0.34 (p<0.05). A significant inverse correlation was observed for self-reported screen time and 24-h step count (rho = -0.19, p<0.05). Correlations for A&TSI students were equal to or greater than those observed for non-indigenous students. The PDPAR-24 instrument is a quick, unobtrusive, and cost-effective assessment tool. that would be useful for evaluating physical activity and sedentary behaviour in population-based studies. (C) 2006 Sports Medicine Australia.

Effects of short-duration and long-duration exercise on lipoprotein(a)

Purpose Most studies that use either a single exercise session, exercise training, or a cross-sectional design have failed to find a relationship between exercise and plasma lipoprotein(a) [Lp(a)] concentrations. However, a few studies investigating the effects of longer and/or more strenuous exercise have shown elevated Lp(a) concentrations, possibly as an acute-phase reactant to muscle damage. Based on the assumption that greater muscle damage would occur with exercise of longer duration, the purpose of the present study was to determine whether exercise of longer duration would increase Lp(a) concentration and creatine kinase. (CK) activity more than exercise of shorter duration. Methods Ten endurance-trained men (mean +/- SD: age, 27 +/- 6 yr; maximal oxygen consumption [(V)over dotO(2max)], 57 +/- 7 mL(.)kg(-1) min(-1)) completed two separate exercise sessions at 70% (V)over dotO(2max). One session required 900 kcal of energy expenditure (60 +/- 6 min), and the other required 1500 kcal (112 +/- 12 min). Fasted blood samples were taken immediately before (0-pre), immediately after (0-post), 1 d after (1-post), and 2 d after (2-post) each exercise session. Results CK activity increased after both exercise sessions (mean +/- SE; 800 kcal: 0-pre 55 +/- 11, 1-post 168 +/- 64 U(.)L(-1.)min(-1); 1500 kcal: 0-pre 51 +/- 5, 1-post 187 +/- 30, 2-post 123 +/- 19 U(.)L(-1.)min(-1); P < 0.05). However, median Lp(a) concentrations were not altered by either exercise session (800 kcal: 0-pre 5.0 mg(.)dL(-1), 0-post 3.2 mg(.)dL(-1), 1-post 4.0 mg(.)dL(-1), 2-post 3.4 mg(.)dL(-1); 1500 kcal: 0-pre 5.8 mg(.)dL(-1), 0-post 4.3 mg(.)dL(-1), 1-post 3.2 mg(.)dL(-1), 2-post 5.3 mg(.)dL(-1)). In addition, no relationship existed between exercise-induced changes in CK activity and Lp(a) concentration (800 kcal: r = -0.26; 1500 kcal: r = -0.02). Conclusion These results suggest that plasma Lp(a) concentration will not increase in response to minor exercise-induced muscle damage in endurance-trained runners.

Tracking of physical activity in young children

The purpose of this study was to determine whether physical activity behavior tracks during early childhood. Forty-seven children (22 males, 25 females) aged 3-4 yr at the beginning of the study were followed over a 3-yr period. Heart rates were measured at least 2 and up to 4 d . yr(-1) with a Quantum XL Telemetry heart rate monitor. Physical activity was quantified as the percentage of observed minutes between 3:00 and 6:00 p.m. during which heart rate was 50% or more above individual resting heart rate (PAHR-50 Index). Tracking of physical activity was analyzed using Pearson and Spearman correlations. Yearly PAHR-50 index tertiles were created and examined for percent agreement and Cohen's kappa. Repeated measures ANOVA was used to calculate the intraclass correlation coefficient across the 3 yr of the study. Spearman rank order correlations ranged from 0.57 to 0.66 (P < 0.0001). Percent agreement ranged from 49% to 62%. The intraclass R for the 3 yr was 0.81. It was concluded that physical activity behavior tends to track during early childhood.

Using objective physical activity measures with youth : How many days of monitoring are needed?

Purpose The purpose of this study was to establish the minimal number of days of monitoring required for accelerometers to assess usual physical activity in children. Methods A total of 381 students (189 M, 192 F) wore a CSA 7164 uniaxial accelerometer for seven consecutive days. To examine age-related trends students were grouped as follows: Group I: grades 1-3 (N = 92); Group II: grades 4-6 (N = 98); Group III: grades 7-9 (N = 97); Group IV: grades 10-12 (N = 94). Average daily time spent in moderate-to-vigorous physical activity (MVPA) was calculated from minute-by-minute activity counts using the regression equation developed by Freedson et al. (1997). Results Compared with adolescents in grades 7 to 12, children in grades 1 to 6 exhibited less day-to-day variability in MVPA behavior. Spearman-Brown analysts indicated that between 4 and 5 d of monitoring would be necessary to a achieve a reliability of 0.80 in children, and between 8 and 9 d of monitoring would be necessary to achieve a reliability of 0.80 in adolescents. Within all grade levels, the 7-d monitoring protocol produced acceptable estimates of daily participation in MVPA (R = 0.76 (0.71-0.81) to 0.87 (0.84-0.90)). Compared with weekdays, children exhibited significantly higher levels of MVPA on weekends, whereas adolescents exhibited significantly lower levels of MVPA on weekends. Principal components analysis revealed two distinct time components for MVPA during the day for children (early morning, rest of the day), and three distinct time components for MVPA during the day for adolescents (morning, afternoon, early evening). Conclusions These results indicate that a 7-d monitoring protocol provides reliable estimates of usual physical activity behavior in children and adolescents and accounts for potentially important differences in weekend versus weekday activity behavior as well as differences in activity patterns within a given day.

Physical activity levels among children attending after-school programs

Purpose To describe the physical activity (PA) levels of children attending after-school programs, 2) examine PA levels in specific after-school sessions and activity contexts, and 3) evaluate after-school PA differences in groups defined by sex and weight status. Methods One hundred forty-seven students in grades 3-6 (mean age: 10.1 +/- 0.7, 54.4% male, 16.5% overweight (OW), 22.8% at-risk for OW) from seven after-school programs in the midwestern United States wore Actigraph GT1M accelerometers for the duration of their attendance to the program. PA was objectively assessed on six occasions during an academic year (three fall and three spring). Stored activity counts were uploaded to a customized data-reduction program to determine minutes of sedentary (SED), light (LPA), moderate (MPA), vigorous (VPA), and moderate-to-vigorous (MVPA) physical activity. Time spent in each intensity category was calculated for the duration of program attendance, as well as specific after-school sessions (e.g., free play, snack time). Results On average, participants exhibited 42.6 min of SED, 40.8 min of LPA, 13.4 min of MPA, and 5.3 min of VPA. The average accumulation of MVPA was 20.3 min. Boys exhibited higher levels of MPA, VPA, and MVPA, and lower levels of SED and LPA, than girls. OW and at-risk-for-OW students exhibited significantly less VPA than nonoverweight students, but similar levels of LPA, MPA, and MVPA. MVPA levels were significantly higher during free-play activity sessions than during organized or structured activity sessions. Conclusion After-school programs seem to be an important contributor to the PA of attending children. Nevertheless, ample room for improvement exists by making better use of existing time devoted to physical activity.

Factors associated with physical activity in children attending family child care homes

Objective To determine the relationship between family child care home (FCCH) practices and characteristics, and objectively measured physical activity (PA) among children attending FCCHs. Methods FCCH practices and characteristics were assessed in 45 FCCHs in Oregon (USA) in 2010-2011 using the Nutrition and Physical Activity Self-Assessment for Child Care Instrument. Within the 45 FCCHs, 136 children between ages 2 and 5. years wore an accelerometer during child care attendance over a one-week period. Time spent in light, moderate, and vigorous PA per hour was calculated using intensity-related cut-points (Pate et al., 2006). Results FCCH characteristics and practices associated with higher levels of PA (min/h; p < 0.05) included provision of sufficient outdoor active play [32.2 (1.0) vs. 28.6 (1.3)], active play using portable play equipment [31.7 (1.0) vs. 29.3 (1.4)], the presence of a variety of fixed play equipment [32.2 (1.0) vs. 28.9 (1.3)], and suitable indoor play space [32.2 (1.0) vs. 28.6 (1.3)], engaging in active play with children [32.1 (1.1) vs. 29.6 (1.2)], and receiving activity-related training [33.1 (1.2) vs. 30.3 (1.1)]. Conclusions This is the first study to identify practices and characteristics of FCCHs that influence children's PA. These data should be considered when developing programs and policies to promote PA in FCCHs.

A prospective study of the determinants of physical activity in rural fifth-grade children

Background Understanding the factors that influence physical activity behavior is important in the design of intervention programs targeted at youth. Methods A prospective study design was used to identify the predictors of vigorous physical activity (VPA) (greater than or equal to 6 METs) and moderate and vigorous physical activity (MVPA) (greater than or equal to 3 METs) among 202 rural, predominantly African-American children. Selected social-cognitive determinants of physical activity were assessed via questionnaire in the fifth grade. Participation in VPA and MVPA was assessed via the previous day physical activity recall 1 year later in the sixth grade. Results For girls, participation in community sports, self-efficacy in overcoming barriers, enjoyment of school physical education, race (white > black), and perception of mother's activity level (active vs inactive) were significant predictors of VPA. For MVPA, participation in community sports and self-efficacy in overcoming barriers were significant predictors. For boys, self-efficacy in overcoming barriers was the only significant predictor of VPA, while beliefs regarding activity outcomes and participation in community sports were significant predictors of MVPA. Conclusion Social-cognitive constructs such as physical activity self-efficacy, access to community physical activity outlets, and positive beliefs regarding physical activity outcomes are important predictors of future physical activity behavior among rural, predominantly African-American children.