Accelerometer and GPS Data to Analyze Built Environments and Physical Activity

ABSTRACT

Purpose: Most built environment studies have quantified characteristics of the areas around participants’ homes. However, the environmental exposures for physical activity (PA) are spatially dynamic rather than static. Thus, merged accelerometer and global positioning system (GPS) data were utilized to estimate associations between the built environment and PA among adults. Methods: Participants (N = 142) were recruited on trails in Massachusetts and wore an accelerometer and GPS unit for 1–4 days. Two binary outcomes were created: moderate-to-vigorous PA (MVPA vs. light PA-to-sedentary); and light-to-vigorous PA (LVPA vs. sedentary). Five built environment variables were created within 50-meter buffers around GPS points: population density, street density, land use mix (LUM), greenness, and walkability index. Generalized linear mixed models were fit to examine associations between environmental variables and both outcomes, adjusting for demographic covariates. Results: Overall, in the fully adjusted models, greenness was positively associated with MVPA and LVPA (odds ratios [ORs] = 1.15, 95% confidence interval [CI] = 1.03, 1.30 and 1.25, 95% CI = 1.12, 1.41, respectively). In contrast, street density and LUM were negatively associated with MVPA (ORs = 0.69, 95% CI = 0.67, 0.71 and 0.87, 95% CI = 0.78, 0.97, respectively) and LVPA (ORs = 0.79, 95% CI = 0.77, 0.81 and 0.81, 95% CI = 0.74, 0.90, respectively). Negative associations of population density and walkability with both outcomes reached statistical significance, yet the effect sizes were small. Conclusions: Concurrent monitoring of activity with accelerometers and GPS units allowed us to investigate relationships between objectively measured built environment around GPS points and minute-by-minute PA. Negative relationships between street density and LUM and PA contrast evidence from most built environment studies in adults. However, direct comparisons should be made with caution since most previous studies have focused on spatially fixed buffers around home locations, rather than the precise locations where PA occurs.     

Effect of Strenuous Physical Activity upon Reaction Time

Abstract

This study was concerned with the effect of bench-stepping in the Harvard Step Test upon finger and foot reaction time and, secondarily, with ascertaining the relationship, if any, between these reaction times and scores on the Harvard Step Test. The subjects were university freshman males. Reaction times were taken before, immediately after, and four minutes after the stepping exercise for 80 subjects. Thirty-six subjects served as controls, involving the reaction times and pulse counts at the prescribed intervals but without exercise. The findings failed to divulge any discernible effect of stepping exercise upon reaction time, or any apparent relationship between reaction time and the sum of the recovery pulse counts following the exercise. In view of these findings it is suggested that study be directed to two related aspects — the effect of exercise to exhaustion on reaction time, and the effect of strenuous and exhaustive exercise upon speed of movement.     

Specificity of a Maximal Step Exercise Test

To adhere to the principle of “exercise specificity” exercise testing should be completed using the same physical activity that is performed during exercise training. The present study was designed to assess whether aerobic step exercisers have a greater maximal oxygen consumption (max VO₂) when tested using an activity specific, maximal step exercise test (SET; arms and legs) versus a maximal running test (legs only). Female aerobic step exercisers (N=18; 20.7 ± 1.5 years) performed three maximal graded exercise tests (GXTs): 2 SETs; 1 treadmill test (TMT). The SET consisted of six 3-min progressive stages of alternate lead, basic step, basic step with biceps curls, knee raise with pull-down, repeater knee with pull-down, lateral lunge with pull-down, and side squat with shoulder presses. Stepping rate was 32 steps· min^?1 on an 8-in (20.32 cm) step for stages 1–3, and a 10-in (25.4 cm) step for stages 4–6. Submaximal and maximal heart rate (HR) and oxygen consumption (VO₂) were recorded at the end of each stage. Test–retest reliability for the first five stages of the SET ranged from .91 to .97 for HR, and from .84 to .96 for VO₂. Maximal HR was significantly greater (p =.0001) for the SET (200 ± 6.2 beats·min^?1) as compared to the TMT (193 ± 7.9 beats·min^?1). No significant difference was found for max VO₂ (42.9 ± 8.5, 41.2 ± 5.9 ml·kg^?1·min^?1, p =.14). The SET was a valid and reliable protocol for assessing responses of these aerobic step exercisers; however, max VO₂ from a TMT did not differ significantly from the SET. Conversely, max HR obtained from the criterion TMT was 7 beats·min^?1 lower than from the SET. If a training HR for step exercise (arms and legs exercise) is prescribed based on the max HR from treadmill exercise (legs only), then the training HR should be calculated from a TMT max HR that has been increased by 7 beats·min^?1 to obtain an intensity of step exercise comparable to that of running.     

Development of the Exercise Motives and Gains Inventory

There are existing measures of exercise motives (what people want from exercise), but corresponding measures of gains (what people get) are needed, because motives and gains could influence each other and together influence other variables. An exercise motives and gains inventory (EMGI) was developed by creating gains scales to complement existing Exercise Motivations Inventory 2 scales. Confirmatory factor analyses of EMGI items established that items reflected their intended constructs; and that motive and gain constructs were distinct. Exploratory structural equation modeling of EMGI scales established that the higher-order structures of motives and gains were somewhat different: Appearance motive was associated with weight management, whereas appearance gain was associated with health and fitness. Paired-sample t-tests established that gains were less than motives in some instances (ill-health avoidance, positive health), and greater in others (e.g., affiliation, challenge). The EMGI can be used to investigate the consequences and causes of motives and gains.     

Leisure time physical activity in Australian women: relationship with well being and symptoms

This paper explores the association between moderate levels of physical activity (PA) and health benefits in well being and symptoms such as tiredness, back pain, and constipation. Participants in the Australian Longitudinal Study on Women's Health, 14,502 young women (ages 18-23 years), 13,609 middle-age women (45-50 years), and 11,421 older women (ages 70-75 years), answered questions about vigorous and less vigorous exercise (used to determine a physical activity score), well being (SF-36), symptoms, and medical conditions. There were significant associations between the PA score and SF-36 in each cohort. Odds ratios (OR) for a range of symptoms and conditions were lower for women who reported low to moderate activity than for sedentary women, for example, for young women or for constipation = 0.76 (CI, 0.65-0.89), for middle-age women or for tiredness = 0.70 (0.63-0.78). There was no threshold of PA at which health benefits increased significantly. Although cross-sectional, the findings suggest that low-to-moderate levels of exercise are associated with a range of health benefits for women of all ages. These preliminary findings will be followed up during the longitudinal study.     

Biomechanics and visual-motor control: how it has, is, and will be used to reveal the secrets of hitting a cricket ball

Cricket batting is an incredibly complex task which requires the coordination of full-body movements to successfully hit a fast moving ball. Biomechanical studies on batting have helped to shed light on how this intricate skill may be performed, yet the many different techniques exhibited by batters make the systematic examination of batting difficult. This review seeks to critically evaluate the existing literature examining cricket batting, but doing so by exploring the strong but often neglected relationship between biomechanics and visual-motor control. In three separate sections, the paper seeks to address (i) the different theories of motor control which may help to explain how skilled batters can hit a ball, (ii) strategies used by batters to overcome the (at times excessive) temporal constraints, and (iii) an interpretation from a visual-motor perspective of the prevailing biomechanical data on batting.     

Bowling ball dynamics revealed by miniature wireless MEMS inertial measurement unit

This paper presents a novel sensor technology to deduce the dynamics of a bowling ball. The sensor, a miniature wireless inertial measurement unit (IMU), incorporates MEMS accelerometers and angular rate gyros, a microcontroller, a low power RF transceiver, and a rechargeable battery. When embedded in a bowling ball, the IMU transmits the acceleration and angular velocity data that define the dynamics of the ball starting with the bowler’s delivery and its motion in the lane. Example results from professional bowlers illustrate how this technology can be used to assess bowler skill and ball performance. For instance, the IMU accurately measures the spin dynamics of the ball which are crucial to develop the ball “hook.” An analysis of ball dynamics in the lane is distilled to a measurable “hook potential” metric for further assessing bowler skill. Finally, the sensor presented herein is believed to be the world’s smallest, wireless IMU. This highly miniaturized and wireless design will enable parallel training systems for many sports, including basketball, baseball, crew, cricket, golf, fly fishing, soccer, softball, tennis, rowing, among others.     

TGMD-3在中国3~12岁儿童基本运动技能测试中的信效度研究

目的: 验证TGMD-3在中国3~12岁儿童基本运动技能测试中的可靠性和有效性。方法: 选取上海、深圳、重庆、洛阳、长沙的512名3~12岁儿童为研究对象进行TGMD-3测试,对测试的难度、区分度、一致性信度、重测信度和评价者信度、结构效度进行统计检验。结果: TGMD-3的13个项目难度范围为0.27~0.78,区分度范围为0.38~0.49。每个年龄组儿童基本运动技能测试(TGMD-3)的内部一致性系数范围为0.808~0.902,其中男女生的内部一致性系数均为0.95;总体的基本运动技能评价者信度(肯德尔协同系数)w为0.944, 2值为28.331,达到显著性水平;重测检验中,移动式运动技能(组内相关系数)ICC为0.755、球类运动技能(组内相关系数)ICC为0.741、总的基本运动技能(组内相关系数)ICC为0.743,均达到了较高水平。通过探索性因子分析验证了TGMD-3的双因子结构,并通过验证性因子分析支持双因子模型(χ²(64)=103.28,p<0.001,CFI=0.960,TLI=0.952,RMSEA=0.049,SRMR=0.043)。结论: TGMD-3儿童基本运动技能测试具有良好的项目难度、区分度,以及可靠的内部一致性信度、重测信度和结构效度,对我国3~12岁儿童具有良好的适用性,可以作为我国儿童基本运动技能发展评价的有效工具。