Building Up Geometry

Much of the text you are about to read is made up. GASP! Second, many people don’t think the subject of this story, Euclid, was a real person. GASP, again!! I happen to believe Euclid was real and did a lot of great mathematics work that is still used today. That said, there is little known about Euclid or his life. Historians who believe in Euclid speculate that he was born around 300BC in Alexandria, Egypt, was taught by Plato in Athens, Greece, and taught mathematics later in his life. His greatest works are collected in his book, Elements, a collection of geometric constructions and arguments. Whether you’re a math lover like I am or not, I hope you enjoy this story about Euclid, a magical wizard, and an exciting journey

Longitudinal changes in heart rate after participating in the Groningen Active Living Model (GALM) recreational sports programme

The aim of this study was to investigate changes in heart rate during submaximal exercise as an index of cardiovascular function in older adults participating in the Groningen Active Living Model recreational sports programme who were sedentary or underactive at baseline. A repeated measurement design was conducted; 151 participants were included, providing 398 heart rate files over a period of 18 months. Multi-level analyses were conducted; growth and final models were developed. Significant decreases in mean heart rate over time were observed for all walking speeds. The covariates of sex and body mass index (BMI) were significantly related to mean heart rate at each walking speed, except for BMI at 7 km/h. No significant relationships were observed between energy expenditure for recreational sports activities and leisure-time physical activities and mean heart rate, except for energy expenditure for leisure-time physical activities at 7 km/h. From baseline to December 2002, decreases in predicted mean heart rate were 5.5, 6.0, 10.0, and 9.0 beats/min at walking speeds of 4, 5, 6, and 7 km/h; relative decreases ranged from 5.1 to 7.4%. Significant decreases in heart rate observed during submaximal exercise reflected a potential increase in cardiovascular function after 18 months of participation in the Groningen Active Living Model recreational sports programme. DOI:10.1080/0264041090300874

Is Your Neighborhood Designed to Support Physical Activity? A Brief Streetscape Audit Tool.

INTRODUCTION:Macro level built environment factors (eg, street connectivity, walkability) are correlated with physical activity. Less studied but more modifiable microscale elements of the environment (eg, crosswalks) may also affect physical activity, but short audit measures of microscale elements are needed to promote wider use. This study evaluated the relation of a 15-item neighborhood environment audit tool with a full version of the tool to assess neighborhood design on physical activity in 4 age groups. METHODS:From the 120-item Microscale Audit of Pedestrian Streetscapes (MAPS) measure of street design, sidewalks, and street crossings, we developed the 15-item version (MAPS-Mini) on the basis of associations with physical activity and attribute modifiability. As a sample of a likely walking route, MAPS-Mini was conducted on a 0.25-mile route from participant residences toward the nearest nonresidential destination for children (n = 758), adolescents (n = 897), younger adults (n = 1,655), and older adults (n = 367). Active transportation and leisure physical activity were measured with age-appropriate surveys, and accelerometers provided objective physical activity measures. Mixed-model regressions were conducted for each MAPS item and a total environment score, adjusted for demographics, participant clustering, and macrolevel walkability. RESULTS:Total scores of MAPS-Mini and the 120-item MAPS correlated at r = .85. Total microscale environment scores were significantly related to active transportation in all age groups. Items related to active transport in 3 age groups were presence of sidewalks, curb cuts, street lights, benches, and buffer between street and sidewalk. The total score was related to leisure physical activity and accelerometer measures only in children. CONCLUSION:The MAPS-Mini environment measure is short enough to be practical for use by community groups and planning agencies and is a valid substitute for the full version that is 8 times longer

Applying Mixed-Effects Location Scale Modeling to Examine Within-Person Variability in Physical Activity Self-Efficacy

Abstract: Background: Physical activity self-efficacy is conceptualized as a construct that is changeable and responsive to contextual factors. The current study applied mixed-effects location scale modeling to examine within-person variability in physical activity self-efficacy among middle-aged and older adults (N = 14 adults, mean age = 59.4 years) who were attempting behavior change. Methods: An electronic diary was used to record self-reported self-efficacy and physical activity via Ecological Momentary Assessment (EMA) twice a day (2:00 pm and 9:00 pm). Data from weeks 1-6 were analyzed using a Mixed-Effects Location Scale Model in SAS PROC NLMIXED. Results: Participants differed from each other in the degree to which physical activity self-efficacy varied from day to day (p = .03). Within-person variation in self-efficacy was negatively related to levels of brisk walking each week (p = .002), and decreased over time (p = .03). Conclusions: Preliminary results suggest that fluctuations in self-efficacy may be as important for predicting short-term behavior as the overall or mean level of self-efficacy

Changes in CVD risk factors in the activity counseling trial

Primary care facilities may be a natural setting for delivering interventions that focus on behaviors that improve cardiovascular disease (CVD) risk factors. The purpose of this study was to examine the 24-month effects of the Activity Counseling Trial (ACT) on CVD risk factors, to examine whether changes in CVD risk factors differed according to baseline risk factor status, and to examine whether changes in fitness were associated with changes in CVD risk factors. ACT was a 24-month multicenter randomized controlled trial to increase physical activity. Participants were 874 inactive men and women aged 35–74 years. Participants were randomly assigned to one of three arms that varied by level of counseling, intensity, and resource requirements. Because there were no significant differences in change over time between arms on any of the CVD risk factors examined, all arms were combined, and the effects of time, independent of arm, were examined separately for men and women. Time × Baseline risk factor status interactions examined whether changes in CVD risk factors differed according to baseline risk factor status. Significant improvements in total cholesterol, high-density lipoprotein cholesterol (HDL-C) and low-density lipoprotein cholesterol, the ratio of total cholesterol to HDL-C, and triglycerides were seen in both men and women who had high (or low for HDL-C) baseline levels of risk factors, whereas significant improvements in diastolic blood pressure were seen only in those men with high baseline levels. There were no improvements in any risk factors among participants with normal baseline levels. Changes in fitness were associated with changes in a number of CVD risk factors. However, most relationships disappeared after controlling for changes in body weight. Improvements in lipids from the ACT interventions could reduce the risk of coronary heart disease in people with already high levels of lipids by 16%–26% in men and 11%–16% in women. Interventions that can be implemented in health care settings nationwide and result in meaningful population-wide changes in CVD risk factors are needed. The ACT physical activity interventions produced substantial improvements among men and women with elevated CVD risk factors

Accuracy of Name and Age Data Provided About Network Members in a Social Network Study of People Who Use Drugs: Implications for Constructing Sociometric Networks

Purpose—Network analysis has become increasingly popular in epidemiologic research, but the accuracy of data key to constructing risk networks is largely unknown. Using network data from people who use drugs (PWUD), the study examined how accurately PWUD reported their network members’ (i.e., alters’) names and ages. Methods—Data were collected from 2008 to 2010 from 503 PWUD residing in rural Appalachia. Network ties (n=897) involved recent (past 6 months) sex, drug co-usage, and/or social support. Participants provided alters’ names, ages, and relationship-level characteristics; these data were cross-referenced to that of other participants to identify participant-participant relationships and to determine the accuracy of reported ages (years) and names (binary). Results—Participants gave alters’ exact names and ages within two years in 75% and 79% of relationships, respectively. Accurate name was more common in relationships that were reciprocally reported and those involving social support and male alters. Age was more accurate in reciprocal ties and those characterized by kinship, sexual partnership, recruitment referral, and financial support, and less accurate for ties with older alters. Conclusions—Most participants reported alters’ characteristics accurately, and name accuracy was not significantly different in relationships involving drug-related/sexual behavior compared to those not involving these behaviors