Richard R. Suminski, Rick L. Petosa, Walker C.S. Poston, Emily Stevens and Laura Katzenmoyer
Methods are needed to assess the impact of walk-to-school programs on behavior. This study developed an observation method for counting the number of children and adults walking/biking to school.
Two elementary schools located in different urban, US census tracts were chosen for this study. Six walking/biking routes to each school were observed for 30 min before and after school. Strict guidelines were followed for determining whether a child/adult was counted.
Levels of agreement between observers were over 97% for children and adults. Reliability coefficients (R) for two days of observations exceeded 0.90 for children and adults walking. No differences were seen between days of the week or before and after school observation periods (P > 0.05). The number seen walking did depend on the route observed (P < 0.01).
This study presents a reliable observation method for determining the number of children and adults walking and biking to/from school.
Wendell C. Taylor, Walker S. Carlos Poston, Lovell Jones and M. Katherine Kraft
The term “environmental justice” refers to efforts to address the disproportionate exposure to and burden of harmful environmental conditions experienced by low-income and racial/ethnic minority populations.
Based on computer and manual searches, this paper presents a review of articles in the published literature that discuss disparities in physical activity, dietary habits, and obesity among different populations.
This paper provides evidence that economically disadvantaged and racial/ethnic minority populations have substantial environmental challenges to overcome to become physically active, to acquire healthy dietary habits, and to maintain a healthy weight. For example, residents living in poorer areas have more environmental barriers to overcome to be physically active.
We propose a research agenda to specifically address environmental justice with regard to improving physical activity, dietary habits, and weight patterns.
Richard R. Suminski, Larry T. Wier, Walker Poston, Brian Arenare, Anthony Randles and Andrew S. Jackson
Nonexercise models were developed to predict maximal oxygen consumption (VO2max). While these models are accurate, they don’t consider smoking, which negatively impacts measured VO2max. The purpose of this study was to examine the effects of smoking on both measured and predicted VO2max.
Indirect calorimetry was used to measure VO2max in 2,749 men and women. Physical activity using the NASA Physical Activity Status Scale (PASS), body mass index (BMI), and smoking (pack-y = packs·day * y of smoking) also were assessed. Pack-y groupings were Never (0 pack-y), Light (1–10), Moderate (11–20), and Heavy (>20). Multiple regression analysis was used to examine the effect of smoking on VO2max predicted by PASS, age, BMI, and gender.
Measured VO2max was significantly lower in the heavy smoking group compared with the other pack-y groups. The combined effects of PASS, age, BMI, and gender on measured VO2max were significant. With smoking in the model, the estimated effects on measured VO2max from Light, Moderate, and Heavy smoking were –0.83, –0.85, and –2.56 ml·kg−1·min−1, respectively (P < .05).
Given that 21% of American adults smoke and 12% of them are heavy smokers, it is recommended that smoking be considered when using nonexercise models to predict VO2max.