Urban Containment Policies and Physical Activity A Time–Series Analysis of Metropolitan Areas, 1990–2002

Background: Urban containment policies attempt to manage the location, character, and timing of growth to support a variety of goals such as compact development, preservation of greenspace, and efficient use of infrastructure. Despite prior research evaluating the effects of urban containment policies on land use, housing, and transportation outcomes, the public health implications of these policies remain unexplored. This ecologic study examines relationships among urban containment policies, state adoption of growthmanagement legislation, and population levels of leisure and transportation-related physical activity in 63 large metropolitan statistical areas from 1990 to 2002. Methods: Multiple data sources were combined, including surveys of urban containment policies, the Behavioral Risk Factor Surveillance System, the U.S. Census of Population, the National Resources Inventory, and the Texas Transportation Institute Urban Mobility Study. Mixed models were used to examine whether urban containment policies and state adoption of growth-management legislation were associated with population levels of leisure-time physical activity (LTPA) and walking/bicycling to work over time. Results: Strong urban containment policies were associated with higher population levels of LTPA and walking/bicycling to work during the study period. Additionally, residents of states with legislation mandating urban growth boundaries reported significantly more minutes of LTPA/week compared to residents of states without such policies. Weak urban containment policies showed inconsistent relationships with physical activity. Conclusions: This study provides preliminary evidence that strong urban containment policies are associated with higher population levels of LTPA and active commuting. Future research should examine potential synergies among state, metropolitan, and local policy processes that may strengthen these relationship

Tests for Gaussian repeated measures with missing data in small samples

For small samples of Gaussian repeated measures with missing data, Barton and Cramer (1989) recommended using the EM algorithm for estimation and reducing the degrees of freedom for an analog of Rao's F approximation to Wilks' test. Computer simulations led to the conclusion that the modified test was slightly conservative for total sample size of N = 40. Here we consider additional methods and smaller sample sizes, N ∈ {12.24}. We describe analogs of the Pillai-Bartlett trace, Hotelling-Lawley trace and Geisser-Greenhouse corrected univariate tests which allow for missing data. Eleven sample size adjustments were examined which replace N by some function of the numbers of nonmissing pairs of responses in computing error degrees of freedom. Overall, simulation results allowed concluding that an adjusted test can always control test size at or below the nominal rate, even with as few as 12 observations and up to 10% missing data. The choice of method varies with the test statistic. Replacing N by the mean number of non-missing responses per variable works best for the Geisser-Greenhouse test. The Pillai-Bartlett test requires the stronger adjustment of replacing N by the harmonic mean number of non-missing pairs of responses. For Wilks' and Hotelling-Lawley, an even more aggressive adjustment based on the minimum number of non-missing pairs must be used

BayesCTDesign: An R Package for Bayesian Trial Design Using Historical Control Data

This article introduces the R package BayesCTDesign for two-arm randomized Bayesian trial design using historical control data when available, and simple two-arm randomized Bayesian trial design when historical control data is not available. The package BayesCTDesign, which is available from the Comprehensive R Archive Network, has two simulation functions, historic_sim() and simple_sim() for studying trial characteristics under user-defined scenarios, and two methods print() and plot() for displaying summaries of the simulated trial characteristics. The package BayesCTDesign works with two-arm trials with equal sample sizes per arm. The package BayesCTDesign allows a user to study Gaussian, Poisson, Bernoulli, Weibull, lognormal, and piecewise exponential outcomes. Power for two-sided hypothesis tests at a user-defined α is estimated via simulation using a test within each simulation replication that involves comparing a 95% credible interval for the outcome specific treatment effect measure to the null case value. If the 95% credible interval excludes the null case value, then the null hypothesis is rejected, else the null hypothesis is accepted. In the article, the idea of including historical control data in a Bayesian analysis is reviewed, the estimation process of BayesCTDesign is explained, and the user interface is described. Finally, the BayesCTDesign is illustrated via several examples

Accuracy of commercial geocoding: assessment and implications

BACKGROUND: Published studies of geocoding accuracy often focus on a single geographic area, address source or vendor, do not adjust accuracy measures for address characteristics, and do not examine effects of inaccuracy on exposure measures. We addressed these issues in a Women's Health Initiative ancillary study, the Environmental Epidemiology of Arrhythmogenesis in WHI. RESULTS: Addresses in 49 U.S. states (n = 3,615) with established coordinates were geocoded by four vendors (A-D). There were important differences among vendors in address match rate (98%; 82%; 81%; 30%), concordance between established and vendor-assigned census tracts (85%; 88%; 87%; 98%) and distance between established and vendor-assigned coordinates (mean ρ [meters]: 1809; 748; 704; 228). Mean ρ was lowest among street-matched, complete, zip-coded, unedited and urban addresses, and addresses with North American Datum of 1983 or World Geodetic System of 1984 coordinates. In mixed models restricted to vendors with minimally acceptable match rates (A-C) and adjusted for address characteristics, within-address correlation, and among-vendor heteroscedasticity of ρ, differences in mean ρ were small for street-type matches (280; 268; 275), i.e. likely to bias results relying on them about equally for most applications. In contrast, differences between centroid-type matches were substantial in some vendor contrasts, but not others (5497; 4303; 4210) p(interaction )< 10(-4), i.e. more likely to bias results differently in many applications. The adjusted odds of an address match was higher for vendor A versus C (odds ratio = 66, 95% confidence interval: 47, 93), but not B versus C (OR = 1.1, 95% CI: 0.9, 1.3). That of census tract concordance was no higher for vendor A versus C (OR = 1.0, 95% CI: 0.9, 1.2) or B versus C (OR = 1.1, 95% CI: 0.9, 1.3). Misclassification of a related exposure measure – distance to the nearest highway – increased with mean ρ and in the absence of confounding, non-differential misclassification of this distance biased its hypothetical association with coronary heart disease mortality toward the null. CONCLUSION: Geocoding error depends on measures used to evaluate it, address characteristics and vendor. Vendor selection presents a trade-off between potential for missing data and error in estimating spatially defined attributes. Informed selection is needed to control the trade-off and adjust analyses for its effects

MRI measurements of carotid plaque in the atherosclerosis risk in communities (ARIC) study: Methods, reliability and descriptive statistics

To measure carotid plaque components using MRI and estimate reliability in the population-based Atherosclerosis Risk in Communities (ARIC) study

SELP and SELPLG Genetic Variation Is Associated with Cell Surface Measures of SELP and SELPLG: The Atherosclerosis Risk in Communities Carotid MRI Study

P-selectin (SELP) and its ligand, P-selectin glycoprotein ligand 1 (SELPLG), play key roles in both the inflammatory response and the atherosclerotic process. Previous studies have shown genetic variation in the SELP gene [selectin P (granule membrane protein 140kDa, antigen CD62)] to be associated with plasma SELP concentrations; however, the major biological function of SELP (and SELPLG) is at the cell surface. We therefore investigated the association of SELP polymorphisms with platelet SELP measures and polymorphisms in the SELPLG gene (selectin P ligand) with lymphocyte, granulocyte, and monocyte SELPLG measures among 1870 participants in the Atherosclerosis Risk in Communities (ARIC) Carotid MRI study

Neighbourhood characteristics and mortality in the Atherosclerosis Risk in Communities Study

Background This study investigates the relationship between neighbourhood characteristics and mortality (all-cause, cardiovascular disease [CVD], and cancer) in the Atherosclerosis Risk in Communities Study (ARIC). Methods Analysis was limited to African-American and white participants 45–64 years of age at baseline whose records were linked to census data. Deaths ascertained through 31 December 1999 were included in the analysis. Individual-level characteristics were obtained from the baseline interview. A composite index was used to characterize the neighbourhood socioeconomic environment. Proportional hazards regression was used to estimate the effect of neighbourhood socioeconomic status (SES) index and family income on the survival time. Results The rate of mortality adjusted for age and gender was highest among those who lived in disadvantaged neighbourhoods and were of lower SES. In general, all-cause and CVD mortality rates decreased with increasing neighbourhood SES advantage and family income in all race-gender groups. Although this pattern generally persisted after adjustment for individual socioeconomic factors, statistically significant associations persisted for CVD mortality in whites only (hazard ratio = 1.4, 95% CI: 1.0, 2.0) for most disadvantaged versus most advantaged tertile). When compared with the most affluent participants living in the most advantaged neighbourhoods, the increased risk of all-cause and CVD mortality associated with being poor and living in the most disadvantaged neighbourhoods was equivalent to being 11 and 13 years older at baseline for whites and African Americans, respectively. Conclusion Our findings indicate that neighbourhood socioeconomic characteristics are associated with modest increases in CVD mortality in white adults. The lack of neighbourhood effects in African Americans needs to be interpreted with caution due to the limited range in the characteristics of the neighbourhood from which these participants were drawn.http://deepblue.lib.umich.edu/bitstream/2027.42/57743/1/Neighborhood characteristics and mortality in the Atherosclerosis Risk in Communities Study.pd

Predicting Energy Expenditure from Accelerometry Counts in Adolescent Girls

Calibration of accelerometer counts against oxygen consumption to predict energy expenditure has not been conducted in middle school girls. We concurrently assessed energy expenditure and accelerometer counts during physical activities on adolescent girls to develop an equation to predict energy expenditure

Weekend schoolyard accessibility, physical activity, and obesity: The Trial of Activity in Adolescent Girls (TAAG) study

To assess the accessibility and suitability of schools as recreational sites and to determine whether they are associated with young adolescent girls’ weekend metabolic equivalent-weighted moderate-to-vigorous (MW-MVPA) physical activity and body mass index (BMI)

Defining Accelerometer Thresholds for Activity Intensities in Adolescent Girls

Purpose - To derive a regression equation that estimates metabolic equivalent (MET) from accelerometer counts, and to define thresholds of accelerometer counts that can be used to delineate sedentary, light, moderate, and vigorous activity. Methods - Seventy-four healthy 8th grade girls, age 13-14 yr, were recruited from urban areas of Baltimore, MD, Minneapolis/St. Paul, MN, and Columbia, SC, to participate in the study. Accelerometer and oxygen consumption (VO2) data for 10 activities that varied in intensity from sedentary (e.g., TV watching) to vigorous (e.g., running) were collected. While performing these activities, the girls wore two accelerometers, a heart rate monitor and a Cosmed K4b2 portable metabolic unit for measurement of VO2. A random-coefficients model was used to estimate the relationship between accelerometer counts and VO2. Activity thresholds were defined by minimizing the false positive and false negative classifications. Results - The activities provided a wide range in VO2 (3-36 mL·kg-1·min-1) with a correspondingly wide range in accelerometer counts (1-3928 counts·30 s-1). The regression line for MET score versus counts was MET=2.01+0.00171 (counts·30 s-1) (mixed model R2=0.84, SEE=1.36). A threshold of 1500 counts·30 s-1 defined the lower end of the moderate intensity (~4.6 METs) range of physical activity. That cutpoint distinguished between slow and brisk walking, and gave the lowest number of false positive and false negative classifications. The threshold ranges for sedentary, light, moderate, and vigorous physical activity were found to be 0-50, 51-1499, 1500-2600, and \u3e2600 counts·30 s-1, respectively. Conclusion - The developed equation and these activity thresholds can be used for prediction of MET score from accelerometer counts and participation in various intensities of physical activity in adolescent girls