Considerations for Using a Geographic Information System to Assess Environmental Supports for Physical Activity

The use of a geographic information system (GIS) to study environmental supports for physical activity raises several issues, including acquisition and development, quality, and analysis. We recommend to public health professionals interested in using GIS that they investigate available data, plan for data development where none exists, ensure the availability of trained personnel and sufficient time, and consider issues such as data quality, analyses, and confidentiality. This article shares information about data-related issues that we encountered when using GIS to validate responses to a questionnaire about environmental supports for physical activity

Physical Activity Levels Among Overweight and Obese Adults in South Carolina

Background: Obesity in the United States has reached epidemic proportions and is a major cause of morbidity and mortality. Methods: We describe the activity levels of South Carolina adults on the basis of data derived from the Centers for Disease Control and Prevention Behavioral Risk Factor Surveillance System. Results: Overweight and obese men and women reported less leisure time physical activity than did people of normal weight, with women found to be less active than men. Conclusion: Physical inactivity is more prevalent among obese and overweight men and women than among people of normal weight. Visiting the physician's office offers a unique opportunity to educate patients about the health benefits and appropriate amount of physical activity. (C) 2003 Southern Medical Associatio

Associations of Perceived Social and Physical Environmental Supports With Physical Activity and Walking Behavior

We evaluated perceived social and environmental supports for physical activity and walking using multivariable modeling. Perceptions were obtained on a sample of households in a southeastern county. Respondents were classified according to physical activity levels and walking behaviors. Respondents who had good street lighting; trusted their neighbors; and used private recreational facilities, parks, playgrounds, and sports fields were more likely to be regularly active. Perceiving neighbors as being active, having access to sidewalks, and using malls were associated with regular walking

Descriptive Epidemiology of Pedometer-Determined Physical Activity

Purpose: The dual purposes of this study were: 1) to provide preliminary descriptive epidemiology data representing pedometer-determined physical activity (PA) and 2) to explore sources of intra-individual variability in steps per day. Methods: All participants (76 males, age = 48.4 +/- 16.3 yr, body mass index (BMI) = 27.1 +/- 5.1 kg[middle dot]m-2; 133 females, age = 47.4 +/- 17.5 yr, BMI = 26.9 +/- 5.7 kg[middle dot]m-2) resided in Sumter County, SC, and were recruited by telephone to receive a mailed kit to self-monitor PA for 1 wk. Statistical analyses compared mean steps per day between sexes, races, age groups, education and income levels, and BMI categories. Mean steps per day were also compared between: 1) weekdays versus weekend days, 2) workdays versus nonworkdays, and 3) days of sport/exercise versus no participation. Results: The entire sample took 5931 +/- 3664 steps[middle dot]d-1 (males = 7192 +/- 3596 vs females = 5210 +/- 3518 steps[middle dot]d-1, t = 7.88, P < 0.0001). Significant differences were also indicated by race, age, education, income, and BMI. In addition, weekdays were significantly higher than weekend days, workdays were higher than nonworkdays, and sport/exercise days were higher than nonsport/exercise days. Conclusions: The large standard deviations reflect a wide distribution of ambulatory behavior. Regardless, important differences are still evident by demographic characteristics, BMI categories, day of the week, and reported engagement in work or sport/exercise

Changes in Disparity in County-Level Diagnosed Diabetes Prevalence and Incidence in the United States, between 2004 and 2012.

In recent decades, the United States experienced increasing prevalence and incidence of diabetes, accompanied by large disparities in county-level diabetes prevalence and incidence. However, whether these disparities are widening, narrowing, or staying the same has not been studied. We examined changes in disparity among U.S. counties in diagnosed diabetes prevalence and incidence between 2004 and 2012.We used 2004 and 2012 county-level diabetes (type 1 and type 2) prevalence and incidence data, along with demographic, socio-economic, and risk factor data from various sources. To determine whether disparities widened or narrowed over the time period, we used a regression-based β-convergence approach, accounting for spatial autocorrelation. We calculated diabetes prevalence/incidence percentage point (ppt) changes between 2004 and 2012 and modeled these changes as a function of baseline diabetes prevalence/incidence in 2004. Covariates included county-level demographic and, socio-economic data, and known type 2 diabetes risk factors (obesity and leisure-time physical inactivity).For each county-level ppt increase in diabetes prevalence in 2004 there was an annual average increase of 0.02 ppt (p<0.001) in diabetes prevalence between 2004 and 2012, indicating a widening of disparities. However, after accounting for covariates, diabetes prevalence decreased by an annual average of 0.04 ppt (p<0.001). In contrast, changes in diabetes incidence decreased by an average of 0.04 ppt (unadjusted) and 0.09 ppt (adjusted) for each ppt increase in diabetes incidence in 2004, indicating a narrowing of county-level disparities.County-level disparities in diagnosed diabetes prevalence in the United States widened between 2004 and 2012, while disparities in incidence narrowed. Accounting for demographic and, socio-economic characteristics and risk factors for type 2 diabetes narrowed the disparities, suggesting that these factors are strongly associated with changes in disparities. Public health interventions that target modifiable risk factors, such as obesity and physical inactivity, in high burden counties might further reduce disparities in incidence and, over time, in prevalence

Small area variation in diabetes prevalence in Puerto Rico

OBJECTIVE: To estimate the 2009 prevalence of diagnosed diabetes in Puerto Rico among adults ≥ 20 years of age in order to gain a better understanding of its geographic distribution so that policymakers can more efficiently target prevention and control programs. METHODS: A Bayesian multilevel model was fitted to the combined 2008-2010 Behavioral Risk Factor Surveillance System and 2009 United States Census data to estimate diabetes prevalence for each of the 78 municipios (counties) in Puerto Rico. RESULTS: The mean unadjusted estimate for all counties was 14.3% (range by county, 9.9%-18.0%). The average width of the confidence intervals was 6.2%. Adjusted and unadjusted estimates differed little. CONCLUSIONS: These 78 county estimates are higher on average and showed less variability (i.e., had a smaller range) than the previously published estimates of the 2008 diabetes prevalence for all United States counties (mean, 9.9%; range, 3.0%-18.2%)

Estimates of percentage point change in county-level diabetes incidence between 2004 and 2012.^†

<p>Estimates of percentage point change in county-level diabetes incidence between 2004 and 2012.<a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0159876#t003fn001" target="_blank">^†</a></p

Average county-level characteristics.

<p>Average county-level characteristics.</p