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Objectives. We tested the reliability of 3 instruments that assessed social and physical environments. Methods. We conducted a test--retest study among US adults (n=289). We used telephone survey methods to measure suitableness of the perceived (vs objective) environment for recreational physical activity and nonmotorized transportation. Results. Most questions in our surveys that attempted to measure specific characteristics of the built environment showed moderate to high reliability. Questions about the social environment showed lower reliability than those that assessed the physical environment. Certain blocks of questions appeared to be selectively more reliable for urban or rural respondents. Conclusions. Despite differences in content and in response formats, all 3 surveys showed evidence of reliability, and most items are now ready for use in research and in public health surveillance. (Am J Public Health. 2004;94:473-483)

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 south eastern 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.

In the United States, diabetes is common and costly. Programs to prevent new cases of diabetes are often carried out at the level of the county, a unit of local government. Thus, eficient targeting of such programs requires county-level estimates of diabetes incidence??the fraction of the nondiabetic population who received their diagnosis of diabetes during the past 12 months. Previously, only estimates of prevalence??the overall fraction of population who have the disease??have been available at the county level. Counties with high prevalence might or might not be the same as counties with high incidence, due to spatial variation in mortality and relocation of persons with incident diabetes to another county. Existing methods cannot be used to estimate county-level diabetes incidence, because the fraction of the population who receive a diabetes diagnosis in any year is too small. Here, we extend previously developed methods of Bayesian small-area estimation of prevalence, using diffuse priors, to estimate diabetes incidence for all U.S. counties based on data from a survey designed to yield state-level estimates. We found high incidence in the southeastern United States, the Appalachian region, and in scattered counties throughout the western U.S. Our methods might be applicable in other circumstances in which all cases of a rare condition also must be cases of a more common condition (in this analysis, \newly diagnosed cases of diabetes" and \cases of diabetes"). If appropriate data are available, our methods can be used to estimate proportion of the population with the rare condition at greater geographic specificity than the data source was designed to provide. [ABSTRACT FROM AUTHOR]

The purpose of this study was to develop a tool for assessing the quality of public recreation facilities' amenities. Knowing the location, distribution, and quality of recreation facilities can assist administrators in developing more effective programs for encouraging physical activity across city, county, and state systems. Based on a literature review, expert opinions, and professional standards, a tool was developed for assessing the safety, condition, and maintenance of recreation facilities. A Geographic Information System (GIS) database was developed to locate public recreation facilities in a southeastern county of the United States. Objective ratings of recreation facility quality were computed from the tool. Items on the tool were tested for inter-rater reliability among three independent raters. The findings demonstrated that overall the items in the tool were reliable and effective in evaluating objective physical features of the recreation facilities. Total Quality Management systems would benefit from the addition of an objective component to the evaluation of facility quality. The tool also provides a means of evaluating park quality over time, and can be modified to focus on users of particular ages, or for families versus individual users. Parks and recreation agencies have an important role to play in developing environmental supports for physical activity that may aid in reducing the national epidemic of obesity and related chronic diseases. [ABSTRACT FROM AUTHOR]

Asians and Native Hawaiians or other Pacific Islanders (NHPIs) are fast-growing U.S. minority populations at high risk for type 2 diabetes. Although national studies have described diabetes prevalence, incidence, and risk factors among Asians and NHPIs compared with non-Hispanic whites, little is known about state-level diabetes prevalence among these two racial groups, or about how they differ from one another with respect to diabetes risk factors. To examine state-level prevalence of self-reported, physician-diagnosed (diagnosed) diabetes and risk factors among Asians and NHPIs aged ≥18 years, CDC analyzed data from the 2011-2014 Behavioral Risk Factor Surveillance System (BRFSS). Among five states and Guam with sufficient data about NHPIs for analysis, the age-adjusted diabetes prevalence estimate for NHPIs ranged from 13.4% (New York) to 19.1% (California). Among 32 states, the District of Columbia (DC), and Guam that had sufficient data about Asians for analysis, diabetes prevalence estimates for Asians ranged from 4.9% (Arizona) to 15.3% (New York). In the five states and Guam with sufficient NHPI data, NHPIs had a higher age-adjusted prevalence of diabetes than did Asians, and a higher proportion of NHPIs were overweight or obese and had less than a high school education compared with Asians. Effective interventions and policies might reduce the prevalence of diabetes in these growing, high-risk minority populations.

Vision loss and blindness are among the top 10 disabilities in the United States, causing substantial social, economic, and psychological effects, including increased morbidity, increased mortality, and decreased quality of life.* There are disparities in vision loss based on age, sex, race/ethnicity, socioeconomic status, and geographic location. Current surveillance activities using national and state surveys have characterized vision loss at national and state levels. However, there are limited data and research at local levels, where interventions and policy decisions to reduce the burden of vision loss and eliminate disparities are often developed and implemented. CDC analyzed data from the American Community Survey (ACS) to estimate county-level prevalence of severe vision loss (SVL) (being blind or having serious difficulty seeing even when wearing glasses) in the United States and to describe its geographic pattern and its association with poverty level. Distinct geographic patterns of SVL prevalence were found in the United States; 77.3% of counties in the top SVL prevalence quartile (≥4.2%) were located in the South. SVL was significantly correlated with poverty (r = 0.5); 437 counties were in the top quartiles for both SVL and poverty, and 83.1% of those counties were located in southern states. A better understanding of the underlying barriers and facilitators of access and use of eye care services at the local level is needed to enable the development of more effective interventions and policies, and to help planners and practitioners serve the growing population with and at risk for vision loss more efficiently.

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.