Estimating vaccination coverage for routinely recommended vaccines among children aged 24 months and adolescents aged 13 through 17 years using data from immunization information systems in the United States.

OBJECTIVE: To use a model-based approach to estimate vaccination coverage of routinely recommended childhood and adolescent vaccines for the United States. METHODS: We used a hierarchical model with retrospective cohort data from eleven IIS jurisdictions, which contains vaccination records submitted by providers. Numerators included data from 2014 to 2019 at the county level for 2.4 million children at age 24 months and 14.4 million adolescents aged 13-17. Age-appropriate Census populations were used as denominators. Covariates associated with childhood and adolescent vaccinations were included in the model. Model-based estimates for each county were generated and aggregated to the national level to produce national vaccination coverage estimates and compared to National Immunization Survey (NIS) estimates of vaccination coverage. Trends of estimated vaccination coverage were compared between the model-based approach and NIS. RESULTS: From 2014 to 18, model-based national vaccination coverage estimates were within ten percentage points of NIS-Child vaccination coverage estimates for most vaccines among children at age 24 months. One notable difference was higher model-based vaccination coverage estimates for hepatitis B birth dose compared to NIS-Child coverage estimates. From 2014 to 19, model-based national vaccination coverage estimates were within ten percentage points of NIS-Teen vaccination coverage estimates for most vaccines among adolescents aged 13-17 years. Model-based vaccination coverage estimates were notably lower for varicella, MMR, and Hepatitis B compared to NIS-Teen coverage estimates among adolescents. Trends in estimates of national vaccination coverage were similar between model-based estimates for children and adolescents as compared to NIS-Child and NIS-Teen, respectively. CONCLUSIONS: A hierarchical model applied to data from IIS may be used to estimate coverage for routinely recommended vaccines among children and adolescents and allows for timely analyses of childhood and adolescent vaccines to quickly assess trends in vaccination coverage across the United States. Monitoring real-time vaccination coverage can help promote immunizations to protect children and adolescents against vaccine-preventable diseases.

Frequency and cost of live vaccines administered too soon after prior live vaccine in children aged 12 months through 6 years, 2014-2017.

OBJECTIVE: To identify number of children who received live vaccines outside recommended intervals between doses and calculate corrective revaccination costs. METHODS: We analyzed >1.6 million vaccination records for children aged 12 months through 6 years from six immunization information system (IIS) Sentinel Sites from 2014-15 when live attenuated influenza vaccine (LAIV, FluMist® Quadrivalent) was recommended for use, and from 2016-17, when not recommended for use. Depending on the vaccine, insufficient intervals between live vaccine doses are less than 24 or 28 days from a preceding live vaccine dose. Private and public purchase costs of vaccines were used to determine revaccination costs of live vaccine doses administered during the live vaccine conflict interval. Measles, mumps, rubella (MMR), varicella, combined MMRV, and LAIV were live vaccines evaluated in this study. RESULTS: Among 946,659 children who received at least one live vaccine dose from 2014-15, 4,873 (0.5%) received at least one dose too soon after a prior live vaccine (revaccination cost, $786,413) with a median conflict interval of 16 days. Among 704,591 children who received at least one live vaccine dose from 2016-17, 1,001 (0.1%) received at least one dose too soon after a prior live vaccine (revaccination cost, $181,565) with a median conflict interval of 14 days. The live vaccine most frequently administered outside of the recommended intervals was LAIV from 2014-15, and varicella from 2016-17. CONCLUSIONS: Live vaccine interval errors were rare (0.5%), indicating an adherence to recommendations. If all invalid doses were corrected by revaccination over the two time periods, the cost within the IIS Sentinel Sites would be nearly one million dollars. Provider awareness about live vaccine conflicts, especially with LAIV, could prevent errors, and utilization of clinical decision support functionality within IISs and Electronic Health Record Systems can facilitate better vaccination practices.

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

BACKGROUND: 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. METHODS: 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 ß-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). RESULTS: 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. CONCLUSIONS: 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.

Diabetes Among Asians and Native Hawaiians or other Pacific Islanders--United States, 2011-2014.

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.

Geographic disparity of severe vision loss - United States, 2009-2013.

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.

Diabetes Interactive Atlas.

The Diabetes Interactive Atlas is a recently released Web-based collection of maps that allows users to view geographic patterns and examine trends in diabetes and its risk factors over time across the United States and within states. The atlas provides maps, tables, graphs, and motion charts that depict national, state, and county data. Large amounts of data can be viewed in various ways simultaneously. In this article, we describe the design and technical issues for developing the atlas and provide an overview of the atlas' maps and graphs. The Diabetes Interactive Atlas improves visualization of geographic patterns, highlights observation of trends, and demonstrates the concomitant geographic and temporal growth of diabetes and obesity.

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%).

Small area variation in diabetes prevalence in Puerto Rico / Variación en un área pequeña de la prevalencia de la diabetes en 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%).

OBJETIVO: Calcular la prevalencia en el año 2009 de casos con diagnóstico de diabetes en Puerto Rico en adultos de 20 años de edad o mayores, para conocer mejor su distribución geográfica con objeto de que los responsables políticos puedan encauzar más eficientemente los programas de prevención y control. MÉTODOS: Se ajustó un modelo multinivel bayesiano a la combinación de datos del Sistema de Vigilancia de Factores de Riesgo del Comportamiento 2008-2010 y del Censo de los Estados Unidos del 2009 para calcular la prevalencia de la diabetes en cada uno de los 78 municipios de Puerto Rico. RESULTADOS: El cálculo del valor medio no ajustado para todos los municipios fue de 14,3% (intervalo por municipio de 9,9 a 18,0%). La amplitud promedio de los intervalos de confianza fue de 6,2%. Hubo poca diferencia entre los cálculos ajustados y los no ajustados. CONCLUSIONES: Los valores obtenidos mediante estos cálculos correspondientes a 78 municipios fueron por término medio más elevados y mostraron menor variabilidad (es decir, el intervalo era más pequeño) que los cálculos anteriormente publicados sobre la prevalencia de la diabetes en todos los municipios de los Estados Unidos en el 2008 (media, 9,9%; intervalo de 3,0 a 18,2%).

Bayesian Small Area Estimates of Diabetes Incidence by United States County, 2009.

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, efficient targeting of such programs requires county-level estimates of diabetes incidence-the fraction of the non-diabetic 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.

State-specific synthetic estimates of health status groups among inactive older adults with self-reported diabetes, 2000-2009.

INTRODUCTION: Physical activity helps diabetic older adults who have physical impairments or comorbid conditions to control their disease. To enable state planners to select physical activity programs for these adults, we calculated synthetic state-specific estimates of inactive older adults with diabetes, categorized by defined health status groups. METHODS: Using data from the 2000 through 2009 National Health Interview Survey (NHIS) and the Behavioral Risk Factor Surveillance System (BRFSS), we calculated synthetic state-specific estimates of inactive adults with diabetes who were aged 50 years or older for 5 mutually exclusive health status groups: 1) homebound, 2) frail (functional difficulty in walking one-fourth mile, climbing 10 steps, standing for 2 hours, and stooping, bending, and kneeling), 3) functionally impaired (difficulty in 1 to 3 of these functions), 4) having 1 or more comorbid conditions (with no functional impairments), and 5) healthy (no impairments or comorbid conditions). We combined NHIS regional proportions for the health status groups of inactive, older diabetic adults with BRFSS data of older diabetic adults to estimate state-specific proportions and totals. RESULTS: State-specific estimates of health status groups among all older adults ranged from 2.2% to 3.0% for homebound, 5.8% to 8.8% for frail, 20.1% to 26.1% for impaired, 34.9% to 43.7% for having comorbid conditions, and 4.0% to 6.9% for healthy; the remainder were older active diabetic adults. Except for the homebound, the percentages in these health status groups varied significantly by region and state. CONCLUSION: These state-specific estimates correspond to existing physical activity programs to match certain health status characteristics of groups and may be useful to program planners to meet the needs of inactive, older diabetic adults.

Geographic distribution of diagnosed diabetes in the U.S.: a diabetes belt.

BACKGROUND: The American "stroke belt" has contributed to the study of stroke. However, U.S. geographic patterns of diabetes have not been as specifically characterized. PURPOSE: This study identifies a geographically coherent region of the U.S. where the prevalence of diagnosed diabetes is especially high, called the "diabetes belt." METHODS: In 2010, data from the 2007 and 2008 Behavioral Risk Factor Surveillance System were combined with county-level diagnosed diabetes prevalence estimates. Counties in close proximity with an estimated prevalence of diagnosed diabetes ≥11.0% were considered to define the diabetes belt. Prevalence of risk factors in the diabetes belt was compared to that in the rest of the U.S. The fraction of the excess risk associated with living in the diabetes belt associated with selected risk factors, both modifiable (sedentary lifestyle, obesity) and nonmodifiable (age, gender, race/ethnicity, education), was calculated. RESULTS: A diabetes belt consisting of 644 counties in 15 mostly southern states was identified. People in the diabetes belt were more likely to be non-Hispanic African-American, lead a sedentary lifestyle, and be obese than in the rest of the U.S. Thirty percent of the excess risk was associated with modifiable risk factors, and 37% with nonmodifiable factors. CONCLUSIONS: Nearly one third of the difference in diabetes prevalence between the diabetes belt and the rest of the U.S. is associated with sedentary lifestyle and obesity. Culturally appropriate interventions aimed at decreasing obesity and sedentary lifestyle in counties within the diabetes belt should be considered.

Knowledge and perceived risk of tuberculosis: US racial and regional differences.

The purpose of this study is to report the findings of the 2004 National Health Interview Survey (NHIS) questions on tuberculosis (TB) knowledge and perceived risk of contracting TB. Tuberculosis (TB) continues to be a major health threat in the United States, but minimal effort is made on public education to increase knowledge about TB. Using data from the 2004 NHIS, this study examined knowledge and perceived risk of TB of 26,136 US respondents. Results showed that nationally, how much a respondent knew about tuberculosis, knowing someone with tuberculosis, being 18-34 years old, and being Black were most strongly associated with perceived high to medium risk of getting TB. Black respondents were nearly twice as likely to perceive a high to moderate risk compared to other races in the Northeast and South. Knowing someone with tuberculosis or having a lot or some knowledge of the disease was strongly associated with perceived risk in all regions of the nation. Conclusions were to increase efforts targeted toward broad health promotion education activities on TB risk.

Self-reported physical activity among South Carolina adults trying to maintain or lose weight.

OBJECTIVES: The obesity epidemic is related to widespread physical inactivity in the United States. This study determined the proportion of South Carolinians trying to maintain or lose weight and within that subpopulation, the number who practiced a restricted diet and engaged in physical activity. METHODS: Data from the 2002 South Carolina Behavioral Risk Factor Surveillance System survey were used to classify adults who were trying to maintain weight or lose weight. Self-reported prevalence of restricted diet and participation in physical activity were investigated. Of those who reported weight control practices, levels of physical activity were analyzed to determine if those trying to maintain weight or lose weight were meeting the national guidelines for moderate or vigorous physical activity. RESULTS: More than 70% of South Carolina adults reported trying to control their weight and the majority reported using physical activity for weight control. Though the majority reported use of restricted diet and physical activity, more than one-half of those individuals did not meet the minimum standards for physical activity designed for heart health. CONCLUSIONS: Although most adults who are trying to maintain or lose weight are participating in physical activity, public health efforts need to focus on encouraging these adults to increase their levels of physical activity to meet the minimum standards for health benefits. Health care providers have an opportunity to educate and encourage patients about the recommended levels of physical activity to obtain maximum health benefits.

Development and use of a tool for assessing sidewalk maintenance as an environmental support of physical activity.

The importance of regular physical activity is well documented, yet according to epidemiological surveillance data, physical inactivity among all age groups persists. Past attempts to promote physical activity focused on individual-level changes; current approaches focus on environmental changes that will provide opportunities for whole communities to be active. The current ecological focus has led to an increase in funding and research regarding environmental supports of physical activity. As this is a new area of research, much work needs to be done to improve the ability to assess environmental features that support physical activity. This article describes a partnership between researchers and community members to develop and test an objective tool to measure sidewalk maintenance. Community members used data collected with the tool to increase awareness about sidewalk maintenance issues among local policy makers. Collaboration between researchers and community partners was critical for the success of this study.

Physical activity trends in South Carolina, 1994-2000.

OBJECTIVES: During the 1990s, physical activity recommendations and surveillance methods were developed in an attempt to increase and monitor, respectively, regular physical activity prevalence rates. For this article, Behavioral Risk Factor Surveillance System data were analyzed to determine whether regular physical activity proportions in South Carolina adults changed from 1994 to 2000. The physical activity prevalence rates for South Carolina were compared with national rates and Healthy People 2000 goals to measure progress. The rate of physical activity counseling by physicians and other health professionals was also analyzed from 1998 to 1999. METHODS: Total subjects included 10,495 adults ages 18 years and older from South Carolina and 545,445 from the remainder of the United States. Using random-digit dialing procedures in 1994, 1996, 1998 and 2000, the two most frequent types of leisure-time physical activity performed in the past month were identified. For activities listed, the frequency (days/wk) and duration (minutes/d) were obtained. Linear regressions were performed on regular physical activity and inactivity for the total population and by gender, race, age, and body mass index (BMI). Data pertaining to whether or not a physician or other health professional had provided physical activity counseling were also obtained for 1998 and 1999. RESULTS: From 1994 to 2000, the proportion of South Carolina adults participating in regular leisure time physical activity significantly increased (10.8%). Interestingly, the prevalence of regular physical activity in the rest of the nation remained unchanged during this time. Although significant increases were observed in nearly all subgroups, physical activity prevalence rates for South Carolina adults lagged behind national levels and did not meet Healthy People 2000 goals. Physical activity counseling by physicians and other health professionals increased from 1998 (24.1%) to 1999 (30.4%). CONCLUSIONS: While it is not known what factors influenced regular physical activity from 1994 to 2000, they seem to have been equally effective in South Carolina adults of both genders, both races, regular and overweight status, and nearly all age groups. Despite these positive trends, additional efforts are needed to develop and implement effective community and primary care physical activity interventions that facilitate improvements among the nearly two-thirds of South Carolina adults who do not participate in sufficient physical activity to reap significant health benefits.

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 x m(-2); 133 females, age = 47.4 +/- 17.5 yr, BMI = 26.9 +/- 5.7 kg x 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 x d(-1) (males = 7192 +/- 3596 vs females = 5210 +/- 3518 steps x 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.

Socioeconomic status and perceptions of access and safety for physical activity.

BACKGROUND: Environmental factors may play an important role on influencing physical activity (PA) behaviors. PURPOSE: Perceptions of access and safety for PA were compared among residents who were stratified as low or high in socioeconomic status (SES). METHODS: Residents of a U.S. southeastern county (N = 1,194, 18-96 years of age) were contacted using a random-digit-dial method and asked about neighborhood and community environmental supports for PA. A Geographic Information System (GIS) was used to identify trails, sidewalks, public recreation facilities, and violent crime incidents. RESULTS: A cluster analysis identified 10 census tracts as low SES and 11 census tracts as high SES (median household income, owner-occupied houses). More African Americans (66.5%) than Whites (33.5%) were classified as living in low-SES areas. Respondents from low-SES areas also reported engaging in less PA based on Centers for Disease Control and Prevention and American College of Sports Medicine recommendations than respondents from high-SES areas (p <.05). Respondents from low-SES (vs. high-SES) areas reported higher perceptions of neighborhood crime, unattended dogs, unpleasantness of neighborhoods, untrustworthy neighbors, and less access to public recreation facilities (ps <.05). GIS data for presence of sidewalks, recreation facilities, and crime did not support these differences in perceptions; however, respondents from low-SES (vs. high-SES) areas had substantially fewer trails. Having and using trails in one's community predicted sufficient PA and walking for 150 min/week for low-SES respondents but not for high SES respondents (ps =.05, adjusted for covariates). CONCLUSIONS: Having access to trails is an important environmental feature among low-SES communities and should be the focus of future community-based PA interventions.

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.

Measuring the environment for friendliness toward physical activity: a comparison of the reliability of 3 questionnaires.

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.