Nonmetro Counties Research Articles

The necessity of sociodemographic status adjustment in hospital value rankings for perforated appendicitis in children

Hospitals are increasingly focused on demonstration of high-value care for common surgical procedures. Although sociodemographic status (SDS) factors have been tied to various surgical outcomes, the impact of SDS factors on hospital value rankings has not been well explored. Our objective was to examine effects of SDS factors on high-value surgical care at the patient level, and to illustrate the importance of SDS adjustment when evaluating hospital-level performance. Perforated appendicitis hospitalizations were identified from the 2012 Kids' Inpatient Database. The primary outcome of interest was high-value care as defined by evaluation of duration of stay and cost. SDS factors included race, health insurance type, median household income, and patient location. The impact of SDS on high-value care was estimated using regression models after accounting for hospital-level variation. Risk-adjusted value rankings were compared before and after adjustment for SDS. From 9,986 hospitalizations, 998 high-value encounters were identified. African Americans were less likely to experience high-value care compared with white patients after adjusting for all SDS variables. Although private insurance and living in nonmetro counties were associated independently with high-value care, the effects were attenuated in the fully adjusted models. For the 136 hospitals ranked according to risk-adjusted value status, 59 hospitals' rankings improved after adjustment and 53 hospitals' rankings declined. After adjustment for patient and hospital factors, SDS has a small but significant impact on risk-adjusted hospital performance ranking for pediatric appendicitis. Adjustment for SDS should be considered in future comparative performance assessment.

Disparities in the Availability of Farmers Markets in the United States.

Farmers markets (FM) have been proposed by researchers, policymakers, and health agencies as a potential community-level strategy to prevent obesity and reduce disparities in healthy food access in the U.S. Information about disparities in farmers market availability is scarce. This research aimed to examine county-level associations between farmers market (FM) availability and demographic, socioeconomic, health, and environmental measures in an effort to determine if disparities in availability exist in the U.S. An ecological study of 3,135 U.S. counties was conducted in 2013 using 2009-2010 data extracted from the United States Department of Agriculture Food Environment Atlas. Logistic regression and Poisson regression models were used to determine associations between county-level FM availability and measures such as percentage of non-Hispanic black residents, median household income, and number of grocery stores per 100,000 residents (i.e., per capita). Regression models were stratified by metro county status and all analyses were adjusted for state-level clustering. There were 1,774 (56.6%) counties with at least one FM available. Median household income was associated with increased odds of having at least one FM available among non-metro counties, but not metro counties. Percentage of non-Hispanic black residents and residents living in poverty were negatively associated with per capita FMs among metro and non-metro counties. Per capita fast food restaurants was negatively associated with per capita FMs among metro counties. Disparities in FM availability exist in the U.S. More research on the behavioral and health implications of farmers market availability should be conducted.

Rural Bound: Determinants of Metro to Non‐Metro Migration in the United States

AbstractA general global precept is that agglomeration forces lead to migration from rural to urban areas. Yet for much of the time since the early 1970s, more people have moved from metro to nonmetro U.S. counties. The underlying causes of this pattern have changed over time with economic shocks and changing household preferences. For instance, the post 2000 period has seen a significant decline in domestic migration rates, a significant increase in commodity prices that favor rural areas, and potential changes in the valuation of natural amenities that would affect migration. This article investigates the determinants of U.S. gross migration from metro to nonmetro counties and nonmetro to metro counties for the 1995–2000 and 2005–2009 periods in order to compare the differences in rural to urban and urban to rural migration, as well as compare the 1990s to the 2005–2009 periods. More specifically, the present study extends the literature by more broadly examining the underlying factors associated with deconcentration and economic restructuring arguments of metro to nonmetro migration. The article uses (1) extensive county‐to‐county migration flows and (2) the utility maximization theory that extends the framework of a discrete choice model. The results show that population density, distance to urban areas, industry mix employment growth, natural amenities, and percentage of older people are key factors underlying these migration patterns. We also find a slight fading of effects of natural amenities and population density, and a slight increase in the effects of wage and employment growth from 2005–2009.

County-Level Determinants of Mental Health, 2002–2008

Poor mental health is a concern in the US and world-wide. In this study we examine the effects of socioeconomic and environmental variables on the number of days of poor mental health reported across US counties. The results suggest that educational attainment, employment opportunities including self-employment, and social capital have important benefits in terms of community mental health. Other socio-demographic variables also tend to have predicted effects, as does the amount of sunshine in January, which is our control for Seasonal Affective Disorder. The general conclusion of the study is that living in a non-metro county and adjacent to a metro core, is associated with greater happiness. Mental health days also increase considerably due to natural disasters and they are affected by regional climate variability. For policymakers concerned about reducing the average number of poor mental health days across the nation, our results suggest that reducing poverty is a more powerful strategy than reducing income inequality.

Does rural broadband impact jobs and income? Evidence from spatial and first-differenced regressions

In order to better understand the association between broadband and jobs/income in non-metropolitan counties, this study conducts spatial and first-differenced regressions using recent data from the Federal Communications Commission and the National Broadband Map. The relationships between broadband adoption/availability and jobs/income in rural areas are analyzed after controlling for a host of potentially influential variables such as age, race, educational attainment, transportation infrastructure, and the presence of natural amenities. Results from spatial error models using 2011 data provide evidence that high levels of broadband adoption in non-metro counties are positively related to the number of firms and total employees in those counties. The first-differenced regressions use data from 2008 and 2011 to suggest that increases in broadband adoption levels are associated with increases in median household income and the percentage of non-farm proprietors in non-metro counties. Interestingly, simply obtaining increases in broadband availability (not adoption) over this time has no statistical impact on either jobs or income.

“Space Obesity”: The Effect of Remoteness on County Obesity

We test if remoteness of a county is one of the environmental factors that contribute to obesity. First, we employ geographically weighted regressions (GWRs) that allow us to observe local or regional patterns. We find that county obesity rate is spatially non-stationary, remoteness affects county obesity rates, and there are spatial heterogeneities in how distance affects county obesity rates. Next, we refine our estimates of the effect of remoteness on county obesity rate using a random effect model that accounts for county-level unobserved heterogeneity. Even after accounting for these heterogeneities and state fixed effects, we find measurable impact of remoteness on county obesity rate. Splitting the sample into metro and non-metro counties, we find that remoteness matters more for the obesity rates in the metro counties.

Abstract P118: County-Level Disparities in the Availability of Farmers Markets in the United States: An Ecological Study

Introduction: Farmers markets (FM) have been hypothesized to be a potential community-level obesity prevention strategy for populations at risk for chronic diseases because they provide a mechanism for communities to purchase healthy locally grown produce. This study aimed to identify county-level factors associated with FM availability in an effort to determine if disparities in availability exist in the US. Hypothesis: Increased FM availability will be associated with higher median household income, lower % minority residents, lower % obese residents and a higher number of grocery stores and recreation centers per 100,000 residents. Methods: An ecological study was conducted using 2009 data from the USDA Food Environment Atlas on 3,135 US counties. Crude and multivariable adjusted logistic regression models where used to determine associations between having at least one FM available and county-level variables such as % African American (AA) residents, % Hispanic residents, median household income, % WIC participants, % adults obese, % adults with diabetes, per capita grocery stores, per capita supercenters and per capita recreation centers. All analyses were stratified by metro county status and adjusted to address data clustering at the state-level. Results: There were 1,088 and 2,047 counties labeled metro and non-metro respectively. Metro Results : Median household income (p = 0.002) and per capita recreation centers (p < 0.0001) were positively associated with FM availability while % WIC residents (p = 0.008), per capita grocery stores (p = 0.02) and % adults with diabetes (p < 0.0001) showed a negative association. Non-Metro Results: Median household income (p < 0.0001), per capita recreation centers (p < 0.0001) and per capita supercenters (p < 0.0001) were positively associated with FM availability while % WIC residents (p = 0.02), per capita grocery stores (p < 0.0001) and % adults with diabetes (p < 0.03) showed a negative association. The % AA residents appeared to be negatively associated with FM availability but did not achieve statistical significance. County obesity prevalence was not associated with FM availability in both metro and non-metro counties. Conclusion: Results showed that counties with more recreation centers and a higher median household income have increased FM availability while counties with more WIC participants and residents with diabetes have less availability. More information on the association between FM access, diet and obesity in at risk populations should be collected at the individual level.

Poverty Segregation in Nonmetro Counties: A Spatial Exploration of Segregation Patterns in the US

Abstract Most research on segregation focuses on racial residential segregation in metropolitan statistical areas and typically uses a-spatial measures of segregation. What is less clear is if segregation measures operate in a similar fashion in nonmetropolitan areas and if spatial patterns exist for poverty segregation in nonmetro counties. The purpose of this research was to examine multiple dimensions of poverty segregation in the United States the period 2006–2010 for metropolitan and nonmetropolitan counties. Data for this analysis come from the 2006–2010 American Community Survey 5 year estimates, the 2000 U.S. Census of Population and Housing, Summary File 3 and the USDA Economic Research Service. Four different measures of poverty segregation were calculated, including both aspatial and spatial measures. A nonparametric Kruskal-Wallis test was used to test for variation in the segregation indices across metro and nonmetro areas and spatially autoregressive models were used to examine the socioeconomic correlates of poverty segregation. Results indicate significant variation in poverty segregation patterns in metro and nonmetro counties in the US, and nonmetro counties outside of the South have significantly lower levels of poverty segregation. This research adds to the literature by exploring patterns of metro and nonmetro poverty segregation and measuring different dimensions of segregation with an explicit spatial referent across counties in the contiguous United States in an effort to note differences in how segregation works across rural and urban places.

ENTREPRENEURSHIP IN RURAL AMERICA ACROSS TYPOLOGIES, GENDER AND MOTIVATION

This study examines the effect of rurality on early-stage necessity and opportunity entrepreneurship among women and men in America from three rural typology perspectives. To achieve this objective, we build a dataset that combines GEM U.S. individual data for 2005—2010 and county economic characteristics from the Bureau of Labor Statistics and the Census Bureau. We use three typologies to define rurality and compare the results, the OMB metro-nonmetro classification system (2003), Isserman (2005) and county population density. We further analyze this data in subsamples by gender using cross-section time-series rare events logistic regression with clustered robust errors and year fixed effects. Key findings indicate the three rural typologies show similar results in magnitude, direction and significance, although population density shows sensitivity to the rurality variable and subsamples. Also, compared to women in OMB metro counties in America, women who live in OMB nonmetro counties have a higher probability of engaging in opportunity entrepreneurship. This probability increases with college education and decreases if the woman lives alone or is retired. Among men, living in OMB nonmetro or Isserman rural counties also increases their probability of engaging in opportunity entrepreneurship. College education and being African American also increases this probability. Predictors of necessity entrepreneurship are having an income below 50,000 among women and being employed part time among men.

General surgeon workforce in Tennessee in the era of the Affordable Care Act

BackgroundThe Affordable Care Act of (ACA) 2010 may result in an increase in demand for surgery and may exacerbate any existing surgeon shortage. The purpose of this study was to examine factors associated with general surgeon workforce within counties in Tennessee in light of the ACA. Materials and methodsThe Area Resource File for 2011 was utilized for this study. Counties with less than 3 active surgeons/100,000 persons were classified as shortage counties (SC). Counties with more than 6 active surgeons/100,000 persons were considered over-supply counties (OC). Demographic factors for each county were determined. Univariate and multivariable analysis was used to determine factors associated with SC. ResultsThere are 95 counties in the state and 45.3% were SC and 33.7% were OC. Sixty-nine (72.6%) of the counties had at least one hospital and 57 (60%) were in non-metro counties. Multivariable logistic regression analysis revealed that increasing percent uninsured in a county was positively associated with a SC. No other factors were associated with SC. To meet the cutoff of three surgeons per 100,000 in SC 23 general surgeons would be required. There was an excess of 219 general surgeons in OCs. ConclusionsThere appears to be an adequate supply of general surgeons but a maldistribution exists, particularly if demand increases with the implementation of the ACA. If redistribution of surgeons does not occur through natural changes in supply and demand, careful policy changes may be considered to encourage redistribution of surgeon resources to meet demand in counties that are currently underserved.

Broadband's Contribution to Economic Health in Rural Areas: A Causal Analysis

The diffusion of broadband Internet access across America during the 2000s brought with it a significant amount of concern that rural areas might be left behind in terms of the availability, adoption, and benefits of this technology. i. The presence of a rural-urban broadband “digital divide” is well documented in the economic literature. ii. Several studies have suggested that broadband access positively impacts employment as well as other quality of life issues (health care, education, social linkages) in rural areas; iii. however, many analyses were based on hypothetical assumptions or case studies. State and federal policies related to broadband investment and deployment remain contested. As the funds flowing to additional advanced broadband infrastructure under the American Reinvestment and Recovery Act end and as the FCC initiates changes to universal service, questions regarding where American broadband infrastructure stands and how high speed capability contributes to economic development are receiving new attention. Better data from the NTIA/Census Current Population Supplements and the more detailed data from NTIA’s investments in statewide mapping can be used to provide better responses to questions regarding broadband’s contributions to economic health. This paper uses the latest data on both broadband availability and adoption to empirically gauge the contribution of broadband to the economic health of rural areas. We utilize availability data from the National Broadband Map aggregated to county level, and county-level adoption data from Federal Communication Commission’s Form 477. Economic health variables of interest are gathered from a variety of sources and include median household income, number of firms with paid employees, total employed, percentage in poverty, and the percentage of employees classified as either creative class or non-farm proprietors. A propensity score matching technique (between a “treated” group and a control group) is used to make causal statements regarding broadband and economic health. We measure whether the growth rates between 2001 and 2010 for different economic measures are statistically different for the treated and non-treated groups, restricting the analysis to non-metropolitan counties. Results suggest that high levels of broadband adoption in rural areas do causally (and positively) impact income growth between 2001 and 2010 as well as (negatively) influence poverty and unemployment growth. Similarly, low levels of broadband adoption in rural areas lead to declines in the number of firms and total employment numbers in the county. Broadband availability measures (as opposed to adoption) demonstrate only limited impact in the results. We also use the FCC data to assess whether Connected Nation participants in two states achieved higher increases in broadband providers or adoption rates when compared to similar counties that did not participate in the program. We find that the program has a dramatic influence on the number of residential broadband providers in non-metro counties but no impact on increases in broadband adoption rates compared to otherwise similar non-participating counties. Consequently, there is no particular effect on economic growth. This research offers an empirical documentation of the causal relationship between broadband and economic growth in rural areas, and offers an outside assessment of the highly visible Connected Nation program. It meshes the latest data on availability with that for adoption, and incorporates a technique that can make causal claims about how broadband affects specific measures of economic health. Thresholds for adoption / availability can be identified as having measurable impact on economic growth rates in rural areas, which leads to policy prescriptions. NOTES: i Malecki, 2003; Parker, 2000; Strover, 2001. ii Whitacre and Mills, 2007; Dickes, Lamie and Whitacre, 2010; Strover, 2011. iii Katz and Suter, 2009; LaRose et al., 2008, Stenberg et al., 2009.

Association of elevation, urbanization and ambient temperature with obesity prevalence in the United States

The macrogeographic distribution of obesity in the United States, including the association between elevation and body mass index (BMI), is largely unexplained. This study examines the relationship between obesity and elevation, ambient temperature and urbanization. Data from a cross-sectional, nationally representative sample of 422603 US adults containing BMI, behavioral (diet, physical activity, smoking) and demographic (age, sex, race/ethnicity, education, employment, income) variables from the 2011 Behavioral Risk Factor Surveillance System were merged with elevation and temperature data from WorldClim and with urbanization data from the US Department of Agriculture. There was an approximately parabolic relationship between mean annual temperature and obesity, with maximum prevalence in counties with average temperatures near 18 °C. Urbanization and obesity prevalence exhibited an inverse relationship (30.9% in rural or nonmetro counties, 29.2% in metro counties with <250000 people, 28.1% in counties with population from 250000 to 1 million and 26.2% in counties with >1 million). After controlling for urbanization, temperature category and behavioral and demographic factors, male and female Americans living <500 m above sea level had 5.1 (95% confidence interval (CI) 2.7-9.5) and 3.9 (95% CI 1.6-9.3) times the odds of obesity, respectively, as compared with counterparts living ≥ 3000 m above sea level. Obesity prevalence in the United States is inversely associated with elevation and urbanization, after adjusting for temperature, diet, physical activity, smoking and demographic factors.

Inflammatory and non-inflammatory breast cancer survival by socioeconomic position in the Surveillance, Epidemiology, and End Results database, 1990-2008.

Although it has been previously reported that patients with inflammatory breast cancer (IBC) experience worse survival than patients with other breast cancer (BC) types, the socioeconomic and ethnic factors leading to this survival difference are not fully understood. The association between county-level percent of persons below the poverty level and BC-specific (BCS) survival for cases diagnosed from 1990 to 2008 in the Surveillance, Epidemiology, and End Results (SEER) database linked to census derived county attributes was examined. A sub-analysis of cases from 2000 to 2008 also examined BCS survival by an index combining percent below poverty and less than high school graduates as well as metropolitan versus non-metropolitan county of residence. The Kaplan-Meier estimator was used to construct survival curves by stage, inflammatory status, and county-level socioeconomic position (SEP). Stage and inflammatory status stratified proportional hazards models, adjusted for age, race/ethnicity, tumor and treatment characteristics were used to determine the hazard of BCS death by county-level SEP. Kaplan-Meier survival curves indicated IBC has worse survival than stage matched non-IBC, (stage III IBC median survival = 4.75 years vs. non-IBC = 13.4 years, p < 0.0001). Residing in a lower SEP, non-metro county significantly worsens BCS survival for non-IBC in multivariate proportional hazards models. African American cases appear to have worse survival than non-Hispanic Whites regardless of inflammatory status, stage, county-level SEP, tumor, or treatment characteristics. This is the first study to examine IBC survival by SEP in a nation-wide population-based tumor registry. As this analysis found generally poorer survival for IBC, regardless of SEP or race/ethnicity, it is important that interventions that help educate women on IBC symptoms target women in various SEP and race/ethnicity groups.

Rural Entrepreneurship in a Time of Recession

Economic recessions increase costs, risk, stress, uncertainty, and business failures while decreasing the availability of employment. Individuals who seek to become self-employed in recessionary times, whether out of need or for opportunity reasons, face difficult and unique circumstances. We use cross-section repeated-measures rare events logistic regression to model the effects that living in rural America and changes in the economy have on the probability of individuals engaging in necessity or opportunity entrepreneurial activities both before the recession (2005–2007) and during the recession (2008–2010). Key findings indicate that before the recession, individuals living in rural metro and nonmetro counties were more likely to engage in opportunity-driven entrepreneurial activities when compared to individuals living in more urban counties. Positive employment growth rates before the recession also increased the probability that individuals in rural areas would engage in opportunity entrepreneurship. The recession marked a shift in the motivation of individuals in rural America to become self-employed. There is a clear decline in opportunity entrepreneurship and an increase in necessity entrepreneurship. In all rural and mixed-rural counties, college education positively predicts opportunity entrepreneurship, whereas individuals with incomes below $50,000 or working in a part-time job are more likely to engage in entrepreneurship driven by need.

Self-Rated Health and the “First Move” Around Retirement: A Longitudinal Study of Older Americans

I examine whether less favorable self-rated health raises the risk of outmigration more for young-old adults (aged 53-63 at the start of the 10-year longitudinal study in 1994) in nonmetro than metro counties and increases the odds that both groups of outmigrants will choose metro over nonmetro destinations. Finally, I examine whether nonmetro outmigrants are more likely than metro outmigrants to cite a health concern or a desire to get closer to relatives or friends as a reason for the migration. I use the Health and Retirement Study (HRS) to track the main residences of nonmetro and metro older adults from 1994-2003. With a discrete-time Event History Analysis, I assess the joint effects of nonmetro/metro residence in 1994 and self-rated health (updated at each biennial wave) upon the risk of a first migration. Those who migrated were asked to recall why. At worse levels of self-rated health, the odds of remaining in a nonmetro county of residence drop in favor of migrating to another nonmetro county. Among migrants, the worse the self-rated health, the higher the odds of within-type migration (nonmetro-nonmetro and metro-metro) over cross-type migration (nonmetro-metro and metro-nonmetro). The percentages of migrants citing a health concern or a desire to live closer to relatives or friends as a reason for migration do not differ by county type of origin. An implication for rural health policy is that young-old adults with worse self-rated health tend to remain in nonmetro areas, even when they migrate.

Examining Associations among Obesity and Per Capita Farmers' Markets, Grocery Stores/Supermarkets, and Supercenters in US Counties

Fruit and vegetable consumption is an important component of a healthful diet, yet fruits and vegetables are underconsumed, especially among low-income groups with high prevalence rates of obesity. This study used data from the US Department of Agriculture Economic Research Service Food Environment Atlas to examine county-level associations among obesity prevalence and per capita farmers' markets, grocery stores/supermarkets, and supercenters, adjusted for natural amenities, percent black, percent Hispanic, median age, and median household income, stratified by county metropolitan status. In models that included all three of the food venues, supercenters and grocery stores per capita were inversely associated with obesity in the combined (metro and nonmetro) and metro counties. Farmers' markets were not significant in the model for combined (metro and nonmetro) or for metro counties alone, but were significantly inversely related to obesity rates in the model for nonmetro counties. In this ecologic study, density of food venues was inversely associated with county-level obesity prevalence. Thus, future research should examine similar associations at the individual-level.

Moving Up in Rural America: Economic Attainment of Nonmetro Latino Immigrants

AbstractRapid Hispanic population growth represents a pronounced demographic transformation in many nonmetropolitan counties, particularly since 1990. Its considerable public policy implications stem largely from high proportions of new foreign‐born residents. Despite the pressing need for information on new immigrants in nonmetro counties and a bourgeoning scholarship on new rural destinations, few quantitative analyses have measured systematically the social and economic well‐being of Latino immigrants. This study analyzes the importance of place for economic well‐being, an important public policy issue related to rural Hispanic population growth. We consider four measures of economic mobility: full‐time, year‐round employment; home ownership; poverty status; and income exceeding the median national income. We conduct this analysis for 2000 and 2006–2007 to capture two salient periods of nonmetro Hispanic population growth, using a typology that distinguishes among nonmetropolitan areas by the categories of “traditional” immigrant destinations concentrated in the Southwest and Northwest, “new” immigrant destinations to capture recent and rapid Hispanic population growth in the Midwest and Southeast, and “all other” rural destinations as a reference category representing more typical nonmetro population trends. We also compare our results to those for metropolitan destinations. We find that place type matters little for stable employment but more so for wealth accumulation and income security and mobility. Compared with urban Latino immigrants, rural Latino immigrants exhibit higher rates of homeownership as well as greater likelihoods of falling into poverty and lower likelihoods of earning a measure of U.S. median income. From 2000 to 2006–2007, rural‐urban differences deteriorated slightly in favor of urban areas. We conclude by discussing implications of these findings and those of addressing rural immigrant economic well‐being more generally.

The evolving rural and urban interdependence: Opportunities and challenges for community economic development

Regional science researchers and scholars continue to distinguish between “urban or metro” and “rural or nonmetro” counties and erroneously portray metro counties to be synonymous to urbanized areas and nonmetro as rural. But the U.S. Census Bureau in 2005 indicated that 51% of nonmetro counties are actually urban places and about 41% of all metro counties in the U.S. can also be classified as rural (U.S. Census Bureau, 2005). A possible conclusion from the above is that there is an emerging interdependence between metro and nonmetro counties and hence between urban and rural areas which can generate both opportunities and challenges for economic development policymaking. Some of the challenges include differentiating urban from rural areas and how such distinctions could militate against public policy formulation to stir up development in the two areas. The review of the literature in this paper shows that the interdependence between rural and urban areas is real and that it is important for regional development practitioners and policy makers to engage in region-based development planning. The paper concluded that the interdependence between adjacent rural and urban or metro and non-metro counties could be used to leverage growth, and engage in successful cooperation to engender regional and global economic power for American communities. Key words: Rural, urban, interdependence, regional economic development.

Migration of Retirement-Age Blacks to Nonmetropolitan Areas in the 1990s

Older blacks migrated to nonmetropolitan (nonmetro) communities in the 1990s to a degree not true of the past. Some of the nonmetro counties that attracted them are well-known retirement areas also favored by other retirees, mostly whites. Two-thirds of black retirement counties, however, are areas in the Old South that are not attracting other retirees at a substantial rate, if at all. Although the data indicate significant rates of retirement-age blacks migrating to 85 nonmetro counties, most migration by older blacks is to metro destinations. Language: en

Spatial Patterns of Obesity and Associated Risk Factors in the Conterminous U.S.

The obesogenic environment is hypothesized to increase obesity risk by discouraging physical activity and limiting the availability of healthy food. This research reports the prevalence of obesity and risk factors (physical activity and fruit and vegetable consumption) by creating spatially smoothed maps and analyzing local autocorrelation and aims to examine associations of obesity and risk factors at the national level. Data were obtained in 2008 from the Behavioral Risk Factor Surveillance System for the years 2000-2006 aggregated to the county level. A weighted head-banging smoothing algorithm was used that effectively replaced the proportion of obesity and risk factors for each county with a weighted median that incorporates data from neighboring counties. Significant spatial clusters of obesity and risk factors were identified by a local Moran's I analysis. All analyses were performed in 2008-2009. A higher prevalence of obesity was generally found in the non-metro counties of the South, whereas lower prevalence was found in the West and the Northeast. A lower prevalence of leisure-time physical activity was generally found in the areas where obesity prevalence was higher and vice versa. A lower prevalence of fruit and vegetable consumption was found mainly in the non-metro counties of the South and the Great Plains. The national patterns of obesity and associated risk factors obtained may reflect a unique set of meso-environmental drivers, including climate, land use, population density, and culture. Future research should address this regional variability and explicitly consider the spatial scales at which such environmental factors operate.