Approximately 46 million persons (14%) in the United States live in nonmetropolitan counties.[\*](#FN1){ref-type="fn"} Compared with metropolitan residents, nonmetropolitan residents have a higher prevalence of obesity-associated chronic diseases such as diabetes ([@R1]), coronary heart disease ([@R1]), and arthritis ([@R2]). The 2005--2008 National Health and Nutrition Examination Survey (NHANES) found a significantly higher obesity prevalence among adults in nonmetropolitan (39.6%) than in metropolitan (33.4%) counties ([@R3]). However, this difference has not been examined by state. Therefore, CDC examined state-level 2016 Behavioral Risk Factor Surveillance System (BRFSS) data and found that the prevalence of obesity (body mass index \[BMI\] ≥30 kg/m^2^) was 34.2% among U.S. adults living in nonmetropolitan counties and 28.7% among those living in metropolitan counties (p\<0.001). Obesity prevalence was significantly higher among nonmetropolitan county residents than among metropolitan county residents in all U.S. Census regions, with the largest absolute difference in the South (5.6 percentage points) and Northeast (5.4 percentage points). In 24 of 47 states, obesity prevalence was significantly higher among persons in nonmetropolitan counties than among those in metropolitan counties; only in Wyoming was obesity prevalence higher among metropolitan county residents than among nonmetropolitan county residents. Both metropolitan and nonmetropolitan counties can address obesity through a variety of policy and environmental strategies to increase access to healthier foods and opportunities for physical activity ([@R4]).

BRFSS is a state-based, random-digit--dialed telephone survey of U.S. adults aged ≥18 years, conducted annually by CDC and state and territorial health departments to monitor health conditions and related behaviors.[^†^](#FN2){ref-type="fn"} BRFSS uses multistage, stratified sampling to select a representative sample of the noninstitutionalized adult population in 50 states, the District of Columbia (DC), and selected U.S. territories. In 2016, using combined landline and cell phone data across all states, the median response rate was 47.0%, which was calculated using rates from the American Association of Public Opinion Research.[^§^](#FN3){ref-type="fn"} Self-reported weight and height were used to calculate BMI (weight \[kg\]/height \[m\]^2^); obesity was defined as BMI ≥30 kg/m^2^.[^¶^](#FN4){ref-type="fn"} Among 477,665 respondents, 39,186 (8.2%) were excluded, including 36,848 with missing BMI values and 2,338 with implausible BMI values, leaving a final analytic sample of 438,479 adults from 50 states and DC. Unadjusted obesity prevalence is presented overall and by sociodemographic characteristics (age, sex, race/ethnicity, education, income, and employment status), state, and four U.S. Census regions and nine divisions: Northeast region (New England and Middle Atlantic divisions), Midwest region (East North Central and West North Central divisions), South region (South Atlantic, East South Central, and West South Central divisions), and West region (Mountain and Pacific divisions).[\*\*](#FN5){ref-type="fn"}

Using 2010 Census data, CDC's National Center for Health Statistics (NCHS) developed an Urban-Rural Classification Scheme for Counties,[^††^](#FN6){ref-type="fn"} which specified six county types; for this analysis, to ensure sufficient sample size for regional and state-level comparisons, counties were collapsed into two categories: metropolitan (large central metro, large fringe metro, medium metro, and small metro) and nonmetropolitan (micropolitan and noncore). In this analysis, the nonmetropolitan designation was used to classify counties with small populations (\<50,000). Rhode Island, New Jersey, Delaware, and DC do not have nonmetropolitan counties; for these jurisdictions, obesity prevalence was calculated for adults living in metropolitan counties only. U.S. territories were excluded because the NCHS classification scheme does not include them. Unadjusted obesity prevalence was stratified by metropolitan and nonmetropolitan status. Differences in obesity prevalence between adults living in metropolitan and nonmetropolitan counties were examined using multivariable logistic regression, controlling for age, sex, and race/ethnicity within levels of the sociodemographic characteristics, states, and Census regions and divisions (statistically significant at p\<0.05). All analyses accounted for complex survey design and sampling weights.

In 2016, overall obesity prevalence was 29.6% and was highest among persons residing in the South (32.0%) and Midwest (31.4%) regions and the East South Central (35.3%) and West South Central (33.9%) divisions ([Table 1](#T1){ref-type="table"}). Overall, obesity prevalence was significantly higher among adults living in nonmetropolitan counties (34.2%) than among those living metropolitan counties (28.7%) (p\<0.001), and the same was found in all Census regions and Census divisions. Among Census regions, the largest difference in obesity prevalence between persons living in nonmetropolitan and metropolitan counties was in the South (5.6 percentage points) and Northeast (5.4 percentage points); among Census divisions, the largest difference in obesity prevalence between nonmetropolitan and metropolitan residents was in the Middle Atlantic division (6.6 percentage points). Obesity prevalence was also significantly higher among nonmetropolitan county residents than among metropolitan county residents for all sociodemographic categories except Hispanics and persons with less than a high school education.

###### Prevalence of self-reported obesity among adults (aged ≥18 years) by respondent characteristics and metropolitan/nonmetropolitan status --- Behavioral Risk Factor Surveillance System, 50 states and the District of Columbia, 2016

  Characteristic                        No. of respondents   Unadjusted adult obesity prevalence--weighted % (95% CI)\*                              
  ------------------------------------- -------------------- ------------------------------------------------------------ -------------------------- --------------------------
  **Total**                             **438,479**          **29.6 (29.3--29.8)**                                        **28.7 (28.4--29.0)^§^**   **34.2 (33.6--34.8)^§^**
  **Age group (yrs)^¶^**                                                                                                                             
  18--24                                23,734               17.3 (16.5--18.1)                                            16.5 (15.6--17.4)^§^       22.2 (20.3--24.2)^§^
  25--34                                42,706               27.2 (26.5--27.9)                                            26.4 (25.6--27.2)^§^       32.5 (30.8--34.3)^§^
  35--44                                48,951               33.1 (32.3--33.8)                                            32.0 (31.2--32.9)^§^       39.6 (38.0--41.2)^§^
  45--54                                68,854               35.1 (34.4--35.8)                                            34.0 (33.2--34.8)^§^       40.8 (39.4--42.3)^§^
  55--64                                96,566               34.2 (33.6--34.8)                                            33.4 (32.7--34.1)^§^       38.0 (36.9--39.2)^§^
  ≥65                                   157,668              28.0 (27.5--28.5)                                            27.5 (26.9--28.1)^§^       30.1 (29.3--31.0)^§^
  **Sex\*\***                                                                                                                                        
  Male                                  198,440              29.6 (29.2--30.0)                                            28.8 (28.3--29.2)^§^       34.4 (33.6--35.2)^§^
  Female                                240,000              29.5 (29.1--29.9)                                            28.7 (28.2--29.1)^§^       34.0 (33.2--34.8)^§^
  **Race/Ethnicity^¶,^\*\***                                                                                                                         
  White, non-Hispanic                   341,192              28.6 (28.3--28.9)                                            27.5 (27.2--27.9)^§^       33.2 (32.6--33.8)^§^
  Black, non-Hispanic                   35,091               38.3 (37.4--39.3)                                            37.7 (36.7--38.7)^§^       44.2 (41.7--46.7)^§^
  Hispanic, any race                    28,666               33.1 (32.1--34.1)                                            32.9 (31.9--33.9)          36.0 (32.6--39.5)
  Other, non-Hispanic                   26,954               18.2 (17.3--19.2)                                            16.8 (15.8--17.8)^§^       33.2 (31.2--35.3)^§^
  **Education^¶,^\*\***                                                                                                                              
  \<High school                         32,325               35.5 (34.5--36.5)                                            35.4 (34.3--36.6)          35.9 (34.0--37.8)
  High school                           123,241              32.3 (31.8--32.8)                                            31.5 (30.9--32.1)^§^       35.6 (34.7--36.5)^§^
  Some college                          120,735              31.0 (30.5--31.5)                                            30.3 (29.7--30.9)^§^       34.7 (33.7--35.7)^§^
  College graduate                      161,309              22.2 (21.9--22.6)                                            21.5 (21.1--21.9)^§^       28.8 (27.9--29.7)^§^
  **Annual household income^¶,^\*\***                                                                                                                
  \<\$25,000                            99,244               34.1 (33.5--34.7)                                            33.4 (32.7--34.2)^§^       37.1 (35.9--38.2)^§^
  \$25,000--49,999                      95,553               31.9 (31.3--32.6)                                            31.1 (30.3--31.8)^§^       35.9 (34.7--37.1)^§^
  \$50,000--74,999                      61,211               31.1 (30.3--31.8)                                            30.2 (29.4--31.1)^§^       35.4 (34.0--36.8)^§^
  ≥\$75,000                             120,901              25.4 (24.9--25.9)                                            24.8 (24.3--25.3)^§^       30.9 (29.8--32.1)^§^
  **Employment status^¶,^\*\***                                                                                                                      
  Employed                              215,226              29.0 (28.6--29.4)                                            28.2 (27.8--28.6)^§^       34.1 (33.3--34.9)^§^
  Out of work                           17,009               32.9 (31.6--34.3)                                            32.4 (30.9--34.0)^§^       35.8 (33.1--38.7)^§^
  Homemaker                             22,372               29.0 (27.7--30.3)                                            28.4 (27.0--29.9)^§^       32.0 (29.5--34.7)^§^
  Student                               11,277               15.2 (14.1--16.3)                                            14.8 (13.6--16.0)^§^       18.8 (16.2--21.7)^§^
  Retired                               136,638              29.1 (28.5--29.6)                                            28.6 (28.0--29.2)^§^       31.2 (30.3--32.2)^§^
  Unable to work                        33,534               45.8 (44.8--46.9)                                            45.5 (44.2--46.8)^§^       47.1 (45.2--49.1)^§^
  **Census region^¶,††^**                                                                                                                            
  Northeast                             88,335               26.9 (26.3--27.5)                                            26.4 (25.8--27.0)^§^       31.8 (30.4--33.2)^§^
  Midwest                               106,697              31.4 (30.9--31.9)                                            30.5 (29.9--31.2)^§^       34.2 (33.3--35.1)^§^
  South                                 146,919              32.0 (31.5--32.5)                                            31.0 (30.4--31.6)^§^       36.6 (35.6--37.6)^§^
  West                                  96,528               26.0 (25.4--26.6)                                            25.7 (25.1--26.4)^§^       28.6 (27.5--29.7)^§^
  **Census division^¶,††^**                                                                                                                          
  New England                           43,889               25.4 (24.7--26.1)                                            25.0 (24.2--25.8)^§^       28.7 (27.4--30.0)^§^
  Middle Atlantic                       44,446               27.4 (26.7--28.2)                                            26.9 (26.1--27.7)^§^       33.5 (31.5--35.6)^§^
  East North Central                    42,215               31.8 (31.1--32.5)                                            31.0 (30.2--31.8)^§^       34.9 (33.5--36.3)^§^
  West North Central                    64,482               30.6 (30.0--31.2)                                            29.3 (28.5--30.1)^§^       33.3 (32.4--34.2)^§^
  South Atlantic                        93,367               29.9 (29.3--30.4)                                            29.1 (28.5--29.7)^§^       35.3 (33.9--36.7)^§^
  East South Central                    26,587               35.3 (34.4--36.2)                                            34.5 (33.3--35.6)^§^       36.9 (35.6--38.1)^§^
  West South Central                    26,965               33.9 (32.7--35.2)                                            33.1 (31.7--34.5)^§^       37.8 (35.4--40.3)^§^
  Mountain                              57,788               26.2 (25.6--26.8)                                            26.0 (25.3--26.7)^§^       27.2 (26.3--28.1)^§^
  Pacific                               38,740               25.9 (25.0--26.7)                                            25.6 (24.7--26.4)^§^       30.3 (28.1--32.6)^§^

**Abbreviation:** CI = confidence interval.

\* Obesity defined as having a body mass index ≥30 kg/m^2^ determined by self-reported weight and height.

^†^ Based on National Center for Health Statistics Urban-Rural Classification Scheme for Counties. Metropolitan includes large central metro, large fringe metro, medium metro, and small metro categories. Nonmetropolitan includes micropolitan and noncore categories.

^§^ Significant difference in the prevalence of obesity between metropolitan and nonmetropolitan areas at the p\<0.05 level. Determined using multivariable logistic regression within levels of the sociodemographic and geographic characteristics to control for age, sex, and race/ethnicity.

^¶^ Significant difference in the prevalence of obesity across levels of the characteristic at the p\<0.05 level using Chi-square test.

\*\* Missing data: sex (n = 39; 0.009%), race/ethnicity (n = 6,576; 1.5%), education (n = 869; 0.2%), income (n = 61,570; 14.0%), and employment status (n = 2,423; 0.6%).

^††^ The United States Census Bureau defines four census regions and nine census divisions: Northeast region (New England and Middle Atlantic divisions), Midwest region (East North Central and West North Central divisions), Southern region (South Atlantic, East South Central, and West South Central divisions), and Western region (Mountain and Pacific divisions).

Among adults living in nonmetropolitan counties, obesity prevalence ranged from 20.8% in Colorado to 39.1% in Louisiana; among those living in metropolitan counties, prevalence ranged from 22.5% in Colorado to 36.9% in West Virginia. ([Table 2](#T2){ref-type="table"}). In 24 (51%) of the 47 states with both metropolitan and nonmetropolitan counties, obesity prevalence was significantly higher among adults living in nonmetropolitan counties than among those living in metropolitan counties; in 22 (47%) states, no difference was observed. Wyoming was the only state where obesity prevalence was significantly higher among metropolitan county residents (32.8%) than among nonmetropolitan residents (25.4%; p = 0.002).

###### Prevalence of self-reported obesity among adults (aged ≥18 years) by state and metropolitan/nonmetropolitan status --- Behavioral Risk Factor Surveillance System, 50 states and the District of Columbia, 2016

  Census division^†^/State   No. of respondents   Unadjusted adult obesity prevalence--weighted % (95% CI)\*   
  -------------------------- -------------------- ------------------------------------------------------------ -----------------------
  **New England**                                                                                              
  Connecticut                9,960                25.9 (24.7--27.1)                                            28.1 (22.7--34.2)
  Maine                      9,554                29.3 (27.3--31.3)                                            30.9 (29.1--32.7)
  Massachusetts              7,480                23.6 (22.2--24.9)                                            24.4 (16.9--34.0)
  New Hampshire              5,888                26.0 (23.8--28.2)                                            27.6 (25.4--29.9)
  Rhode Island               4,936                26.6 (24.9--28.4)                                            ^---¶^
  Vermont                    6,071                24.1 (21.3--27.1)\*\*                                        28.7 (26.9--30.6)\*\*
  **Middle Atlantic**                                                                                          
  New Jersey                 6,810                27.4 (25.7--29.1)                                            ^---¶^
  New York                   31,269               24.9 (23.9--26.0)\*\*                                        33.0 (31.6--34.5)\*\*
  Pennsylvania               6,367                29.7 (28.1--31.4)\*\*                                        33.9 (30.4--37.5)\*\*
  **East North Central**                                                                                       
  Illinois                   4,518                31.0 (29.2--32.9)\*\*                                        35.7 (31.0--40.6)\*\*
  Indiana                    10,319               32.0 (30.6--33.5)                                            33.9 (31.3--36.7)
  Michigan                   11,130               31.6 (30.4--32.9)\*\*                                        36.0 (33.7--38.5)\*\*
  Ohio                       11,455               30.7 (29.2--32.3)\*\*                                        34.4 (32.1--36.8)\*\*
  Wisconsin                  4,793                29.1 (27.0--31.3)\*\*                                        34.4 (31.6--37.3)\*\*
  **West North Central**                                                                                       
  Iowa                       6,645                31.4 (29.4--33.5)                                            32.7 (30.7--34.8)
  Kansas                     10,947               29.9 (28.5--31.3)\*\*                                        33.7 (32.0--35.5)\*\*
  Minnesota                  15,420               26.5 (25.6--27.5)\*\*                                        31.7 (30.1--33.2)\*\*
  Missouri                   6,578                30.5 (28.4--32.6)\*\*                                        34.9 (32.1--37.9)\*\*
  Nebraska                   14,173               30.8 (29.1--32.6)\*\*                                        34.2 (32.9--35.5)\*\*
  North Dakota               5,348                30.5 (28.2--32.9)                                            33.4 (31.2--35.6)
  South Dakota               5,371                27.0 (23.9--30.5)\*\*                                        31.8 (29.2--34.5)\*\*
  **South Atlantic**                                                                                           
  Delaware                   3,702                30.7 (28.7--32.8)                                            ^---¶^
  District of Columbia       3,479                22.6 (20.9--24.3)                                            ^---¶^
  Florida                    33,186               27.2 (26.1--28.2)\*\*                                        34.9 (32.6--37.2)\*\*
  Georgia                    4,884                30.8 (28.9--32.8)                                            34.0 (30.3--37.9)
  Maryland                   16,701               29.8 (28.7--30.9)\*\*                                        35.1 (32.0--38.3)\*\*
  North Carolina             5,984                31.1 (29.5--32.9)                                            34.1 (31.4--37.0)
  South Carolina             10,503               31.2 (29.8--32.7)\*\*                                        37.8 (35.1--40.6)\*\*
  Virginia                   8,293                27.7 (26.3--29.1)\*\*                                        36.1 (33.2--39.1)\*\*
  West Virginia              6,635                36.9 (35.2--38.7)                                            38.8 (36.6--41.0)
  **East South Central**                                                                                       
  Alabama                    6,526                35.6 (33.8--37.5)                                            36.0 (33.1--38.9)
  Kentucky                   9,583                32.1 (30.2--34.0)\*\*                                        36.9 (34.7--39.2)\*\*
  Mississippi                4,821                36.5 (33.4--39.7)                                            37.9 (35.7--40.1)
  Tennessee                  5,657                34.3 (32.1--36.6)                                            36.4 (33.6--39.3)
  **West South Central**                                                                                       
  Arkansas                   4,859                35.4 (32.2--38.8)                                            36.1 (32.6--39.7)
  Louisiana                  4,868                34.8 (32.5--37.3)                                            39.1 (34.7--43.7)
  Oklahoma                   6,449                30.8 (28.8--32.8)\*\*                                        36.3 (33.9--38.8)\*\*
  Texas                      10,789               32.9 (31.0--34.8)\*\*                                        38.7 (34.3--43.2)\*\*
  **Mountain**                                                                                                 
  Arizona                    10,033               28.8 (27.2--30.4)                                            33.6 (29.1--38.4)
  Colorado                   13,637               22.5 (21.5--23.5)                                            20.8 (19.0--22.8)
  Idaho                      4,880                26.3 (23.9--28.8)                                            29.6 (27.0--32.4)
  Montana                    5,483                25.9 (23.1--29.0)                                            25.3 (23.3--27.3)
  Nevada                     3,981                25.1 (23.1--27.3)\*\*                                        32.1 (28.6--35.9)\*\*
  New Mexico                 5,531                27.0 (24.7--29.4)\*\*                                        31.1 (28.7--33.6)\*\*
  Utah                       10,043               25.4 (24.2--26.7)                                            24.9 (22.7--27.2)
  Wyoming                    4,200                32.8 (29.0--36.9)\*\*                                        25.4 (23.1--27.8)\*\*
  **Pacific**                                                                                                  
  Alaska                     2,739                30.9 (27.1--35.0)                                            32.4 (28.8--36.4)
  California                 10,352               25.0 (24.0--26.1)                                            24.2 (19.2--30.0)
  Hawaii                     7,659                23.3 (21.8--24.9)\*\*                                        26.1 (23.5--28.8)\*\*
  Oregon                     5,000                27.4 (25.8--29.1)\*\*                                        35.1 (31.5--38.8)\*\*
  Washington                 12,990               27.8 (26.8--28.9)\*\*                                        35.3 (32.3--38.4)\*\*

**Abbreviation:** CI = confidence interval.

\* Obesity defined as having a body mass index ≥30 kg/m^2^, determined by self-reported weight and height.

^†^ The United States Census Bureau defines nine census divisions within four regions: Northeast region (New England and Middle Atlantic divisions), Midwest region (East North Central and West North Central divisions), Southern region (South Atlantic, East South Central, and West South Central divisions), and Western region (Mountain and Pacific divisions).

^§^ Based on National Center for Health Statistics Urban-Rural Classification Scheme for Counties. Metropolitan includes large central metro, large fringe metro, medium metro, and small metro categories. Nonmetropolitan includes micropolitan and noncore categories.

^¶^ Data not available because state does not have counties in the nonmetropolitan classification.

\*\* Significant difference in the prevalence of obesity between metropolitan and nonmetropolitan areas at the p\<0.05 level. Within states, differences in obesity prevalence between metropolitan and nonmetropolitan areas were determined using multivariable logistic regression, controlling for age, sex, and race/ethnicity.

Discussion
==========

In this study, obesity prevalence was significantly higher among adults living in nonmetropolitan counties than among those living in metropolitan counties, overall, in all Census regions, all Census divisions, and in approximately half of states with both county types. Across regions and divisions, this disparity in obesity prevalence was highest in the South and Northeast regions and the Middle Atlantic division. With the exception of Hispanics and persons with less than a high school education, the higher obesity prevalence among nonmetropolitan residents was observed in all sociodemographic groups.

These findings are consistent with those previously reported using 2005--2008 NHANES data, which documented higher overall obesity prevalence among adults living in nonmetropolitan versus metropolitan counties of the United States ([@R3]), and expand the understanding of this health disparity by highlighting differences across states and regions. Research has documented differences between adults living in nonmetropolitan and metropolitan counties in health behaviors and community factors, which could influence obesity risk ([@R5]--[@R7]). An analysis of 2013 BRFSS data found that adults living in U.S. nonmetropolitan counties were less physically active and less likely to meet physical activity recommendations than their metropolitan counterparts ([@R5]). Data from 2011 indicated that across all regions, adults living in rural areas were less likely to have access to healthier food retailers (supermarkets, large grocery stores, and fruit/vegetable specialty stores) than were those living in urban areas ([@R6]). In addition, several social determinants of health that are risk factors for obesity, such as persistent poverty and food insecurity ([@R7]), are more prevalent in rural than in urban areas.[^§§^](#FN7){ref-type="fn"}^,^[^¶¶^](#FN8){ref-type="fn"}

In this analysis, the highest obesity prevalence and the greatest disparity in prevalence between persons living in nonmetropolitan and metropolitan counties were in the South Census region. One possible contributing factor is the high rate of persistent poverty in the South, which also is affected by the largest difference in poverty rate between metropolitan and nonmetropolitan county residents.[^¶¶^](#FN8){ref-type="fn"}

The findings in this report are subject to at least two limitations. First, data are self-reported, and self-reported weight and height data underestimate BMI values, particularly among persons with a higher BMI ([@R8]). It is not known whether self-reporting bias is comparable across regions and between metropolitan and nonmetropolitan counties. Second, to ensure sufficient sample size for regional and state-level comparisons, the nonmetropolitan classification was used to designate counties with small populations (\<50,000 persons). The literature on rural obesity disparities and prevention strategies uses various methods to define rural areas, some of which might differ in population size from the nonmetropolitan designation used in this paper.

CDC recommends 24 obesity-prevention policy and environmental strategies ([@R4]). Two systematic reviews summarized the relevance and effectiveness of these strategies in rural areas and identified how these strategies could be adapted for rural settings ([@R9],[@R10]). One nutrition-related obesity prevention strategy, increasing the availability of healthier food and beverage choices, is challenging to implement in rural areas because of the long distances between food suppliers and retailers and between retailers and consumers, which can influence food cost and the availability of fresh foods. Approaches to overcoming this challenge include strengthening networks between food producers, distributors, and retail food outlets, as well as reducing the distance customers need to travel, for example, by increasing access to nearby farmers' markets ([@R9]). The 2018 CDC State Indicator Report on Fruits and Vegetables also highlights approaches to increase the purchase, supply, and demand of fruits and vegetables in states and communities across the United States.[\*\*\*](#FN9){ref-type="fn"} Other approaches include working with schools and worksites to develop nutrition-related policies and forming strong partnerships with groups such as the Cooperative Extension Service to promote federal food and nutrition assistance program benefits ([@R9]).

Strategies to increase physical activity in rural areas should take into consideration geographic dispersion, transportation challenges, and limitations on community resources that might not be present in urban areas ([@R10]). Strategies that have been implemented in rural settings include improving community access to public buildings (e.g., school facilities) after hours for physical activity purposes; improving infrastructure and land use design to support walking and other physical activity (e.g., bicycle paths, paved sidewalks, and outdoor public recreation facilities); promoting existing places for physical activity with improved signage; enhancing physical education in schools; and implementing worksite policies to promote physical activity ([@R10]). The data in this report can serve as a resource for states seeking to reduce obesity disparities in nonmetropolitan counties through strategies to increase physical activity and healthier eating.

###### Summary

What is already known about this topic?
---------------------------------------

National estimates from a decade ago found a higher prevalence of obesity among adults living in nonmetropolitan counties than among those living in metropolitan counties.

What is added by this report?
-----------------------------

Analysis of 2016 Behavioral Risk Factor Surveillance System data found a higher obesity prevalence among adults in nonmetropolitan counties than among those in metropolitan counties. The greatest differences in obesity prevalence between nonmetropolitan and metropolitan residents were in the South (5.6 percentage points) and Northeast (5.4 percentage points).

What are the implications for public health practice?
-----------------------------------------------------

Both nonmetropolitan and metropolitan counties can address obesity through a variety of policy and environmental strategies to increase access to healthier foods and opportunities for physical activity.

William Garvin, Division of Population Health, National Center for Chronic Disease Prevention and Health Promotion, CDC; state and DC BRFSS staff members.

<https://www.ers.usda.gov/webdocs/publications/80894/eib-162.pdf?v=42684>.

<https://www.cdc.gov/brfss/annual_data/annual_2016.html>.

<https://www.cdc.gov/brfss/annual_data/2016/pdf/2016-sdqr.pdf>.

<https://www.nhlbi.nih.gov/files/docs/guidelines/ob_gdlns.pdf>.

<https://www.census.gov/geo/reference/gtc/gtc_census_divreg.html>.

<https://www.cdc.gov/nchs/data_access/urban_rural.htm>.

<https://www.ers.usda.gov/webdocs/publications/79761/err-215.pdf?v=42636>.

<https://www.ers.usda.gov/topics/rural-economy-population/rural-poverty-well-being/>.

<https://www.cdc.gov/nutrition/data-statistics/2018-state-indicator-report-fruits-vegetables.html>.

**Conflict of Interest:** No conflicts of interest were reported.
