Abstract
Purpose
Childhood obesity is more prevalent in rural compared to urban communities and may be related to urban‐rural differences in environmental factors known to affect obesity. However, understanding of how environmental factors impact childhood obesity in rural settings remains limited. This study aimed to address this gap by exploring the relationship between obesogenic environments and childhood overweight/obesity rates, including variations across the urban‐rural continuum.
Methods
This study analyzed data for counties in the United States (N = 3140). Linear regression models were employed to examine the relationship between the Childhood Obesogenic Environment Index, which consisted of ten variables from a variety of sources associated with physical activity and healthy eating, and childhood overweight/obesity rates estimates derived from the 2016 National Survey of Children's Health. County rurality was categorized using Rural‐Urban Continuum Codes and a moderation analysis was conducted to identify potential variations by rurality.
Findings
There was a significant positive association between the COEI and childhood overweight/obesity rates nationally, with notable variations across the urban‐rural continuum for specific index components. Neighborhood walkability showed a significant positive association across rurality, indicating that childhood overweight/obesity rates were higher in less walkable communities. Full‐service restaurants exhibited an inverse relationship with childhood overweight/obesity rates across all RUCC levels.
Conclusions
These results underscore the obesogenic environmental factors associated with childhood overweight/obesity rates nationally and how they vary across the urban‐rural continuum. This study highlights the importance of considering these variations when designing interventions to address childhood obesity.
Keywords: built environment, childhood obesity, nutrition, physical activity, rural
INTRODUCTION
Childhood obesity poses a public health concern in the United States, 1 , 2 , 3 , 4 especially in rural areas where unique challenges exist such as a lack of sidewalks or decreased traffic safety. 5 , 6 Approximately 20% of children live in rural communities, 7 and 38% of rural children are overweight or obese, surpassing the 30% prevalence in urban areas. 8 Causes of childhood weight gain are complex and exacerbated by the distinct built environments of rural communities. For example, adolescents in rural areas have less access to neighborhoods that support physical activity (PA) compared to those in urban areas, 9 where research indicates that shorter distances and better walkability are more likely to encourage PA. 10
The Childhood Obesogenic Environment Index (COEI) was recently developed for counties in the United States to evaluate the collective impact of environmental features that can influence youth PA, healthy eating, and obesity. 11 The COEI includes ten county‐level environmental variables (e.g., walkability, density of fast‐food establishments). 11 Analysis of the index across the United States indicated that rural counties had significantly worse COEI scores than urban counties. 11 , 12 However, few studies have comprehensively evaluated obesogenic environment features in rural communities using an index like the COEI, 11 , 12 and none have examined the relationship between these features and childhood obesity rates at the national scale and across the urban‐rural continuum. Moreover, research on individual obesogenic environment features has produced mixed results and thus requires further investigation. 13 , 14 , 15 , 16 For example, some studies found that access to fruit and vegetable markets was linked to lower childhood obesity rates, while others reported a connection to higher obesity rates. 13 Similar inconsistent results have been found with other food and PA environment features. 14 , 15 , 16
Communities and counties differ significantly in their levels of rurality or urbanicity, and there is limited research investigating the association between specific obesogenic environment features and childhood obesity across the spectrum of rurality. 17 To address these research gaps, the objectives of this study were to (1) examine the relationship between obesogenic environment features and childhood overweight/obesity rates and (2) investigate whether these associations vary across both continuous and dichotomous urban‐rural definitions.
METHODS
Study setting
This study analyzed data about childhood obesogenic environments and childhood overweight/obesity for counties in the United States (N = 3140). Rural‐Urban Continuum Codes (RUCC) were utilized as counties could be both classified across the urban‐rural continuum while also dichotomized as metropolitan/urban (RUCC 1–3) or nonmetropolitan/rural (RUCC 4–9). 18
Measures
The county‐level COEI was developed as part of a previous effort to better characterize obesogenic environments for children and is fully described elsewhere. 11 Briefly, a comprehensive literature review, expert review, and data availability considerations were utilized to identify ten variables included in the COEI (Table 1) that were key environmental factors associated with child PA, healthy eating, and obesity. 11 Six variables were related to the food environment (density of fast‐food restaurants, full‐service restaurants, grocery stores/supercenters, farmer's markets, and convenience stores, and percentage of births at baby‐friendly hospitals, the latter an indicator of breastfeeding support and healthy early‐life feeding practices that could influence obesity), and four were related to the PA environment (exercise opportunities, violent crime, walkability, proximity to schools). 11 Each variable within the COEI was ranked across all counties and assigned a percentile ranging from 0 to 100. 11 Variables considered health‐promoting (grocery stores/supercenters, farmer's markets, births at baby‐friendly hospitals, exercise opportunities, walkability, proximity to schools) were reverse‐coded such that higher scores for all variables indicated worse environments. 11 The overall COEI and separate index scores for the food and PA environments (all 0–100) were then calculated for each county by averaging the percentile values for the respective ten, six, or four variables. 11
TABLE 1.
Childhood Obesogenic Environment Index variable definitions and sources. 11
| Variable | Definition | Source |
|---|---|---|
| Fast‐food restaurants | Number of fast‐food restaurants per 1000 county residents | U.S. Department of Agriculture, 2014 |
| Census County Business Patterns, Population Estimates | ||
| Full‐service restaurants | Number of full‐service restaurants per 1000 county residents | U.S. Department of Agriculture, 39 2014 |
| Census County Business Patterns, Population Estimates | ||
| Grocery stores/supermarkets | Number of grocery stores/supermarkets per 1000 county residents | U.S. Department of Agriculture, 39 2014 |
| Census County Business Patterns, Population Estimates | ||
| Farmer's markets | Number of farmer's markets per 1000 county residents | U.S. Department of Agriculture, 39 2014 |
| Agriculture Market Services, Census Population Estimates | ||
| Convenience stores | Number of convenience stores per 1000 county residents | U.S. Department of Agriculture, 39 2014 |
| Census County Business Patterns, Population Estimates | ||
| Births at baby‐friendly hospitals | Percentage of births at baby‐friendly hospitals, state level | Centers for Disease Control and Prevention, 40 2016 |
| Breastfeeding Report Cards, National Center for Chronic Disease Prevention and Health Promotion | ||
| Exercise opportunities | Percentage residing in census block within the county with access to exercise opportunities (aggregated up to county) | County Health Rankings, 41 2018 |
|
Census Population Estimates, SIC codes, Parks, Business Analyst—ESRI | |
| Violent crime | Number of violent crimes per 100,000 county residents | County Health Rankings, 42 2012–2014 |
| Federal Bureau of Investigation Uniform Crime Reporting Statistics | ||
| Walkability | National walkability index score | EPA Smart Growth Smart Location Mapping Database, 43 2010–2012 |
| Proximity to schools | Percentage of the county within ½ mile buffers of public schools | National Center for Education Statistics, 44 2016–2017 |
Childhood overweight/obesity rates for counties in the United States were derived from a previous study using small area estimates based on the 2016 National Survey of Children's Health. 19 Rates were predicted at the county‐level using multi‐level mixed‐effects logistic regression models that included child‐level factors such as race/ethnicity and age, area‐level factors such as state Medicaid expansion status and school funding, and county‐level sociodemographic data such as food insecurity and poverty rates. 19 Individual county estimates were developed via survey weights and post‐stratification. 19
Analyses
Descriptive statistics were used to examine the distribution of COEI variables and childhood overweight/obesity rates across the urban‐rural continuum. Linear regression models were used to determine the relationship between childhood overweight/obesity rates and (1) overall COEI score, (2) food and PA environment index scores, and (3) the ten individual COEI variables. To achieve the second study objective, moderation analysis was employed to examine the effect of county rurality (RUCC, metropolitan/nonmetropolitan) on the relationships between the childhood overweight/obesity rates and the COEI, the food and PA environment indices, and the COEI variables. Regional divisions from the US Census Bureau were utilized to cluster standard errors to account for similarities in observations that may be due to geographic differences. Tests were considered significant at p < 0.05. Stratified models were presented for effect modification found based on product terms (RUCC 1–9: α = 0.01, metropolitan/nonmetropolitan: α = 0.02). All analyses were conducted using Stata 17 (College Station, TX).
RESULTS
Table 2 provides an overview of overweight/obesity rates and obesogenic environment variables based on RUCC classification. Of all counties analyzed, 62.9% were nonmetropolitan (RUCC 4–9). The overall overweight/obesity prevalence was 32.9%, varying from 29.4% (RUCC 1) to 35.6% (RUCC 6). Notably, mean COEI scores (0–100) ranged from 43.7 (SD = 8.4) in RUCC 1 to 54.4 (SD = 9.3) in RUCC 8, reflecting distinct obesogenic environment characteristics across rural classifications. Across the dichotomous metropolitan/nonmetropolitan classification, nonmetropolitan counties had higher (worse) scores than metropolitan counties for the overall COEI (M = 52.1, SD = 8.7 vs. M = 46.5, SD = 8.5) and PA environment (M = 55.7, SD = 14.9 vs. M = 41.0, SD = 17.9). Food environment indices for nonmetropolitan counties (M = 49.9, SD = 11.4) were similar to metropolitan counties (M = 50.3, SD = 9.4).
TABLE 2.
Overweight/obesity rates and obesogenic environment variable values by rurality.
| Rural‐urban continuum codes | ||||||||||||
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| National N = 3140 | 1 n = 432 | 2 n = 378 | 3 n = 356 | 4 n = 214 | 5 n = 92 | 6 n = 592 | 7 n = 433 | 8 n = 220 | 9 n = 423 | Metro n = 1166 | Nonmetro n = 1974 | |
| Overweight/obesity rate | 32.9% | 29.4% | 30.5% | 30.9% | 35.0% | 34.5% | 35.6% | 33.7% | 35.0% | 32.9% | 30.2% | 34.4% |
| Mean (SD) | Mean (SD) | Mean (SD) | Mean (SD) | Mean (SD) | Mean (SD) | Mean (SD) | Mean (SD) | Mean (SD) | Mean (SD) | Mean (SD) | Mean (SD) | |
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| COEI | 50.0 (9.0) | 43.7 (8.4) | 47.3 (8.1) | 49.0 (8.0) | 48.5 (8.1) | 50.2 (7.2) | 52.3 (8.5) | 51.9 (8.3) | 54.4 (9.3) | 53.1 (9.0) | 46.5 (8.5) | 52.1 (8.7) |
| Food environment index | 50.0 (10.7) | 49.8 (8.6) | 49.9 (9.8) | 51.2 (10.0) | 51.1 (9.7) | 54.2 (9.9) | 49.4 (10.2) | 51.2 (11.1) | 48.9 (12.7) | 48.1 (13.1) | 50.3 (9.4) | 49.9 (11.4) |
| Convenience | 50.0 (28.9) | 29.5 (23.8) | 38.0 (24.5) | 41.8 (26.0) | 47.1 (23.7) | 45.9 (25.6) | 59.2 (24.6) | 57.3 (27.0) | 64.7 (28.2) | 63.2 (31.0) | 36.0 (25.6) | 58.3 (27.5) |
| Fast food | 50.0 (28.9) | 59.9 (24.5) | 55.2 (26.8) | 54.7 (28.4) | 61.9 (20.9) | 71.0 (17.5) | 46.7 (24.7) | 55.0 (27.5) | 31.5 (30.1) | 30.1 (30.9) | 56.8 (26.6) | 46.0 (29.4) |
| Full‐service | 50.0 (28.9) | 46.9 (23.8) | 44.0 (25.5) | 45.6 (26.1) | 50.9 (23.7) | 58.6 (30.1) | 46.3 (27.6) | 58.3 (29.6) | 48.4 (34.4) | 57.6 (35.6) | 45.6 (25.1) | 52.7 (30.6) |
| Grocery | 50.0 (28.9) | 63.6 (24.0) | 63.8 (22.8) | 60.0 (23.9) | 57.9 (22.8) | 55.7 (23.3) | 48.3 (26.0) | 40.6 (27.0) | 39.7 (31.3) | 27.4 (30.8) | 62.6 (23.6) | 42.6 (29.1) |
| Farmer's markets | 50.0 (28.5) | 56.2 (19.0) | 53.4 (20.8) | 53.0 (23.1) | 45.4 (19.5) | 43.1 (19.9) | 45.6 (29.2) | 42.6 (31.7) | 53.9 (36.2) | 53.6 (38.6) | 54.3 (20.9) | 47.4 (31.9) |
| Baby friendly | 50.0 (28.8) | 42.9 (23.8) | 45.0 (28.4) | 51.9 (28.8) | 43.3 (27.5) | 51.1 (32.4) | 50.2 (28.4) | 53.4 (30.4) | 55.4 (28.6) | 56.7 (30.2) | 46.3 (27.2) | 52.2 (29.6) |
| PA environment index | 50.0 (17.6) | 34.7 (17.7) | 43.5 (17.1) | 45.9 (16.8) | 44.6 (13.1) | 43.9 (11.2) | 56.8 (14.0) | 53.0 (13.6) | 63.0 (14.4) | 61.4 (13.8) | 41.0 (17.9) | 55.7 (14.9) |
| Exercise | 50.0 (28.9) | 30.5 (27.7) | 41.7 (28.4) | 45.2 (28.2) | 45.6 (21.5) | 36.3 (20.0) | 59.0 (24.3) | 49.4 (26.1) | 67.8 (28.0) | 65.4 (27.3) | 38.6 (28.7) | 56.7 (26.8) |
| Schools | 50.0 (28.9) | 19.9 (20.2) | 29.2 (23.7) | 37.9 (24.5) | 34.8 (18.0) | 47.7 (20.1) | 56.2 (19.0) | 66.4 (21.8) | 70.9 (18.8) | 81.2 (16.2) | 28.4 (23.9) | 62.7 (23.5) |
| Violent crime | 50.0 (28.9) | 53.0 (29.6) | 60.9 (27.1) | 57.2 (26.9) | 56.2 (26.3) | 62.5 (23.3) | 51.9 (27.7) | 47.6 (26.2) | 35.4 (27.5) | 29.1 (26.2) | 56.9 (28.2) | 45.8 (28.5) |
| Walkability | 50.0 (28.9) | 35.0 (30.5) | 42.0 (29.8) | 43.3 (29.2) | 42.0 (20.2) | 29.9 (21.1) | 59.7 (23.4) | 47.6 (26.4) | 73.6 (23.1) | 63.1 (25.2) | 39.8 (30.1) | 56.0 (26.3) |
Abbreviations: COEI, Childhood Obesogenic Environment Index; PA, physical activity.
Table 3 presents the regression coefficients showing the COEI associations with overweight/obesity rates. The COEI (p < 0.001) and PA environment index (p < 0.001) exhibited significant positive associations, indicating worsening obesogenic environments being associated with greater overweight/obesity rates. Conversely, the food environment index was negatively associated with national childhood overweight/obesity rates (p = 0.002) such that worsening obesogenic environments were associated with lower overweight/obesity rates. Among the COEI variables, eight were significantly associated with childhood overweight/obesity rates at the national level. Convenience stores (p < 0.001), farmer's markets (p = 0.002), access to exercise opportunities (p < 0.001), violent crime (p < 0.001), school proximity (p < 0.001) and walkability (p < 0.001) all had positive associations which indicated that as the environment worsened, so did childhood overweight/obesity rates. Fast‐food restaurants (p < 0.001) and full‐service restaurants (p < 0.001) had negative associations, indicating that as the environment worsened, childhood overweight/obesity rates improved.
TABLE 3.
Coefficients for the association between obesogenic environment variables and childhood overweight/obesity by rurality from regression models.
| Rural‐urban continuum codes | ||||||||||||
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| National | 1 | 2 | 3 | 4 | 5 | 6 | 7 | 8 | 9 | Metro | Nonmetro | |
| COEI | 0.0022 *** | 0.0028 * | 0.0025 ** | 0.0025 * | 0.0015 | 0.0035 * | 0.0018 * | 0.0014 * | 0.001 * | −0.0000 | 0.0026 ** | 0.0011 * |
| Food environment index | −0.0005 ** | −0.0004 | −0.0003 | −0.0001 | −0.0003 | 0.0013 | −0.0002 | −0.0004 | −0.0011 * | −0.001 | −0.0002 | −0.0005 |
| Convenience | 0.0007 *** | 0.0008 * | 0.0007 * | 0.0007 ** | 0.0011 * | 0.0011 * | 0.0005 * | 0.0004 | 0.0002 | −0.0001 | 0.0008 ** | 0.0003 |
| Fast food | −0.0003 *** | −0.0004 | −0.0005 * | −0.0001 | −0.0003 | −0.0008 | −0.0000 | −0.0003 | −0.0006 * | −0.0003 | −0.0004 ** | −0.0002 |
| Full service | −0.0009 *** | −;0.0012 ** | −0.0008 ** | −0.0008 ** | −0.0013 *** | −0.0014 *** | −0.0009 ** | −0.0012 ** | −0.0011 ** | −0.0009 * | −0.0009 ** | −0.001 ** |
| Grocery | 0.0001 | −0.0002 | 0.0002 | −0.0002 | 0.0000 | 0.0005 | 0.0002 | 0.0005 ** | 0.0006 *** | 0.0006 | −0.0000 | 0.0005 ** |
| Farmer's market | 0.0002 ** | 0.0005 | 0.0004 | 0.0003 | 0.0011 * | 0.0012 | 0.0003 | 0.0004 | 0.0002 | 0.0000 | 0.0004 | 0.0002 |
| Baby friendly | −0.00002 | 0.0004 | −0.00003 | 0.00005 | −0.0005 | 0.0003 | −0.0001 | −0.0001 | −0.0004 | −0.0002 | 0.0001 | −0.0001 |
| PA environment index | 0.0017 *** | 0.0005 ** | 0.0015 ** | 0.0015 *** | 0.0017 | 0.0021 *** | 0.0018 *** | 0.0019 ** | 0.0025 ** | 0.0013 *** | 0.0016 ** | 0.0014 ** |
| Exercise | 0.0009 *** | 0.001 * | 0.0008 | 0.0009 ** | 0.0009 * | 0.0012 * | 0.0007 ** | −0.0009 * | 0.001 ** | 0.0002 | 0.0009 ** | 0.0006 * |
| Schools | 0.0002 *** | 0.0007 | 0.0004 | 0.0001 | −0.0011 ** | −0.0005 | −0.0006 | −0.001 | −0.0004 | −0.0016 * | 0.0004 | −0.0008 * |
| Violent Crime | 0.0004 *** | 0.0005 ** | 0.0005 ** | 0.0004 * | 0.0007 | 0.0001 | 0.0007 ** | 0.0005 | 0.0007 ** | 0.0003 | 0.0005 ** | 0.0006 ** |
| Walkability | 0.0011 *** | 0.0007 * | 0.0007 ** | 0.0007 *** | 0.0014 ** | 0.0016 ** | 0.0012 ** | 0.0013 ** | 0.0015 ** | 0.0015 ** | 0.0007 ** | 0.0011 ** |
p < 0.05.
p < 0.01.
p < 0.001.
For the second research objective evaluating the effect modification of rurality, all interaction terms were significant in predicting childhood overweight/obesity (all p < 0.001). Therefore, Table 3 presents stratified analyses based on RUCC codes and metropolitan/nonmetropolitan classifications. The overall COEI was consistently and positively associated with childhood overweight/obesity rates across RUCC codes 1–3 and 5–8, as well as within metropolitan and nonmetropolitan classifications. The PA environment index exhibited significant positive associations across all classifications except RUCC 4 (all p < 0.01). The food environment index had a significant negative association in only RUCC 8 (p = 0.05).
The significance of individual variables varied across the urban‐rural continuum (Table 3). Walkability consistently exhibited a positive association across all RUCC classifications, while full‐service restaurants displayed a negative association with overweight/obesity rates across all classifications (all p < 0.05). Access to exercise opportunities demonstrated a significant positive association with overweight/obesity rates across most classifications (all p < 0.05), except for RUCC 2 and 9. Convenience stores showed a positive association within urban (RUCC 1–2) and some rural (RUCC 3–6) counties (all p < 0.05) but lacked significance within more remote areas (RUCC 7–9). Similarly, convenience stores exhibited a significant positive association in counties classified as metropolitan (p < 0.05) but not nonmetropolitan. Violent crime displayed a positive association among urban (RUCC 1–3) counties, as well as within some rural counties (RUCC 6 and 8) (all p < 0.05), and across both metropolitan and nonmetropolitan classifications (all p < 0.05). Few other associations were significant: fast‐food restaurants were negatively associated in RUCC 8, farmer's markets positively associated in RUCC 4, grocery stores positively associated in RUCC 7–8, and proximity to schools negatively associated in RUCC 4 and 9 (all p < 0.05). Notably, while some variables were only significant within specific RUCC codes, they exhibited significance within the broader metropolitan/nonmetropolitan classification. For instance, fast‐food restaurants were negatively associated with overweight/obesity rates within the metropolitan classification, while grocery stores showed a positive association within nonmetropolitan areas. Proximity to schools exhibited a significant negative association within the nonmetropolitan classification (all p < 0.05).
DISCUSSION
This study's objectives were to explore the relationships between county‐level childhood overweight/obesity rates and the overall COEI as well as food environment, PA environment, and individual COEI variables. Additionally, it examines whether degree of county rurality influenced this relationship. We observed positive associations between the COEI and childhood overweight/obesity rates, in line with previous findings and underscoring the critical impact of built environments. 13 , 20 , 21 , 22 A poorer PA environment was significantly associated with increased overweight/obesity rates, with many PA environment variables also found to be significant, similar to previous research. 15 , 16 , 20 , 21 , 23 , 24 , 25 Contrary to prior studies, 14 , 26 , 27 , 28 , 29 food environment exhibited a significant inverse relationship with overweight/obesity rates. One potential explanation for this difference in findings is that food environment variables in the COEI rely on density metrics (e.g., number of outlets per 1000 residents), which might not fully reflect access. 30 Proximity may instead be a better measure; for example, previous research has indicated the proximity of fast‐food and convenience stores to school zones may be a strong predictor of childhood obesity. 14 , 31
The effect modification by rurality sheds light on the diversity of challenges faced by rural communities. While full‐service restaurants and walkability emerged as consistent predictors across all levels of rurality, similar to previous findings regarding their impact on childhood obesity outcomes., 16 , 20 , 21 , 32 , 33 the varying effects of thother variables highlight the need for strategies tailored to the specific access challenges of different rural areas. This approach is necessary because the impact of these variables differs based on the degree of rurality, reflecting the mixed results observed in earlier research. 5 , 13 , 14 , 15
Our study builds upon existing knowledge by emphasizing the importance of exploring associations across diverse definitions of rurality. 12 , 34 Variability in the significance of individual COEI variables across different urban‐rural classifications implies that a one‐size‐fits‐all approach may not be effective in mitigating childhood obesity in rural communities. Further, the dichotomous metropolitan/nonmetropolitan classification masked many differences across the varying levels of rurality. This is similar to past research which has reported that more specific rural definitions are more likely to capture nuances missed by broader definitions. 12 These findings align with the growing recognition that rural areas exhibit unique characteristics that influence health outcomes, which depend on the way rurality is defined; thus, interventions must be tailored to address these specific challenges. 12 , 34 , 35
Limitations
This study had several limitations. First, analyzing data at the county‐level may not capture localized variations in resource availability, potentially masking differences across census tracts or neighborhoods. Additionally, the varying years of data in the COEI may not fully reflect current resource availability. Using RUCC might oversimplify the complexities of rural landscapes and may not accurately capture the variations observed across the urban‐rural continuum, especially considering differences in resource access and potential disparities in health behaviors among counties in nonmetropolitan RUCC codes adjacent to metropolitan areas. This study also could not account for individual‐level determinants of obesity, which can impact a child's PA and nutrition behaviors. 36 , 37 , 38 The associations observed in the study were small. This limited effect size may reduce the overall impact and practical significance of the findings. Nonetheless, this study adds to the limited body of evidence regarding environmental influences on childhood obesity rates in rural areas.
CONCLUSIONS
This research examined the association between obesogenic environments and childhood obesity rates across all US counties, highlighting the impact of rurality on this relationship. By identifying specific obesogenic features linked to childhood obesity in urban and rural areas, the study provides a foundation for evidence‐based strategies to develop targeted policies and interventions in resource‐limited rural settings, aiding public health efforts to reduce childhood obesity and promote health equity.
CONFLICT OF INTEREST STATEMENT
The authors report no conflicts of interest.
Davis K, Abshire DA, Monroe C, Rudisill C, Kaczynski AT. Association between obesogenic environments and childhood overweight/obesity across the United States: Differences by rurality. J Rural Health. 2025;41:e12891. 10.1111/jrh.12891
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