Obesity disproportionately affects different communities — including communities of color, communities with high levels of poverty, and adults with lower education levels.
1. Racial and Ethnic Groups
Obesity rates vary widely among racial/ethnic groups, with Latinos and Blacks having significantly higher rates than Whites and Asians. According to the most recent national data (2013-2014, age adjusted), obesity rates are:1
Broken down by sex and race/ethnicity, Black women have the highest obesity rates at 57.2 percent, while Asian-American women have the lowest rates at 12.4 percent. Below are obesity rates by sex and race/ethnic origin.
Limited Data For Racial And Ethnic Populations
The total sample sizes for BRFSS in states is often 600-800 people. Many states do not have large enough populations of Asian/Pacific Islanders and American Indian/Alaska Natives to be reflected in the survey findings. For some states, the sample sizes for Black and Latino populations are too small to be reported. Increasing sample sizes for each state (requiring additional funding) would provide an opportunity to collect more meaningful information about different racial and ethnic groups in each state.
American Indian/Alaska Natives Obesity State-Data
According to an analysis by the Kaiser Family Foundation (KFF) of 2014 BRFSS surveys in states with reportable data for American Indian/Alaska Native populations, 14 of the 24 states analyzed had adult overweight and obesity rates above 70 percent. Ohio had the highest adult rate at 93.9 percent and North Carolina had the lowest at 60.9 percent.2
Promoting Healthy Weight in American Indian/Alaska Native Children
What began as a golf program for American Indian/Alaska Native youth in Albuquerque in 2005 has expanded into a national effort to prevent childhood obesity and type 2 diabetes in Native children. Founded by former PGA golfer Notah Begay III, the NB3 Foundation (NB3F) works to reduce the staggering rates of obesity in Native communities where childhood obesity rates often exceed 50 percent.3
NB3F has invested $2.3 million in grants and $7 million in direct spending on evidence-based obesity-prevention programs, including sports programs, culturally appropriate nutrition education and community garden projects. The Foundation has improved the lives of 24,000 American Indian/Alaska Native in 59 different communities.4
In 2013, NB3F launched Native Strong: Healthy Kids, Healthy Futures, a national initiative that supports Native communities’ obesity-prevention efforts through grants, technical assistance, research and advocacy.5 The program supports community efforts that promote physical activity, nutrition education and eating healthy foods. Native Strong is aimed at building the capacity in Native communities to help their children lead longer and healthier lives.
Obesity and Asians
Asian-Americans have dramatically lower obesity rates than other U.S. racial and ethnic groups. This is consistent with world trends: in general, Asian populations have median BMIs lower than other population groups.6 While the reasons for this disparity are not fully understood, research has shown that foreign-born AsianAmericans have lower rates of obesity than those born in the United States, and obesity increases with more years in the country.7 In addition, low obesity rates among Asian-Americans could create a false sense of health security. Research shows that a substantial number of Asians with weights in the “normal” BMI range (i.e., below 25) have an elevated risk for obesity-related health problems, including type 2 diabetes and heart disease.8
A World Health Organization expert consultation met in 2002 to determine whether there should be a unique population-specific BMI cut-off point for Asians. While the group found that Asians generally have a higher level of body fat than Whites with the same BMI, it determined there is not enough scientific data to suggest a clear cut-off point for all Asians for obesity. However, Asian-Americans — particularly those with Indonesian, Hong Kong Chinese or Singaporean ancestry — should recognize that BMI represents a continuum of risk and their risk of developing obesity-related disease could be elevated at BMIs as low as 23.9
2. Education and Income
Obesity rates also vary by income levels. Obesity rates are generally inversely correlated with income, with low-income individuals far more likely to be obese than higher-income individuals. There was one aberration to this rule in the most recent national survey: the very poor (those living below 100 percent of the poverty level) had lower obesity rates (39.2 percent) than those with incomes between 100 percent to 199 percent of the poverty level, who had a rate of 42.6 percent.54 But both groups had far higher obesity levels than those with incomes at 400 percent or more of the poverty level, whose obesity rate was 29.7 percent.
Children from low-income families are also more likely to be obese. In 2007, 27.4 percent of children living in households below the federal household poverty level were obese, compared to only 10 percent of children living in households exceeding 400 percent of the federal poverty level.10
Individuals with lower education levels are also disproportionately more likely to be obese. In 2015, 34.0 percent of those with less than a high school education were obese compared to 21.7 percent among college graduates (BRFSS analysis).11 An analysis of the 2007 National Survey of Children’s Health found that children of parents with less than 12 years of education had an obesity rate 3.1 times higher (30.4 percent) than those whose parents have a college degree (9.5 percent).12
3. Regional Differences
Rural, suburban and urban communities all have different environmental factors impacting their residents’ health. Urban residents also face different challenges that vary according to the size of the city in which they live.
Rural counties have higher rates of obesity than urban or suburban counties, with the highest adult obesity rates in the United States found in rural counties of Mississippi and Alabama.13
Low-income neighborhoods are 4.5 times more likely not to have pools, tracks, tennis courts, sports fields and other recreational facilities.
Rural communities face different challenges than their urban and suburban counterparts. Fewer children in rural areas walk to school, and the populace relies heavily on automobiles for transportation. Lifestyle differences may also contribute, including higher rates of television watching, higher calorie consumption and lower rates of exercise in rural areas.14 There are also likely structural differences at play, which may include lack of nutrition education, fewer nutrition services, fewer sidewalks and reduced access to facilities that foster healthy behavior, such as recreation centers and supermarkets that sell healthy, affordable food.15,16 Some strategies to improve diet and physical activity that have been effective in rural areas include farmers’ markets, farm-to-school programs, activity programs for older adults, and increasing access to new or existing facilities for physical activity.17
While urban communities have lower rates of obesity than rural communities, inner-city residents have higher rates of obesity than their suburban counterparts. One reason may be the lower rates of physical activity among urban residents compared to suburban dwellers. This disparity may be caused by the fact that there are often fewer safe places to play and be physically active in urban environments, along with fewer venues selling healthy, affordable foods.
Researchers are still trying to understand aspects of small cities that may be different from larger urban areas. One study found that low-income women in small cities (less than 40,000) had a higher risk of obesity, which actually increased if they lived within a one-mile radius of a supermarket.18 This study contrasts with other research that revealed that living close to a supermarket has been shown to lower the risk of obesity.19
Low-income communities face their own unique challenges. Numerous studies have found that healthy foods are less available in low-income communities.20 One study found that low-income neighborhoods were 4.5 times more likely than high-income neighborhoods to lack recreational facilities such as pools, tracks, tennis courts and sports fields.21 A New England Journal of Medicine study found that when low-income families were provided housing vouchers that allowed them to move out of a high-poverty neighborhood, adults experienced lower rates of extreme obesity and diabetes than adults who received vouchers for housing within the high-poverty neighborhood or adults who received no housing vouchers at all.22
Living in a predominantly racial/ethnic minority community also correlates with certain environmental factors that may contribute to obesity. For example, one study found that fast-food establishments were more prevalent in both high-income and low-income Black communities than in White communities.23 Another found that minority neighborhoods were significantly less likely to have recreational facilities than White neighborhoods.24 A study of food stores found four times more supermarkets located in White neighborhoods than Black neighborhoods.25
1 Flegal KM, Kruszon-Moran D, Carroll MD, et al. Trends in obesity among adults in the United States, 2005 to 2014. JAMA. 2016;315(21):2284-2291. doi:10.1001/jama.2016.6458.
2 49 Kaiser Family Foundation. Overweight and Obesity Rates for Adults by Race/Ethnicity. http://kff.org/other/state-indicator/adult-overweightobesity-rate-by-re/. Accessed June 13, 2017.
3 Notah Begay III Foundation website. http://www.nb3foundation.org/who-we-are/about-us/. Accessed April 20, 2017.
4 NB3 Foundation accomplishments. Notah Begay III Foundation website. http://www.nb3foundation.org/our-work/nb3-foundation-accomplishments/. Accessed April 20, 2017
5 Notah Begay III Foundation website. http://www.nb3foundation.org/who-we-are/about-us/. Accessed April 20, 2017.
6 WHO Expert Consultation. Appropriate body-mass index for Asian populations and its implications for policy and intervention strategies. Lancet. 2004;363(9403):157-163.
7 Lauderdale DS, Rathouz PJ. Body mass index in a US national sample of Asian Americans: effects of nativity, years since immigration and socioeconomic status. Int J Obesity. 2000; 24: 1188?94.
8 WHO Expert Consultation. Appropriate body-mass index for Asian populations and its implications for policy and intervention strategies. Lancet. 2004;363(9403):157-163.
9 WHO Expert Consultation. Appropriate body-mass index for Asian populations and its implications for policy and intervention strategies. Lancet. 2004;363(9403):157-163.
10 Singh GK, Kogan MD. Childhood obesity in the United States, 1976-2008: trends and current racial/ethnic, socioeconomic, and geographic disparities. A 75th Anniversary Publication. Health Resources and Services Administration, Maternal and Child Health Bureau. Rockville, Maryland: U.S. Department of Health and Human Services, 2010.
11 Centers for Disease Control and Prevention. National Center for Chronic Disease Prevention and Health Promotion, Division of Nutrition, Physical Activity, and Obesity. Nutrition, Physical Activity, and Obesity: Data, Trends and Maps. https://www.cdc.gov/nccdphp/dnpao/data-trends-maps/index.html. Accessed June 27, 2017.
12 Socioeconomics and Obesity. State of Obesity website. https://stateofobesity.org/socioeconomics-obesity/. Accessed May 15, 2017.
13 Centers for Disease Control and Prevention. Diabetes home: County data, 2013. https://www.cdc.gov/diabetes/data/county.html. Updated May 2, 2017. Accessed May 31, 2017.
14 Gamm LD, Hutchinson LL, Dabney BJ, Dorsey AM. Rural Healthy People 2010: A companion document to Healthy People 2010. College Station, TX: The Texas A&M University System Health Science Center, School of Public Rural Health, Southwest Rural Health Research Center
15 Gamm LD, Hutchinson LL, Dabney BJ, Dorsey AM. Rural Healthy People 2010: A companion document to Healthy People 2010. College Station, TX: The Texas A&M University System Health Science Center, School of Public Rural Health, Southwest Rural Health Research Center
16 Jackson JE, Doescher MP, Jerant AF, Hart LG. A national study of obesity prevalence and trends by type of rural county. J Rural Health. 2005, 21 (2): 140-148. doi: 10.1111/j.1748-0361.2005.tb00074.x.
17 County Health Rankings & Roadmaps. What Works? Strategies to Improve Rural Health. http://www.countyhealthrankings.org/node/35670. Accessed July 18, 2017.
18 Ford PB, Dzewaltowski DA. Limited supermarket availability is not associated with obesity risk among participants in the Kansas WIC program. Obesity. 2010;18:1944?1951. doi:10.1038/oby.2009.487.
19 Powell LM, Auld MC, Chaloupka FJ, O’Malley PM, Johnston LD. Associations between access to food stores and adolescent body mass index. Am J Prev Med. 2007;33:S301?S307.
20 Zenk SN, Powell LM, Rimkus L, et al. Relative and absolute availability of healthier food and beverage alternatives across communities in the United States. Am J Pub Health. 2014;104(11):2170-2178.
21 Moore LV, et al. Availability of recreational resources in minority and low socioeconomic status areas. Am J Prev Med. 2008;34(1):16?22.
22 Ludwig J, Sanbonmatsu L, Gennetian L, et al. Neighborhoods, obesity, and diabetes ? a randomized social experiment. NEJM. 2011;365:1509-1519.
23 Kwate NO, et al. Inequality in obesigenic environments: fast food density in New York City. Health Place. 2009;15(1):364?373.
24 Moore LV, et al. Availability of recreational resources in minority and low socioeconomic status areas. Am J Prev Med. 2008;34(1):16?22.
25 Morland K, et al. Neighborhood characteristics associated with the location of food stores and food service places. Am J Prev Med. 2002;22(1):23?29.