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Obesity - Women in United States
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United States Value:

32.7%

Percentage of women ages 18-44 who have a body mass index of 30.0 or higher based on reported height and weight

Obesity - Women in depth:

Explore Population Data:

Obesity - Women by State: Not Served

Percentage of women who haven't served ages 18-44 who have a body mass index of 30.0 or higher based on reported height and weight

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Data from CDC, Behavioral Risk Factor Surveillance System, 2021-2022

<= 29.9%

30.0% - 32.5%

32.6% - 34.9%

35.0% - 38.3%

>= 38.4%

• Data Unavailable
Top StatesRankValue
123.2%
426.6%
527.9%
Bottom StatesRankValue
4640.5%
4741.4%
4842.0%
5042.7%

Obesity - Women: Not Served

123.2%
426.6%
527.9%
829.0%
929.1%
1029.9%
1330.2%
1430.9%
1531.1%
1631.6%
1831.8%
1932.1%
2032.5%
2132.6%
2232.7%
2433.8%
2534.1%
2634.3%
2734.4%
2834.7%
2934.8%
3034.9%
3135.5%
3135.5%
3436.5%
3637.5%
3737.8%
3938.0%
4038.3%
4138.7%
4238.9%
4339.2%
4540.3%
4640.5%
4741.4%
4842.0%
5042.7%
Data Unavailable
Source:
  • CDC, Behavioral Risk Factor Surveillance System, 2021-2022

Obesity - Women Trends by Veteran Status

Percentage of women ages 18-44 who have a body mass index of 30.0 or higher based on reported height and weight

About Obesity - Women

US Value: 32.7%

Top State(s): Colorado: 23.1%

Bottom State(s): Mississippi: 42.0%

Definition: Percentage of women ages 18-44 who have a body mass index of 30.0 or higher based on reported height and weight

Data Source and Years(s): CDC, Behavioral Risk Factor Surveillance System, 2021-2022

Suggested Citation: America's Health Rankings analysis of CDC, Behavioral Risk Factor Surveillance System, United Health Foundation, AmericasHealthRankings.org, accessed 2024.

Obesity is a complex health condition with biological, economic, environmental, individual and societal causes. Contributing factors to obesity include social and physical environment, genetics, prenatal and early life influences, and behaviors such as poor diet and physical inactivity.

Adults with obesity are at an increased risk of developing serious health conditions, including hypertension, Type 2 diabetes, heart disease and stroke, sleep apnea and breathing problems, some cancers, and mental illnesses like depression and anxiety. 

In addition, obesity during pregnancy can put a pregnant person at risk of gestational hypertension, preeclampsia and gestational diabetes and increases the likelihood of miscarriage, stillbirth, neonatal mortality and infant mortality.

A 2017 study estimated the annual medical cost of obesity in the United States at nearly $173 billion

While body mass index (BMI) can serve as an easily accessible proxy for population health, it has its limitations. BMI does not distinguish between excess fat and muscle or bone mass, and the relationship between BMI and body fat is influenced by sex, age and ethnicity. Further, it does not capture the complexity of human health. For example, individuals can have a high BMI and good cardiovascular health, while others can have what is categorized as a “healthy” or “normal” BMI and poor cardiovascular health. The American Medical Association adopted a new policy in 2023 addressing the shortcomings of BMI as a clinical health measure and suggesting that BMI be used with other valid measures, such as body composition. 

Additionally, weight stigma — also known as weight-based discrimination or weight bias — can have many negative impacts, including mood and anxiety disorders and avoidance of exercise. Weight stigma is pervasive in health care, with reports of medical professionals spending less time with higher-weight patients, engaging in less education and even being reluctant to perform certain procedures on patients with a higher BMI. Weight stigma in the clinical environment can make individuals feel uncomfortable or marginalized, resulting in avoidance of seeking health care.

According to America’s Health Rankings analysis, the prevalence of obesity is higher among:

  • Women ages 35-44 compared with women ages 18-24 and 25-34; the prevalence of obesity is higher with each increase in age group.
  • Black and Hawaiian/Pacific Islander women compared with white and Asian women. Asian women have the lowest prevalence. 
  • Women who did not graduate from college compared with college graduates.
  • Women with household incomes less than $25,000 compared with women who have higher incomes; the prevalence of obesity is higher with each decrease in income level.
  • Women living in non-metropolitan areas compared with those in metropolitan areas.
  • Women who have difficulty with mobility compared with women without a disability.
  • LGBQ+ women compared with straight women.
  • Women who have not served in the U.S. armed forces compared with those who have served. 

Addressing obesity requires a multifaceted approach involving policymakers, state and local governments, health care and childcare professionals, schools, families and individuals. The Centers for Disease Control and Prevention (CDC) offers state, local and community prevention strategies and tips for living a healthy lifestyle

The Community Preventive Services Task Force has compiled a list of resources for preventing and managing obesity. County Health Rankings & Roadmaps also lists several strategies for increasing physical activity and reducing obesity rates. These include neighborhood environment enhancements to create more access to physical activity and multicomponent obesity prevention interventions that coordinate treatments and planning across different areas. 

The CDC recommends weight gain tracking to promote healthy pregnancy weight. The Healthy Weight Checklist provides information and measurable targets for eating healthy, getting enough sleep and physical activity, limiting screen time and reducing stress, all of which influence weight gain and weight management.

 

Healthy People 2030 has several objectives related to weight and obesity, including reducing the proportion of adults with obesity and increasing the proportion of women who had a healthy weight before pregnancy.

 

Biener, Adam, John Cawley, and Chad Meyerhoefer. “The High and Rising Costs of Obesity to the US Health Care System.” Journal of General Internal Medicine 32 (March 7, 2017): 6–8. https://doi.org/10.1007/s11606-016-3968-8.

Broughton, Darcy E., and Kelle H. Moley. “Obesity and Female Infertility: Potential Mediators of Obesity’s Impact.” Fertility and Sterility 107, no. 4 (April 2017): 840–47. https://doi.org/10.1016/j.fertnstert.2017.01.017.

Ely, Danielle M., Elizabeth C. W. Gregory, and Patrick Drake. “Infant Mortality by Maternal Prepregnancy Body Mass Index: United States, 2017-2018.” National Vital Statistics Reports: From the Centers for Disease Control and Prevention, National Center for Health Statistics, National Vital Statistics System 69, no. 9 (August 2020): 1–11.

Gutin, Iliya. “In BMI We Trust: Reframing the Body Mass Index as a Measure of Health.” Social Theory & Health 16, no. 3 (August 2018): 256–71. https://doi.org/10.1057/s41285-017-0055-0.

Tomiyama, A. Janet, Deborah Carr, Ellen M. Granberg, Brenda Major, Eric Robinson, Angelina R. Sutin, and Alexandra Brewis. “How and Why Weight Stigma Drives the Obesity ‘Epidemic’ and Harms Health.” BMC Medicine 16, no. 1 (December 2018): 123. https://doi.org/10.1186/s12916-018-1116-5.

Tomiyama, A. Janet, J. M. Hunger, J. Nguyen-Cuu, and C. Wells. “Misclassification of Cardiometabolic Health When Using Body Mass Index Categories in NHANES 2005–2012.” International Journal of Obesity 40, no. 5 (May 2016): 883–86. https://doi.org/10.1038/ijo.2016.17.

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We have developed detailed analyses on the health of key populations in the country, including women and children, seniors and those who have served in the U.S. Armed Forces, in addition to a deep dive into health disparities across the country.