West Virginia, Mississippi, and Arkansas are the U.S. states with the highest percentage of their population who are obese. The states with the lowest percentage of their population who are obese include Colorado, Hawaii, and Massachusetts. Obesity in the United States Obesity is a growing problem in many countries around the world, but the United States has the highest rate of obesity among all OECD countries. The prevalence of obesity in the United States has risen steadily over the previous two decades, with no signs of declining. Obesity in the U.S. is more common among women than men, and overweight and obesity rates are higher among African Americans than any other race or ethnicity. Causes and health impacts Obesity is most commonly the result of a combination of poor diet, overeating, physical inactivity, and a genetic susceptibility. Obesity is associated with various negative health impacts, including an increased risk of cardiovascular diseases, certain types of cancer, and diabetes type 2. As of 2022, around 8.4 percent of the U.S. population had been diagnosed with diabetes. Diabetes is currently the eighth leading cause of death in the United States.

The prevalence of obesity in the United States has risen gradually over the past decade. As of 2023, around ** percent of the population aged 18 years and older was obese. Obesity is a growing problem in many parts of the world, but is particularly troubling in the United States. Obesity in the United States The states with the highest prevalence of obesity are West Virginia, Mississippi, and Arkansas. As of 2023, a shocking ** percent of the population in West Virginia were obese. The percentage of adults aged 65 years and older who are obese has grown in recent years, compounding health issues that develop with age. Health impacts of obesity Obesity is linked to several negative health impacts including cardiovascular disease, diabetes, and certain types of cancer. Unsurprisingly, the prevalence of diagnosed diabetes has increased in the United States over the years. As of 2022, around *** percent of the population had been diagnosed with diabetes. Some of the most common types of cancers caused by obesity include breast cancer in postmenopausal women, colon and rectum cancer, and corpus and uterus cancer.

National Obesity Percentages by State. Explanation of Field Attributes:Obesity - The percent of the state population that is considered obese from the 2015 CDC BRFSS Survey.

In 2023, Black adults had the highest obesity rates of any race or ethnicity in the United States, followed by American Indians/Alaska Natives and Hispanics. As of that time, around ** percent of all Black adults were obese. Asians/Pacific Islanders had by far the lowest obesity rates. Obesity in the United States Obesity is a present and growing problem in the United States. An astonishing ** percent of the adult population in the U.S. is now considered obese. Obesity rates can vary substantially by state, with around ** percent of the adult population in West Virginia reportedly obese, compared to ** percent of adults in Colorado. The states with the highest rates of obesity include West Virginia, Mississippi, and Arkansas. Diabetes Being overweight and obese can lead to a number of health problems, including heart disease, cancer, and diabetes. Being overweight or obese is one of the most common causes of type 2 diabetes, a condition in which the body does not use insulin properly, causing blood sugar levels to rise. It is estimated that just over ***** percent of adults in the U.S. have been diagnosed with diabetes. Diabetes is now the seventh leading cause of death in the United States, accounting for ***** percent of all deaths.

The adult obesity rate, or the percentage of the county population (age 18 and older*) that is obese, or has a Body Mass Index (BMI) equal to or greater than 30 [kg/m2], is illustrative of a serious health problem, in Champaign County, statewide, and nationally.

The adult obesity rate data shown here spans from Reporting Years (RY) 2015 to 2024. Champaign County’s adult obesity rate fluctuated during this time, peaking in RY 2022. The adult obesity rates for Champaign County, Illinois, and the United States were all above 30% in RY 2024, but the Champaign County rate was lower than the state and national rates. All counties in Illinois had an adult obesity rate above 30% in RY 2024, but Champaign County's rate is one of the lowest among all Illinois counties.

Obesity is a health problem in and of itself, and is commonly known to exacerbate other health problems. It is included in our set of indicators because it can be easily measured and compared between Champaign County and other areas.

This data was sourced from the University of Wisconsin’s Population Health Institute’s and the Robert Wood Johnson Foundation’s County Health Rankings & Roadmaps. Each year’s County Health Rankings uses data from the most recent previous years that data is available. Therefore, the 2024 County Health Rankings (“Reporting Year” in the table) uses data from 2021 (“Data Year” in the table). The survey methodology changed in Reporting Year 2015 for Data Year 2011, which is why the historical data shown here begins at that time. No data is available for Data Year 2018. The County Health Rankings website notes to use caution if comparing RY 2024 data with prior years.

*The percentage of the county population measured for obesity was age 20 and older through Reporting Year 2021, but starting in Reporting Year 2022 the percentage of the county population measured for obesity was age 18 and older.

Source: University of Wisconsin Population Health Institute. County Health Rankings & Roadmaps 2024. www.countyhealthrankings.org.

Normal Weight, Overweight, and Obesity Among Adults Aged 20 and Over by Selected Population Characteristics

Context:

This dataset provides data on the prevalence of normal weight, overweight, and obesity among adults aged 20 and over, segmented by various population characteristics. The data is sourced from the National Health and Nutrition Examination Survey (NHANES) conducted by the National Center for Health Statistics (NCHS). This dataset is invaluable for understanding the distribution and trends of weight-related health metrics across different demographics in the United States.

Source: - National Health and Nutrition Examination Survey (NHANES): Conducted by NCHS. - Supporting Documentation: Refer to the HUS 2019 Data Finder for detailed definitions, measures, and changes over time. - Appendix Entry: Additional information available in the corresponding Appendix entry.

Source URLs: - HUS 2019 Data Finder - Appendix Entry - Data.gov Dataset

Dataset Details and Key Features

This dataset includes data collected over multiple time periods, providing insights into the weight distribution among adults aged 20 and over. Key features include segmentation by sex and specific age ranges.

Key Features:

• Time Coverage: Data spans several decades, from 1988-2018.
• Demographic Breakdown: Includes data by sex and age groups, allowing for detailed analysis.
• Percentage Data: Provides percentage estimates of normal weight, overweight, and obesity.
• Standard Error: Includes standard error for each estimate, indicating the precision of the estimates.

Usage

Research and Analysis:

• Health Trends: Study trends in weight distribution among different demographic groups.
• Public Health Initiatives: Inform public health strategies and interventions targeting obesity and overweight issues.
• Socioeconomic Analysis: Analyze the impact of socio-economic factors on weight-related health metrics.

Policy Making:

• Policy Development: Develop policies aimed at reducing obesity rates and promoting healthy weight.
• Resource Allocation: Allocate resources effectively to areas with higher prevalence of overweight and obesity.
• Program Evaluation: Evaluate the effectiveness of past and current public health programs.

Healthcare Planning:

• Preventive Measures: Design preventive measures and programs based on demographic data.
• Community Outreach: Plan community outreach programs targeting high-risk groups.
• Nutritional Guidelines: Inform the creation of nutritional guidelines and recommendations.

Data Maintenance:

• Maintainer: National Center for Health Statistics
• Publisher: Centers for Disease Control and Prevention
• Last Updated: August 29, 2023

Quality Assurance:

• Data Validation: Ensures data accuracy through rigorous validation processes.
• Consistency Checks: Regular consistency checks to maintain data integrity.

Additional Notes:

• For detailed definitions and explanations of measures, refer to the PDF or Excel version of this table in the HUS 2019 Data Finder.
• Data is collected from the National Health and Nutrition Examination Survey (NHANES), ensuring comprehensive coverage and reliability.

Columns:

In 2023, it was estimated that around 37 percent of adults with an annual income of less than 15,000 U.S. dollars were obese, compared to 29 percent of those with an annual income of 75,000 dollars or more. This statistic shows the percentage of U.S. adults who were obese in 2023, by income.

This dataset includes select data from the U.S. Census Bureau's American Community Survey (ACS) on the percent of adults who bike or walk to work. This data is used for DNPAO's Data, Trends, and Maps database, which provides national and state specific data on obesity, nutrition, physical activity, and breastfeeding. For more information about ACS visit https://www.census.gov/programs-surveys/acs/.

United States US: Prevalence of Overweight: Weight for Height: Female: % of Children Under 5 data was reported at 6.900 % in 2012. This records an increase from the previous number of 6.400 % for 2009. United States US: Prevalence of Overweight: Weight for Height: Female: % of Children Under 5 data is updated yearly, averaging 6.900 % from Dec 1991 (Median) to 2012, with 6 observations. The data reached an all-time high of 8.700 % in 2005 and a record low of 5.100 % in 1991. United States US: Prevalence of Overweight: Weight for Height: Female: % of Children Under 5 data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s USA – Table US.World Bank: Health Statistics. Prevalence of overweight, female, is the percentage of girls under age 5 whose weight for height is more than two standard deviations above the median for the international reference population of the corresponding age as established by the WHO's new child growth standards released in 2006.; ; World Health Organization, Global Database on Child Growth and Malnutrition. Country-level data are unadjusted data from national surveys, and thus may not be comparable across countries.; Linear mixed-effect model estimates; Estimates of overweight children are also from national survey data. Once considered only a high-income economy problem, overweight children have become a growing concern in developing countries. Research shows an association between childhood obesity and a high prevalence of diabetes, respiratory disease, high blood pressure, and psychosocial and orthopedic disorders (de Onis and Blössner 2003). Childhood obesity is associated with a higher chance of obesity, premature death, and disability in adulthood. In addition to increased future risks, obese children experience breathing difficulties and increased risk of fractures, hypertension, early markers of cardiovascular disease, insulin resistance, and psychological effects. Children in low- and middle-income countries are more vulnerable to inadequate nutrition before birth and in infancy and early childhood. Many of these children are exposed to high-fat, high-sugar, high-salt, calorie-dense, micronutrient-poor foods, which tend be lower in cost than more nutritious foods. These dietary patterns, in conjunction with low levels of physical activity, result in sharp increases in childhood obesity, while under-nutrition continues

In 2023, it was estimated that around 32 percent of men and 34 percent of women in the U.S. were obese. This statistic shows the percentage of adults in the United States who were obese in 2023, by gender.

Data on normal weight, overweight, and obesity among adults aged 20 and over by selected population characteristics. Please refer to the PDF or Excel version of this table in the HUS 2019 Data Finder (https://www.cdc.gov/nchs/hus/contents2019.htm) for critical information about measures, definitions, and changes over time. SOURCE: NCHS, National Health and Nutrition Examination Survey. For more information on the National Health and Nutrition Examination Survey, see the corresponding Appendix entry at https://www.cdc.gov/nchs/data/hus/hus19-appendix-508.pdf.

This report presents information on obesity, physical activity and diet drawn together from a variety of sources for England. More information can be found in the source publications which contain a wider range of data and analysis. Each section provides an overview of key findings, as well as providing links to relevant documents and sources. Some of the data have been published previously by NHS Digital. A data visualisation tool (link provided within the key facts) allows users to select obesity related hospital admissions data for any Local Authority (as contained in the data tables), along with time series data from 2013/14. Regional and national comparisons are also provided. The report includes information on: Obesity related hospital admissions, including obesity related bariatric surgery. Obesity prevalence. Physical activity levels. Walking and cycling rates. Prescriptions items for the treatment of obesity. Perception of weight and weight management. Food and drink purchases and expenditure. Fruit and vegetable consumption. Key facts cover the latest year of data available: Hospital admissions: 2018/19 Adult obesity: 2018 Childhood obesity: 2018/19 Adult physical activity: 12 months to November 2019 Children and young people's physical activity: 2018/19 academic year

In Mississippi, over ***** out of ten adults were reported to be either overweight or obese in 2018, making it the leading U.S. state that year. Other prominent states, in terms of overweight and obesity, included Arkansas in ******, Oklahoma in *******, and Louisiana in ***** place.

Corpulence per state

When it comes to obesity, specifically, percentages were still very high for certain states. Almost forty percent of West Virginia’s population was obese in 2018. Colorado, Hawaii, and California were some of the healthier states that year, with obesity rates between ** and ** percent. The average for the country itself stood at just over ** percent.

Obesity-related health problems

Being obese can lead to various health-related complications, such as diabetes and diseases of the heart. In 2017, almost ** people per 100,000 died of diabetes mellitus in the United States. In the same year, roughly *** per 100,000 Americans died of heart disease. While the number of deaths caused by heart disease has decreased significantly over the past sixty to seventy years, it is still one of the leading causes of death in the country.

Observed and age-standardised proportion of adults with a Body Mass Index (BMI) greater than 30 kg/m2. To help reduce the prevalence of obesity. Legacy unique identifier: P00848

Note: This data was created by the Center for Disease Control, not the City of Rochester. This map is zoomed in to show the CDC data at the census tract level. You can zoom out to see data for all 500 cities in the data set. This map has been built to symbolize the percentage of adults who, in 2017, had a body mass index (BMI) at/above 30.0, classifying them as obese according to self-reported data on their height on weight. However, if you click on a census tract, you can see statistics for the other public health statistics mentioned below in the "Overview of the Data" section.Overview of the Data: This service provides the 2019 release for the 500 Cities Project, based on data from 2017 or 2016 model-based small area estimates for 27 measures of chronic disease related to unhealthy behaviors (5), health outcomes (13), and use of preventive services (9). Twenty measures are based on 2017 Behavioral Risk Factor Surveillance System (BRFSS) model estimates. Seven measures (all teeth lost, dental visits, mammograms, Pap tests, colorectal cancer screening, core preventive services among older adults, and sleep less than 7 hours) kept 2016 model estimates, since those questions are only asked in even years. The project was funded by the Robert Wood Johnson Foundation (RWJF) in conjunction with the CDC Foundation. It represents a first-of-its kind effort to release information on a large scale for cities and for small areas within those cities. It includes estimates for the 500 largest US cities and approximately 28,000 census tracts within these cities. These estimates can be used to identify emerging health problems and to inform development and implementation of effective, targeted public health prevention activities. Because the small area model cannot detect effects due to local interventions, users are cautioned against using these estimates for program or policy evaluations.Data were provided by the Centers for Disease Control and Prevention (CDC), Division of Population Health, Epidemiology and Surveillance Branch. Data sources used to generate these measures include BRFSS data (2017 or 2016), Census Bureau 2010 census population data, and American Community Survey (ACS) 2013-2017 or 2012-2016 estimates. For more information about the methodology, visit https://www.cdc.gov/500cities or contact 500Cities@cdc.gov.

Overweight or obese by sex, race/ethnicity, and grade, California Healthy Kids Survey, 2015-16METADATA:Notes (String): Lists table title, sourceYear (String): Year of surveyCategory (String): Lists the category representing the data: Santa Clara County is for total surveyed population, sex: Male and Female, race/ethnicity: African American, Asian/Pacific Islander, Latino and White (non-Hispanic White only) and grade level (7th, 9th, 11th, or non-traditional).Percent (Numeric): Percentage of middle and high school students who are overweight or obese

India IN: Prevalence of Overweight: Weight for Height: % of Children Under 5, Modeled Estimate data was reported at 3.700 % in 2024. This records an increase from the previous number of 3.400 % for 2023. India IN: Prevalence of Overweight: Weight for Height: % of Children Under 5, Modeled Estimate data is updated yearly, averaging 2.300 % from Dec 2000 (Median) to 2024, with 25 observations. The data reached an all-time high of 3.700 % in 2024 and a record low of 2.100 % in 2013. India IN: Prevalence of Overweight: Weight for Height: % of Children Under 5, Modeled Estimate data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s India – Table IN.World Bank.WDI: Social: Health Statistics. Prevalence of overweight children is the percentage of children under age 5 whose weight for height is more than two standard deviations above the median for the international reference population of the corresponding age as established by the WHO's 2006 Child Growth Standards.;UNICEF, WHO, World Bank: Joint child Malnutrition Estimates (JME).;Weighted average;Once considered only a high-income economy problem, overweight children have become a growing concern in developing countries. Research shows an association between childhood obesity and a high prevalence of diabetes, respiratory disease, high blood pressure, and psychosocial and orthopedic disorders (de Onis and Blössner 2003). Childhood obesity is associated with a higher chance of obesity, premature death, and disability in adulthood. In addition to increased future risks, obese children experience breathing difficulties and increased risk of fractures, hypertension, early markers of cardiovascular disease, insulin resistance, and psychological effects. Children in low- and middle-income countries are more vulnerable to inadequate nutrition before birth and in infancy and early childhood. Many of these children are exposed to high-fat, high-sugar, high-salt, calorie-dense, micronutrient-poor foods, which tend be lower in cost than more nutritious foods. These dietary patterns, in conjunction with low levels of physical activity, result in sharp increases in childhood obesity, while under-nutrition continues. Estimates are modeled estimates produced by the JME. Primary data sources of the anthropometric measurements are national surveys. These surveys are administered sporadically, resulting in sparse data for many countries. Furthermore, the trend of the indicators over time is usually not a straight line and varies by country. Tracking the current level and progress of indicators helps determine if countries are on track to meet certain thresholds, such as those indicated in the SDGs. Thus the JME developed statistical models and produced the modeled estimates.

In 2022, over ** percent of both men and women in the United States reported themselves as obese (BMI over 30), making it the country with the highest percentage of obese adults on this list. Other selected countries on the list with a high prevalence of obesity among adults included the United Kingdom and Australia. Obesity groups in the United States In 2023, Black adults had the highest overweight and obesity rates of any race or ethnicity in the United States. Asians and Native Hawaiians or Pacific Islanders had the lowest rates by far, with roughly ** percent. In 2022, almost ** percent of people aged 65 and older were obese in the United States. This estimate has been steadily increasing since 2013 when roughly ** percent of elderly Americans were obese. Leading health problems worldwide Obesity was considered one of 2024’s biggest health problems: ** percent of adults worldwide stated that obesity was the biggest health issue for people within their country. Around ** percent of adults stated that mental health was the most significant problem facing their country that year.

Proportion of children aged 10 to 11 years classified as overweight or living with obesity. For population monitoring purposes, a child’s body mass index (BMI) is classed as overweight or obese where it is on or above the 85th centile or 95th centile, respectively, based on the British 1990 (UK90) growth reference data. The population monitoring cut offs for overweight and obesity are lower than the clinical cut offs (91st and 98th centiles for overweight and obesity) used to assess individual children; this is to capture children in the population in the clinical overweight or obesity BMI categories and those who are at high risk of moving into the clinical overweight or clinical obesity categories. This helps ensure that adequate services are planned and delivered for the whole population.

Rationale There is concern about the rise of childhood obesity and the implications of obesity persisting into adulthood. The risk of obesity in adulthood and risk of future obesity-related ill health are greater as children get older. Studies tracking child obesity into adulthood have found that the probability of children who are overweight or living with obesity becoming overweight or obese adults increases with age[1,2,3]. The health consequences of childhood obesity include: increased blood lipids, glucose intolerance, Type 2 diabetes, hypertension, increases in liver enzymes associated with fatty liver, exacerbation of conditions such as asthma and psychological problems such as social isolation, low self-esteem, teasing and bullying.

It is important to look at the prevalence of weight status across all weight/BMI categories to understand the whole picture and the movement of the population between categories over time.

The National Institute of Health and Clinical Excellence have produced guidelines to tackle obesity in adults and children - http://guidance.nice.org.uk/CG43.

1 Guo SS, Chumlea WC. Tracking of body mass index in children in relation to overweight in adulthood. The American Journal of Clinical Nutrition 1999;70(suppl): 145S-8S.

2 Serdula MK, Ivery D, Coates RJ, Freedman DS, Williamson DF, Byers T. Do obese children become obese adults? A review of the literature. Preventative Medicine 1993;22:167-77.

3 Starc G, Strel J. Tracking excess weight and obesity from childhood to young adulthood: a 12-year prospective cohort study in Slovenia. Public Health Nutrition 2011;14:49-55.

Definition of numerator Number of children in year 6 (aged 10 to 11 years) with a valid height and weight measured by the NCMP with a BMI classified as overweight or living with obesity, including severe obesity (BMI on or above the 85th centile of the UK90 growth reference).

Definition of denominator The number of children in year 6 (aged 10 to 11 years) with a valid height and weight measured by the NCMP.

Caveats Data for local authorities may not match that published by NHS England which are based on the local authority of the school attended by the child or based on the local authority that submitted the data. There is a strong correlation between deprivation and child obesity prevalence and users of these data may wish to examine the pattern in their local area. Users may wish to produce thematic maps and charts showing local child obesity prevalence. When presenting data in charts or maps it is important, where possible, to consider the confidence intervals (CIs) around the figures. This analysis supersedes previously published data for small area geographies and historically published data should not be compared to the latest publication. Estimated data published in this fingertips tool is not comparable with previously published data due to changes in methods over the different years of production. These methods changes include; moving from estimated numbers at ward level to actual numbers; revision of geographical boundaries (including ward boundary changes and conversion from 2001 MSOA boundaries to 2011 boundaries); disclosure control methodology changes. The most recently published data applies the same methods across all years of data. There is the potential for error in the collection, collation and interpretation of the data (bias may be introduced due to poor response rates and selective opt out of children with a high BMI for age/sex which it is not possible to control for). There is not a good measure of response bias and the degree of selective opt out, but participation rates (the proportion of eligible school children who were measured) may provide a reasonable proxy; the higher the participation rate, the less chance there is for selective opt out, though this is not a perfect method of assessment. Participation rates for each local authority are available in the https://fingertips.phe.org.uk/profile/national-child-measurement-programme/data#page/4/gid/8000022/ of this profile.