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.

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.

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:

**Citation Request: ** Koklu, N., & Sulak, S.A. (2024). Using artificial intelligence techniques for the analysis of obesity status according to the individuals' social and physical activities. Sinop Üniversitesi Fen Bilimleri Dergisi, 9(1), 217-239. https://doi.org/10.33484/sinopfbd.1445215

Obesity Dataset

Obesity is a serious and chronic disease with genetic and environmental interactions. It is defined as an excessive amount of fat tissue in the body that is harmful to health. The main risk factors for obesity include social, psychological, and eating habits. Obesity is a significant health problem for all age groups in the world. Currently, more than 2 billion people worldwide are obese or overweight. Research has shown that obesity can be prevented. In this study, artificial intelligence methods were used to identify individuals at risk of obesity. An online survey was conducted on 1610 individuals to create the obesity dataset. To analyze the survey data, four commonly used artificial intelligence methods in literature, namely Artificial Neural Network, K Nearest Neighbors, Random Forest and Support Vector Machine, were employed after pre-processing. As a result of this analysis, obesity classes were predicted correctly with success rates of 74.96%, 74.03%, 74.03% and 87.82%, respectively. Random Forest was the most successful artificial intelligence method for this dataset and accurately classified obesity with a success rate of 87.82%.

Attributes/Values Sex Male (712) Female (898)

Age Values in integers

Height Values in integers (cm)

Overweight/Obese Families Yes (266) No (1344)

Consumption of Fast Food Yes (436) No (1174)

Frequency of Consuming Vegetables Rarely (400) Sometimes (708) Always (502)

Number of Main Meals Daily 1. 1-2 (444) 3 (928) 3+ (238)

Food Intake Between Meals Rarely (346) Sometimes (564) Usually (417) Always (283)

Smoking Yes (492) No (1118)

Liquid Intake Daily amount smaller than one liter (456) Within the range of 1 to 2 liters (523) In excess of 2 liters (631)

Calculation Of Calorie Intake Yes (286) No (1324)

Physical Exercise No physical activity (206) In the range of 1-2 days (290) In the range of 3-4 days (370) In the range of 5-6 days (358) 6+ days (386)

Schedule Dedicated to Technology Between 0 and 2 hours (382) Between 3 and 5 hours (826) Exceeding five hours (402)

Type of Transportation Used Automobile (660) Motorbike (94) Bike (116) Public transportation (602) Walking (138)

Class Underweight (73) Normal (658) Overweight (592) Obesity (287)

State of Illinois Obesity Percentages by County. Explanation of field attributes: Obesity - The percent of each Illinois county’s population that is considered obese from the 2015 CDC BRFSS Survey.

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

Mali ML: Prevalence of Overweight: Weight for Height: % of Children Under 5 data was reported at 1.900 % in 2015. This records an increase from the previous number of 1.000 % for 2010. Mali ML: Prevalence of Overweight: Weight for Height: % of Children Under 5 data is updated yearly, averaging 2.100 % from Dec 1987 (Median) to 2015, with 6 observations. The data reached an all-time high of 4.700 % in 2006 and a record low of 0.500 % in 1987. Mali ML: Prevalence of Overweight: Weight for Height: % of Children Under 5 data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s Mali – Table ML.World Bank: 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 new child growth standards released in 2006.; ; UNICEF, WHO, World Bank: Joint child malnutrition estimates (JME). Aggregation is based on UNICEF, WHO, and the World Bank harmonized dataset (adjusted, comparable data) and methodology.; 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

Obesity has become a major concern for health officials in the United States. Rates of obesity are higher than ever before and as a result, consequential medical conditions have arisen in those who suffer from obesity; while at the same time, medical expenses are skyrocketing for these same individuals. In this study, I analyze regional trends in the United States of both obesity rates and walkability in 74 cities in the United States. After analyzing the data and constructing visual representations, I found that the Northeast region of the US is most walkable, while the Southeast and Southwestern regions are the least walkable. In regards to obesity rates, I found that the West had the lowest obesity rates in both 2010 and 2013, while the Midwest and the Southeast had a high obesity rate in both 2010 and 2013. Additionally, the Northeastern US had a high obesity rate in 2013.

This is historical data. The update frequency has been set to "Static Data" and is here for historic value. Updated on 8/14/2024

Adults who are not overweight or obese - This indicator shows the percentage of adults who are not overweight or obese. In Maryland in 2015, of adults considered obese, 52% had high blood pressure, 44% had high cholesterol, and 21% had diabetes. Healthy weight can aid in the control of these conditions if they develop. Link to Data Details

Adolescents Who Have Obesity - "This indicator shows the percentage of adolescent public high school students who are obese. In the last 20 years, the percentage of overweight/obese children has more than doubled and, for adolescents, it has tripled. Overweight/obese children are at increased risk of developing life-threatening chronic diseases, such as Type 2 diabetes." Link to Data Details

For more recent aggregated data reports on childhood obesity in NM, visit NM Healthy Kids Healthy Communities Program, NMDOH: https://www.nmhealth.org/about/phd/pchb/hknm/TitleChildhood Obese and Overweight Estimates, NM Counties 2016 - NMCHILDOBESITY2017SummaryCounty level childhood overweight and obese estimates for 2016 in New Mexico. *Most recent data known to be available on childhood obesity*NotesThis map shows NM County estimated rates of childhood overweight and obesity. US data is available upon request. Published in May, 2022. Data is most recent known sub-national obesity data set. If you know of another resource or more recent, please reach out. emcrae@chi-phi.orgSourceData set produced from the American Journal of Epidemiology and with authors and contributors out of the University of South Carolina, using data from the National Survey of Children's Health. Journal SourceZgodic, A., Eberth, J. M., Breneman, C. B., Wende, M. E., Kaczynski, A. T., Liese, A. D., & McLain, A. C. (2021). Estimates of childhood overweight and obesity at the region, state, and county levels: A multilevel small-area estimation approach. American Journal of Epidemiology, 190(12), 2618–2629. https://doi.org/10.1093/aje/kwab176 Journal article uses data fromThe United States Census Bureau, Associate Director of Demographic Programs, National Survey of Children’s Health 2020 National Survey of Children's Health Frequently Asked Questions. October 2021. Available from:https://www.census.gov/programs-surveys/nsch/data/datasets.htmlGIS Data Layer prepared byEMcRae_NMCDCFeature Servicehttps://nmcdc.maps.arcgis.com/home/item.html?id=80da398a71c14539bfb7810b5d9d5a99AliasDefinitionregionRegion NationallystateState (data set is NM only but national data is available upon request)fips_numCounty FIPScountyCounty NamerateRate of Obesitylower_ciLower Confidence Intervalupper_ciUpper Confidence IntervalfipstxtCounty FIPS text

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 data represents the age-adjusted prevalence of high total cholesterol, hypertension, and obesity among US adults aged 20 and over between 1999-2000 to 2017-2018. Notes: All estimates are age adjusted by the direct method to the U.S. Census 2000 population using age groups 20–39, 40–59, and 60 and over. Definitions Hypertension: Systolic blood pressure greater than or equal to 130 mmHg or diastolic blood pressure greater than or equal to 80 mmHg, or currently taking medication to lower high blood pressure High total cholesterol: Serum total cholesterol greater than or equal to 240 mg/dL. Obesity: Body mass index (BMI, weight in kilograms divided by height in meters squared) greater than or equal to 30. Data Source and Methods Data from the National Health and Nutrition Examination Surveys (NHANES) for the years 1999–2000, 2001–2002, 2003–2004, 2005–2006, 2007–2008, 2009–2010, 2011–2012, 2013–2014, 2015–2016, and 2017–2018 were used for these analyses. NHANES is a cross-sectional survey designed to monitor the health and nutritional status of the civilian noninstitutionalized U.S. population. The survey consists of interviews conducted in participants’ homes and standardized physical examinations, including a blood draw, conducted in mobile examination centers.

This Obesity and Diabetes Related Indicators dataset provides a subset of data (40 indicators) for the two topics: Obesity and Diabetes. The dataset includes percentage or rate for Cirrhosis/Diabetes and Obesity and Related Indicators, where available, for all counties, regions and state.
New York State Community Health Indicator Reports (CHIRS) were developed in 2012, and annually updated to provide data for over 300 health indicators, organized by 15 health topic and data for all counties, regions and state are presented in table format with links to trend graphs and maps (http://www.health.ny.gov/statistics/chac/indicators/). Most recent county and state level data are provided. Multiple year combined data offers stable estimates for the burden and risk factors for these two health topics. For more information, check out: http://www.health.ny.gov/statistics/chac/indicators/ or go to the “About” tab.

This subset of the community health indicator report data will not be updated. A dataset containing all of the community health indicators is now available. To view the latest community health obesity and diabetes related indicators, see the featured content section. This Obesity and Diabetes Related Indicators dataset provides a subset of data (40 indicators) for the two topics: Obesity and Diabetes. The dataset includes percentage or rate for Cirrhosis/Diabetes and Obesity and Related Indicators, where available, for all counties, regions and state.
New York State Community Health Indicator Reports (CHIRS) were developed in 2012, and annually updated to provide data for over 300 health indicators, organized by 15 health topic and data for all counties, regions and state are presented in table format with links to trend graphs and maps. Most recent county and state level data are provided. Multiple year combined data offers stable estimates for the burden and risk factors for these two health topics.

United States US: Prevalence of Overweight: Weight for Height: % of Children Under 5 data was reported at 6.000 % in 2012. This records a decrease from the previous number of 7.800 % for 2009. United States US: Prevalence of Overweight: Weight for Height: % of Children Under 5 data is updated yearly, averaging 7.000 % from Dec 1991 (Median) to 2012, with 5 observations. The data reached an all-time high of 8.100 % in 2005 and a record low of 5.400 % in 1991. United States US: Prevalence of Overweight: Weight for Height: % 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 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 new child growth standards released in 2006.; ; UNICEF, WHO, World Bank: Joint child malnutrition estimates (JME). Aggregation is based on UNICEF, WHO, and the World Bank harmonized dataset (adjusted, comparable data) and methodology.; 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

United States Prevalence of Overweight: % of Adults data was reported at 67.900 % in 2016. This records an increase from the previous number of 67.400 % for 2015. United States Prevalence of Overweight: % of Adults data is updated yearly, averaging 55.200 % from Dec 1975 (Median) to 2016, with 42 observations. The data reached an all-time high of 67.900 % in 2016 and a record low of 41.000 % in 1975. United States Prevalence of Overweight: % of Adults data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s United States – Table US.World Bank.WDI: Social: Health Statistics. Prevalence of overweight adults is the percentage of adults ages 18 and over whose Body Mass Index (BMI) is more than 25 kg/m2. Body Mass Index (BMI) is a simple index of weight-for-height, or the weight in kilograms divided by the square of the height in meters.;World Health Organization, Global Health Observatory Data Repository (http://apps.who.int/ghodata/).;;

Cameroon CM: Prevalence of Overweight: Weight for Height: Male: % of Children Under 5 data was reported at 12.200 % in 2018. This records an increase from the previous number of 7.100 % for 2014. Cameroon CM: Prevalence of Overweight: Weight for Height: Male: % of Children Under 5 data is updated yearly, averaging 8.200 % from Dec 1991 (Median) to 2018, with 7 observations. The data reached an all-time high of 12.200 % in 2018 and a record low of 6.000 % in 1991. Cameroon CM: Prevalence of Overweight: Weight for Height: Male: % of Children Under 5 data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s Cameroon – Table CM.World Bank.WDI: Social: Health Statistics. Prevalence of overweight, male, is the percentage of boys 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). Aggregation is based on UNICEF, WHO, and the World Bank harmonized dataset (adjusted, comparable data) and methodology.;;Estimates of overweight children are 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.

The Student Weight Status Category Reporting System (SWSCR) collects weight status category data (underweight, healthy weight, overweight or obese, based on BMI-for-age percentile). The dataset includes separate estimates of the percent of students overweight, obese and overweight or obese for all reportable grades within the county and/or region and by grade groups (elementary and middle/high). The rates of overweight and obesity reported are percentages based on counts of students in selected grades (Pre-K, K, 2, 4, 7, 10) reported to the NYSDOH. Because these rates reflect a broad range of factors that vary by school district, to make comparisons about observed differences in the rates of obesity and overweight between school districts requires the use of multivariate statistics. County, regional and statewide estimates will only be provided biennially, District estimates will be updated annually. For more information check out http://www.health.ny.gov/prevention/obesity/, see our Instruction Guide on How to Create Visualizations https://health.data.ny.gov/api/assets/6490BDA9-AE4D-406F-BA5A-703793526B9F. The "About" tab contains additional details concerning this dataset.

Quality of life is a measure of comfort, health, and happiness by a person or a group of people. Quality of life is determined by both material factors, such as income and housing, and broader considerations like health, education, and freedom. Each year, US & World News releases its “Best States to Live in” report, which ranks states on the quality of life each state provides its residents. In order to determine rankings, U.S. News & World Report considers a wide range of factors, including healthcare, education, economy, infrastructure, opportunity, fiscal stability, crime and corrections, and the natural environment. More information on these categories and what is measured in each can be found below:

Healthcare includes access, quality, and affordability of healthcare, as well as health measurements, such as obesity rates and rates of smoking. Education measures how well public schools perform in terms of testing and graduation rates, as well as tuition costs associated with higher education and college debt load. Economy looks at GDP growth, migration to the state, and new business. Infrastructure includes transportation availability, road quality, communications, and internet access. Opportunity includes poverty rates, cost of living, housing costs and gender and racial equality. Fiscal Stability considers the health of the government's finances, including how well the state balances its budget. Crime and Corrections ranks a state’s public safety and measures prison systems and their populations. Natural Environment looks at the quality of air and water and exposure to pollution.