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, 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.

Obesity rates for each Census Tract in Allegheny County were produced for the study “Developing small-area predictions for smoking and obesity prevalence in the United States." The data is not explicitly based on population surveys or data collection conducted in Allegheny County, but rather estimated using statistical modeling techniques. In this technique, researchers applied the obesity rate of a demographically similar census tract to one in Allegheny County to compute an obesity rate.

Support for Health Equity datasets and tools provided by Amazon Web Services (AWS) through their Health Equity Initiative.

This statistical report presents information on obesity, physical activity and diet, drawn together from a variety of sources. The topics covered include: Obesity related hospital admissions. Prescription items for the treatment of obesity. Adult obesity prevalence. Childhood obesity prevalence. Physical activity levels among adults and children. Diet among adults and children, including trends in purchases, and consumption of food and drink and energy intake. Each section provides an overview of the key findings from these sources, as well as providing sources of further information and links to relevant documents and sources. Some of the data have been published previously by NHS Digital. A data visualisation tool at the link below allows users to select obesity related hospital admissions data for any Local Authority (as contained in Excel tables 3, 7 and 11 of this publication), along with time series data from 2013/14. Regional and national comparisons are also provided.

Obesity percentages for Lake County, Illinois. Explanation of field attributes: Pct_Obese – The percent of people in the zip code who are considered obese, defined as having a BMI greater than or equal to 30. ObsOrOvrwt –The percent of people in the zip code who are considered overweight (defined as having a BMI greater than or equal to 25 but less than 30) or obese (defined as having a BMI greater than or equal to 30).

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:

From 2021 to 2023, the obesity prevalence among the total U.S. population aged 20 and older was around ** percent. This statistic shows the prevalence of obesity among adults aged 20 and older in the United States from 2021 to 2023, by gender and age group.

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.

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.

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.

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.

This statistical report presents a range of information on obesity, physical activity and diet, drawn together from a variety of sources. The topics covered include: Overweight and obesity prevalence among adults and children Physical activity levels among adults and children Trends in purchases and consumption of food and drink and energy intake Health outcomes of being overweight or obese. This report contains seven chapters which consist of the following: Chapter 1: Introduction; this summarises government policies, targets and outcome indicators in this area, as well as providing sources of further information and links to relevant documents. Chapters 2 to 6 cover obesity, physical activity and diet and provides an overview of the key findings from these sources, whilst maintaining useful links to each section of these reports. Chapter 7: Health Outcomes; presents a range of information about the health outcomes of being obese or overweight which includes information on health risks, hospital admissions and prescription drugs used for treatment of obesity. Figures presented in Chapter 7 have been obtained from a number of sources and presented in a user-friendly format. Some of the data contained in the chapter have been published previously by the NHS Information Centre (NHS IC) or the National Audit Office. Previously unpublished figures on obesity-related Finished Hospital Episodes and Finished Consultant Episodes for 2010/11 are presented using data from the NHS IC's Hospital Episode Statistics as well as data from the Prescribing Unit at the NHS IC on prescription items dispensed for treatment of obesity.

**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)

The prevalence of obesity in the adult population (18 years and older) in Trinidad and Tobago. Overweight and obesity are defined as abnormal or excessive fat accumulation that may impair health. Body mass index (BMI) is a simple weight-for-height index commonly used to classify overweight and obesity in adults. It is defined as a person's weight in kilograms divided by the square of his height in meters (kg/m2). Adults For adults, the World Health Organization (WHO) defines overweight and obesity as follows: overweight is a BMI greater than or equal to 25; and obesity is a BMI greater than or equal to 30. BMI provides the most useful population-level measure of overweight and obesity as it is the same for both sexes and all ages of adults. However, it should be considered a rough guide because it may not correspond to the same degree of fatness in different individuals. The Creative Commons Attribution-NonCommercial-ShareAlike 3.0 IGO (CC BY-NC-SA 3.0 IGO) specifies that you must give appropriate attribution and credit to FAO for any work produced using a dataset or when data is re-disseminated. The following citation is recommended: [© FAO] [Year of publication] [Title of content] [Page number (for publications)] [Location on FAO website] [Date accessed and/or downloaded] Example: © FAO 2023, Prevalence of Moderate and Severe Food Insecurity, https://www.fao.org/faostat/en/#country/220, Accessed on November 21, 2023

Note August 2011: A number of errors have been identified in Table 7.5 - GHQ 12 score by body mass index (BMI) and gender, 2006 on page 164 of the Statistics on Obesity, Physical Activity and Diet: England, 2009 report. The errors also affect the corresponding table in the accompanying Excel workbook. The commentary in the pdf report is unaffected. Please see the errata note for further information and corrected figures. The NHS IC apologises for any inconvenience this may have caused. Summary: This publication presents a range of information on obesity, physical activity and diet, drawn together from a variety of sources. This publication also summarises government plans and targets in this area, as well as providing sources of further information and links to relevant documents and key sources. This, our third report on obesity, physical activity and diet includes: overweight and obesity prevalence among adults and children physical activity levels among adults and children trends in purchases and consumption of food and drink, and energy intake and health outcomes of being overweight or obese. For the first time, the report provides information on attitudes towards and knowledge about leading a healthy lifestyle for both adults and children. This includes information on how much physical activity should be done, barriers towards doing more physical activity, knowledge of the recommended daily number of portions of fruit and vegetables and attitudes towards a healthy diet.

Layers in this service includes: Birth, Cancer, Hospitalization Discharge, Mortality and STI Rates, as well as Demographics.

In the United States, the rate of obesity is lower among college graduates compared to those who did not graduate from college. For example, in 2023, around 27 percent of college graduates were obese, while 36 percent of those with some college or technical school were obese. At that time, rates of obesity were highest among those with less than a high school education, at around 37 percent. Income and obesity As with education level, there are also differences in rates of obesity in the United States based on income. Adults in the U.S. with an annual income of 75,000 U.S. dollars or more have the lowest rates of obesity, with around 29 percent of this population obese in 2023. On the other hand, those earning less than 15,000 U.S. dollars per year had the highest rates of obesity at that time, at 37 percent. One reason for this disparity may be a lack of access to fresh food among those earning less, as cheap food in the United States tends to be unhealthier. What is the most obese state? As of 2023, the states with the highest rates of obesity were West Virginia, Mississippi, and Arkansas. At that time, around 41 percent of adults in West Virginia were obese. The states with the lowest rates of obesity were Colorado, Hawaii, and Massachusetts. Still, around a quarter of adults in Colorado were obese in 2023. West Virginia and Mississippi are also the states with the highest rates of obesity among high school students. Children with obesity are more likely to be obese as adults and are at increased risk of health conditions such as asthma, type 2 diabetes, and sleep apnea.