This map shows where obesity and diabetes are happening in the US, by county. It shows each component of the map as its own layer, and also shows the patterns overlapping. Diabetes prevalence (% of adults)Obesity prevalence (% of adults)This data can be used to assess the health factors, and answer questions such as:Are certain counties more/less at risk in regards to diabetes and obesity?Are diabetes, obesity, and physical inactivity happening within the same areas of the US?According to the CDC: "These data can help the public to better use existing resources for diabetes management and prevention efforts." The data comes from the Behavioral Risk Factor Surveillance System (BRFSS) through the Centers for Disease Control and Prevention (CDC), and the data vintage is 2013. To explore other county indicators, different vintages, or the original data, click here. To view the interactive map through the CDC website, click here. To learn more about the methodology of how county-level estimates are calculated, see this PDF.

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.

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.

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.

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

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.

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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/.

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/.

Between 2015 and 2018, obesity rates in U.S. children and adolescents stood at 19.3 and 20.9 percent, respectively. This is a noteworthy increase compared to the percentages seen between 1988 and 1994.

U.S. high school obesity rates

Roughly 18 percent of black, as well as Hispanic students in the United States, were obese between 2016 and 2017. Male obesity rates were noticeably higher than those of female students for each of the ethnicities during the measured period. For example, about 22 percent of male Hispanic high school students were obese, compared to 14 percent of female students. The American states with the highest number of obese high school students in 2019 included Mississippi, West Virginia, and Arkansas, respectively. Mississippi had a high school student obesity rate of over 23 percent that year.

Physically inactive Americans

Adults from Mississippi and Arkansas were also reported to be some of the least physically active people in the United States in 2018. When surveyed, over 30 percent of adults from Kentucky and Arkansas had not exercised within the preceding 30 days. The national physical inactivity average stood at approximately 26 percent that year.

Although insulin resistance (IR) is a key pathophysiologic condition underlying various metabolic disorders, impaired cellular glucose uptake is one of many manifestations of metabolic derangements in the human body. To study the systems-wide molecular changes associated with obesity-dependent IR, we integrated information on plasma proteins and microRNAs in eight obese insulin-resistant (OIR, HOMA-IR > 2.5) and nine lean insulin-sensitive (LIS, HOMA-IR < 1.0) normoglycemic males. Of 374 circulating miRNAs we profiled, 65 species increased and 73 species decreased in the OIR compared to the LIS subjects, suggesting that the overall balance of the miRNA secretome is shifted in the OIR subjects. We also observed that 40 plasma proteins increased and 4 plasma proteins decreased in the OIR subjects compared to the LIS subjects, and most proteins are involved in metabolic and endocytic functions. We used an integrative -omics analysis framework called iOmicsPASS to link differentially regulated miRNAs with their target genes on the TargetScan map and the human protein interactome. Combined with tissue of origin information, the integrative analysis allowed us to nominate obesity-dependent and obesity-independent protein markers, along with potential sites of post-transcriptional regulation by some of the miRNAs. We also observed the changes in each -omics platform that are not linked by the TargetScan map, suggesting that proteins and microRNAs provide orthogonal information for the progression of OIR. In summary, our integrative analysis provides a network of elevated plasma markers of OIR and a global shift of microRNA secretome composition in the blood plasma.

BMI data is obtained from each systems’ electronic health record and combined into one database managed by the Colorado Department of Public Health and Environment. These data represent individuals who presented for routine care at one of the participating health care organizations, and had a valid height and weight measured. Overweight and obesity prevalence estimates are available for the 7 metro Denver counties, and for rural Prowers County. Estimates generated from the Colorado BMI Monitoring System may be linked with other data sources to identify contributory social and environmental factors.This feature layer represents childhood/youth obesity estimates only.DefinitionsCoverage: The total number of individuals in the BMI Monitoring System with a valid BMI divided by the total estimated population from the American Community Survey Population and Demographic Estimates produced by the US Census Bureau in the specified geographic area and age group.Obesity Children/Youth: BMI is calculated from height and weight and plotted on the Centers for Disease Control and Prevention (CDC) male or female BMI-for-age growth chart to determine a percentile. Obesity is defined as a BMI at the 95th percentile or higher.Obesity Prevalence Estimates: Percentage of individuals with obesity based upon the total number of individuals with obesity in the specified geographic area and age group divided by the total number of valid BMI measurements in the same specified geographic area and age group.

BMI data is obtained from each systems’ electronic health record and combined into one database managed by the Colorado Department of Public Health and Environment. These data represent individuals who presented for routine care at one of the participating health care organizations, and had a valid height and weight measured. Overweight and obesity prevalence estimates are available for the 7 metro Denver counties, and for rural Prowers County. Estimates generated from the Colorado BMI Monitoring System may be linked with other data sources to identify contributory social and environmental factors.This feature layer represents adult obesity estimates only.DefinitionsCoverage: The total number of individuals in the BMI Monitoring System with a valid BMI divided by the total estimated population from the American Community Survey Population and Demographic Estimates produced by the US Census Bureau in the specified geographic area and age group.Obesity Adults: Obesity is defined as a BMI, calculated from height and weight, of 30 kilograms per meter squared (kg/m2) or greater.Obesity Prevalence Estimates: Percentage of individuals with obesity based upon the total number of individuals with obesity in the specified geographic area and age group divided by the total number of valid BMI measurements in the same specified geographic area and age group.

"The poverty rate is one of several socioeconomic indicators used by policy makers to evaluate economic conditions. It measures the percentage of people whose income fell below the poverty threshold. Federal and state governments use such estimates to allocate funds to local funds to local communities. Local communities use these estimates to identify the number of individuals or families eligible for various programs. " Source: U.S. Census Bureau.The map shows the poverty ratio for states, counties, tracts and block groups, with the data source from the U.S. Census Bureau's American Community Survey (ACS) for 2013 for the previous 12 months. The percent of each Illinois county’s population that is considered obese from the 2015 CDC BRFSS Survey (Source, Lake County Illinois).

Quarterly sales of weight loss and anti-obesity drug Wegovy increased more than eightfold within only one year. The drug is manufactured by Danish biopharma company Novo Nordisk, primarily known for its focus on diabetes treatments. The most recent quarterly sales figure (Q4 2024) set a record at around 20 billion Danish kronor. Why Wegovy has blockbuster potential Wegovy and Novo Nordisk have been very present in the media lately, since the drug is expected to have huge potential in markets with large populations affected by overweight and obesity. In its latest report, the World Obesity Federation estimated the global population that is obese or overweight will increase from 2.6 billion individuals in 2020 to over four billion by 2035. The United States, which is the largest pharmaceutical market globally, is also one of the most obese countries in the world. It is estimated that more than 36 percent of adult Americans are obese. Thus, the preconditions for a drug like Wegovy are more than just a given. This is also reflected in Novo Nordisk's increasing share prices and a currently record-high market capitalization. The risks of weight loss drugs Wegovy seems to cut the risks of certain conditions that usually come with overweight and obesity, like stroke and heart attack. But of course, there are also risks that must be considered. The most common side effects of the drugs are nausea, dizziness, diarrhea, and vomiting. Doctors also warn that weight loss drugs like Wegovy can lead to serious complications for patients who need anesthesia for surgery when the stomach must be completely empty. There is an increased risk of pulmonary aspiration since these drugs slow down digestion. Another problem weight loss drugs can cause is that people, instead of changing their lifestyle and mostly out of convenience, immediately turn to such drugs.