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.

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.

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.

BackgroundFew studies have examined weight transitions in contemporary multi-ethnic populations spanning early childhood through adulthood despite the ability of such research to inform obesity prevention, control, and disparities reduction.Methods and ResultsWe characterized the ages at which African American, Caucasian, and Mexican American populations transitioned to overweight and obesity using contemporary and nationally representative cross-sectional National Health and Nutrition Examination Survey data (n = 21,220; aged 2–80 years). Age-, sex-, and race/ethnic-specific one-year net transition probabilities between body mass index-classified normal weight, overweight, and obesity were estimated using calibrated and validated Markov-type models that accommodated complex sampling. At age two, the obesity prevalence ranged from 7.3% in Caucasian males to 16.1% in Mexican American males. For all populations, estimated one-year overweight to obesity net transition probabilities peaked at age two and were highest for Mexican American males and African American females, for whom a net 12.3% (95% CI: 7.6%-17.0%) and 11.9% (95% CI: 8.5%-15.3%) of the overweight populations transitioned to obesity by age three, respectively. However, extrapolation to the 2010 U.S. population demonstrated that Mexican American males were the only population for whom net increases in obesity peaked during early childhood; age-specific net increases in obesity were approximately constant through the second decade of life for African Americans and Mexican American females and peaked at age 20 for Caucasians.ConclusionsAfrican American and Mexican American populations shoulder elevated rates of many obesity-associated chronic diseases and disparities in early transitions to obesity could further increase these inequalities if left unaddressed.

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

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/.

Geospatial data about Adult obesity rate (county), 2010. Export to CAD, GIS, PDF, CSV and access via API.

This driver measures the percentage of US citizens aged 18 and older who are considered obese based on their body mass index (BMI). Data is sourced from the Centers for Disease Control and Prevention (CDC).

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.

Non-communicable diseases (NCDs) such as cardiovascular disease and stroke are a major public health concern across Latin America. A key modifiable risk factor for NCDs is overweight and obesity highlighting the need for policy to reduce prevalence rates and ameliorate rising levels of NCDs. A cross-sectional regression analysis was used to project BMI and related disease trends to 2050. We tested the extent to which interventions that decrease body mass index (BMI) have an effect upon the number of incidence cases avoided for each disease. Without intervention obesity trends will continue to rise across much of Latin America. Effective interventions are necessary if rates of obesity and related diseases are to be reduced.

The global overweight-patient care system market is estimated to be valued at USD XXX million in 2025 and is projected to grow at a CAGR of XX% from 2025 to 2033. The increasing prevalence of obesity and overweight conditions worldwide is driving the growth of this market. As per the World Health Organization (WHO), in 2016, over 650 million adults were obese, and more than 1.9 billion were overweight. This increasing prevalence of obesity and overweight conditions has led to a growing demand for healthcare services specifically designed for overweight patients. The overweight-patient care system market is segmented based on application, type, and region. By application, the market is segmented into home, hospital, and others. By type, the market is segmented into 500-700 lbs weight capacity, 750-950 lbs weight capacity, and ≥1000 lbs weight capacity. By region, the market is segmented into North America, South America, Europe, Middle East & Africa, and Asia Pacific. North America is expected to hold the largest share of the market due to the high prevalence of obesity and overweight conditions in the region.

Proportion of children aged 4 to 5 years classified as 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 reception (aged 4 to 5 years) with a valid height and weight measured by the NCMP with a BMI classified as living with obesity or severe obesity (BMI on or above 95th centile of the UK90 growth reference).

Definition of denominator Number of children in reception (aged 4 to 5 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.

Data for cities, communities, and City of Los Angeles Council Districts were generated using a small area estimation method which combined the survey data with population benchmark data (2022 population estimates for Los Angeles County) and neighborhood characteristics data (e.g., U.S. Census Bureau, 2017-2021 American Community Survey 5-Year Estimates). Data for this indicator are based on self-reported height and weight. Body Mass Index (BMI) is calculated by dividing a person’s weight in kilograms by the square of their height in meters. Individuals with a BMI ≥ 30 are considered to have obesity. Note, while BMI can be helpful in screening for individuals with obesity or overweight, it does not measure how much body fat an individual has or provide any diagnostic information about their overall health.Obesity is associated with increased risk for heart disease, diabetes, and cancer. Cities and communities can help curb the current obesity epidemic by adopting policies that support healthy food retail and physical activity and improve access to preventive care services.For more information about the Community Health Profiles Data Initiative, please see the initiative homepage.

Title Childhood Obese and Overweight Estimates, NM Counties 2016 - NMCHILDOBESITY2017

Summary County level childhood overweight and obese estimates for 2016 in New Mexico. Most recent data known to be available on childhood obesity

Notes This 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.org

Source Data 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 Source Zgodic, 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 from The 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.html

GIS Data Layer prepared by EMcRae_NMCDC

Feature Service https://nmcdc.maps.arcgis.com/home/item.html?id=80da398a71c14539bfb7810b5d9d5a99

Alias Definition

region Region Nationally

state State (data set is NM only but national data is available upon request)

fips_num County FIPS

county County Name

rate Rate of Obesity

lower_ci Lower Confidence Interval

upper_ci Upper Confidence Interval

fipstxt County FIPS text

Geospatial data about Low income preschool obesity rate (% change), 2006 08 to 2009 11. Export to CAD, GIS, PDF, CSV and access via API.

The report on North America Obesity Management covers a summarized study of several factors supporting market growth, such as market size, market type, major regions, and end-user applications. The report enables customers to recognize key drivers that influence and govern the market.

The global market for overweight patient care systems is experiencing robust growth, driven by rising obesity rates worldwide and an increasing demand for specialized healthcare solutions. The market, currently valued at approximately $2.5 billion in 2025, is projected to exhibit a Compound Annual Growth Rate (CAGR) of 7% from 2025 to 2033. This expansion is fueled by several key factors, including technological advancements in bariatric equipment, a growing awareness of the health risks associated with obesity, and an increasing focus on patient safety and comfort during treatment and recovery. The aging global population also contributes significantly to market growth, as older adults are more prone to obesity-related health issues requiring specialized care. Major players like Stryker, Hill-Rom, and Invacare are driving innovation through the development of advanced, adaptable equipment designed to accommodate the specific needs of overweight patients. Segment-wise, the market is witnessing strong growth in areas like bariatric beds, patient lifts, and specialized wheelchairs. The increasing adoption of telehealth and remote patient monitoring solutions is also contributing to the overall market expansion. However, high initial investment costs for advanced equipment and the potential for reimbursement challenges in some healthcare systems pose constraints to market growth. Despite these hurdles, the long-term outlook for the overweight patient care system market remains positive, driven by sustained demand, technological innovation, and an expanding global healthcare infrastructure. Further geographic segmentation reveals strong growth in North America and Europe, fueled by robust healthcare spending and an established healthcare ecosystem, while emerging markets in Asia-Pacific are expected to exhibit high growth potential in the coming years.

BackgroundUnderstanding the social environmental around obesity has been limited by available data. One promising approach used to bridge similar gaps elsewhere is to use passively generated digital data.PurposeThis article explores the relationship between online social environment via web-based social networks and population obesity prevalence.MethodsWe performed a cross-sectional study using linear regression and cross validation to measure the relationship and predictive performance of user interests on the online social network Facebook to obesity prevalence in metros across the United States of America (USA) and neighborhoods within New York City (NYC). The outcomes, proportion of obese and/or overweight population in USA metros and NYC neighborhoods, were obtained via the Centers for Disease Control and Prevention Behavioral Risk Factor Surveillance and NYC EpiQuery systems. Predictors were geographically specific proportion of users with activity-related and sedentary-related interests on Facebook.ResultsHigher proportion of the population with activity-related interests on Facebook was associated with a significant 12.0% (95% Confidence Interval (CI) 11.9 to 12.1) lower predicted prevalence of obese and/or overweight people across USA metros and 7.2% (95% CI: 6.8 to 7.7) across NYC neighborhoods. Conversely, greater proportion of the population with interest in television was associated with higher prevalence of obese and/or overweight people of 3.9% (95% CI: 3.7 to 4.0) (USA) and 27.5% (95% CI: 27.1 to 27.9, significant) (NYC). For activity-interests and national obesity outcomes, the average root mean square prediction error from 10-fold cross validation was comparable to the average root mean square error of a model developed using the entire data set.ConclusionsActivity-related interests across the USA and sedentary-related interests across NYC were significantly associated with obesity prevalence. Further research is needed to understand how the online social environment relates to health outcomes and how it can be used to identify or target interventions.

Technological advancements in the North America Obesity Treatment industry are shaping the future market landscape. The report evaluates innovation-driven growth and how emerging technologies are transforming industry practices, offering a comprehensive outlook on future opportunities and market potential.

The global market for overweight-patient surgery devices is experiencing robust growth, driven by rising obesity rates worldwide and advancements in minimally invasive surgical techniques. The market, valued at approximately $5 billion in 2025, is projected to exhibit a compound annual growth rate (CAGR) of 5%, reaching an estimated $7 billion by 2033. This growth is fueled by several key factors. Increased awareness of the health risks associated with obesity is leading to a greater acceptance of bariatric surgery. Technological advancements in devices, such as the development of more precise and less invasive tools like implantable gastric stimulators and improved surgical staples, are enhancing surgical outcomes and patient satisfaction. Furthermore, the expansion of healthcare infrastructure in developing economies, coupled with rising disposable incomes in these regions, is creating new market opportunities. The market is segmented by device type (e.g., implantable gastric stimulators, surgical staples, gastric surgery clamps, trocars, sutures), application (hospitals, clinics, beauty institutions), and geography. North America currently holds a significant market share, driven by high obesity prevalence and advanced healthcare infrastructure. However, Asia-Pacific is expected to witness substantial growth due to the rapidly increasing number of obese individuals and rising healthcare spending. Competition in this space is fierce, with major players including Medtronic, Johnson & Johnson, and Intuitive Surgical constantly innovating and expanding their product portfolios. Despite this positive outlook, challenges remain. These include the high cost of procedures, potential complications associated with bariatric surgery, and regulatory hurdles in certain markets. Despite the challenges, the long-term outlook for the overweight-patient surgery device market remains optimistic. The ongoing development of less invasive procedures, coupled with the increasing prevalence of obesity, will continue to drive demand for these devices. The market is likely to see further consolidation, with larger players acquiring smaller companies to expand their product portfolios and market reach. Focus on improving patient outcomes, reducing complications, and developing cost-effective solutions will be critical for success in this dynamic market. Technological innovation, such as the development of robotic-assisted surgery and artificial intelligence-driven diagnostics, will significantly shape future market trends. Furthermore, the increasing emphasis on personalized medicine and preventative healthcare strategies will also influence the development and adoption of new devices and surgical techniques.