In 2021, around ** percent of high school students in the state of West Virginia were obese, making it the state with the highest share of obese high school students that year. Colorado and Utah had the lowest obesity rates among students that year. The state with the highest share of obese adults West Virginia not only has the highest rate of obese high school students, it is also the U.S. state with the highest percentage of obese adults, which was about ** percent as of 2023. Obesity remains a growing problem in the United States, especially in the southern states. Body image among college students In the fall of 2024, just over half of U.S. college students (18 years and older) described their weight as “about the right weight”. Over ********* of the respondents stated that they were slightly overweight, while *** percent said they were very overweight. Furthermore, roughly ** percent of college students rated their health as very good, while just ****percent of this group rated their general health as poor.

About a fifth of Hispanic high school students in the United States were overweight between 2016 and 2017, making it the ethnic group with the highest percentage of overweight high school students. Female obesity rates were considerably higher than those of male students for the black and Hispanic groups during the measured period.

Overweight and obese U.S. adults

U.S. overweight rates in adults differed slightly from those of U.S. high school students in 2017. That year, the African American population had the highest overweight and obesity rates of any race or ethnicity, closely followed by American Indians/Alaska Natives and Hispanics. Over 73 percent of all African American adults in the country were either overweight or obese. In 2018, the highest rates of obesity among African Americans could be found in states, such as Mississippi, Arkansas, and Tennessee.

Overweight youth worldwide

Many children and adolescents in other countries, such as New Zealand, Greece, and Italy, also struggle with overweight and obesity. In New Zealand, for example, over forty percent of boys and girls, up to age 19, were overweight or obese in 2016. In the same year, less than ten percent of Indian children and teenagers were overweight.

Roughly 15 percent of U.S. high school students from grades 9 to 12, across all genders and ethnicities, were obese between 2016 and 2017. On average, African and Hispanic students struggled more with obesity than white students. Over 22 percent of male students with a Hispanic background were reported to be obese.

Prevalence among adults

Obesity is a growing problem among all age groups in the United States. Among American adults aged 20 and over, obesity rates have risen considerably since 1997. By 2018, roughly 12 percent more adults were obese, compared to 21 years earlier.

Fast food industry

Unhealthy ingredients, larger portions, and lower cost are some of the reasons why fast food easily leads to obesity in the United States. Between 2004 and 2018, U.S. consumer spending in quick-service restaurants has increased by approximately 37.5 percent. Examples of leading restaurant chains within this sector, in terms of company value, are McDonald’s, KFC, and Domino’s Pizza.

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. 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 or go to the "About" tab.

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.

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." https://health.maryland.gov/pophealth/Documents/SHIP/SHIP%20Lite%20Data%20Details/Adolescents%20who%20have%20Obesity.pdf" > Link to Data Details

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.

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. 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 or go to the "About" tab.

This layered map shows the locations of Creating Healthy Places interventions that are targeted towards children and the percentage of students (elementary, middle, and high school) who are obese (95th percentile or higher) by county (source: Student Weight Status Category Reporting System). The purpose of the Creating Healthy Places initiative is to implement community level interventions to promote healthy lifestyles to prevent obesity and type 2 diabetes. The lighter shaded counties have a lower percentage of obese students. The darker shaded counties have a higher percentage of obese students. This map can help identify areas that could benefit from more community level and school level interventions like the ones implemented through the Creating Healthy Places Initiative. The "About" tab contains additional details concerning this dataset.

Graph and download economic data for Expenditures: Fats and Oils by Highest Education: Less Than College Graduate: High School Graduate (CXUFATSOILSLB1404M) from 2012 to 2023 about no college, fat, secondary schooling, secondary, oil, education, expenditures, and USA.

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. 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 or go to the "About" tab.

These data were collected as part of the evaluation of the Healthy School Program (HSP), a program that provides support to elementary, middle, and high schools in the United States as they work to create healthy school environments that promote physical activity and healthy eating for students and staff. HSP was created in 2006 by the Alliance for a Healthier Generation with funding from the Robert Wood Johnson Foundation. The HSP evaluation addressed both process and impact outcomes: Is the HSP technical assistance and training model effective in increasing the implementation of policies and programs that promote and provide access to healthier foods and more physical activity before, during and after school? Are there distinctive or common school-level characteristics that hasten or hinder school-level implementation of policies and programs that promote and provide access to healthy foods and physical activity in the school setting in HSP schools? Does participation in HSP contribute to an increase in healthy eating behaviors and physical activity participation among students? Does participation in HSP contribute to a decrease in body mass index (BMI) among students? The evaluation used a mixed-method design incorporating both quantitative and qualitative components. The quantitative component of the evaluation was a longitudinal design that measured student changes in eating and physical activity behaviors and BMI and schools' implementation of policies and practices promoted by HSP. For the qualitative component the evaluation team conducted site visits in a sample of HSP schools. Nine data files constitute this data collection: HSP Participation and Inventory Data File, 2006-2011 (originally called the Inventory Data File) Pilot Student Survey Data File Pilot Student Height and Weight Measurements Data File Survey of Students in Boston and Miami-Dade Public Schools Data File HSP Participation and Inventory Data File, 2006-2014 Arizona, Prince George's County and Nevada Healthy Schools Youth Survey Data File Arizona and Prince George's County Youth Height and Weight Measurements Data File Arizona Academic Achievement Data File Prince George's County School Wellness Coordinator Survey Data File Dataset 1 contains data on school characteristics, HSP engagement indicators, baseline and follow-up responses to the Healthy Schools Inventory, and indices derived from the Inventory for all HSP schools as of August 2011. The Inventory collected information about each school's adherence to the Healthy Schools Program Framework, a set of best practice guidelines that promote physical activity and healthy eating among students and staff. Datasets 2, 4 and 6 contain data from baseline and follow-up administrations of the Healthy Schools Youth Survey questionnaire in three samples of HSP schools: students in grades 5-12 in the initial pilot cohort of HSP schools; students in grades 5, 8 and 10 in the 2007-2008 cohort of HSP schools in Boston, Massachusetts and Miami-Dade County, Florida; and students in grades 5, 8 and 10 or 11 in HSP schools in Arizona, Nevada and Prince George's County, Maryland. Topics covered by the Healthy Schools Youth Survey questionnaire include eating and physical activity habits, attitudes about healthy eating and physical activity, health knowledge, and school food environments. Datasets 3 and 7 contain baseline and follow-up height and weight measurements and derived BMIs, the former for students in grades 4-12 in schools sampled by the Pilot Student Survey and the latter for students in grades 5, 8, and 10 in Arizona and grades 1-12 in Prince George's County in schools sampled by the Arizona, Prince George's County and Nevada Healthy Schools Youth Survey. Dataset 5 is an update to Dataset 1. Like Dataset 1 it contains data on HSP participation and engagement and school characteristics. Dataset 5 covers 8,500 schools that participated in HSP through fall 2014. It includes 4,028 of the 4,542 schools in Dataset 1. Dataset 8 contains average math, reading and language scores for grades in HSP and comparable non-HSP schools in Arizona. Every record in the data file represents a grade (one or more of the grades 2-9) within a school (150 schools) for a given school year (up to seven years 2007-2008 to 2013-2014). Dataset 9 contains data from a survey of HSP scho

ObjectivesHerbal medicine (HM) is widely used to treat obesity in adolescents worldwide since the currently available interventions have low compliance and lack long-term effects and safety data. This study aimed to analyze the factors affecting HM use for weight loss in overweight and obese adolescents.MethodsA total of 46,336 adolescents were included in this cross-sectional study based on the Korea Youth Risk Behavior Web-Based Survey. Three models of HM use for weigh loss were developed by sequentially adding predisposing, enabling, and need factors according to Andersen's model using multiple logistic regression analyses considering the complex sampling design.ResultsMale and female high school students and students from low perceived household economic status were less likely to use HM for weight loss. Students whose fathers had a college degree or higher, depressed mood, and two or more chronic allergic diseases were more likely to use HM. Male students who perceived their body image as fat or very fat tended to use HM less than those who perceived their body image as very thin, thin, or moderate. Obese female students tended to use HM more than overweight female students.ConclusionThese results can be used as the bases to promote HM use, provide ideas for future research, and strengthen the health insurance coverage extension for weight loss interventions.

In 2022, the U.S. states with the highest rates of obesity among women were Tennessee, Louisiana, and Mississippi. At that time, almost ** percent of women in Tennessee were considered obese. The states with the highest rates of obesity among men are West Virginia, Arkansas, and Oklahoma. Obesity: Women vs. men As of 2023, women in the United States had slightly higher rates of obesity than men. At that time, around **** percent of women were considered obese, compared to **** percent of men. Rates of obesity among both men and women are higher in the United States than any other OECD country, with high-calorie diets, often from fast food and sugary drinks, and large food portion sizes being partly to blame. In 2024, the mean self-reported weight among men in the United States was *** pounds, while women reported weighing an average of *** pounds. Which state is the most obese? As of 2023, West Virginia had the highest prevalence of adult obesity in the United States, with around ** percent of the population considered obese. Following West Virginia, Mississippi, Arkansas, and Louisiana, had some of the highest rates of obesity in the country. Colorado had the lowest share of adults who were obese at that time, but still, ********* of adults in the state were obese. West Virginia is also the state with the highest prevalence of obesity among high school students, with ** percent of high schoolers considered obese in 2021. Obesity in childhood is associated with obesity as adults, as well as mental health problems such as anxiety and depression.

BackgroundThere is a strong association between lifestyle behavior and health status. While young adulthood is a critical period for adopting and stabilizing lifelong healthy behavior, university life is independently associated with psychological stressors that may further affect health and well-being.ObjectiveThe present multidisciplinary study aimed to examine the health behavior of Austrian college and university students, differentiated based on diet types (vegan, vegetarian, and omnivorous) and physical activity (PA) habits.MethodsFollowing a cross-sectional study design, a total number of 6,148 students (65.3% females; 66.1% bachelor students, 67.0% from urban areas; mean age: 24.8 years) from 52 Austrian college/universities participated in an online survey and provided data on sociodemographic characteristics, dietary patterns, PA habits, and other lifestyle behavior characteristics, including alcohol intake and smoking.ResultsAcross the total sample, 74.0% had a normal weight (BMI = 18.5–25.0 kg/m2), while the prevalence of overweight/obesity (BMI ≥ 30.0 kg/m2) was lower in females than males and more in rural than urban students (p 

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. 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 or go to the "About" tab.

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) at school entry (pre-kindergarten or kindergarten) and in grades 2, 4, 7 and 10 for students attending all public schools outside of the five boroughs of New York City.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). Variables representing the number of students on which the percentages are based are also included.

For more information check out http://www.health.ny.gov/prevention/obesity/, or go to the "About" tab.

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) at school entry (pre-kindergarten or kindergarten) and in grades 2, 4, 7 and 10 for students attending all public schools outside of the five boroughs of New York City.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). Variables representing the number of students on which the percentages are based are also included.

For more information check out http://www.health.ny.gov/prevention/obesity/, or go to the "About" tab.

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.

Nutrition literacy plays an important role in children's dietary habits and nutrition. This study aimed to analyse the status of nutrition literacy and its influencing factors amongst middle school students in Chongqing, China. “Nutrition literacy scale for middle school students in Chongqing” was used in 29 districts of Chongqing in September 2020. The scores of nutrition literacy and its' three sub-domains (functional, interactive and critical nutrition literacy) were divided into low and high groups based on their median scores. Binary logistic regression was used to measure the influencing factors of nutrition literacy. A total of 18,660 middle school students were included in this study. The median of nutrition literacy of middle school students was 61.68 (IQR = 14.37). Interactive nutrition literacy had the highest score (median = 70.00, IQR = 20.00), followed by functional nutrition literacy (median = 68.69, IQR = 14.14) and critical nutrition literacy (median = 45.83, IQR = 25.00). Students who were the minority (OR = 0.71, 95% CI = 0.637–0.785), in senior high school (OR = 0.51, 95% CI = 0.477–0.548), in rural areas (OR = 0.85, 95% CI = 0.790–0.911), receiving school meal support from the government (OR = 0.63, 95% CI = 0.591–0.664), with other caregivers' parenting (OR = 0.86, 95% CI = 0.805–0.914), with parents having a low level of education and with an abnormal BMI [thin (OR = 0.91, 95% CI = 0.837–0.990), overweight (OR = 0.87, 95% CI = 0.785–0.968), and obese (OR = 0.83, 95% CI = 0.767–0.902)] presented less probability of being a high level of nutrition literacy. Our results could assist public health authorities in developing strategies of nutrition literacy promotion for references and theoretical foundations.