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.

From 2017 to March 2020, the obesity prevalence among Hispanic men was around ** percent. This statistic represents the obesity prevalence among adults aged 20 and older in the United States from 2017 to March 2020, sorted by gender and race/ethnicity.

Abstract The incidence of medical costs of obesity disproportionately falls on women and racial minorities. Prior research has shown that when employers provide health insurance coverage to workers, the additional healthcare costs associated with obesity are passed through to obese workers in the form of reduced wages, relative to their non-obese counterparts. However, estimation of a population-level wage penalty of obesity obscures substantial variation in the relative impact of these wage differences by race and gender. We partition the 1979 NLSY data by race and gender, and find that while the dollar-denominated wage penalty borne by obese workers with health insurance is borne predominantly by white women, these wage offsets disproportionately impact blacks and white women when modeled as a percentage of income. Upload includes data, R code, and write-up

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.

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.

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.

This dataset includes data on adult's diet, physical activity, and weight status from Behavioral Risk Factor Surveillance System. 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. I was particularly curious on whether socioeconomic status has an impact on obesity. In my analysis, I compare the obesity rate in each state, and then perform a linear regression on the obesity rate for each educational status and the income bracket.

This statistic shows the results of a survey among American high school students in grades 9 to 12 on obesity in 2017, by gender and ethnicity. About 22.2 percent of male student respondents with a Hispanic background stated they are obese.

Yearly citation counts for the publication titled "Differences in Obesity Prevalence by Demographics and Urbanization in US Children and Adolescents, 2013-2016".

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

BMI, body mass index; N, unweighted number; IQR, interquartile range.

These data represent the predicted (modeled) prevalence of being Obese among adults (Age 18+) for each census tract in Colorado. Obese is defined as a BMI of 30 or greater. BMI is calculated from self-reported height and weight.The estimate for each census tract represents an average that was derived from multiple years of Colorado Behavioral Risk Factor Surveillance System data (2014-2017).CDPHE used a model-based approach to measure the relationship between age, race, gender, poverty, education, location and health conditions or risk behavior indicators and applied this relationship to predict the number of persons' who have the health conditions or risk behavior for each census tract in Colorado. We then applied these probabilities, based on demographic stratification, to the 2013-2017 American Community Survey population estimates and determined the percentage of adults with the health conditions or risk behavior for each census tract in Colorado.The estimates are based on statistical models and are not direct survey estimates. Using the best available data, CDPHE was able to model census tract estimates based on demographic data and background knowledge about the distribution of specific health conditions and risk behaviors.The estimates are displayed in both the map and data table using point estimate values for each census tract and displayed using a Quintile range. The high and low value for each color on the map is calculated based on dividing the total number of census tracts in Colorado (1249) into five groups based on the total range of estimates for all Colorado census tracts. Each Quintile range represents roughly 20% of the census tracts in Colorado. No estimates are provided for census tracts with a known population of less than 50. These census tracts are displayed in the map as "No Est, Pop < 50."No estimates are provided for 7 census tracts with a known population of less than 50 or for the 2 census tracts that exclusively contain a federal correctional institution as 100% of their population. These 9 census tracts are displayed in the map as "No Estimate."

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

ObjectiveThe representativeness of participants is crucial to ensure external validity of clinical trials. We focused on the randomized clinical trials which assessed COVID-19 vaccines to assess the reporting of age, sex, gender identity, race, ethnicity, obesity, sexual orientation, and socioeconomic status in the results (description of the participants' characteristics, loss of follow-up, stratification of efficacy and safety results).MethodsWe searched the following databases for randomized clinical trials published before 1st February 2022: PubMed, Scopus, Web of Science, and Excerpta Medica. We included peer-reviewed articles written in English or Spanish. Four researchers used the Rayyan platform to filter citations, first reading the title and abstract, and then accessing the full text. Articles were excluded if both reviewers agreed, or if a third reviewer decided to discard them.ResultsSixty three articles were included, which assessed 20 different vaccines, mainly in phase 2 or 3. When describing the participants' characteristics, all the studies reported sex or gender, 73.0% race, ethnicity, 68.9% age groups, and 22.2% obesity. Only one article described the age of participants lost to follow-up. Efficacy results were stratified by age in 61.9%, sex or gender in 26.9%, race and/or, ethnicity in 9.5%, and obesity in 4.8% of the articles. Safety results were stratified by age in 41.0%, and by sex or gender in 7.9% of the analysis. Reporting of gender identity, sexual orientation or socioeconomic status of participants was rare. Parity was reached in 49.2% of the studies, and sex-specific outcomes were mentioned in 22.9% of the analysis, most of the latter were related to females' health.ConclusionsAxes of social inequity other than age and sex were hardly reported in randomized clinical trials that assessed COVID-19 vaccines. This undermines their representativeness and external validity and sustains health inequities.

This dataset provides an estimate of the percentage of adult respondents ages 18+ who had a body mass index (BMI) of 30 or above by zip code as well as an estimate of the population ages 18+ residing in that zip code. The estimates covered are from the years 2013-2014. Information like this may be useful for studying obesity rates across zip codes of different demographics.Spatial Extent: Los Angeles Spatial Unit: Zip Code Created: 2018 Updated: n/a Source: California Health Interview SurveySurvey Contact Telephone: 310-794-0909 Contact Email: dacchpr@ucla.edu Source Link: https://askchisne.ucla.edu/ask/_layouts/ne/dashboard.aspx#/API Source Link: https://www.arcgis.com/home/item.html?id=342a05f149004bb0ab43eb976682beba

Pseudo panel by gender, education and race/ethnicity

From 2017 to March 2020, the prevalence of obesity among children and adolecents aged 2 to 19 years in the U.S. was highest among non-Hispanic black girls. This statistic shows the age-adjusted prevalence of obesity among U.S. children and adolecents from 2017 to March 2020, by gender and race/ethnicity.

BMI, body mass index; FPG, fasting plasma glucose; HOMA-IR, homeostasis model assessment of insulin resistance; HDL-C, high density lipoprotein cholesterol; LDL-C, low density lipoprotein cholesterol; TC, total cholesterol; TG, triglycerides.Results are presented as coefficients of correlation (r) with respective P-value through partial correlation analysis after adjusting for age, sex, and BMI overall, and after adjusting for age and BMI in boys and girls separately.*indicates significant correlation. (P<0.05).

Network of 46 papers and 64 citation links related to "Differences in Obesity Prevalence by Demographics and Urbanization in US Children and Adolescents, 2013-2016".

ObjectiveThis study investigates the association between phenotypic age acceleration (PAA) and all-cause and cause-specific mortality in obese individuals.MethodsData were drawn from the National Health and Nutrition Examination Survey (NHANES) between 1999 and 2018, including 9,925 obese adults (BMI ≥ 30 kg/m2). PAA, defined as phenotypic age exceeding chronological age, was assessed using clinical biomarkers. Kaplan-Meier survival analysis and Cox proportional hazards models were used to assess the relationship between PAA and all-cause, cardiovascular, and cancer mortality, adjusting for covariates such as age, gender, race, lifestyle, and health status. Subgroup and sensitivity analyses were performed to ensure the robustness of the findings.ResultsDuring a median follow-up of 10.6 years, 1,537 deaths were recorded, including 419 from cardiovascular disease and 357 from cancer. PAA was significantly associated with all-cause mortality (HR = 1.84, 95% CI: 1.64–2.06), cardiovascular mortality (HR = 1.86, 95% CI: 1.50–2.31), and cancer mortality (HR = 1.47, 95% CI: 1.17–1.85). These associations remained significant after adjusting for multiple variables, and sensitivity analyses confirmed the robustness of the results.ConclusionPAA is an independent predictor of all-cause, cardiovascular, and cancer mortality in obese individuals. This study highlights the importance of PAA in mortality risk assessment and health management in the obese population.