This statistic depicts the average body mass index (BMI) of U.S. adults aged 20 years and over as of 2016, by gender. According to the data, the average male BMI has increased from 27.8 in 1999-2000 to 29.1 as of 2015-2016.

This statistic depicts the average body mass index (BMI) of U.S. females aged 20 years and over from 1999 to 2016, by age. According to the data, the average female BMI for those aged 40-59 years was 29 in 1999-2000 and increased to 30.4 as of 2015-2016.

In 2022, men aged 55 to 64 years had an average body mass index (BMI) of 29 kg/m2 and women in the same age group had a BMI of 28.8 kg/m2, the highest mean BMI across all the age groups. Apart from individuals aged 16 to 24 years, every demographic in England had an average BMI which is classified as overweight.An increasing problem It is shown that the mean BMI of individuals for both men and women has been generally increasing year-on-year in England. The numbers show in England, as in the rest of the United Kingdom (UK), that the prevalence of obesity is an increasing health problem. The prevalence of obesity in women in England has increased by around nine percent since 2000, while for men the share of obesity has increased by six percent. Strain on the health service Being overweight increases the chances of developing serious health problems such as diabetes, heart disease and certain types of cancers. In the period 2019/20, England experienced over 10.7 thousand hospital admissions with a primary diagnosis of obesity, whereas in 2002/03 this figure was only 1,275 admissions. Furthermore, the number of bariatric surgeries taking place in England, particularly among women, has significantly increased over the last fifteen years. In 2019/20, over 5.4 thousand bariatric surgery procedures were performed on women and approximately 1.3 thousand were carried out on men.

In 2023, it was estimated that around 32 percent of men and 34 percent of women in the U.S. were obese. This statistic shows the percentage of adults in the United States who were obese in 2023, by gender.

RationaleObesity hypoventilation syndrome (OHS) is often underdiagnosed, with significant morbidity and mortality. Bicarbonate, as a surrogate of arterial carbon dioxide, has been proposed as a screening tool for OHS. Understanding the predictors of serum bicarbonate could provide insights into risk factors for OHS. We hypothesized that the bicarbonate levels would increase with an increase in body mass index (BMI), since the prevalence of OHS increases with obesity.MethodsWe used the TriNetX Research Network, an electronic health record database with de-identified clinical data from participating healthcare organizations across the United States, to identify 93,320 adults without pulmonary or advanced renal diseases who had serum bicarbonate and BMI measurements within 6 months of each other between 2017 and 2022. We used linear regression analysis to examine the associations between bicarbonate and BMI, age, and their interactions for the entire cohort and stratified by sex. We also applied a non-linear machine learning algorithm (XGBoost) to examine the relative importance of age, BMI, sex, race/ethnicity, and obstructive sleep apnea (OSA) status on bicarbonate.ResultsThis cohort population was 56% women and 72% white and 80% non-Hispanic individuals, with an average (SD) age of 49.4 (17.9) years and a BMI of 29.1 (6.1) kg/m2. The mean bicarbonate was 24.8 (2.8) mmol/L, with higher levels in men (mean 25.2 mmol/L) than in women (mean 24.4 mmol/L). We found a small negative association between bicarbonate and BMI, with an expected change of −0.03 mmol/L in bicarbonate for each 1 kg/m2 increase in BMI (p < 0.001), in the entire cohort and both sexes. We found sex differences in the bicarbonate trajectory with age, with women exhibiting lower bicarbonate values than men until age 50, after which the bicarbonate levels were modestly higher. The non-linear machine learning algorithm similarly revealed that age and sex played larger roles in determining bicarbonate levels than the BMI or OSA status.ConclusionContrary to our hypothesis, BMI is not associated with elevated bicarbonate levels, and age modifies the impact of sex on bicarbonate.

In 2024, the mean average weight reported by men was 195 pounds, while the mean average weight for women was 164 pounds. This statistic shows the mean self-reported weight among U.S. adults from 1990 to 2024, by gender, in pounds.

ObjectiveWe aimed to estimate trends in population-level adult body weight indicators in the 26 state capitals and the Federal District of Brazil.MethodsSelf-reported weight and height data of 572,437 adults were used to estimate the mean body mass index (BMI), and the prevalence of BMI categories ranging from underweight to morbid obesity, in Brazil’s state capitals and Federal District, from 2006 to 2016, by sex. All estimates were standardized by age.ResultsFrom 2006 to 2016, the main findings showed that: (i) the overall mean BMI increased from 25.4 kg/m2 to 26.3 kg/m2 in men, and from 24.5 kg/m2 to 25.8 kg/m2 in women; (ii) the overall prevalence of overweight increased from 48.1% to 57.5% in men, and from 37.8% to 48.2% in women; (iii) the overall prevalence of obesity increased from 11.7% to 18.1% in men, and from 12.1% to 18.8% in women; (iv) in general, the largest increases in overweight and obesity prevalence were found in state capitals located in the north, northeast, and central-west regions of Brazil; (v) the prevalence of severe obesity surpassed the prevalence of underweight in 22 and 9 state capitals among men and women, respectively; and (vi) the mean BMI trend was stable only in Vitória state capital in men.ConclusionsThe policies for preventing and treating obesity in Brazil over the past years were not able to halt the increase in obesity prevalence either in the state capitals or the Federal District. Thus, a revision of policies is warranted. Furthermore, although policies are necessary in all state capitals, our results suggest that policies are especially necessary in the north, northeast, and central-west regions’ state capitals, where, in general, the largest increases in overweight and obesity prevalence were experienced.

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.

Surveys in which U.S. adults report their current weight have shown that the share of those reporting they weigh 200 pounds or more has increased over the past few decades. In 2024, around 28 percent of respondents reported their weight as 200 pounds or more, compared to 15 percent in 1990. However, the same surveys show the share of respondents who report they are overweight has decreased compared to figures from 1990. What percentage of the U.S. population is obese? Obesity is an increasing problem in the United States that is expected to become worse in the coming decades. As of 2023, around one third of adults in the United States were considered obese. Obesity is slightly more prevalent among women in the United States, and rates of obesity differ greatly by region and state. For example, in West Virginia, around 41 percent of adults are obese, compared to 25 percent in Colorado. However, although Colorado is the state with the lowest prevalence of obesity among adults, a quarter of the adult population being obese is still shockingly high. The health impacts of being obese Obesity increases the risk of developing a number of health conditions including high blood pressure, heart disease, type 2 diabetes, and certain types of cancer. It is no coincidence that the states with the highest rates of hypertension are also among the states with the highest prevalence of obesity. West Virginia currently has the third highest rate of hypertension in the U.S. with 45 percent of adults with the condition. It is also no coincidence that as rates of obesity in the United States have increased so have rates of diabetes. As of 2022, around 8.4 percent of adults in the United States had been diagnosed with diabetes, compared to six percent in the year 2000. Obesity can be prevented through a healthy diet and regular exercise, which also increases overall health and longevity.

PurposeCurrent research has not extensively explored the correlation between Systemic Inflammatory Index (SII) and prostate-specific antibody (PSA) levels. This study aimed to investigate the relationship between the SII and PSA levels in American males aged > 40 years without prostate cancer.MethodsData were obtained from the 2003–2010 National Health and Nutrition Examination Survey (NHANES). Patients without complete SII or PSA data were excluded. Multiple linear regression models were used to investigate the possibility of a linear association between the SII and PSA levels. Fitted smoothed curves and threshold effect analyses were used to characterize the nonlinear relationships.ResultsThe study included 5982 male participants over the age of 40 years from the United States. The average SII (mean ± standard deviation) was 562.78 ± 355.60. The mean value of PSA was 1.85 ± 3.24. The results showed that SII exhibited a positive correlation with PSA (β = 0.0005, 95% CI: (0.0002, 0.0007)), and an interaction test indicated that the effects of age, body mass index, hypertension, and diabetes were not significant for this positive correlation between SII and PSA (all P > 0.05). We discovered an inverted U-shaped connection between the SII and PSA with a turning point (K) of 1168.18 by using a two-segment linear regression model. To the left of the turning point, there was a positive connection between SII and PSA (β = 0.0009,95% CI: (0.0006, 0.0012); P < 0.0001).ConclusionIn the population of men over 40 years old without prostate cancer, SII and PSA exhibited a non-linear relationship. Specifically, there was a positive correlation between SII and PSA levels when the SII value was < 1168.18.

The purpose of this data set was to compile body mass information for all mammals on Earth so that we could investigate the patterns of body mass seen across geographic and taxonomic space and evolutionary time. We were interested in the heritability of body size across taxonomic groups (How conserved is body mass within a genus, family, and order?), in the overall pattern of body mass across continents (Do the moments and other descriptive statistics remain the same across geographic space?), and over evolutionary time (How quickly did body mass patterns iterate on the patterns seen today? Were the Pleistocene extinctions size specific on each continent, and did these events coincide with the arrival of man?). These data are also part of a larger project that seeks to integrate body mass patterns across very diverse taxa (NCEAS Working Group on Body size in ecology and paleoecology: linking pattern and process across space, time and taxonomic scales). We began with the updated version of Wilson and Reeder’s (1993) taxonomic list of all known Recent mammals of the world (N = 4629 species) to which we added status, distribution, and body mass estimates compiled from the primary and secondary literature. Whenever possible, we used an average of male and female body mass, which was in turn averaged over multiple localities to arrive at our species body mass values. The sources are line referenced in the main data set, with the actual references appearing in a table within the metadata. Mammals have individual records for each continent they occur on. Please note that our data set is more than an amalgamation of smaller compilations. Although we relied heavily a data set for Chiroptera by K. E. Jones (N = 905), the CRC handbook of Mammalian Body Mass (N = 688), and a data set compiled for South America by P. Marquet (N = 505), these total less than half the records in the current database. The remainder are derived from more than 150 other sources (see reference table). Furthermore, we include a comprehensive late Pleistocene species assemblage for Africa, North and South America, and Australia (an additional 230 species). 'Late Pleistocene' is defined as approximately 11 ka for Africa, North and South America, and as 50 ka for Australia, because these times predate anthropogenic impacts on mammalian fauna. Estimates contained within this data set represent a generalized species value, averaged across gender and geographic space. Consequently, these data are not appropriate for asking population-level questions where the integration of body mass with specific environmental conditions is important. All extant orders of mammals are included, as well as several archaic groups (N = 4859 species). Because some species are found on more than one continent (particularly Chiroptera), there are 5731 entries.

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.

The purpose of this data set was to compile body mass information for all mammals on Earth so that we could investigate the patterns of body mass seen across geographic and taxonomic space and evolutionary time. We were interested in the heritability of body size across taxonomic groups (How conserved is body mass within a genus, family, and order?), in the overall pattern of body mass across continents (Do the moments and other descriptive statistics remain the same across geographic space?), and over evolutionary time (How quickly did body mass patterns iterate on the patterns seen today? Were the Pleistocene extinctions size specific on each continent, and did these events coincide with the arrival of man?). These data are also part of a larger project that seeks to integrate body mass patterns across very diverse taxa (NCEAS Working Group on Body size in ecology and paleoecology: linking pattern and process across space, time and taxonomic scales). We began with the updated version of Wilson and Reeder's (1993) taxonomic list of all known Recent mammals of the world (N = 4629 species) to which we added status, distribution, and body mass estimates compiled from the primary and secondary literature. Whenever possible, we used an average of male and female body mass, which was in turn averaged over multiple localities to arrive at our species body mass values. The sources are line referenced in the main data set, with the actual references appearing in a table within the metadata. Mammals have individual records for each continent they occur on. Please note that our data set is more than an amalgamation of smaller compilations. Although we relied heavily a data set for Chiroptera by K. E. Jones (N = 905), the CRC handbook of Mammalian Body Mass (N = 688), and a data set compiled for South America by P. Marquet (N = 505), these total less than half the records in the current database. The remainder are derived from more than 150 other sources (see reference table). Furthermore, we include a comprehensive late Pleistocene species assemblage for Africa, North and South America, and Australia (an additional 230 species). "Late Pleistocene" is defined as approximately 11 ka for Africa, North and South America, and as 50 ka for Australia, because these times predate anthropogenic impacts on mammalian fauna. Overall, the temporal coverage is from the late Pleistocene to present (ca. 45,000 ybp to present). Estimates contained within this data set represent a generalized species value, averaged across gender and geographic space. Consequently, these data are not appropriate for asking population-level questions where the integration of body mass with specific environmental conditions is important. All extant orders of mammals are included, as well as several archaic groups (N = 4859 species). Because some species are found on more than one continent (particularly Chiroptera), there are 5731 entries. We have body masses for the following: Artiodactyla (280 records), Bibymalagasia (2 records), Carnivora (393 records), Cetacea (75 records), Chiroptera (1071 records), Dasyuromorphia (67 records), Dermoptera (3 records), Didelphimorphia (68 records), Diprotodontia (127 records), Hydracoidea (5 records), Insectivora (234 records), Lagomorpha (53 records), Litopterna (2 records), Macroscelidea (14 records), Microbiotheria (1 record), Monotremata (7 records), Notoryctemorphia (1 record), Notoungulata (5 records), Paucituberculata (5 records), Peramelemorphia (24 records), Perissodactyla (47 records), Pholidota (8 records), Primates (276 records), Proboscidea (14 records), Rodentia (1425 records), Scandentia (15 records), Sirenia (6 records), Tubulidentata (1 record), and Xenarthra (75 records).

Data has undergone substantial data quality and assurance checking, though this is an on-going process. Histograms of the body masses of each order were produced, and values at the tails were double-checked for accuracy. When multiple sources of information were available for a species, or new sources encountered, we used those with higher sample sizes and gender-specific information.

Headers are given here as header name followed by more information such as measurement units or other basic descriptor. More information on the variable definitions can be found in Section B, variable information (at http://www.esapubs.org/archive/ecol/E084/094/metadata.htm). Continent (SA, NA, EA, insular, oceanic, AUS, AF), Status (extinct, historical, introduction, or extant), Order, Family, Genus, Species, Log Mass (grams), Combined Mass (grams), Reference.

The purpose of this data set was to compile body mass information for all mammals on Earth so that we could investigate the patterns of body mass seen across geographic and taxonomic space and evolutionary time. We were interested in the heritability of body size across taxonomic groups (How conserved is body mass within a genus, family, and order?), in the overall pattern of body mass across continents (Do the moments and other descriptive statistics remain the same across geographic space?), and over evolutionary time (How quickly did body mass patterns iterate on the patterns seen today? Were the Pleistocene extinctions size specific on each continent, and did these events coincide with the arrival of man?). These data are also part of a larger project that seeks to integrate body mass patterns across very diverse taxa (NCEAS Working Group on Body size in ecology and paleoecology: linking pattern and process across space, time and taxonomic scales). We began with the updated version of Wilson and Reeder's (1993) taxonomic list of all known Recent mammals of the world (N = 4629 species) to which we added status, distribution, and body mass estimates compiled from the primary and secondary literature. Whenever possible, we used an average of male and female body mass, which was in turn averaged over multiple localities to arrive at our species body mass values. The sources are line referenced in the main data set, with the actual references appearing in a table within the metadata. Mammals have individual records for each continent they occur on. Please note that our data set is more than an amalgamation of smaller compilations. Although we relied heavily a data set for Chiroptera by K. E. Jones (N = 905), the CRC handbook of Mammalian Body Mass (N = 688), and a data set compiled for South America by P. Marquet (N = 505), these total less than half the records in the current database. The remainder are derived from more than 150 other sources (see reference table). Furthermore, we include a comprehensive late Pleistocene species assemblage for Africa, North and South America, and Australia (an additional 230 species). "Late Pleistocene" is defined as approximately 11 ka for Africa, North and South America, and as 50 ka for Australia, because these times predate anthropogenic impacts on mammalian fauna. Estimates contained within this data set represent a generalized species value, averaged across gender and geographic space. Consequently, these data are not appropriate for asking population-level questions where the integration of body mass with specific environmental conditions is important. All extant orders of mammals are included, as well as several archaic groups (N = 4859 species). Because some species are found on more than one continent (particularly Chiroptera), there are 5731 entries. We have body masses for the following: Artiodactyla (280 records), Bibymalagasia (2 records), Carnivora (393 records), Cetacea (75 records), Chiroptera (1071 records), Dasyuromorphia (67 records), Dermoptera (3 records), Didelphimorphia (68 records), Diprotodontia (127 records), Hydracoidea (5 records), Insectivora (234 records), Lagomorpha (53 records), Litopterna (2 records), Macroscelidea (14 records), Microbiotheria (1 record), Monotremata (7 records), Notoryctemorphia (1 record), Notoungulata (5 records), Paucituberculata (5 records), Peramelemorphia (24 records), Perissodactyla (47 records), Pholidota (8 records), Primates (276 records), Proboscidea (14 records), Rodentia (1425 records), Scandentia (15 records), Sirenia (6 records), Tubulidentata (1 record), and Xenarthra (75 records).

Data has undergone substantial data quality and assurance checking, though this is an on-going process. Histograms of the body masses of each order were produced, and values at the tails were double-checked for accuracy. When multiple sources of information were available for a species, or new sources encountered, we used thosewith higher sample sizes and gender-specific information.Headers are given here as header name followed by more information such as measurement units or other basic descriptor. More information on the variable definitions can be found in Section B, variable information (at http://www.esapubs.org/archive/ecol/E084/094/metadata.htm). Continent (SA, NA, EA, insular, oceanic, AUS, AF), Status (extinct, historical, introduction, or extant), Order, Family, Genus, Species, Log Mass (grams), Combined Mass (grams), Reference.

ABSTRACT Objective To validate self-reported weight and height data for people living with HIV/AIDS. Methods This cross-sectional study involved 481 people living with HIV/AIDS seen at a reference unit in João Pessoa, state of Paraíba, Brazil, between September and December 2015, 99 (20.5%) of whom had their weight and height measured. The intraclass correlation coefficient was calculated to determine the relationship between the self-reported and measured weight, height and body mass index values, and linear regression analysis was used to generate equations to predict weight and height. It were significant p-value under 5% for statistic tests applied. Results In the sample with measured values, 57.6% of men, with a mean age of 44 years old and a mean income per capita equivalent to US$145.50, high correlations (r>0.90) between the self-reported and measured values for weight, height and body mass index were observed. The accuracy was 92.6%, and the Kappa coefficient was greater than 0.85. Women tended to underestimate weight and overestimate height. The men overestimated weight and underestimated height. The intraclass correlation coefficients were greater than 0.95. Conclusion The use of self-reported measures of weight, height and body mass index for nutritional assessment of people living with HIV/AIDS is valid and must be considered for similar populations when time and resources are limiting factors.

In 2024, around 40 percent of U.S. men reported weighing 200 pounds or more. This statistic shows the average self-reported weight among U.S. men from 1990 to 2024.

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.

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.

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.

Approximately half of all people in the Netherlands had a normal body weight in 2022, measured by the industry-standard Body Mass Index method. Men were more likely to be overweight than women, whereas more women than men were underweight. Interestingly, obesity was found more often among women, with approximately ** percent of Dutch females suffering from being severely overweight. Looking at the overall population, more than half of the Dutch inhabitants aged 20 years and older were overweight.

Weight issues vary between generations

Age groups in the Netherlands suffered from several different health problems related to weight and body image. A recent study found that obesity occured in more than ** percent of Dutch inhabitants aged 50 to 64 years old, whereas only * percent of Gen Z and millennials (aged 18 to 34 years old) were obese. When confronted with the question of how they perceive their own bodies, nearly ** percent of the Dutch millennials think they are overweight. This may have something to do with the omnipresence of unattainable beauty ideals on social media, often portrayed by fitgirl/boy influencers.

Global perspective

When looking at adults, the share of obesity in the Netherlands was quite close to the global average, being much lower than in the United States, Russia, or Iceland, to name but a few examples. In contrast, the prominence of underweight issues among Dutch youth was disproportionate in an international context. Nearly ** percent of Dutch ** and 15-year-old boys were underweight, which was more than in any other European country. the aforementioned negative body image may have been part of the cause for this frequency of underweight issues.