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.

This statistic depicts the average male body weight of U.S. adults aged 20 years and over from 1999 to 2016. According to the data, the average male body weight for those aged 40-59 years was ***** in 1999-2000 and increased to ***** as of 2015-2016.

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.

Data on normal weight, overweight, and obesity among adults aged 20 and over by selected population characteristics. Please refer to the PDF or Excel version of this table in the HUS 2019 Data Finder (https://www.cdc.gov/nchs/hus/contents2019.htm) for critical information about measures, definitions, and changes over time. SOURCE: NCHS, National Health and Nutrition Examination Survey. For more information on the National Health and Nutrition Examination Survey, see the corresponding Appendix entry at https://www.cdc.gov/nchs/data/hus/hus19-appendix-508.pdf.

This statistic depicts the average body weight of U.S. men aged 20 years and over from 1999 to 2016, by ethnicity. According to the data, the average male body weight for those that identified as non-Hispanic white has increased from 192.3 in 1999-2000 to 202.2 in 2015-2016.

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 2024, around 16 percent of U.S. women reported weighing 200 pounds or more. This statistic shows the average self-reported weight among U.S. women from 1990 to 2024.

This statistic depicts the average body weight of U.S. females aged 20 years and over from 1999 to 2016, by ethnicity. According to the data, the average female body weight for those that identified as non-Hispanic white has increased from ***** in ********* to ***** in *********.

Data on overweight and obesity among adults aged 20 and over in the United States, by selected characteristics, including sex, age, race, Hispanic origin, and poverty level. Data are from Health, United States. SOURCE: National Center for Health Statistics, National Health and Nutrition Examination Survey. Search, visualize, and download these and other estimates from over 120 health topics with the NCHS Data Query System (DQS), available from: https://www.cdc.gov/nchs/dataquery/index.htm.

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Weight Management Market Size 2025-2029

The weight management market size is forecast to increase by USD 114.79 billion at a CAGR of 10.9% between 2024 and 2029.

The market is driven by the growing obese population and rising demand for weight management services from developing economies. The increasing prevalence of obesity and related health issues globally presents a significant opportunity for market participants. However, marketing challenges associated with weight management products and services pose a significant hurdle. The stigma surrounding obesity and the perception that weight loss is a personal responsibility rather than a health issue create barriers to market penetration. Health insurance plays a pivotal role in covering costs, while fitness apps and mobile health apps enhance accessibility and tracking.
Companies seeking to capitalize on market opportunities must address these challenges through innovative marketing strategies, affordable pricing, and education initiatives to shift societal perceptions and increase accessibility to weight management services. By focusing on these areas, market participants can effectively navigate challenges and capitalize on the growing demand for weight management solutions. Innovative weight management solutions include waistline control, fitness equipment, surgical equipment, healthy dietary choices, and lifestyle changes.

What will be the Size of the Weight Management Market during the forecast period?

Explore in-depth regional segment analysis with market size data - historical 2019-2023 and forecasts 2025-2029 - in the full report.
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The market for weight management solutions continues to evolve, reflecting the complex and multifaceted nature of weight management and its applications across various sectors. Sleeve gastrectomy and adjustable gastric banding are among the surgical interventions, while anti-obesity medications and pharmacological interventions offer alternative approaches. The prevalence of metabolic syndrome and its associated health risks, including cardiovascular disease and type 2 diabetes, underscores the urgency for sustainable weight loss solutions. Mindful eating, nutrition education, and meal planning are essential components of health behavior modification, while physical fitness and regular exercise routines contribute to weight regain prevention. Fitness and recreational sports centers are offering a wide range of HIIT classes, and HIIT fitness videos are flooding the market.

Hormonal imbalance and stress management are also crucial factors in weight management. The industry is expected to grow by 5.3% annually, driven by the increasing prevalence of obesity and related health issues. For instance, a study showed that patients who underwent bariatric surgery experienced an average weight loss of 30% within the first year. Social media and the young population's hectic lifestyles have led to increased fast food consumption and weight-related health issues, necessitating preventive measures and weight management programs. Additionally, the complexity and cost of weight management solutions can deter potential customers, particularly in developing economies with limited resources.

How is this Weight Management Industry segmented?

The weight management industry research report provides comprehensive data (region-wise segment analysis), with forecasts and estimates in 'USD million' for the period 2025-2029, as well as historical data from 2019-2023 for the following segments.

Type

  Diet
  Equipment
  Services


Distribution Channel

  Offline
  Online


End-user

  Fitness centers and health clubs
  Commercial weight loss centers
  Online weight loss programs
  Slimming centers
  Others


Geography

  North America

    US
    Canada


  Europe

    France
    Germany
    Italy
    UK


  APAC

    China
    India
    Japan
    South Korea


  Rest of World (ROW)

By Type Insights

The Diet segment is estimated to witness significant growth during the forecast period. The market is driven by the growing concern over health issues related to visceral fat, weight fluctuation, and obesity. Obesity, characterized by a body mass index (BMI) of 30 or higher, affects over one-third of the global population. This condition can lead to various health complications, including high blood pressure, joint problems, diabetes, and insulin sensitivity issues. To combat these health concerns, weight loss programs focusing on calorie expenditure through diet and physical activity have gained popularity. Diets, specifically, dominate the market, as they offer a more sustainable approach to weight management. Nutritional counseling and micronutrient intake are essential components of effective weight loss programs, ensuring a balanced macronutrient and micronutrient intake. Obesity rates continue to rise, fueling

This statistic depicts the average body weight of U.S. females aged 20 years and over from 1999 to 2016, by age. According to the data, the average female body weight for those aged 40-59 years was 169.4 in 1999-2000 and increased to 176.4 as of 2015-2016.

This dataset tracks the updates made on the dataset "Normal weight, overweight, and obesity among adults aged 20 and over, by selected characteristics: United States" as a repository for previous versions of the data and metadata.

Data from a clustered randomized controlled trial of 12 Head Start Centers in San Antonio, Texas: !Míranos! Look at Us, We Are Healthy! (¡Míranos!)The prevalence of obesity remains high in American children aged 2-5 while one in three Head Start children is overweight or obese. The !Míranos! study was designed to test the efficacy of !Míranos!, an early childhood obesity prevention program, which promoted healthy growth in predominantly Latino children in Head Start. The Míranos! included center-based (policy changes, staff development, gross motor program, and nutrition education) and home-based (parent engagement/ education and home visits) interventions to address key enablers and barriers in obesity prevention in young children. In partnership with Head Start, the study team demonstrated the feasibility and acceptability of the proposed interventions to influence energy-balance-related behaviors favorably in Head Start children. Using a three-arm cluster randomized design, 21 Head Start centers in equal numbers wiere randomly assigned to one of three conditions: 1) a combined center- and home-based intervention, 2) center-based intervention only, or 3) control. The interventions were delivered during the academic year (an 8-month period). A total of 526 3-year-old children were enrolled in the study and followed prospectively one year post-intervention. Outcome data collection was conducted at baseline, immediate post-intervention, and 1-year follow-up and included height, weight, physical activity (PA), and sedentary behaviors by accelerometry, parent reports of sleep duration and TV watching time, gross motor development, dietary intakes, and food and activity preferences. Information on family background, parental weight, PA- and nutrition-related practices and behaviors, PA and nutrition policy and environment at center and home, intervention program costs, and treatment fidelity will also be collected. The study had three specific aims: 1) to test the efficacy of the !Míranos! intervention on healthy weight growth (primary outcome) in normal weight, overweight and obese children, 2) to test the impact of the !Míranos! intervention on children’s PA, sedentary behavior, sleep, and dietary behaviors (secondary outcomes), and 3) to evaluate the cost-effectiveness of the !Míranos! intervention. By targeting different levels of influence and in multiple settings, the !Míranos! showed great promise of developing long-term health habits that reduce the energy imbalance gap by targeting multiple energy-balance-related behaviors. The !Míranos! can be disseminated to various organized childcare settings since it is built on the Head Start program and its infrastructure—a gold standard in early childhood education, as well as current PA and nutrition recommendations for preschool children.

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.

Figure 7: Railroad Fuel Surcharges, North American Weight Average

Forecast: Chromite Ore Import Average Value, Gross Weight in the US 2023 - 2027 Discover more data with ReportLinker!

This dataset tracks the updates made on the dataset "DEV DQS Normal weight, overweight, and obesity among adults aged 20 and over, by selected characteristics: United States" as a repository for previous versions of the data and metadata.

This dataset tracks the updates made on the dataset "DQS Normal weight, overweight, and obesity among adults aged 20 and over, by selected characteristics: United States" as a repository for previous versions of the data and metadata.

Table 2 - Application of a transparent artificial intelligence algorithm for US adults in the obese category of weight

Objective and aimsIdentification of associations between the obese category of weight in the general US population will continue to advance our understanding of the condition and allow clinicians, providers, communities, families, and individuals make more informed decisions. This study aims to improve the prediction of the obese category of weight and investigate its relationships with factors, ultimately contributing to healthier lifestyle choices and timely management of obesity.MethodsQuestionnaires that included demographic, dietary, exercise and health information from the US National Health and Nutrition Examination Survey (NHANES 2017–2020) were utilized with BMI 30 or higher defined as obesity. A machine learning model, XGBoost predicted the obese category of weight and Shapely Additive Explanations (SHAP) visualized the various covariates and their feature importance. Model statistics including Area under the receiver operator curve (AUROC), sensitivity, specificity, positive predictive value, negative predictive value and feature properties such as gain, cover, and frequency were measured. SHAP explanations were created for transparent and interpretable analysis.ResultsThere were 6,146 adults (age > 18) that were included in the study with average age 58.39 (SD = 12.94) and 3122 (51%) females. The machine learning model had an Area under the receiver operator curve of 0.8295. The top four covariates include waist circumference (gain = 0.185), GGT (gain = 0.101), platelet count (gain = 0.059), AST (gain = 0.057), weight (gain = 0.049), HDL cholesterol (gain = 0.032), and ferritin (gain = 0.034).ConclusionIn conclusion, the utilization of machine learning models proves to be highly effective in accurately predicting the obese category of weight. By considering various factors such as demographic information, laboratory results, physical examination findings, and lifestyle factors, these models successfully identify crucial risk factors associated with the obese category of weight.