The statistic depicts the share of participants in physical activity in the United States in 2018, by age group. During the survey, 42 percent of Millennial respondents in 2018 stated that they actively engaged in physical activities.

According to a study conducted at the end of 2023, China reported the highest physical activity participation among 22 countries studied worldwide. At that time, nearly ***** out of ten Chinese respondents said that they engaged in at least 150 minutes per week of moderate exercise.

During a survey in the United States in 2023, around ** percent of respondents stated that they exercised at least three times a week. In the same survey, some of the most popular physical activities in the U.S. were hiking, biking, and running.

This is a source dataset for a Let's Get Healthy California indicator at https://letsgethealthy.ca.gov/. This table displays the percentage of adults meeting Aerobic Physical Activity guidelines in California. It contains data for California only. The data are from the California Behavioral Risk Factor Surveillance Survey (BRFSS). The California BRFSS is an annual cross-sectional health-related telephone survey that collects data about California residents regarding their health-related risk behaviors, chronic health conditions, and use of preventive services. The BRFSS is conducted by the Public Health Survey Research Program of California State University, Sacramento under contract from CDPH. The column percentages are weighted to the 2010 California Department of Finance (DOF) population statistics. Population estimates were obtained from the CA DOF for age, race/ethnicity, and sex. Values may therefore differ from what has been published in the national BRFSS data tables by the Centers for Disease Control and Prevention (CDC) or other federal agencies.

Note:

Because this dataset has been used in a competition, we had to hide some of the data to prepare the test dataset for the competition. Thus, in the previous version of the dataset, only train.csv file is existed.

Content

This dataset represents 10 different physical poses that can be used to distinguish 5 exercises. The exercises are Push-up, Pull-up, Sit-up, Jumping Jack and Squat. For every exercise, 2 different classes have been used to represent the terminal positions of that exercise (e.g., “up” and “down” positions for push-ups).

Collection Process

About 500 videos of people doing the exercises have been used in order to collect this data. The videos are from Countix Dataset that contain the YouTube links of several human activity videos. Using a simple Python script, the videos of 5 different physical exercises are downloaded. From every video, at least 2 frames are manually extracted. The extracted frames represent the terminal positions of the exercise.

Processing Data

For every frame, MediaPipe framework is used for applying pose estimation, which detects the human skeleton of the person in the frame. The landmark model in MediaPipe Pose predicts the location of 33 pose landmarks (see figure below). Visit Mediapipe Pose Classification page for more details.

https://mediapipe.dev/images/mobile/pose_tracking_full_body_landmarks.png" alt="33 pose landmarks">

Explore this extensive dataset on daily exercise and fitness metrics, designed to provide valuable insights into individuals' exercise routines, health status, and fitness progress. With a rich collection of attributes, this dataset enables researchers, fitness enthusiasts, and health professionals to analyze and draw meaningful conclusions about exercise patterns and their impact on overall well-being.

Number and percentage of adults being moderately active or active during leisure time, by age group and sex.

In 2023, it was found that 22.4 percent of men in the United States participated in sports, exercise, and recreational activities daily, compared to only 19.9 percent of women. These statistics highlight a notable difference in the daily engagement of different genders in sporting activities. Other factors influencing this participation include socioeconomic status, age, disability, ethnicity, geography, personal interests, and societal expectations. These barriers can prevent individuals from having equal access to, and opportunities for, sport participation. What role does gender play in sports participation? Historically, many sports have been segregated by gender, with men and women participating in separate leagues and competitions. This segregation has led to a lack of opportunities for women and girls to participate in sports at the same level as men and boys. Additionally, societal attitudes and stereotypes about gender can discourage women and girls from participating in sports or limit their access to resources and support for their athletic pursuits. This often results in fewer women and girls participating in sports and a lack of representation of women and girls in leadership roles within the sports industry. However, in recent years, there has been an increased focus on promoting gender equality in sports and providing equal opportunities for men and women to participate in sports. This includes initiatives to increase funding and support for women's sports, as well as efforts to challenge gender stereotypes and discrimination in the athletic world. Impact of the COVID-19 pandemic on sports participation The COVID-19 pandemic led to many people spending more time at home due to lockdowns, remote work, and school closures. This resulted in many people having more time to engage in sports and other physical activities, as seen in the share of the U.S. population engaged in sports and exercise peaking in 2020. With gyms and sports facilities closed or with limited access, many people turned to home-based workouts and other activities. This included activities such as running, cycling, and strength training that could all be done at home with minimal equipment. Online classes and streaming services also saw an increase in usage during the pandemic, providing people with access to a wide range of workout options and fitness programs.

This dataset provides a detailed overview of gym members' exercise routines, physical attributes, and fitness metrics. It contains 973 samples of gym data, including key performance indicators such as heart rate, calories burned, and workout duration. Each entry also includes demographic data and experience levels, allowing for comprehensive analysis of fitness patterns, athlete progression, and health trends.

Key Features:

• Age: Age of the gym member.
• Gender: Gender of the gym member (Male or Female).
• Weight (kg): Member’s weight in kilograms.
• Height (m): Member’s height in meters.
• Max_BPM: Maximum heart rate (beats per minute) during workout sessions.
• Avg_BPM: Average heart rate during workout sessions.
• Resting_BPM: Heart rate at rest before workout.
• Session_Duration (hours): Duration of each workout session in hours.
• Calories_Burned: Total calories burned during each session.
• Workout_Type: Type of workout performed (e.g., Cardio, Strength, Yoga, HIIT).
• Fat_Percentage: Body fat percentage of the member.
• Water_Intake (liters): Daily water intake during workouts.
• Workout_Frequency (days/week): Number of workout sessions per week.
• Experience_Level: Level of experience, from beginner (1) to expert (3).
• BMI: Body Mass Index, calculated from height and weight.

This dataset is ideal for data scientists, health researchers, and fitness enthusiasts interested in studying exercise habits, modeling fitness progression, or analyzing the relationship between demographic and physiological data. With a wide range of variables, it offers insights into how different factors affect workout intensity, endurance, and overall health.

This dataset is from the 2013 California Dietary Practices Survey of Adults. This survey has been discontinued. Adults were asked a series of eight questions about their physical activity practices in the last month. These questions were borrowed from the Behavior Risk Factor Surveillance System. Data displayed in this table represent California adults who met the aerobic recommendation for physical activity, as defined by the 2008 U.S. Department of Health and Human Services Physical Activity Guidelines for Americans and Objectives 2.1 and 2.2 of Healthy People 2020. The California Dietary Practices Surveys (CDPS) (now discontinued) was the most extensive dietary and physical activity assessment of adults 18 years and older in the state of California. CDPS was designed in 1989 and was administered biennially in odd years up through 2013. The CDPS was designed to monitor dietary trends, especially fruit and vegetable consumption, among California adults for evaluating their progress toward meeting the 2010 Dietary Guidelines for Americans and the Healthy People 2020 Objectives. For the data in this table, adults were asked a series of eight questions about their physical activity practices in the last month. Questions included: 1) During the past month, other than your regular job, did you participate in any physical activities or exercise such as running, calisthenics, golf, gardening or walking for exercise? 2) What type of physical activity or exercise did you spend the most time doing during the past month? 3) How many times per week or per month did you take part n this activity during the past month? 4) And when you took part in this activity, for how many minutes or hours did you usually keep at it? 5) During the past month, how many times per week or per month did you do physical activities or exercises to strengthen your muscles? Questions 2, 3, and 4 were repeated to collect a second activity. Data were collected using a list of participating CalFresh households and random digit dial, approximately 1,400-1,500 adults (ages 18 and over) were interviewed via phone survey between the months of June and October. Demographic data included gender, age, ethnicity, education level, income, physical activity level, overweight status, and food stamp eligibility status. Data were oversampled for low-income adults to provide greater sensitivity for analyzing trends among our target population.

This dataset includes data on weight status for children aged 3 months to 4 years old from Women, Infant, and Children Participant and Program Characteristics (WIC-PC). 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 WIC-PC visit https://www.fns.usda.gov/wic/national-survey-wic-participants.

During a survey in the United States in 2024, almost **** of respondents stated that their favorite physical activity was exercising outdoors. In comparison, ***** percent of respondents said that playing golf was their favorite way of staying fit.

This statistical report presents information on obesity, physical activity and diet, drawn together from a variety of sources. The topics covered include: Obesity related hospital admissions. Prescription items for the treatment of obesity. Adult obesity prevalence. Childhood obesity prevalence. Physical activity levels among adults and children. Diet among adults and children, including trends in purchases, and consumption of food and drink and energy intake. Each section provides an overview of the key findings from these sources, as well as providing sources of further information and links to relevant documents and sources. Some of the data have been published previously by NHS Digital. A data visualisation tool at the link below allows users to select obesity related hospital admissions data for any Local Authority (as contained in Excel tables 3, 7 and 11 of this publication), along with time series data from 2013/14. Regional and national comparisons are also provided.

This dataset includes data on policy and environmental supports for physical activity, diet, and breastfeeding. 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.

ABSTRACT Introduction Outdoor sports can help people develop good living habits and improve people’s physical fitness. For this reason, it is very important to cultivate sports hobbies and analyze the factors of healthy sports. Objective To understand the factors that affect the healthy sports behavior of college students, we provide a reference for the relevant departments of the school and physical education teachers. Methods The thesis uses literature data method, questionnaire survey method and mathematical statistics method to analyze sports influencing factors with college students as the research object. Results The physical education method and the completeness of the facilities will affect the students’ interest in sports. Students from different family backgrounds have very different preferences for healthy sports. Conclusions The school environment and sports atmosphere are the main factors that constitute the school sports environment. College students’ cognition and understanding of healthy sports will affect their own sports situation. Level of evidence II; Therapeutic studies - investigation of treatment results.

The raw data on behavior and physical fitness. The behavior for sampling worker before joining WE is on sheet behavior 31 and 62 Then, we show all data for behavior and physical fitness.

Distribution of the household population by physical fitness classification, by sex and age group.