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CDC Nutrition, Physical Activity, and Obesity - Legislation
This dataset contains policy data for 50 US states and DC from 2001 to 2017. Data include information related to state legislation and regulations on nutrition, physical activity, and obesity in settings such as early care and education centers, restaurants, schools, work places, and others. To identify individual bills, use the identifier ProvisionID. A bill or citation may appear more than once because it could apply to multiple health or policy topics, settings, or states. As of Q 2 2016, data include only enacted legislation.
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Nutrition, Physical Activity, and Obesity - Policy and Environmental Data
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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.
Nutrition, Physical Activity, and Obesity - Behavioral Risk Factor Surveillance System
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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.
Nutrition, Physical Activity, and Obesity - American Community Survey
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This dataset includes select data from the U.S. Census Bureau's American Community Survey (ACS) on the percent of adults who bike or walk to work. 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 ACS visit https://www.census.gov/programs-surveys/acs/.
Nutrition, Physical Activity, and Obesity - Youth Risk Behavior Surveillance System
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This dataset includes data on adolescent's diet, physical activity, and weight status from Youth Risk Behavior Surveillance System (YRBSS). 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 YRBSS visit https://www.cdc.gov/healthyyouth/data/yrbs/index.htm.
Nutrition, Physical Activity, and Obesity - National Survey of Children's Health (NSCH)
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This dataset includes select data from the National Survey of Children’s Health (NSCH) sponsored by the Maternal and Child Health Bureau of the Health Resources and Services Administration, an Agency in the U.S. Department of Health and Human Services. The dataset includes the percent of children who eat fruits and vegetables less than once a day, 1–5-year-olds who drink sugar sweetened beverages, and infants who are fed anything other than breastmilk of formula before they are 4 months old. 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 NSCH visit https://www.census.gov/programs-surveys/nsch.html.
Nutrition, Physical Activity, and Obesity - Women, Infant, and Child
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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.
(주)어메이징푸드솔루션 - 칼로리 섭취 관리용 저칼로리 레시피 데이터
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음식군에 대한 상위 분류를 기준으로 칼로리가 낮게 설정된 레시피 기반의 음식 데이터로 저칼로리 음식을 섭취할 필요가 있는 체중 조절을 요하는 환자에게 적용할 수 있다.
충청남도교육청 충남방과후학교지원센터 음식별칼로리
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이 데이터는 다양한 식품의 1회 제공량 기준 칼로리 정보를 담고 있는 영양 데이터입니다. 각 항목은 식품 고유 ID(ITM_ID), 식품명(ITM_NM), 그리고 해당 식품의 열량(CALORIE)으로 구성되어 있으며, 일상적으로 자주 섭취하는 음식들을 중심으로 정리되어 있습니다. 이 데이터는 식단 구성, 칼로리 조절, 영양 교육, 건강관리 앱 개발 등에 활용될 수 있으며, 특히 체중 관리나 당뇨병 등 질환 예방을 위한 식품 선택 시 유용한 참고 자료로 활용됩니다. 또한 식품별 중량과 열량을 함께 제공함으로써 보다 정확한 섭취량 조절이 가능하도록 돕습니다.
Urban Greenery and Body Mass Index
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The datasets include individual-level BMI in Phoenix, AZ and Portland, OR obtained from the state DMVs, greenery along walkable roads within 500, 1000, 1500, and 2000 network buffers, and covariates. This dataset is not publicly accessible because: EPA cannot release personally identifiable information regarding living individuals, according to the Privacy Act and the Freedom of Information Act (FOIA). This dataset contains information about human research subjects. Because there is potential to identify individual participants and disclose personal information, either alone or in combination with other datasets, individual level data are not appropriate to post for public access. Restricted access may be granted to authorized persons by contacting the party listed. It can be accessed through the following means: EnviroAtlas data can be assessed through https://www.epa.gov/enviroatlas Individual-level residential location and body mass index can be requested from state DMVs. Navteq street data can be assessed through EPA internal network by EPA Region. Format: Data used in this study include: 1) EnviroAtlas 1m landcover data (Raster) 2) EnviroAtlas metrics related to street greenery (Raster) 3) Boundaries of neighborhood extents (buffers) (Vector, polygon) 4) Navteq street dataset (Vector, polyline) 5) Individual residential addresses (CSV) and its geocoded points (Vector, point) 6) Individual-level body mass index (CSV) 7) EnviroAtlas Intersection Density of Walkable Roads (Raster) 8) EnviroAtlas Distance to a Park Entrance (Raster) 9) EnviroAtlas Percent Population below the Adjusted Threshold for Quality of Life (CSV) 10) EnviroAtlas Percent Population with Income Twice below the Poverty Level (CSV) 11) EnviroAtlas Percent Non-White Population (CSV) 12) Age and Sex. This dataset is associated with the following publication: Tsai, W., A.S. Davis, and L.E. Jackson. Associations between types of greenery along neighborhood roads and weight status in different climates. Urban Forestry & Urban Greening. Elsevier B.V., Amsterdam, NETHERLANDS, 41: 104-107, (2019).
Obesity in California, 2012 and 2013
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These data are from the 2013 California Dietary Practices Surveys (CDPS), 2012 California Teen Eating, Exercise and Nutrition Survey (CalTEENS), and 2013 California Children’s Healthy Eating and Exercise Practices Surveys (CalCHEEPS). These surveys have been discontinued. Adults, adolescents, and children (with parental assistance) were asked for their current height and weight, from which, body mass index (BMI) was calculated. For adults, a BMI of 30.0 and above is considered obese. For adolescents and children, obesity is defined as having a BMI at or above the 95th percentile, according to CDC growth charts. The California Dietary Practices Surveys (CDPS), the California Teen Eating, Exercise and Nutrition Survey (CalTEENS), and the California Children’s Healthy Eating and Exercise Practices Surveys (CalCHEEPS) (now discontinued) were the most extensive dietary and physical activity assessments of adults 18 years and older, adolescents 12 to 17, and children 6 to 11, respectively, in the state of California. CDPS and CalCHEEPS were administered biennially in odd years up through 2013 and CalTEENS was administered biennially in even years through 2014. The surveys were designed to monitor dietary trends, especially fruit and vegetable consumption, among Californias for evaluating their progress toward meeting the Dietary Guidelines for Americans and the Healthy People 2020 Objectives. All three surveys were conducted via telephone. Adult and adolescent data were collected using a list of participating CalFresh households and random digit dial, and child data were collected using only the list of CalFresh households. Older children (9-11) were the primary respondents with some parental assistance. For younger children (6-8), the primary respondent was parents. Data were oversampled for low-income and African American to provide greater sensitivity for analyzing trends among the target population. Wording of the question used for these analyses varied by survey (age group). The questions were worded are as follows: Adult:1) How tall are you without shoes?2) How much do you weigh?Adolescent:1) About how much do you weigh without shoes?2) About how tall are you without shoes? Child:1) How tall is [child's name] now without shoes on?2) How much does [child's name] weigh now without shoes on?