USDA’s Food Patterns Equivalents Database (FPED) converts the foods and beverages in the Food and Nutrient Database for Dietary Studies to the 37 USDA Food Patterns components. The FPED was formerly known as the MyPyramid Equivalents Database. The FPED serves as a unique research tool to evaluate food and beverage intakes of Americans with respect to the 2015-2020 Dietary Guidelines for Americans recommendations. The Food Patterns are measured as cup equivalents of Fruit, Vegetables, and Dairy; ounce equivalents of Grains and Protein Foods; teaspoon equivalents of Added Sugars; gram equivalents of Solid Fats and Oils; and the number of Alcoholic Drinks. In addition to the SAS datasets, the FPED release includes: (1) the Food Patterns Equivalents Ingredient Database (FPID) that includes the 37 USDA Food Patterns components per 100 grams of each unique ingredient used in the FNDDS; and (2) listings of gram weights for one cup equivalents of fruits, vegetables, dairy, and legumes used in the FPED. Resources in this dataset:Resource Title: Food Patterns Equivalents Database. File Name: Web Page, url: https://www.ars.usda.gov/northeast-area/beltsville-md-bhnrc/beltsville-human-nutrition-research-center/food-surveys-research-group/docs/fped-overview/ Food Patterns Equivalents Database (FPED) converts the foods and beverages in the Food and Nutrient Database for Dietary Studies to the 37 USDA Food Patterns components. The FPED serves as a unique research tool to evaluate food and beverage intakes of Americans with respect to the 2015-2020 Dietary Guidelines for Americans recommendations.

SuperTracker was an online tool offered by USDA (2011-2018) that helped users track diet, physical activity and weight. SuperTracker provided a personalized plan based on the 2015-2020 Dietary Guidelines for Americans for what you should eat and drink and guided users to making better choices. This dataset includes the SuperTracker source code (latest update April 2018), including: front end application, database schema, documentation, deployment scripts and a ReadMe.txt file that provides high level instructions for the source code. Database connection strings and actual data are not included. The full foods database spreadsheet is attached as well; these foods are based on the Food and Nutrient Database for Dietary Studies (FNDDS), and the Food Patterns Equivalents Database (FPED), both from the USDA/ARS Food Surveys Research Group.

It is important to note that the code is based on 2015-2020 Dietary Guidelines for Americans and will not be updated to reflect future guidance. In addition, the food database is based on FNDDS from 2011-2012 (FNDDS 6.0) and FPED from 2011-2012 and will not be updated with future data releases.

Graph and download economic data for SNAP Benefits Recipients in Ford County, KS (CBR20057KSA647NCEN) from 1989 to 2022 about Ford County, KS; KS; SNAP; nutrition; food stamps; benefits; food; and USA.

BackgroundWhile the intake of larger quantities of vegetables has been linked to a reduction in constipation risk, which vegetables in particular underlie this risk reduction remains incompletely understood. As such, the present study was developed to explore correlations between the intake of particular vegetable types and the risk of constipation.MethodsThis cross-sectional analysis was based on data from the National Health and Nutrition Examination Survey (NHANES) collected from 2005-2010. Classifications and intake assessments for different vegetables were assessed with the Food Patterns Equivalents Database (FPED), while stool frequency or stool consistency was used to define constipation. Relationships between the intake of particular vegetable components and constipation were assessed through a weighted logistic regression approach. Subgroup and restricted cubic spline (RCS) regression analyses were further employed to explore associations between specific vegetable subtypes and constipation.ResultsThis study included 13,860 eligible subjects, of whom 1,405 and 12,455 were respectively classified into the constipated and non-constipated groups. Following multivariate adjustment, the intake of non-starchy vegetables including orange, red, dark green, and other vegetables was found to be positively associated with a reduction in constipation risk. In contrast, constipation was unrelated to total starchy vegetable or potato intake. Tomatoes, in particular, were associated with a marked decrease in constipation risk (odds ratios: 0.80, 95% confidence interval: 0.71–0.91). These results were confirmed through RCS and subgroup analyses.ConclusionNon-starchy vegetables, particularly tomatoes, were found to be associated with a pronounced reduction in constipation risk, which was unaffected by the intake of potatoes or starchy vegetables.

Timeseries data from 'Ford Dry Lake, CA (2184)' (gov_usda_nrcs_scan_2184) _NCProperties=version=2,netcdf=4.8.1,hdf5=1.12.2 cdm_altitude_proxy=z cdm_data_type=TimeSeriesProfile cdm_profile_variables=time cdm_timeseries_variables=station,longitude,latitude contributor_email=askusda@usda.gov,feedback@axiomdatascience.com contributor_name=US Department of Agriculture (USDA),Axiom Data Science contributor_role=contributor,processor contributor_role_vocabulary=NERC contributor_url=https://www.usda.gov/,https://www.axiomdatascience.com Conventions=IOOS-1.2, CF-1.6, ACDD-1.3 defaultDataQuery=lwe_precipitation_rate_cm_time_sum_over_pt1h,relative_humidity_qc_agg,wind_speed_of_gust_qc_agg,wind_speed_of_gust,solar_irradiance_cm_time_mean_over_pt1h_qc_agg,lwe_thickness_of_precipitation_amount,solar_irradiance_cm_time_mean_over_pt1h,wind_speed,soil_salinity_qc_agg,wind_speed_qc_agg,lwe_thickness_of_precipitation_amount_qc_agg,soil_moisture_percent_qc_agg,wind_from_direction,air_temperature_qc_agg,wind_from_direction_qc_agg,soil_salinity,air_temperature,air_pressure_qc_agg,soil_temperature,soil_temperature_qc_agg,lwe_precipitation_rate_cm_time_sum_over_pt1h_qc_agg,z,soil_moisture_percent,time,relative_humidity,air_pressure&time>=max(time)-3days Easternmost_Easting=-115.09763 featureType=TimeSeriesProfile geospatial_lat_max=33.6547 geospatial_lat_min=33.6547 geospatial_lat_units=degrees_north geospatial_lon_max=-115.09763 geospatial_lon_min=-115.09763 geospatial_lon_units=degrees_east geospatial_vertical_max=0.0 geospatial_vertical_min=-1.02 geospatial_vertical_positive=up geospatial_vertical_units=m history=Downloaded from US Department of Agriculture (USDA) at https://wcc.sc.egov.usda.gov/nwcc/site?sitenum=2184 id=104379 infoUrl=https://sensors.ioos.us/#metadata/104379/station institution=Soil Climate Analysis Network (SCAN) naming_authority=com.axiomdatascience Northernmost_Northing=33.6547 platform=fixed platform_name=Ford Dry Lake, CA (2184) platform_vocabulary=http://mmisw.org/ont/ioos/platform processing_level=Level 2 references=https://wcc.sc.egov.usda.gov/nwcc/site?sitenum=2184,https://wcc.sc.egov.usda.gov/nwcc/site?sitenum=2184,https://admin.axds.co/PRISM%20Probabilistic%20PRISM%20Probabilistic-Spatial%20QC%20(PSQC)%20System%20Spatial%20QC%20(PSQC)%20System sourceUrl=https://wcc.sc.egov.usda.gov/nwcc/site?sitenum=2184 Southernmost_Northing=33.6547 standard_name_vocabulary=CF Standard Name Table v72 station_id=104379 time_coverage_end=2025-10-22T07:00:00Z time_coverage_start=2011-11-16T20:00:00Z Westernmost_Easting=-115.09763

Additional file 3: Table S3. Results of the paired t-test (P-values) between FPED and all FROH estimates.

Additional file 2: Table S2. Correlation matrix between FPED and all FROH estimates.

This dataset tracks annual free lunch eligibility from 2022 to 2023 for Ford Elementary School vs. Colorado and Littleton School District No. 6 In The County Of Arapahoe

This dataset tracks annual free lunch eligibility from 2000 to 2023 for Albert F Ford Middle School vs. Massachusetts and Acushnet School District

This dataset tracks annual free lunch eligibility from 1992 to 2023 for Ford Elementary School vs. California and West Contra Costa Unified School District

This dataset tracks annual reduced-price lunch eligibility from 2003 to 2023 for William Ford Elementary School vs. Michigan and Dearborn City School District

This dataset tracks annual free lunch eligibility from 2014 to 2023 for Ford Early Learning Center vs. Michigan and Ypsilanti Community Schools

This dataset tracks annual free lunch eligibility from 1992 to 2023 for Gerald R. Ford Elementary School vs. California and Desert Sands Unified School District

This dataset tracks annual free lunch eligibility from 2004 to 2023 for Ford Elementary School vs. Arizona and Tucson Unified District (4403)

This dataset tracks annual reduced-price lunch eligibility from 1999 to 2023 for Ford Elementary School vs. Texas and Conroe Independent School District

This dataset tracks annual reduced-price lunch eligibility from 2005 to 2023 for Ford Elementary School vs. Arizona and Tucson Unified District (4403)