The datasets below have been archived and will not receive further updates, but remain available for reference. The up-to-date and more comprehensive Neighborhood Food Retail data is available and will be updated annually going forward. For those conducting analysis using this data, please be advised that the previous methodology is vastly different from the more recent data, so it would not make sense to compare the two. This dataset is derived from the Walkable Access to Healthy Foods in Philadelphia, 2012-2014 report analyses.

FSIS’ FoodKeeper application educates users about food and beverages storage to help them maximize the freshness and quality of these items. By helping users understand food storage, the application empowers consumers to choose storage methods that extend the shelf life of their items. By doing so users will be able to keep items fresh longer than if they were not stored properly.

This dataset tracks the updates made on the dataset "Food Environment Atlas" as a repository for previous versions of the data and metadata.

This dataset tracks the updates made on the dataset "Child and Adult Care Food Program Participation" as a repository for previous versions of the data and metadata.

The data presented in this paper is used to examine the behavioral factors that influence the preferences of foods in Indonesia, and Indonesian audiences’ segmentation behind those preferences, provided by social media data. We collected the data through an online platform by performing a query search on Facebook Audience Insights Interests. The keywords that we use in the question quest are based on the United Nations Food and Agriculture Organisation (FAO) Food Balance Sheet (FBS) which is retrieved from FAOStat in May 2020. The data was gathered between 15 May and 2 July 2020. With a sample size of 100-150 million viewers or about 36.95 per cent-55.43 per cent of Indonesia 's 2019 population, we limited our sample to Indonesia. The dataset is made up of ten tables that can be separately analyzed. For each table, we carry out exploratory data analysis (EDA) to provide more insights. Such data could be of interest to various fields, including food scientists, government and policymakers, data scientists/analysts, and marketers. This data could also be the complementary source for the scarcity of food survey data from the government, particularly the behavioral aspects.

Date Accepted: 2022-06-14

This statistic shows the number of disposable food storage containers used within one month in the United States in 2020. The data has been calculated by Statista based on the U.S. Census data and Simmons National Consumer Survey (NHCS). According to this statistic, 22.73 million Americans used 6 or more containers of disposable food storage containers in 2020.

A database was compiled with the most frequently consumed foods in the Netherlands and their taste intensity relative to other available foods Smaak, Vet en Textuur database - smaakwaarden Nederlandse Voedingsmiddelen Date Submitted: 2020-12-16

In the Chinese Food Life Cycle Assessment Database (CFLCAD), Greenhouse Gas Emissions (GHGE) for 80 food items, Water Use (WU) for 93 food items and Land Use (LU) for 50 food items are collected through a literature review. The CFLCAD applies conversion factors for the edible portion of food, food loss ratio and processing, storage, packaging, transportation, and food preparation stages to estimate the environmental footprints of food from production to consumption. Similar food groups and recipes are used to match those food items without LCA value in the Chinese food composition table, resulting in a total of 17 food groups in the database. Date Submitted: 2022-01-26

This statistic shows the brands of disposable food storage containers used most often in the United States in 2020. The data has been calculated by Statista based on the U.S. Census data and Simmons National Consumer Survey (NHCS). According to this statistic, 75.28 million Americans used Ziploc in 2020.

Human societies have always faced temporal and spatial fluctuations in food availability. The length of time that food remains edible and nutritious depends on temperature, moisture, and other factors that affect the growth rates of organisms that cause spoilage. Some storage techniques, such as drying, salting, and smoking, date back to ancient hunter–gatherer and early agricultural societies and use relatively low energy inputs. Newer technologies developed since the industrial revolution, such as canning and compressed-gas refrigeration, require much greater energy inputs. Coincident with the development of storage technologies, the transportation of food helped to overcome spatial and temporal fluctuations in productivity, culminating in today's global transport system, which delivers fresh and preserved foods worldwide. Because most contemporary humans rely on energy-intensive technologies for storing and transporting food, there are formidable challenges for feeding a growing and increasingly urbanized global population as finite supplies of fossil fuels rapidly deplete.

This statistic shows the usage of disposable food storage containers in the United States from 2011 to 2020 and a forecast thereof until 2024. The data has been calculated by Statista based on the U.S. Census data and Simmons National Consumer Survey (NHCS). According to this statistic, 199.52 million Americans used disposable food storage containers in 2020. This figure is projected to increase to 205.25 million in 2024.

This database contains historical information about CDRH Advisory Committees and Panel meetings through 2008, including summaries and transcripts.

Food banks and food aid agencies help address food insecurity issues throughout the United States. This mission focused on understanding how critical infrastructure failures impact the function of food aid agencies and how the change in functioning changes food access. This research focused on five infrastructure systems -- transportation, electric power, communications, water, and the buildings or facilities utilized by food aid agencies to carry out their normal activities. The functioning of food aid agencies was broken down into three branches or domains that are critical for the operation of a food aid agencies. Specifically, food aid agencies need 1) people to help run the operation, 2) property or, more generally, a physical structure or structures, to house and conduct operations; 3) products or food stuffs to distribute. This mission includes five social science collections. The first two collections provide background on the planning and agenda for a focus group and the data collected from the focus group. The next three collections relate to an online survey of food aid agencies. These collections include the sample frame (a list of all active food aid agencies invited to participate in the survey), the primary (raw) data collected from the survey, and an example of a secondary (curated) dataset that focuses on critical infrastructure failures and changes in food aid agency functioning.

This dataset tracks the updates made on the dataset "Food Service Establishment: Last Inspection" as a repository for previous versions of the data and metadata.

[ARCHIVED] Community Counts data is retained for archival purposes only, such as research, reference and record-keeping. This data has not been maintained or updated. Users looking for the latest information should refer to Statistics Canada’s Census Program (https://www12.statcan.gc.ca/census-recensement/index-eng.cfm?MM=1) for the latest data, including detailed results about Nova Scotia. This table reports the monthly cost of a nutritious diet. Geographies available: district health authorities

[Note: Integrated as part of FoodData Central, April 2019.] The USDA Branded Food Products Database is the result of a Public-Private Partnership, whose goal is to enhance public health and the sharing of open data by complementing USDA Food Composition Databases with nutrient composition of branded foods and private label data provided by the food industry. Members of the Public-Private Partnership include: Agricultural Research Service (ARS), USDA (www.ars.usda.gov) Institute for the Advancement of Food and Nutrition Sciences (IAFNS) (www.iafns.org) GS1 US (www.gs1us.org/) 1WorldSync (www.1worldsync.com) Label Insight (www.labelinsight.com) University of Maryland, Joint Institute for Food Safety and Applied Nutrition (jifsan.umd.edu) The BFPDB includes: product name and generic descriptor, serving size in grams or milliliters, nutrients on the Nutrition Facts Panel per serving size and 100 gram-basis, 100 ml-basis, or fluid oz-basis, ingredient list, (never before captured by USDA), and date stamp associated with most current product formulation. All data will be archived, allowing for dietary trends tracking. The BFPDB allows: dietitians to provide specific dietary guidance; researchers to better link dietary intakes to disease measures; and policy makers to develop guidance which promotes public health. New in this August 2018 release are downloadable database files (ASCII .csv and MS Access), Application Programming Interface (API), and Documentation and Download User Guide.

Subscribers can find out export and import data of 23 countries by HS code or product’s name. This demo is helpful for market analysis.

Estimates of daily activity and consequent demand for food during winter are scarce for many polar seabirds, yet essential for assessing constraints on foraging effort, demand for food, and potential competition with local fisheries. We affixed archival temperature tags to gentoo penguins (Pygoscelis papua) from two colonies in the South Shetland Islands to measure the frequency, timing, and duration of foraging trips and to estimate minimum food requirements during winter. Foraging trip frequencies ranged from 0.85 to 1.0 trips day-1 and were positively correlated with day length. Early winter foraging trips more closely matched day length than late winter foraging trips. The data suggest that individuals maximize foraging time during the early winter period, likely to recover body mass following the breeding season and molt. The more attenuated response of foraging trip durations to increasing day length in late winter may be related to differences in local resource availability or individual behaviors prior to the upcoming breeding season. Minimum food requirements also exhibited a seasonal cycle with a mid-winter minimum. On average, minimum food requirements were estimated at 0.70 ± 0.12 kg day-1. Extrapolated to the regional population of gentoo penguins, winter food requirements by gentoo penguins were equivalent to roughly 33% of annual krill catches by commercial fisheries in the South Shetland Island region over the past decade. Current expansion of the gentoo population and the krill fishery in the southern Scotia Sea warrants continued monitoring of gentoo penguins during winter.

Abstract copyright UK Data Service and data collection copyright owner.

Background:
A household food consumption and expenditure survey has been conducted each year in Great Britain (excluding Northern Ireland) since 1940. At that time the National Food Survey (NFS) covered a sample drawn solely from urban working-class households, but this was extended to a fully demographically representative sample in 1950. From 1957 onwards the Family Expenditure Survey (FES) provided information on all household expenditure patterns including food expenditure, with the NFS providing more detailed information on food consumption and expenditure. The NFS was extended to cover Northern Ireland from 1996 onwards. In April 2001 these surveys were combined to form the Expenditure and Food Survey (EFS), which completely replaced both series. From January 2008, the EFS became known as the Living Costs and Food (LCF) module of the Integrated Household Survey (IHS). As a consequence of this change, the questionnaire was altered to accommodate the insertion of a core set of questions, common to all of the separate modules which together comprised the IHS. Some of these core questions are simply questions which were previously asked in the same or a similar format on all of the IHS component surveys. For further information on the LCF questionnaire, see Volume A of the LCF 2008 User Guide, held with SN 6385. Further information about the LCF, including links to published reports based on the survey, may be found by searching for 'Living Costs and Food Survey' on the ONS website. Further information on the NFS and Living Costs and Food Module of the IHS can be found by searching for 'Family Food' on the GOV.UK website.

History:
The LCF (then EFS) was the result of more than two years' development work to bring together the FES and NFS; both survey series were well-established and important sources of information for government and the wider community, and had charted changes and patterns in spending and food consumption since the 1950s. Whilst the NFS and FES series are now finished, users should note that previous data from both series are still available from the UK Data Archive, under GNs 33071 (NFS) and 33057 (FES).

Purpose of the LCF
The Office for National Statistics (ONS) has overall project management and financial responsibility for the LCF, while the Department for Environment, Food and Rural Affairs (DEFRA) sponsors the food data element. As with the FES and NFS, the LCF continues to be primarily used to provide information for the Retail Prices Index, National Accounts estimates of household expenditure, analysis of the effect of taxes and benefits, and trends in nutrition. The results are multi-purpose, however, providing an invaluable supply of economic and social data. The merger of the two surveys also brings benefits for users, as a single survey on food expenditure removes the difficulties of reconciling data from two sources.

Design and methodology The design of the LCF is based on the old FES, although the use of new processing software by the data creators has resulted in a dataset which differs from the previous structure. The most significant change in terms of reporting expenditure, however, is the introduction of the European Standard Classification of Individual Consumption by Purpose (COICOP), in place of the codes previously used. An additional level of hierarchy has been developed to improve the mapping to the previous codes. The LCF was conducted on a financial year basis from 2001, then moved to a calendar year basis from January 2006 (to complement the IHS) until 2015-16, when the financial year survey was reinstated at the request of users. Therefore, whilst SN 5688 covers April 2005 - March 2006, SN 5986 covers January-December 2006. Subsequent years cover January-December until 2014. SN 8210 returns to the financial year survey and currently covers April 2015 - March 2016.

Northern Ireland sample
Users should note that, due to funding constraints, from January 2010 the Northern Ireland (NI) sample used for the LCF was reduced to a sample proportionate to the NI population relative to the UK.

Family Food database:
'Family Food' is an annual publication which provides detailed statistical information on purchased quantities, expenditure and nutrient intakes derived from both household and eating out food and drink. Data is collected for a sample of households in the United Kingdom using self-reported diaries of all purchases, including food eaten out, over a two week period. Where possible quantities are recorded in the diaries but otherwise estimated. Energy and nutrient intakes are calculated using standard nutrient composition data for each of some 500 types of food. Current estimates are based on data collected in the Family Food...