In the process of migrating data to the current DDL platform, datasets with a large number of variables required splitting into multiple spreadsheets. They should be reassembled by the user to understand the data fully. This is the second spreadsheet of two in the Feed The Future Interim Population-Based Assessment of Cambodia-Module E2, Non-food Expenditures Over Past 7 Days.

In the process of migrating data to the current DDL platform, datasets with a large number of variables required splitting into multiple spreadsheets. They should be reassembled by the user to understand the data fully. This is the fourth spreadsheet of five in the Feed The Future Interim Population-Based Assessment of Cambodia, Modules F-G, Hunger Scale and Women's Empowerment.

This dataset captures information about food shared with others during the 7 days before the survey from the first interim assessment of Feed the Future's population-based indicaors for the ZOI in Cambodia. It has 1019 rows and 14 columns. The ZOI is the Pursat, Battambang, Kampong Thom, and Siem Reap Provinces. The sampling design called for a two-stage cluster sample. In the first stage, 84 villages were selected; in the second stage, households were selected within each sampled village. The sampling of villages was stratified by province, with the number of villages in each stratum proportional to the population in the stratum and with villages selected with probability proportional to size, based on the 2013 Commune Database. The data is split into survey modules. Modules A through C includes location information, informed consent, and the household roster. Module D includes household characteristics. Module E is the expenditures module broken up into 8 different parts. Modules F and G include the hunger scale data and WEIA index data. Data in modules H and I include mother and child dietary diversity.

This dataset captures the non-food expenditures over the past 7 days for each household surveyed during the first interim assessment of Feed the Future’s population-based indicators for the ZOI in Cambodia. It has 1019 rows and 579 columns. The ZOI is the Pursat, Battambang, Kampong Thom, and Siem Reap Provinces. The sampling design called for a two-stage cluster sample. In the first stage, 84 villages were selected; in the second stage, households were selected within each sampled village. The sampling of villages was stratified by province, with the number of villages in each stratum proportional to the population in the stratum and with villages selected with probability proportional to size, based on the 2013 Commune Database. The data is split into survey modules. Modules A through C includes location information, informed consent, and the household roster. Module D includes household characteristics. Module E is the expenditures module broken up into 8 different parts. Modules F and G include the hunger scale data and WEIA index data. Data in modules H and I include mother and child dietary diversity. In the process of migrating data to the current DDL platform, datasets with a large number of variables required splitting into multiple spreadsheets. They should be reassembled by the user to understand the data fully.

Helping Address Rural Vulnerabilities and Ecosystem Stability (Cambodia-HARVEST) was a five-year program (2011-2016) supported under the Global Hunger and Food Security Initiative (GHFSI) and the Global Climate Change (GCC) and Biodiversity program. Cambodia-HARVEST set strategic goals to improve food security, strengthen natural resource management and resilience to climate change, and increase the capacity of the public and private sectors and civil society to support agricultural competitiveness. Implemented in four targeted provinces of Cambodia -- Kampong Thom, Siem Reap, Pursat, and Battambang -- Cambodia-HARVEST had five major components: Agribusiness Value Chains; Aquaculture and Fisheries; Natural Resource Management; Biodiversity, and Climate Change, Social Inclusion, Business Development Services; and Capacity Development. Cambodia-Harvest worked with local partners and government to initiate policy reforms and eliminate obstacles to development. This data asset enables the evaluation of the program. It is comprised of a baseline, endline and community level survey. This is the endline survey.

Feed the Future Zambia Interim Survey in the Zone of Infuence: This dataset (n=13,203, vars=111) is the second of two datasets needed to calculate the WEAI-related measures. It includes the 24-hour time allocation data from Module G6, the time use module, and thus each respondent on Module G has multiple records, one for each of the 18 time use activities (13,301 records divided by 18 activities = 739 Module G respondents with time use data in the file.)

충청남도_로컬푸드 연계형 학교급식지원 견적등록 현재 현황으로 견적일, 입력일시, 수정일시, 상세 식품명 등의 정보를 제공합니다.

Feed the Future Nepal Interim Survey in the Zone of Influence: This dataset (n=800, var=163) is the first of two datasets needed to calculate the WEAI-related measures. It is a household-level file and contains the records for Module G data from the primary adult (18+) female decisionmaker within each household (for the sub-sample of households with a primary adult female decisionmaker).

본 데이터는 2025년 기준 고창군 읍·면별 영양플러스사업 수혜인원 현황을 집계한 자료로, 각 행정구역별 영양플러스사업 수혜 규모를 파악할 수 있도록 제공됩니다. 데이터는 읍·면 단위로 영양플러스사업에 참여하는 수혜 인원 수를 기준으로 구성되어 있으며, 지역별 영양지원 수요 분석 및 모자보건 정책 수립을 위한 기초자료로 활용할 수 있습니다.데이터 구성은 연번, 행정동, 영양플러스사업 수혜인원 항목으로 이루어져 있으며, 행정구역별 수혜 인원 현황을 확인할 수 있습니다. 해당 자료는 보건사업 수행 과정에서 집계된 행정자료를 기반으로 작성되었습니다.본 데이터는 지역별 영양취약계층 분포를 공시적으로 분석하거나, 특정 지역의 영양지원 수요 변화를 파악하는 데 활용할 수 있습니다. 또한 공공데이터를 활용하여 다음과 같은 분석 및 연구에 활용이 가능합니다.단순 예시 사례이니 참고 바랍니다.○ 지역별 분포 분석: 읍·면별 영양플러스사업 수혜인원 현황을 통해 지역 간 영양지원 수요 차이를 파악하고 정책 수립에 활용할 수 있습니다.○ 수혜 대상자 규모 파악: 영양플러스사업 참여 인원 규모를 분석하여 향후 지원 계획 수립에 활용할 수 있습니다.○ 취약계층 영양지원 분석: 임산부 및 영유아 등 대상자 분포를 기반으로 영양지원 사각지대 해소를 위한 기초자료로 활용할 수 있습니다.

Feed the Future Northern Kenya Interim Survey in the Zone of Influence: This dataset (n=53,070, vars=17) contains data from sub-Module E3: Non-Food Expenditures Over Past One Month. Each household with data for non-food expenditures over the past month has multiple records (for the 29 non-food items in sub-Module E3). (53,070 records divided by 29 non-food items = 1,830 Module E households with sub-Module E3 data.)