Kenya Nutrition Round 2 SQ Survey

Survey Title:

Dataset Persistent ID:

10.34976/sqey-4p33

Country:

Kenya

Description:

Kenya Nutrition Round 2 Service Delivery Point (SQ) survey used a multi-stage stratified cluster design with urban-rural and selected 11 counties as strata. A sample of 151 enumeration areas (EAs) was drawn by the Kenya National Bureau of Statistics from its master sampling frame for the Kenya Round 5 PMA2020 family planning survey and these EAs were used for the nutrition survey. Each EA was listed and mapped. Public facilities were included if a selected EA fell within the catchment area. Up to three private facilities were included if they fell within the boundaries of the EA. Data collection was conducted between May and July 2018.

Field work:

May 2018 - July 2018

Suggested Citation:

International Centre for Reproductive Health Kenya (ICRHK); and the Bill & Melinda Gates Institute for Population and Reproductive Health at the Johns Hopkins Bloomberg School of Public Health. Performance Monitoring and Accountability 2020 (PMA2020) Kenya Nutrition Round 2: Service Delivery Point Survey (Version 2.0), PMA2018/KE-NutR2-SQ. 2018. Kenya and Baltimore, Maryland, USA. https://doi.org/10.34976/sqey-4p33

Organizations:

International Centre for Reproductive Health Kenya (ICRHK); and the Bill & Melinda Gates Institute for Population and Reproductive Health at the Johns Hopkins Bloomberg School of Public Health.

Keywords:

Nutrition
Service Delivery Point
Survey Research
Kenya

Funding:

PMA2020 project is funded by the Bill & Melinda Gates Foundation.

Dataset Request:

To request access to the dataset, please email Dr. Phil Anglewicz panglew1@jhu.edu with the following information:

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PMA Data Use Policy:

The dataset must not be shared or redistributed to other users or researchers. The data must not be used for marketing or commercial purposes. The data will be treated as confidential, and no effort will be made to identify any individual, household, or enumeration area in the survey. No results will be published that could identify specific communities or individuals. The dataset must be cited properly in all publications and outputs.