Nigeria - National Nutrition and Health Survey 2014, Second round
Reference ID | NGA-NBS-NNHS-2014-v1.0 |
Year | 2014 |
Country | Nigeria |
Producer(s) | National Bureau of Statistics (NBS) - Federal Government of Nigeria (FGN) |
Sponsor(s) | United Nations Children’s Fund - UNICEF - Funding Micronutrient Initiative - MI - Funding Nigeria's Saving One Million Lives Initiative - - Funding United State Agency International Development - USAID - Funding UKAID - - Funding |
Metadata | Documentation in PDF Download DDI Download RDF |
Created on | Dec 21, 2016 |
Last modified | Dec 21, 2016 |
Page views | 183702 |
Downloads | 13926 |
Data Processing
Data Editing
Data quality was reviewed daily during the first week of data collection and weekly during the remainder of field work. The review of data quality comprised downloading the raw data in CSV format, converting the data to STATA, ENA and GPS data formats and producing the plausibility checks from the ENA software and analysis of timing of data collection and missing data.
The data on the daily standardization of anthropometric tools allowed quick detection and replacement of broken or non-functioning scales, height boards or MUAC strips. All supervision teams traveled with replacement scales, height boards, MUAC strips, tablets and other survey materials to resupply teams.
The GPS points of survey data collection were mapped to compare against selected clusters to identify obvious sampling errors. The daily sign-in of the data collection team along with GPS data allowed validation that personnel were in the field in the assigned geographic point as planned.
The data were assessed to ensure that data were sent daily from the tablets to the server and that all teams were following the sampling plans as trained. The time and date stamps on each data point provided data to review the number of interviews per day and the duration of each interview. The timestamps were evaluated to determine if data were collected at appropriate times during the day, not before 7AM or after 8PM.
The data were evaluated by team for missing data. If any variable had more than 5% missing data then supervision staff were alerted and asked to pay specific attention to the data collection of those teams
with missing data. Anthropometric data quality was reviewed by % of data with WHO flags, sex ratio,
Other Processing
Data collection on mobile devices provided many advantages. As data quality was reviewed during the data collection and supervision, strong rigor was ensured for the survey data. The double data entry steps were eliminated and the time needed to process the data after fieldwork was reduced. The data analysis and preliminary results were available in two weeks after data collection. The rapid production of survey results allowed the government and partners to ensure greater consensus on conditions across the 36 states plus Federal Capital Territory and make more informed decisions quickly on the conditions identified by the national survey.