Snapshot of Indicators
Summary of the sample design for º£½Ç»»ÆÞ2017/Nigeria National Round 2:
In Nigeria, the Performance Monitoring for Accountability 2020 (º£½Ç»»ÆÞ2020) survey collects data at the state-level to allow for the estimation of key indicators to monitor progress in family planning at the population and the facility level. The º£½Ç»»ÆÞ2017/Nigeria (National) R2 survey used a two-stage cluster design within a sample of seven states (Anambra, Kaduna, Kano, Lagos, Nasarawa, Rivers, and Taraba). One state was selected using probability proportional to size from among those in each of six zones. The seventh state (Kaduna) was allocated to the northwest zone. A sample of 302 enumeration areas (EAs) was drawn from the National Population Commission master sampling frame. For each EA, 35 households (40 in Lagos) were randomly selected. A random start method was used to systematically select households within the EA.
Eligible females of reproductive age (15-49 years) living in selected households were contacted and consented for interviews. The final completed sample included 10,063 households (97.2% response rate) and 11,380 females (98.7% response rate). Data collection was conducted between April and May 2017.
The sample was powered to generate state-level estimates of all women mCPR with less than 3% margin of error. For more on the º£½Ç»»ÆÞ2020 Nigeria sampling strategy, please view the sampling strategy document.
SOI Tables
Round 1 Sample Design
In Nigeria, the º£½Ç»»ÆÞ2020 survey collects data at the state-level to allow for the estimation of key indicators to monitor progress in family planning at the population and the service delivery points (SDPs) levels. The resident enumerator (RE), º£½Ç»»ÆÞ’s female data collector, model enables replication of the surveys on an annual basis, or more frequently.
For º£½Ç»»ÆÞ2016/Nigeria (National) R1, the project used a two-stage cluster design and drew a sample of enumeration areas (EAs) from the National Population Commission (NPopC) master sampling frame to achieve a representative sample of each state. This was the first round in Anambra, Kano, Nasarawa, Rivers, and Taraba states and the third round in Lagos and Kaduna states where the same EAs were used from previous rounds. The EAs were selected systematically using probability proportional to size. The NPopC provided the selection probabilities for the º£½Ç»»ÆÞ2020 sampled clusters which were used to construct sample weights.
In each selected EA, households and private health facilities were listed and mapped. Field supervisors randomly selected 35 households (40 in Lagos) from the household listing using a random start method. A household roster was completed and all eligible women age 15-49 in selected households were approached and asked to provide informed consent to participate in the study.
For the service delivery point (SDP) survey, up to three private SDPs, including pharmacies, within each sampled EA cluster boundary were randomly selected from the listing. In addition, three public health SDPs (lowest, second-lowest and third-lowest level) designated to serve each EA population were selected.
Round 2 Sample Update
For this round of º£½Ç»»ÆÞ2020 data collection - which was the second round in Anambra, Kano, Nasarawa, Rivers, and Taraba states and the fourth round in Lagos and Kaduna states - the same sample of enumeration areas (EAs) from previous rounds was used. A new random selection of 35 households (40 in Lagos) was drawn from the listing. A household roster was completed and all eligible women age 15-49 in selected households were approached and asked to provide informed consent to participate in the study.
The majority of SDPs are repeated in each round, forming a panel survey. If an EA had more than three private SDPs identified during the listing process, then a new sample of the private SDPs is selected during each round.
º£½Ç»»ÆÞ2020/Nigeria continued in the two selected states: Kaduna and Lagos. No adjustments were made to the household sample size in Kaduna. After Round 1 in Lagos, however, a shortfall in the targeted sample size was observed, with only 771 completed female interviews. This was subsequently determined to be the result of a lower-than-expected response rate (75% among households and 89% among women). In addition, while one woman per household was assumed, it was much lower in Lagos. For Round 2, therefore, a few adjustments were made to calculate the required sample size: a new DEFF estimate of 2.03 was applied; the average number of eligible women per household was assumed to be 0.90; and the take size was raised to 40 households per EA cluster. The resulting required sample size was 1791 women from 50 EA clusters. Considering low response rates during Round 1, a total of 52 EA clusters – 37 from Round 1 and additionally selected 15 – were included for implementation in Round 2 and onward. The final completed sample included 10,063 households (97.2% response rate) and 11,380 de facto females (98.7% response rate). Data collection was conducted between April and May 2017. The majority of SDPs are repeated in subsequent rounds, forming a panel survey. If an EA had more than three private SDPs identified during the listing process, then a new, random sample of three private SDPs is selected during each round.
º£½Ç»»ÆÞ2020 uses standardized questionnaires to gather data about households, individual females and health facilities that are comparable across program countries and consistent with existing national surveys. Prior to launching the survey in each country, local experts review and modify these questionnaires to ensure all questions are appropriate to each setting. Three questionnaires were used to collect data from the º£½Ç»»ÆÞ2017/Nigeria (national) R2 survey: the household questionnaire, the female questionnaire and the service delivery point questionnaire.
The household, female, and the service delivery point (SDP) questionnaire) were based on model surveys designed by º£½Ç»»ÆÞ2020 staff at the Bill & Melinda Gates Institute for Population and Reproductive Health at the Johns Hopkins Bloomberg School of Public Health in Baltimore, Maryland, USA, the Center for Evaluation Resources and Development (CRERD), Bayero University Kano (BUK), and fieldwork materials of the Nigeria Demographic and Health Survey (DHS).
All º£½Ç»»ÆÞ2020 questionnaires are administered using Open Data Kit (ODK) software and Android smartphones. The questionnaires were in English, Hausa, Igbo, Pidgin, and Yoruba on the phone. The questionnaires were translated using available translations from similar population surveys and experts in translation. The interviews were conducted in the local language, or English in a few cases when the respondent was not comfortable with the local language. Female resident enumerators (data collectors) in each enumeration area (EA) administered the household and female questionnaires in the selected households and the SDP questionnaire for sampled private SDPs. Field supervisors administered the SDP questionnaire in public SDPs.
The household questionnaire gathers basic information about the household, such as ownership of livestock and durable goods, as well as characteristics of the dwelling unit, including wall, floor and roof materials, water sources, and sanitation facilities. This information is used to construct a wealth index.
The first section of the household questionnaire, the household roster, lists basic demographic information about all usual members of the household and visitors who stayed with the household the night before the interview. This roster is used to identify eligible respondents for the female questionnaire. In addition to the roster, the household questionnaire also gathers data that are used to measure key water, sanitation, and hygiene (WASH) indicators, including regular sources and uses of WASH facilities used and prevalence of open defecation by household members.
The female questionnaire is used to collect information from all women age 15 to 49 who were listed on the household roster at selected households. The female questionnaire gathers specific information on: education; fertility and fertility preferences; family planning access, choice and use; quality of family planning services; and exposure to family planning messaging in the media.
The SDP questionnaire collected information about the provision and quality of reproductive health services and products, integration of health services, and water and sanitation within the SDP.
Training
The º£½Ç»»ÆÞ2017 fieldwork training started with a centralized training of field supervisors and central staff in Spring 2017. The training was led by º£½Ç»»ÆÞ2020 staff from the Center for Research, Evaluation Resources, and Development (CRERD) and Bayero University Kano (BUK), with support from the Bill & Melinda Gates Institute for Population and Reproductive Health at the Johns Hopkins Bloomberg School of Public Health. Field supervisors, supported by the central team and º£½Ç»»ÆÞ2020 team, then became the trainers for the subsequent resident enumerator (RE) training sessions that took place before the start of data collection.
Throughout the trainings, resident enumerators (REs) and supervisors were evaluated based on their performance on phone-based assessments. The RE trainings were conducted the predominant language in each state whereas some small group review sessions were conducted in other local languages.
Supervisors received additional training prior to and after the RE training to further strengthen their supervision skills, including instruction on conducting re-interviews, carrying out random spot checks, and dealing with the local/community leaders and engaging the communities.
Data Collection & Processing
Data collection in all seven states was conducted between April and May 2017. Unlike traditional paper-and-pencil surveys, º£½Ç»»ÆÞ2020 uses Open Data Kit (ODK) Collect, an open-source software application, to collect data on mobile phones. All the questionnaires were programmed using this software and installed onto all project smartphones. The ODK questionnaire forms are programmed with automatic skip-patterns and built-in response constraints to reduce data entry errors.
The ODK application enabled REs and supervisors to collect and transfer survey data to a central ODK Aggregate cloud server. This instantaneous aggregation of data also allowed for concurrent data processing and course corrections while º£½Ç»»ÆÞ2020 was still active in the field. Throughout data collection, central staff at CRERD in Nigeria and the data manager at the Gates Institute at Johns Hopkins in Baltimore, Maryland routinely monitored the incoming data and notified field staff of any potential errors, missing data or problems found with form submissions on the central server. The use of mobile phones combined data collection and data entry into one step; therefore, data entry was completed when the last interview form was uploaded at the end of data collection in May.
Once all data were on the server, data analysts cleaned and de-identified the data, applied survey weights, and prepared the final dataset for analysis using Stata. The findings were shared with government and community stakeholders at dissemination events organized in each state.
This table shows response rates for household and female respondents by residence (rural/urban) for º£½Ç»»ÆÞ2017 Nigeria (national) Round 2. A total of 10,826 households were selected for the survey; 10,352 households were found to be occupied at the time of the fieldwork. 10,063 (97.2%) of the occupied households consented to a household-level interview. The response rate for the household level was higher in the rural (99.2%) relative to the urban (95.3%) enumeration areas (EAs).
To view the sample errors for the º£½Ç»»ÆÞ2020 indicators described above, download the full SOI report here. For more information about º£½Ç»»ÆÞ2020 indicators, including estimate type and base population, click here.
Centre for Research, Evaluation Resources and Development (CRERD), Bayero University Kano (BUK), 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 (º£½Ç»»ÆÞ2020) Survey Round 4, º£½Ç»»ÆÞ2017/Nigeria-R4 (National) Snapshot of Indicators. 2017. Nigeria and Baltimore, Maryland, USA.