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PMA2016/Anambra-R1 SOI

SNAPSHOT OF INDICATORS

Summary of the sample design for PMA2016/Anambra (Nigeria):

In Nigeria, the PMA2020 survey collects data at the state-level to allow for the estimation of key indicators to monitor progress in family planning - both at the population and the service delivery points (SDPs) levels. The surveys were conducted first in two states, Kaduna and Lagos, and then in additional five states since 2016. Detailed sampling methodology information for Nigeria PMA2020 surveys is available here.

PMA2016/Anambra is the first round of PMA2020 data collection in Anambra state and used a two-stage cluster design within the state. Primary sampling units were selected using probability proportional to size procedures within the state. The sample was powered to generate state-level estimates of all women mCPR with less than 3% margin of error. To read more details on our survey methodology including the survey tools, training, data processing and response rates, please scroll to the end of the table below.

The table below provides a summary of key family planning indicators and their breakdown by respondent background characteristics. Estimates for all indicators are representative for the state. To view the breakdown by background characteristics of the respondents (including education level, wealth quintile, region etc.), please click on the respective indicator link. Distribution of respondents by background characteristics is available here. Distribution of SDPs by background characteristics is available here.

Additional detail on sample design, data collection and processing, response rates, and standard errors are available below the indicator tables.

Download the full SOI tables >>

PMA2020 Standard
Family Planning Indicators

Round 1
All Women Married Women
Utilization Indicators:
Contraceptive Use    
Contraceptive Prevalence Rate (CPR) 25.1 33.5
Modern Contraceptive Prevalence (mCPR) 15.6 17.5
Traditional Contraceptive Prevalence 9.5 15.9
Contraceptive Method Mix    
Contraceptive method mix (stacked bar charts for all/married women)    
Demand for Family Planning and Fertility Preferences:
Unmet need for family planning 14.4 20.4
Demand for family planning 39.5 53.9
Percent of all/married women with demand satisfied by modern contraception 39.6 32.6
Percent of recent births, by intention
Wanted then 71.5 73.6
Wanted later 16.7 16.3
Wanted no more 11.8 10.0
Access, Equity, Quality and Choice:
Percent of users who chose their current method by themselves or jointly with a partner/provider 85.8 85.0
Percent of users who paid for family planning services 29.0 23.7
Method Information Index Components    
Percent of current users who were informed about other methods 36.3 39.4
Percent of current users who were informed about side effects 25.1 28.6
Percent of current users who were told what to do if they experienced side effects 68.6 70.6
Percent of current users who would return and/or refer others to their provider 43.5 53.2
Percent of women receiving family planning information in the past 12 months 11.4 16.4
Service Environment:
Charging fees for family planning    
Contraceptive choice: Availability of at least 3 or at least 5 modern contraceptive methods    
Contraceptive choice: Availability of modern contraception, by method    
Contraceptive stock-outs, by method    
Number of new and continuing family planning visits, by method    

The PMA2016/Anambra Survey in Detail

Sample Design

Round 1 Sample Design

In Nigeria, the PMA2020 survey collects data at the state-level to allow for the estimation of key indicators to monitor progress in family planning - both at the population and the service delivery points (SDPs) levels. The resident enumerator (RE) model enables replication of the surveys twice a year for the first two years, and annually each year after that, to track progress.

For this first round of PMA2020 data collection in Anambra, Nigeria (PMA2016/Anambra), the project used a two-stage cluster design within the state and drew a sample of 41 enumeration areas (EAs) from the National Population Commission master sampling frame to achieve a representative sample of Anambra State. The master frame of enumeration areas (EAs) was based on the 2006 Nigerian population census. Census EAs in Nigeria are on average 47 households in size. In order to obtain an EA of approximately 200 households, a cluster of EAs was constructed – hereinafter referred to as EA cluster. An index enumeration area, along with a list of contiguous EAs and associated sampling probabilities, were provided by the National Population Commission (NPopC). EAs were combined into EA clusters - primary sampling units in Nigeria - and sampling probabilities were adjusted.

In each selected EA cluster households and private health facilities were listed and mapped. Field supervisors randomly selected 35 households from the household listing using a random number generation phone application. 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 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—a health post, a health center, and a district hospital designated to serve the EA population—were selected.

Questionnaires

PMA2020 uses standardized questionnaires to gather data about households and individual females 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. All female questionnaires were translated into the local languages, and translations were reviewed for appropriateness.

The household, female, and the service delivery point (SDP) questionnaire) were based on model surveys designed by PMA2020 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 PMA2020 questionnaires are administered using Open Data Kit (ODK) software and Android smartphones. The PMA2016 Nigeria questionnaires were in English and could be switched into local languages (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 in each enumeration area (EA) administered the household and female questionnaires in the selected households.

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 quintile 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, Data Collection and Processing

Training

The PMA2016/Anambra fieldwork training started with a centralized training of field supervisors and central staff in Spring 2016. The training was led by PMA2020 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 PMA2020 team, then became the trainers for the subsequent resident enumerator (RE) training sessions that took place before the start of data collection.

Throughout the training, resident enumerators (REs) and supervisors were evaluated based on their performance on phone-based assessments. The RE training was conducted primarily in Igbo and English, whereas some small group review sessions were conducted in other local languages.
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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 and Processing

Data collection was conducted between May and June 2016. Unlike traditional paper-and-pencil surveys, PMA2020 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 PMA2020 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 June.

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 a dissemination event on September 22, 2016.

Response Rates

The table below shows response rates of household and female respondents for the PMA2016/Anambra survey. Of the 1,435 households selected 1,412 (98.4%) households were occupied at the time of the fieldwork. Among the 1,412 potential respondents, 1,378 consented to the household interview (97.6% response rate).

In the selected households 1,355 eligible women aged 15 to 49 years were identified and 1,309 of them were interviewed (response rate of 96.6%).

    PMA2016/Anambra
Result   Urban Rural Total
Household interviews              
Households selected   770 665 1,435
Households occupied   761 651 1,412
Households interviewed   738 640 1,378
Household response rate* (%)   97.0 98.3 97.6
             
Interviews with women age 15-49
Number of eligible women**   789 566 1,355
Number of eligible women interviewed   762 547 1,309
Eligible women response rate (%)   96.6 96.6 96.6
*Household response rate = households completed/households occupied

**Eligible women response rates include only women identified in completed household interviews

Eligible response rate = eligible women interviewed/eligible women

Sample Error Estimates

The following table shows sample errors for the PMA2020 indicators described above. For more information about PMA2020 indicators, including estimate type and base population, click here.

   
Variable Value[R] Standard Error Confidence Interval
R-2SE R+2SE
All women age 15-49
Currently using a modern method 0.157 0.017 0.122 0.191
Currently using a traditional method 0.095 0.013 0.068 0.122
Currently using any contraceptive method 0.251 0.024 0.204 0.299
Currently using injectables 0.011 0.004 0.004 0.019
Currently using male condoms 0.102 0.015 0.072 0.133
Currently using implants 0.013 0.004 0.005 0.021
Chose method by self or jointly in past 12 months 0.850 0.029 0.791 0.910
Paid fees for family planning services in past 12 months 0.290 0.049 0.192 0.389
Informed by provider about other methods 0.363 0.038 0.285 0.440
Informed by provider about side effects 0.251 0.042 0.165 0.336
Satisfied with provider: Would return and refer friend/relative to provider 0.435 0.057 0.320 0.550
Visited by health worker who talked about family planning in past 12 months 0.114 0.026 0.062 0.166
Women in union age 15-49
Currently using a modern method 0.176 0.023 0.130 0.222
Currently using a traditional method 0.160 0.020 0.120 0.199
Currently using any contraceptive modern method 0.335 0.029 0.277 0.393
Currently using injectables 0.016 0.007 0.003 0.029
Currently using male condoms 0.100 0.018 0.064 0.137
Currently using implants 0.017 0.007 0.003 0.032
Chose method by self or jointly in past 12 months 0.850 0.033 0.782 0.917
Paid fees for family planning services in past 12 months 0.237 0.050 0.137 0.338
Informed by provider about other methods 0.394 0.038 0.317 0.470
Informed by provider about side effects 0.286 0.058 0.168 0.405
Satisfied with provider: Would return and refer friend/relative to provider 0.532 0.056 0.418 0.645
Visited by health worker who talked about family planning in past 12 months 0.164 0.039 0.086 0.242