SNAPSHOT OF INDICATORS
º£½Ç»»ÆÞ2020 Snapshot of Indicators (SOIs) are online tables that provide a summary of key family planning indicators and their breakdown by background characteristics (age, marital status, parity, education, residence, wealth, region). SOI tables include information on sample design, questionnaires, data processing, response rates and sample error estimates.
Summary of the sample design for º£½Ç»»ÆÞ2015-16/Kinshasa, DRC-Round 4:
º£½Ç»»ÆÞ2020 is designed to create sentinel sites for data collection both at the population-level and among service delivery points (SDPs). Enumeration areas (EAs) selected in Round 1 are generally used for data collection in Rounds 2-4. Households within the EA are randomly sampled during each round; however the EA is consistent across rounds. For clarity, the original Round 1 sample design summary is provided below.
º£½Ç»»ÆÞ2015/Kinshasa Round 4 used a two-Âstage cluster design to draw a representative urban sample. A sample of 58 enumeration areas (EAs) was drawn using probability proportional to size procedures from the total of approximately 350 in Kinshasa. For each EA, 30 households were selected, and a random start method was used to systematically select households. All women of reproductive age (15-49) within each selected household were contacted and consented for interviews. Up to six health service delivery points (SDP), three public and three private, were selected in each EA. The sample was powered to generate Kinshasa specific estimates of all woman mCPR with less than a 2% margin of error.
The tables provide a summary of key family planning indicators at the national level and their breakdown by background characteristics.
Round 1 Sample Design
The º£½Ç»»ÆÞ2020 survey collects data annually to allow for the estimation of key indicators to monitor progress in family planning. 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.
This first round of data collection occurred exclusively in Kinshasa. The project sampled 60 enumeration areas (EAs) to achieve a representative urban sample in Kinshasa. The EAs were selected systematically using probability proportional to size.
Before data collection, all households, private service delivery points (SDPs) and key landmarks in each EA were listed and mapped by trained resident enumerators (REs) to create a sampling frame for the second stage of sampling for households and private SDPs. The mapping and listing process took place the first week of data collection in each EA with the help of cartographers and supervisors. Once households had been listed, field supervisors selected 30 households per EA, and a random start method was used to systematically select households. All members of the selected households were enumerated by the interviewers when completing household questionnaires, and from this household roster, all eligible women (aged 15-49) were approached and asked to provide informed consent to participate in the study.
Round 4 Sample Update
Data collection for Round 4 continued in the same 58 EAs as Round 3. Round 4 used the original household list to select households into the sample.
Field supervisors randomly selected 30 households from the original household 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 three private SDPs are randomly selected in each round.
º£½Ç»»ÆÞ2020 uses standardized questionnaires to gather data about households, individual females and health service delivery points (SDPs) 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 questionnaire, the female questionnaire and the SDP questionnaire were based on model surveys designed by º£½Ç»»ÆÞ2020 staff at the Bill & Melinda Gates Institute for Population and Reproductive Health of the Johns Hopkins Bloomberg School of Public Health, in collaboration with Tulane University School of Public Health and Tropical Medicine, and fieldwork materials of the DRC Demographic and Health Survey (DHS).).
All º£½Ç»»ÆÞ2020 questionnaires are administered using Open Data Kit (ODK) software installed on mobile phones (smartphones) using the Android operating system. In addition to French, key words from the º£½Ç»»ÆÞ2015/Kinshasa questions appeared on the phones in the main local languages. REs in each EA administered the household and female questionnaires in the selected households and the private SDP questionnaires. Field supervisors administered questionnaires at public SDPs.
The household questionnaire gathers basic information about the household, such as ownership of durable goods, as well as characteristics of the dwelling unit, including wall, floor, and roof material, water sources and sanitation facilities. This information is used to construct a wealth quintile.
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 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 is used to collect 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 Round 4 fieldwork training was held over four days in October 2015, and was led by project staff from Tulane University and the Kinshasa School of Public Health (KSPH), with support from Johns Hopkins Bloomberg School of Public Health staff. A total of 58 resident enumerators (REs) have been trained in Kinshasa, with a few additional REs trained as back-ups.
In the refresher training prior to Round 4, REs problem-solved challenges in the field from Round 3 with central staff and supervisors, reviewed particular issues noted in data quality, and gained additional practice with the research protocols Throughout the trainings, REs were evaluated based on their performance on several written and phone-based assessments and class participation. As all questionnaires were completed on project smartphones, the training also re-familiarized participants with Open Data Kit (ODK) and smartphone use in general. All responses were captured on project smartphones, and submitted to a practice cloud server—a centralized data storage system. The RE trainings were conducted primarily in French, with discussions about translation to local languages.
Data Collection & Processing
Data collection was conducted between October 2015 and January 2016. 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 the Kinshasa School of Public Health 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 January.
Once all data were on the server, data analysts cleaned and de-identified the data, applied survey weights, and prepared the final data set for analysis using Stata software. Findings were shared with government and community stakeholders at a dissemination eovent in early 2016.
The table shows response rates for household and female respondents by residence (rural/urban) for º£½Ç»»ÆÞ2015-16/Kinshasa Round 4. A total of 1,918 households were selected for the º£½Ç»»ÆÞ2015-16 survey; 1,843 households were found to be occupied at the time of the fieldwork. 1,774 of the occupied households (96.3%) consented to a household-level interview.
In the occupied households that provided an interview, a total of 2,830 eligible women aged 15 to 49 years were identified. Overall, 2,733 (96.6%) of the eligible women were available and consented to the interview. Only de facto females are included in the analyses; the final completed de facto female sample size was 2,733 (unweighted).
This table shows sample errors for the º£½Ç»»ÆÞ2020 indicators described above. For more information about º£½Ç»»ÆÞ2020 indicators, including estimate type and base population, click here.
Tulane University School of Public Health, University of Kinshasa School of Public Health 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»»ÆÞ2015/DRC-R4 (Kinshasa) Snapshot of Indicators. 2015. Kinshasa, DRC and Baltimore, Maryland, USA.