PMA2016/Kinshasa Round 5 Indicators

Round 1 Sample Design

The PMA2020 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 58 enumeration areas (EAs) to achieve a representative sample in Kinshasa. The EAs were selected systematically using probability proportional to size and were obtained from the National Statistical Institute.

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. The same sample design was used for rounds one through four in Kinshasa.

Round 5 Sample Design

The PMA2020 survey collects annual data within Kinshasa 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 of family planning indicators.

PMA2020/Kinshasa is led by the University of Kinshasa’s School of Public Health, in collaboration with Tulane University School of Public Health and Tropical Medicine. The first three rounds of PMA2020/DRC data collection occurred exclusively in Kinshasa. In Round 4, the PMA2020/DRC team expanded to cover Kongo Central, the province adjacent to Kinshasa. The project sampled 58 enumeration areas (EAs) to achieve a representative urban sample in Kinshasa. The EAs were selected systematically using probability proportional to size.

All women of reproductive age (ages 15-49) within each selected household were contacted and consented for interviews. Private and public service delivery points (SDP) who provide services to the EA were also interviewed. 1,841 households (97.2% response rate), and 2,582 de facto females (95.3% response rate), were interviewed, along with 173 SDPs (93.5% response rate). Data collection for Round 5 was conducted between September and October 2016.

PMA2020 uses standardized questionnaires to gather data about households, individual females, and service delivery points 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 PMA2016/Kinshasa-R5 survey data: the household questionnaire, the female questionnaire and the service delivery point questionnaire. 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 PMA2020 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 PMA2020 questionnaires are administered using Open Data Kit (ODK) software installed on mobile phones (smartphones) using the Android operating system. In addition to French, keywords from the PMA2016/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 PMA2016/Kinshasa-R5 fieldwork consisted of a 4-day training for resident enumerators in the fall of 2016 in Kinshasa. PMA2020 staff from the Bill & Melinda Gates Institute for Population and Reproductive Health and Tulane University School of Public Health and Tropical Medicine supported staff from the Kinshasa School of Public Health who led the training.

All participants received training in research ethics, comprehensive instruction on how to map and list households in enumeration areas (EAs), and instruction on how to complete the household and female questionnaires using appropriate and ethical interview skills. In addition to PMA2020 survey training, all participants received training on contraceptive methods by a physician specializing in reproductive health.

Throughout the trainings, REs and supervisors were evaluated based on their performance on several written and phone-based assessments, practical field exercises and class participation. As all questionnaires were completed on project smartphones, the training also familiarized participants with Open Data Kit (ODK) and smartphone use in general. All trainings included three days of practical exercises, during which participants entered a practice EA to conduct mapping and listing, and household, female and SDP interviews. 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 small group discussions in local language to standardize orally the questionnaire translations in Lingala and other local languages in which the survey is administered.

Data Collection & Processing

Data collection was conducted between September and October 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 the Kinshasa School of Public Health and the data manager at Tulane University School of Public Health and Tropical Medicine 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 October.

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.

This table shows response rates for household and female respondents by for PMA2016/Kinshasa. A total of 1,914 households were selected for the PMA2016 survey; 1,895 households were found to be occupied at the time of the fieldwork. Of the occupied households, 1,841 (97.2%) consented to and completed a household-level interview. In the occupied households that provided an interview, a total of 2,738 eligible women aged 15 to 49 years were identified. Overall, 94.8% of the eligible women were available and consented to and completed the interview. Only de facto females are included in the PMA analyses; the final completed de facto female sample size was 2,582 (unweighted).

The final SDP sample included 183 facility interviews, of which 171 were completed for a response rate of 93.4%.

Weights were adjusted for non-response at the household and individual levels and applied to all household and individual estimates in this report. SDP estimates are not weighted.

To view the sample errors for the PMA2020 indicators described above, download the full SOI report here. For more information about PMA2020 indicators, including estimate type and base population, click here.