May 23, 2018 - A new article published in Demographic Research documents methods and assesses the quality of fertility data in Performance Monitoring and Accountability 2020 (PMA2020) surveys, focusing on potential bias introduced from the type of birth history questions in the questionnaire and completeness and distribution of birth month and year input. The article entitled, “Measuring fertility through mobile‒phone-based household surveys: Methods, data quality, and lessons learned from PMA2020 surveys” was published in May 2018.
Dr. Yoonjoung Choi, Deputy Director for PMA2020, and collaborating authors Qingfeng Li and Blake Zachary, simulated births that would be counted using the PMA2020 questionnaires compared to births identified from full birth history. The team also analyzed the latest Demographic and Health Surveys in ten countries where PMA2020 surveys have been implemented.
The researchers found:
+ Simple questions introduced minor bias from undercounting multiple births, which was expected and had been corrected.
+ However, incomplete reporting of birth month was relatively high but had decreased. The default value of January for missing months in data collection software systematically moved births with missing months out of the reference period.
+ On average, across 39 surveys, total fertility rate (TFR) increased by 1.6% and 2.4%, adjusted for undercounted multiple births and heaping on January, respectively.
PMA2020 uses innovative mobile technology to support low-cost, rapid-turnaround surveys to monitor key family planning and other health indicators on an annual basis. The program is implemented by local universities and research organizations in 11 countries, deploying a cadre of female resident data collectors trained in mobile data collection. Overall direction and support is provided by the Bill & Melinda Gates Institute for Population and Reproductive Health at the Johns Hopkins Bloomberg School of Public Health and funded by the Bill & Melinda Gates Foundation.
Wednesday, May 23, 2018