On the empirical study of fertility transition: A case for application of age-adjusted measures in multivariable analysis

Among studies of factors driving fertility transitions, the cumulative children ever born (CEB) has been treated as the dependent variable in multivariable models. Some of these studies have cited total fertility rates (TFRs) in their rationales for investigating the determinants of fertility transition. However, CEB and TFR (which are computed from age-specific fertility rates) are notably disparate measures of fertility. The aim of this study was to argue that where TFRs are cited as a basis for an investigation of driving factors of fertility transitions, the dependent variable in the multivariable modeling ought to be an adjusted measure of fertility. The study applied trend analysis to examine the extent to which CEB and age-specific marital fertility rates (ASMFR) reflected trajectories of the trends of total marital fertility rates (TMFRs) in Ghana, Kenya, Rwanda, and Zimbabwe. Multivariable analysis based on the two-fold Oaxaca-Blinder decomposition technique was applied to examine how using ASMFR compared to CEB impacts the understanding of factors of fertility change, using the case of Zimbabwe. Trend analysis showed that ASMFR was more effective in reflecting fertility trends and measuring the role of associated factors. The results from multivariable analyses show that a case can be made for the use of adjusted measures in the understanding of factors of fertility transition.
Adhikari, R. (2010). Demographic, socio-economic, and cultural factors affecting fertility differentials in Nepal. BMC Pregnancy and Childbirth, 10(1):19. https://doi.org/10.1186/1471-2393-10-19
Al-Balushi, M.S., Ahmed, M.S., Islam, M.M., & Khan, M.H.R. (2020). Multilevel poisson regression modeling to identify factors influencing the number of children ever born to married women in Oman. Journal of Statistics and Management Systems, 23:1-17. https://doi.org/10.1080/09720510.2019.1709328
Ariho, P., Kabagenyi, A., & Nzabona, A. (2018). Determinants of change in fertility pattern among women in Uganda during the period 2006-2011. Fertility Research and Practice, 4:4. https://doi.org/10.1186/s40738-018-0049-1
Ariho, P., & Nzabona, A. (2019). Determinants of change in fertility among women in rural areas of Uganda. Journal of Pregnancy, 2019:6429171. https://doi.org/10.1155/2019/6429171
Be-Ofuriyua, J.E., & Emina, J. (2002). Accelerating fertility transition in sub-Saharan Africa-UN conventional: A point of view-Brief article-statistical data included. UN Chronicle, 39(2):3.
Bongaarts, J. (2015). Modelling the fertility impact of the proximate determinants: Time for a tune-up. Demographic Research, 33:535-560. https://doi.org/10.4054/DemRes.2015.33.19
Cleland, J.G., Ndugwa, R.P., & Zulu, E.M. (2011). Family planning in sub-Saharan Africa: Progress or stagnation? Bulletin of the World Health Organization, 89(2):137-143. https://doi.org/10.2471/BLT.10.077925
Colleran, H., & Snopkowski, K. (2018). Variation in wealth and educational drivers of fertility decline across 45 countries. Population Ecology, 60(1):155-169. https://doi.org/10.1007/s10144-018-0626-5
Croft, T.N., Marshall, A.M.J., & Allen, C.K. (2018). Guide to DHS Statistics DHS-7. Chennai: ICF. Available from: https:// www.dhsprogram.com/data/guide-to-dhs-statistics/index. htm#t=guide_to_dhs_statistics_Dhs-7.htm [Last accessed on 2021 Feb 05].
Garenne, M., & Zwang, J. (2006). DHS Comparative Reports 13. Available from: https://www.dhsprogram.com/pubs/pdf/ CR13/CR13.pdf [Last accessed on 2021 Jun 05].
Gould, W.T., & Brown, M.S. (1996). A fertility transition in Sub-Saharan Africa? International Journal of Population Geography, 2(1):1-22. https://doi.org/10.1002/(SICI)1099-1220(199603)2:1<1:AID-IJPG23>3.0.CO;2-#.
Indongo, N., & Pazvakawambwa, L. (2012). Determinants of fertility in Namibia: African Journal of Reproductive Health, 16(4), 50-57.
Liu, D.H., & Raftery, A.E. (2020). How do education and family planning accelerate fertility decline? Population and Development Review, 46(3):409-441. https://doi.org/10.1111/padr.12347
Locoh, T. (2002). Family structure and fertility trends in inter-mediate fertility countries in West Africa. Population Bulletin of the United Nations, Special Issues(48-49): 165-182.
Ndagurwa, P., & Odimegwu, C. (2019). The elasticity of marital fertility in three sub-Saharan African countries: A decomposition analysis. Genus, 75(1):17. https://doi.org/10.1186/s41118-019-0064-z
Potts, D., & Marks, S. (2001). Fertility in Southern Africa: The quiet revolution. Journal of Southern African Studies, 27(2):189-205. https://doi.org/10.1080/03057070120049921
Pullum, T.W. (2006). An assessment of age and date reporting in the DHS surveys, 1985-2003. Methodological Reports No. 5; DHS Methodological Reports. Tamil Nadu: Macro International Inc, p96.
Retherford, R.D., Choe, M.K., Chen, J., Xiru, L., & Hongyan, C. (2005). How far has fertility in china really declined? Population and Development Review, 31(1):57-84. https://doi.org/10.2307/3401438
Retherford, R.D., & Rele, J.R. (1989). A decomposition of recent fertility changes in South Asia. Population and Development Review, 15(4):739-747. https://doi.org/10.2307/1972598
Schoumaker, B. (2013). A Stata module for computing fertility rates and TFRs from birth histories: Tfr2. Demographic Research, 28(38):1093-1144. https://doi.org/10.4054/DemRes.2013.28.38
Udjo, E.O. (1996). Is fertility falling in Zimbabwe. Journal of Biosocial Science, 28(1):25-35. https://doi.org/10.1017/s0021932000022069
Upadhyay, U.D., & Karasek, D. (2012). Women’s empowerment and ideal family size: An examination of DHS empowerment measures in Sub-Saharan Africa. International Perspectives on Sexual and Reproductive Health, 38(2):78-89. https://doi.org/10.1363/3807812