Page 67 - IJPS-7-2

International Journal of
Population Studies Age-adjusted measures for fertility transition

CEB as the depended variable (Ariho, et al., 2018; Ariho in comparison to the CEB using data from Ghana, Kenya,
& Nzabona, 2019). However, some scholars have analyzed Rwanda, and Zimbabwe. The study explored a multivariable
the TFR as the dependent variable, although such studies decomposition equation using the case of Zimbabwe to
have been few (Liu & Raftery, 2020; Retherford, et al., 2005; demonstrate the extent to which the choice of a fertility
Retherford & Rele, 1989). measure impacts the nature of the findings about driving
The use of CEB instead of TFR or its constituent forces of marital fertility trends.
parts, the age-specific fertility rate (ASFR), has several 2. Methods
conceptual and technical advantages. Conceptually, the
CEB is a measure of actual births that a woman has had. 2.1. Data
Technically, the CEB can be analyzed in its raw form This study analyzed DHS data from Ghana, Kenya, Rwanda,
without the need to transform it into a state that can and Zimbabwe collected between 1988 and 2015, focusing
be analyzed in a multivariable model. However, there on women who reported that they were in a union at the
are disadvantages associated with CEB, especially in time of data collection. This meant that women living
multivariable analyses aimed at establishing the factors with a male partner as husband and wife in cohabitation
influencing trends in fertility rates. First, the CEB is not or living together arrangements were considered married.
an age adjusted measure, and therefore, the change in its The sample sizes from each survey for each country are
average estimate between two time points may contradict reported in Table 1. Ghana and Kenya collected their first
that of the TFR which one may have used to argue for the DHS surveys in 1988 and 1989, respectively, and thereafter
need to investigate determinants of fertility transition. in in 1993, 1998, 2003, 2008, and 2014. Rwanda collected
Second, the CEB is an historical measure which may be its DHS surveys 1992, 2000, 2005, 2010, 2014/15, and
ineffective in capturing short-term changes in fertility 2019/20, but the latest was not included in the study for
patterns. When a birth cohort has unusually high birth rate comparison with other countries and Zimbabwe’s surveys
compared to those older and younger than them, its CEB were collected in 1988, 1994, 1999, 2005/06, 2010/11, and
estimate will potentially inflate the average CEB estimate 2015. The selection of the countries was based on three
for a country despite that the country may be experiencing considerations: (1) to have one country from each of the
a continuous decline in fertility rates. Due to its inability four sub-regions of sub-Saharan Africa, (2) a country must
to capture short-term changes in fertility, it can be argued have at least five rounds of DHS data, and (3) a country
that the use of age adjusted measures may be preferable in must have experienced significant fertility transition for
studies seeking to understand the driving factors of fertility at least one defined period between 1988 and 2015. All
transition. the DHS waves collected between 1988 and 2015 were
The age-adjusted measures, namely, the ASFR and analyzed.
age-specific marital fertility rate (ASMFR) in the case The DHS surveys were collected with funding from
of marital fertility, present a viable alternative for the the United States Agency for International Development
investigation of potential drivers of fertility transition in (USAID) and implemented by host countries’ statistical
multivariable models. Conceptually, age-adjusted fertility agencies with technical support from the Inner-City
rates are aligned to the TFR or total marital fertility rate Fund (ICF) Macro International Inc., usually cited as
(TMFR) when one is studying marital fertility as is the case ICF International (https://dhsprogram.com/). The DHS
in this study. The advantage of ASMFRs is that they reflect surveys collect data from nationally representative samples
contemporary fertility patterns based on recent births and of households on a variety of socioeconomic indicators
are thus more reflective of prevailing fertility determinants which include fertility, maternal and child health, mortality,
compared to historical fertility measures like CEB. and family planning among others (ICF International,
However, the main criticism of ASMFRs is that they are a 2016). The DHS uses a standardized instrument across
synthetic measure which does not reflect actual number of all the countries that it is implemented. This makes the
births that have been recorded. Nonetheless, the ability of DHS datasets comparable across countries and over time.
ASMFRs to reflect short-term changes in fertility provides The surveys have been instrumental in the study of the
a better opportunity for investigating time-dependent demographic transitions of SSA countries, allowing for
drivers of fertility rates. The study of time-dependent detailed investigations of the determinants of fertility
drivers is important in understanding the changing profile rates and drivers of transitions, especially in the African
of determinants of fertility rates, thus providing a platform countries, where there are unreliable and incomplete vital
for designing policy responses accordingly. This paper was registration data (Be-Ofuriyua & Emina, 2002; Bongaarts,
conceived to comparatively test this property of ASMFRs 2015; Cleland, et al., 2011; Gould & Brown, 1996; Indongo

Volume 7 Issue 2 (2021) 61 https://doi.org/10.36922/ijps.v7i2.354