Ghana has experienced an unexpectedly rapid fertility decline over the past 30 years, which has not been adequately explained in light of the concurrent persistently low usage of contraception. Factors at both the individual and contextual level have been investigated for their role in the determination of fertility levels and differentials in Ghana however, the relative contributions of the contextual factors compared with the individual factors to variation in fertility has rarely been studied. This study investigated how much of the observed district level fertility differentials are attributable to contextual versus compositional effects using a multilevel framework.
Data from the second round of the Performance Monitoring and Accountability 2020 survey were analyzed using a 2-level multilevel framework with individuals as the first level and districts at the second level. Age, education, wealth, marital status, history of family planning use and age at first sex were used as individual-level predictors while urban/rural residence was included as a district-level explanatory variable. Multilevel multivariate regression models with interaction terms included were used to determine how much of the variance was attributable to each level.
Age, education, marital status, age at first sex and history of family planning were found to significantly influence cumulative fertility, however, most of the observed effects of these variables were significantly attenuated when age interactions were included in the models. The models also found that only 3-4% of the variance in cumulative fertility could be attributed to contextual effects as opposed to individual effects.

Cumulative fertility is primarily determined by individual-level characteristics, and how these characteristics change with age and over time. Thus, policies aimed at fertility regulation should pay particular attention to improving the socio-economic circumstances of women.

This chapter introduces the basic concepts of fertility, and discusses the current levels and differentials in fertility in Ghana, and what is known about the factors that have contributed to the current state of affairs. It then identifies gaps in the current state of knowledge, which are summarized in the form of a problem statement. It goes on to provide justification for this study in terms of the potential usefulness of the study results. All this is put in the context of a conceptual framework that is derived from two current theories of fertility decline. Finally there is a short discussion of the scope of this study.

Fertility decline is one of the main aims of Ghana’s National Population Policy of 1994. This policy recognizes “…the crucial importance of a wide understanding of the deleterious effects of unlimited population growth and the means by which couples can safely and effectively control their fertility,” (National Population Council, 1994). It aims to reduce the total fertility rate to 4.0 by 2010 and to 3.0 by 2020; (Addo, 1987). Achieving sustainable fertility decline across the country requires a thorough understanding of the factors which influence fertility so that programs can be designed to modify these factors as needed to achieve the goal.

Ghana has achieved remarkable fertility decline in the past four decades. The total fertility rate of Ghana has fallen from the 6.47 recorded in the World Fertility Survey of 1979 (Cleland & Hobcraft, 1985; Cleland & Scott, 1987) to about 3.7 in 2013 (PMA2020, 2013). While varied reasons have been given for this dramatic decline (Benefo & Schultz, 1996; Bongaarts, 2006; Boserup, 1985; Bryant, 2007; John C. Caldwell, Orubuloye, & Caldwell, 1992), fertility transition experienced in Ghana has not conformed to established models. For example, despite the fact that increased contraceptive use is thought to be one of the major drivers of fertility decline across the world, the progress of fertility decline in Ghana has been achieved without a commensurate increase in the utilization of contraception (Benefo & Schultz, 1996; Blanc & Grey, 2002)

Researchers investigating the factors which influence fertility decline have to keep in mind the fact that the levels of aggregation at which they define their variables have an impact on the results they obtain (Bliese, 2000; Klein & Kozlowski, 2000)(Bollen & Van de Sompel, 2006) Population fertility levels result from the aggregation of the individual reproductive behaviors of the members of the population and thus, it would appear that variables used to predict fertility should be defined at the individual level. However, contextual factors such as social norms on marriage and contraception influence individual reproductive behavior. Policies and programs aimed at achieving fertility change are often designed and implemented at population level and these may influence individual reproductive behavior (Bongaarts, 1994; Pritchett, 1994). Thus, there is a strong argument to be made for the inclusion of aggregated and population-level variables in models of fertility (Lloyd & Gage-Brandon, 1994) (Bongaarts, 2001) (John C. Caldwell, 1979).

This interplay between contextual and individual level variables in the determination of reproductive behavior and fertility levels has been studied by a number of researchers including Zaba et al, who in 2004 observed that significant behavioral changes such as increasing age at first sex could be attributed to “tremendous socio-economic change resulting in increased levels of education, wealth accompanied by significant urbanization” and that these were ultimately responsible for the observed decline in fertility in Ghana. (Zaba, Pisani, Slaymaker, & Boerma, 2004) The determinants of fertility interact with each other not just within, but also across levels. The complexity of some of these interactions is illustrated by the interaction between education and urban/rural residence in their effect on fertility. While urban fertility has been consistently found to be lower than rural fertility (Muhuri, 1994) (Mboup, 1998) (Lee, 1993) (Alene, 2008), urban/rural residence is also known to be associated with higher levels of education and literacy (including girl child education) (Zhang, 2006) (Kravdal, 2002), which are also linked in turn to higher levels of income and wealth (Barrett, Reardon, & Webb, 2001) (Sahn & Stifel, 2003) higher usage of contraception, and lower levels of unmet need for contraception (Khan, Mishra, Arnold, & Abderrahim, 2007) (Adongo et al., 1997) (Ainsworth, Beegle, & Nyamete, 1996)). The extent to which the observed urban-rural differentials in fertility are due to differentials in education levels between urban and rural folk, as opposed to differential distributions of the determinants of fertility in the urban-rural space has been less studied and is not clear. Considering the complexity of the determination of fertility, the population policy of Ghana would appear to be right in its broad based approach to fertility decline.

For more Public Health Projects Click here
Item Type: Ghanaian Topic  |  Size: 88 pages  |  Chapters: 1-5
Format: MS Word  |  Delivery: Within 30Mins.


No comments:

Post a Comment

Note: Only a member of this blog may post a comment.

Search for your topic here

See full list of Project Topics under your Department Here!

Featured Post


A hypothesis is a description of a pattern in nature or an explanation about some real-world phenomenon that can be tested through observ...

Popular Posts