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The contribution of contraception, marriage and postpartum insusceptibility to fertility levels in Uganda: an application of the aggregate fertility model

BACKGROUND: While recent studies have indicated that fertility has remained high in Uganda, no systematic attempt has been made to identify the factors responsible for this persistent trend and to quantify these factors. This paper uses the Uganda Demographic and Health Surveys (UDHS) of 2006 and 20...

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Detalles Bibliográficos
Autores principales: Rutaremwa, Gideon, Galande, Johnstone, Nviiri, Hellen Laetitia, Akiror, Edith, Jhamba, Tapiwa
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2015
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5424367/
https://www.ncbi.nlm.nih.gov/pubmed/28620521
http://dx.doi.org/10.1186/s40738-015-0009-y
Descripción
Sumario:BACKGROUND: While recent studies have indicated that fertility has remained high in Uganda, no systematic attempt has been made to identify the factors responsible for this persistent trend and to quantify these factors. This paper uses the Uganda Demographic and Health Surveys (UDHS) of 2006 and 2011, to examine the contribution contraceptive use, marriage and postpartum infecundability on one hand and Total Fertility Rate (TFR) on the other. We constructed a database using the Woman’s Questionnaire from the UDHS 2006 and 2011. We then apply Bongaarts aggregate fertility model procedures to derive estimates of total fertility rate for the different socioeconomic groups. RESULTS: The findings indicate that a woman’s contraceptive behavior; marriage status and postpartum infecundability (also referred to as postpartum insusceptibility due to postpartum amenorrhea, which is intended to measure the effects on fertility breastfeeding), are important predictors of fertility outcomes. The results also show that higher education levels and urban residence are consistently associated with lower fertility rates and are positively associated with contraceptive use. Other key predictors of fertility include: wealth status, and region of residence. CONCLUSION: The country needs to scale-up target interventions that are aimed at uplifting the education status of women and improving their economic wellbeing, because such interventions have a positive impact on fertility reduction and on improving maternal and reproductive health outcomes.