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The current fertility rate(FR) reporting in developing and under developed countries of the globe has drawn the attention of national and demographic planners in seeking for solution to reduce the population growth and its attendant global consequences. It is in this light that this study seeks to determine some significant demographic characterization responsible for influencing fertility behavior and differentials. Using a random sample of 570 mothers both from a rural and urban environment, a set of data on demographic characteristics were obtained and analyzed using the binary logistic regression model. Findings revealed a strong evident that the education level of women, location of resident of families and labour participation has significant effect in influencing the fertility of women and perhaps create fertility differentials. In this communication it was observed that women with little or no education, living in rural location and lack of a decent employment is associated with high fertility behavior.

Keywords: Demographic characteristics, Fertility differential, Binary Logistic regression, Female labour force participation, Birth rate

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Emudiaga Eric, R. & K.A., O (2020). An_Assessment_of_the_Impact_of_Selected_Demographic_Characteristics_on_Fertility_Differentials. Afribary. Retrieved from

MLA 8th

Emudiaga Eric, Rukevwe, and Odior K.A. "An_Assessment_of_the_Impact_of_Selected_Demographic_Characteristics_on_Fertility_Differentials" Afribary. Afribary, 10 Apr. 2020, Accessed 27 Jul. 2021.


Emudiaga Eric, Rukevwe, and Odior K.A. . "An_Assessment_of_the_Impact_of_Selected_Demographic_Characteristics_on_Fertility_Differentials". Afribary, Afribary, 10 Apr. 2020. Web. 27 Jul. 2021. < >.


Emudiaga Eric, Rukevwe and K.A., Odior . "An_Assessment_of_the_Impact_of_Selected_Demographic_Characteristics_on_Fertility_Differentials" Afribary (2020). Accessed July 27, 2021.