An Analysis of the Determinants of Fertility Differentials Amongst the Poorest Women Population in Kenya

Robert Mathenge Mutwiri

doi:doi:10.11648/j.ijsd.20190503.13

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An Analysis of the Determinants of Fertility Differentials Amongst the Poorest Women Population in Kenya

Robert Mathenge Mutwiri

Published in International Journal of Statistical Distributions and Applications (Volume 5, Issue 3)

Received: 2 July 2019 Accepted: 27 July 2019 Published: 13 August 2019

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Abstract

Fertility is one of the major elements in population dynamics that has the highest significant contribution towards population size and structure in the world. In Kenya, fertility levels have been on the decline from approximately 8.1 children in 1979 to 3.9 children in 2014 but still, it is considered high compared to the country’s target of 2.6 by 2030. This has potentially negative consequences to the economic growth and development of a country. The main objective of this study is to determine demographic, socio-economic and cultural factors that explain fertility differential among poor women of childbearing age. A binary logistic regression model was fitted to DHS 2014 data using SPSS Version16. The total number of women in childbearing age is based on 7,262 women who have at least one child and whose age ranges from 15 to 49 years. The majority of women were married 4685 (64.5%), followed by never and formally married 1522 (21.0%) and living with partner 1055 (14.5%) respectively). In the analyses, all the variables Region, women educational level, marital status, age at first marriage and age in 5-years group were found to have a significant effect on the total number of children ever born at a significance level of 5%. From the fitted logistic regression model, the estimated odds ratio for the variable region reference category is Nyanza/Western region. The value of the odds ratio exp(β) =1.060775, for the region that the odds of having TCEB greater than or equals to five children for the North Eastern region has 6.0775% more than women in Nyanza/Western Region (OR=1.060775, C.I=0.873716-1.287883) and its effect is statistically significant.

Published in	International Journal of Statistical Distributions and Applications (Volume 5, Issue 3)
DOI	10.11648/j.ijsd.20190503.13
Page(s)	60-66
Creative Commons	This is an Open Access article, distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution and reproduction in any medium or format, provided the original work is properly cited.
Copyright	Copyright © The Author(s), 2019. Published by Science Publishing Group

Keywords

Fertility Levels, Binary Logistic Regression Model, DHS Data, Total Fertility Rate

References

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Robert Mathenge Mutwiri. (2019). An Analysis of the Determinants of Fertility Differentials Amongst the Poorest Women Population in Kenya. International Journal of Statistical Distributions and Applications, 5(3), 60-66. https://doi.org/10.11648/j.ijsd.20190503.13

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Robert Mathenge Mutwiri. An Analysis of the Determinants of Fertility Differentials Amongst the Poorest Women Population in Kenya. Int. J. Stat. Distrib. Appl. 2019, 5(3), 60-66. doi: 10.11648/j.ijsd.20190503.13

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Robert Mathenge Mutwiri. An Analysis of the Determinants of Fertility Differentials Amongst the Poorest Women Population in Kenya. Int J Stat Distrib Appl. 2019;5(3):60-66. doi: 10.11648/j.ijsd.20190503.13

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@article{10.11648/j.ijsd.20190503.13,
  author = {Robert Mathenge Mutwiri},
  title = {An Analysis of the Determinants of Fertility Differentials Amongst the Poorest Women Population in Kenya},
  journal = {International Journal of Statistical Distributions and Applications},
  volume = {5},
  number = {3},
  pages = {60-66},
  doi = {10.11648/j.ijsd.20190503.13},
  url = {https://doi.org/10.11648/j.ijsd.20190503.13},
  eprint = {https://article.sciencepublishinggroup.com/pdf/10.11648.j.ijsd.20190503.13},
  abstract = {Fertility is one of the major elements in population dynamics that has the highest significant contribution towards population size and structure in the world. In Kenya, fertility levels have been on the decline from approximately 8.1 children in 1979 to 3.9 children in 2014 but still, it is considered high compared to the country’s target of 2.6 by 2030. This has potentially negative consequences to the economic growth and development of a country. The main objective of this study is to determine demographic, socio-economic and cultural factors that explain fertility differential among poor women of childbearing age. A binary logistic regression model was fitted to DHS 2014 data using SPSS Version16. The total number of women in childbearing age is based on 7,262 women who have at least one child and whose age ranges from 15 to 49 years. The majority of women were married 4685 (64.5%), followed by never and formally married 1522 (21.0%) and living with partner 1055 (14.5%) respectively). In the analyses, all the variables Region, women educational level, marital status, age at first marriage and age in 5-years group were found to have a significant effect on the total number of children ever born at a significance level of 5%. From the fitted logistic regression model, the estimated odds ratio for the variable region reference category is Nyanza/Western region. The value of the odds ratio exp(β) =1.060775, for the region that the odds of having TCEB greater than or equals to five children for the North Eastern region has 6.0775% more than women in Nyanza/Western Region (OR=1.060775, C.I=0.873716-1.287883) and its effect is statistically significant.},
 year = {2019}
}

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TY  - JOUR
T1  - An Analysis of the Determinants of Fertility Differentials Amongst the Poorest Women Population in Kenya
AU  - Robert Mathenge Mutwiri
Y1  - 2019/08/13
PY  - 2019
N1  - https://doi.org/10.11648/j.ijsd.20190503.13
DO  - 10.11648/j.ijsd.20190503.13
T2  - International Journal of Statistical Distributions and Applications
JF  - International Journal of Statistical Distributions and Applications
JO  - International Journal of Statistical Distributions and Applications
SP  - 60
EP  - 66
PB  - Science Publishing Group
SN  - 2472-3509
UR  - https://doi.org/10.11648/j.ijsd.20190503.13
AB  - Fertility is one of the major elements in population dynamics that has the highest significant contribution towards population size and structure in the world. In Kenya, fertility levels have been on the decline from approximately 8.1 children in 1979 to 3.9 children in 2014 but still, it is considered high compared to the country’s target of 2.6 by 2030. This has potentially negative consequences to the economic growth and development of a country. The main objective of this study is to determine demographic, socio-economic and cultural factors that explain fertility differential among poor women of childbearing age. A binary logistic regression model was fitted to DHS 2014 data using SPSS Version16. The total number of women in childbearing age is based on 7,262 women who have at least one child and whose age ranges from 15 to 49 years. The majority of women were married 4685 (64.5%), followed by never and formally married 1522 (21.0%) and living with partner 1055 (14.5%) respectively). In the analyses, all the variables Region, women educational level, marital status, age at first marriage and age in 5-years group were found to have a significant effect on the total number of children ever born at a significance level of 5%. From the fitted logistic regression model, the estimated odds ratio for the variable region reference category is Nyanza/Western region. The value of the odds ratio exp(β) =1.060775, for the region that the odds of having TCEB greater than or equals to five children for the North Eastern region has 6.0775% more than women in Nyanza/Western Region (OR=1.060775, C.I=0.873716-1.287883) and its effect is statistically significant.
VL  - 5
IS  - 3
ER  -

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Robert Mathenge Mutwiri

Department of Physical sciences, Kirinya University, Kerugoya, Kenya

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Robert Mathenge Mutwiri. (2019). An Analysis of the Determinants of Fertility Differentials Amongst the Poorest Women Population in Kenya. International Journal of Statistical Distributions and Applications, 5(3), 60-66. https://doi.org/10.11648/j.ijsd.20190503.13

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Robert Mathenge Mutwiri. An Analysis of the Determinants of Fertility Differentials Amongst the Poorest Women Population in Kenya. Int. J. Stat. Distrib. Appl. 2019, 5(3), 60-66. doi: 10.11648/j.ijsd.20190503.13

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Robert Mathenge Mutwiri. An Analysis of the Determinants of Fertility Differentials Amongst the Poorest Women Population in Kenya. Int J Stat Distrib Appl. 2019;5(3):60-66. doi: 10.11648/j.ijsd.20190503.13

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@article{10.11648/j.ijsd.20190503.13,
  author = {Robert Mathenge Mutwiri},
  title = {An Analysis of the Determinants of Fertility Differentials Amongst the Poorest Women Population in Kenya},
  journal = {International Journal of Statistical Distributions and Applications},
  volume = {5},
  number = {3},
  pages = {60-66},
  doi = {10.11648/j.ijsd.20190503.13},
  url = {https://doi.org/10.11648/j.ijsd.20190503.13},
  eprint = {https://article.sciencepublishinggroup.com/pdf/10.11648.j.ijsd.20190503.13},
  abstract = {Fertility is one of the major elements in population dynamics that has the highest significant contribution towards population size and structure in the world. In Kenya, fertility levels have been on the decline from approximately 8.1 children in 1979 to 3.9 children in 2014 but still, it is considered high compared to the country’s target of 2.6 by 2030. This has potentially negative consequences to the economic growth and development of a country. The main objective of this study is to determine demographic, socio-economic and cultural factors that explain fertility differential among poor women of childbearing age. A binary logistic regression model was fitted to DHS 2014 data using SPSS Version16. The total number of women in childbearing age is based on 7,262 women who have at least one child and whose age ranges from 15 to 49 years. The majority of women were married 4685 (64.5%), followed by never and formally married 1522 (21.0%) and living with partner 1055 (14.5%) respectively). In the analyses, all the variables Region, women educational level, marital status, age at first marriage and age in 5-years group were found to have a significant effect on the total number of children ever born at a significance level of 5%. From the fitted logistic regression model, the estimated odds ratio for the variable region reference category is Nyanza/Western region. The value of the odds ratio exp(β) =1.060775, for the region that the odds of having TCEB greater than or equals to five children for the North Eastern region has 6.0775% more than women in Nyanza/Western Region (OR=1.060775, C.I=0.873716-1.287883) and its effect is statistically significant.},
 year = {2019}
}

Copy | Download

TY  - JOUR
T1  - An Analysis of the Determinants of Fertility Differentials Amongst the Poorest Women Population in Kenya
AU  - Robert Mathenge Mutwiri
Y1  - 2019/08/13
PY  - 2019
N1  - https://doi.org/10.11648/j.ijsd.20190503.13
DO  - 10.11648/j.ijsd.20190503.13
T2  - International Journal of Statistical Distributions and Applications
JF  - International Journal of Statistical Distributions and Applications
JO  - International Journal of Statistical Distributions and Applications
SP  - 60
EP  - 66
PB  - Science Publishing Group
SN  - 2472-3509
UR  - https://doi.org/10.11648/j.ijsd.20190503.13
AB  - Fertility is one of the major elements in population dynamics that has the highest significant contribution towards population size and structure in the world. In Kenya, fertility levels have been on the decline from approximately 8.1 children in 1979 to 3.9 children in 2014 but still, it is considered high compared to the country’s target of 2.6 by 2030. This has potentially negative consequences to the economic growth and development of a country. The main objective of this study is to determine demographic, socio-economic and cultural factors that explain fertility differential among poor women of childbearing age. A binary logistic regression model was fitted to DHS 2014 data using SPSS Version16. The total number of women in childbearing age is based on 7,262 women who have at least one child and whose age ranges from 15 to 49 years. The majority of women were married 4685 (64.5%), followed by never and formally married 1522 (21.0%) and living with partner 1055 (14.5%) respectively). In the analyses, all the variables Region, women educational level, marital status, age at first marriage and age in 5-years group were found to have a significant effect on the total number of children ever born at a significance level of 5%. From the fitted logistic regression model, the estimated odds ratio for the variable region reference category is Nyanza/Western region. The value of the odds ratio exp(β) =1.060775, for the region that the odds of having TCEB greater than or equals to five children for the North Eastern region has 6.0775% more than women in Nyanza/Western Region (OR=1.060775, C.I=0.873716-1.287883) and its effect is statistically significant.
VL  - 5
IS  - 3
ER  -

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