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Multilevel Modeling of Determinants of Fertility Status of Married Women in Ethiopia

Received: 21 December 2014     Accepted: 11 January 2015     Published: 21 January 2015
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Abstract

The main objective of this study is to investigate the determinant factors of fertility status of married women in Ethiopia and to examine the reasons for variations of fertility across regions of Ethiopia based on data on 7052 married women obtained from Ethiopian Demographic and Health Survey (EDHS, 2011). Multilevel binary logistic regression models on fertility status of married women were employed. This study revealed that the random intercept and fixed slope model fits the data significantly better than the other multilevel logistic regression models. The results confirmed that woman’s education level, sex of household head, being visited by family planning worker last twelve months, child loss experience, woman’s occupation, religion and age of woman at first birth were found to be significant determinants and also contributing factors for variation in fertility status of married women among the regions of Ethiopia. In random intercept model the overall variance of constant term was found to be statistically significant implies that women with the same characteristics in two different regions have different fertility status: that is, there is a clear region effect. In this study multilevel model best fit the data as compared to single level model.

Published in American Journal of Theoretical and Applied Statistics (Volume 4, Issue 1)
DOI 10.11648/j.ajtas.20150401.14
Page(s) 19-25
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), 2015. Published by Science Publishing Group

Keywords

DHS, High Fertility, Multilevel Logistic Analysis, Random Intercept Model

References
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[2] United Nations (2009). World Population Pros¬pects: New York: Popu¬lation Division, Department of Economic and Social Affairs, United Nations.
[3] CSA and UNFPA (2008), Ethiopia, Summary and Statistical Report of the 2007 Population & Housing Census, Population Census Commission. Addis Ababa, Ethiopia: UNFPA.
[4] Ethiopia Ministry of Finance and Economic Development (2008), Population Department, Population and Development Ethiopia, no. 1.
[5] ILO (2003). Working Out of Poverty, Report of the Director-General, International Labour Conference, 91st Session, Geneva.
[6] Mekbib, Tekle-Ab, Y.G., Hiwot, and M., Fantahun (2002). Survey of Unsafe Abortion in Selected Health Facilities in Ethiopia (unpublished report).
[7] EDHS (2011). Preliminary and final Report. Addis Ababa, Ethiopia and Calverton, Maryland, USA .
[8] CSA and ORC Marco (2001). Ethiopia Demographic and Health Survey. Addis Ababa. Ethiopia and Calverton, Maryland, USA.
[9] United Nations Population Fund (2005). International Migration and the Millennium Development Goals. Selected Papers of the UNFPA Expert Group Meeting; Marrakesh, Morocco. New York: UNFPA.
[10] Snijders, T. A. B. and Roel J. Bosker (1999). An Introduction to Basic and Advanced Multilevel Modeling, 1st ed. Department of Statistics, University of Poone.
[11] Goldstein, H. (1991). Nonlinear Multilevel Models with an Application to Discrete Response Data. Biometrika, Vol. 78: PP. 45–51.
[12] Goldstein, H. and Rabash, J. (1996). Improved Approximations for Multilevel Models with Binary Responses. Journal of Royal Statistics Society, Vol. 159, PP. 505- 513.
[13] Hox, J. (2002). Multilevel Analysis: Techniques and Applications. Mahwah, N.J: Lawrence Erlbaum.
[14] Samson G. and Mulugeta B. (2009). Level and Differentials of Fertility in Awassa Town, Southern Ethiopia. Afr J Reprod Health; Vol. 13[1]: PP. 93-112
[15] Islam, S. and Kamrun, M. (2009). Fertility Transition in Bangladesh: The Role of Education. Proc. Pakistan Acad. Sci. Vol. 46(4): PP. 195-201.
[16] Adhikari, R. (2010). Demographic, Socio-economic, and Cultural Factors Affecting Fertility Differentials in Nepal. BMC Pregnancy and Childbirth, Vol. 10: PP. 19.
[17] Adhikari, R., Kusol, S. and Prasartkul, P. (2009). Correlates of Unintended Pregnancy among Currently Pregnant Married Women in Nepal. BMC International Health and Human Rights, Vol. 9, PP. 17.
[18] Eshetu W. (1998). The influence of Selected Social and Demographic Factors on Fertility: The Case of Bahirdar Town. Ethiopian Journal of Development Research; Vol. 20(1): PP. 1-19.
[19] Tewodros A., Jemal H. and Dereje H. (2010). Determinants of Adolescent Fertility in Ethiopia. Ethiop. J. Health Dev.; Vol. 24(1): PP. 30-38
[20] Bekele B. (2011). Determinants of High Fertility Status among Married Women: A Case Control Study in Kersa District, Eastern Ethiopia. MPH Thesis. Haramaya University, Ethiopia.
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  • APA Style

    Anteneh Mulugeta Eyasu. (2015). Multilevel Modeling of Determinants of Fertility Status of Married Women in Ethiopia. American Journal of Theoretical and Applied Statistics, 4(1), 19-25. https://doi.org/10.11648/j.ajtas.20150401.14

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    ACS Style

    Anteneh Mulugeta Eyasu. Multilevel Modeling of Determinants of Fertility Status of Married Women in Ethiopia. Am. J. Theor. Appl. Stat. 2015, 4(1), 19-25. doi: 10.11648/j.ajtas.20150401.14

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    AMA Style

    Anteneh Mulugeta Eyasu. Multilevel Modeling of Determinants of Fertility Status of Married Women in Ethiopia. Am J Theor Appl Stat. 2015;4(1):19-25. doi: 10.11648/j.ajtas.20150401.14

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  • @article{10.11648/j.ajtas.20150401.14,
      author = {Anteneh Mulugeta Eyasu},
      title = {Multilevel Modeling of Determinants of Fertility Status of Married Women in Ethiopia},
      journal = {American Journal of Theoretical and Applied Statistics},
      volume = {4},
      number = {1},
      pages = {19-25},
      doi = {10.11648/j.ajtas.20150401.14},
      url = {https://doi.org/10.11648/j.ajtas.20150401.14},
      eprint = {https://article.sciencepublishinggroup.com/pdf/10.11648.j.ajtas.20150401.14},
      abstract = {The main objective of this study is to investigate the determinant factors of fertility status of married women in Ethiopia and to examine the reasons for variations of fertility across regions of Ethiopia based on data on 7052 married women obtained from Ethiopian Demographic and Health Survey (EDHS, 2011). Multilevel binary logistic regression models on fertility status of married women were employed. This study revealed that the random intercept and fixed slope model fits the data significantly better than the other multilevel logistic regression models. The results confirmed that woman’s education level, sex of household head, being visited by family planning worker last twelve months, child loss experience, woman’s occupation, religion and age of woman at first birth were found to be significant determinants and also contributing factors for variation in fertility status of married women among the regions of Ethiopia. In random intercept model the overall variance of constant term was found to be statistically significant implies that women with the same characteristics in two different regions have different fertility status: that is, there is a clear region effect. In this study multilevel model best fit the data as compared to single level model.},
     year = {2015}
    }
    

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    T1  - Multilevel Modeling of Determinants of Fertility Status of Married Women in Ethiopia
    AU  - Anteneh Mulugeta Eyasu
    Y1  - 2015/01/21
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    JF  - American Journal of Theoretical and Applied Statistics
    JO  - American Journal of Theoretical and Applied Statistics
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    AB  - The main objective of this study is to investigate the determinant factors of fertility status of married women in Ethiopia and to examine the reasons for variations of fertility across regions of Ethiopia based on data on 7052 married women obtained from Ethiopian Demographic and Health Survey (EDHS, 2011). Multilevel binary logistic regression models on fertility status of married women were employed. This study revealed that the random intercept and fixed slope model fits the data significantly better than the other multilevel logistic regression models. The results confirmed that woman’s education level, sex of household head, being visited by family planning worker last twelve months, child loss experience, woman’s occupation, religion and age of woman at first birth were found to be significant determinants and also contributing factors for variation in fertility status of married women among the regions of Ethiopia. In random intercept model the overall variance of constant term was found to be statistically significant implies that women with the same characteristics in two different regions have different fertility status: that is, there is a clear region effect. In this study multilevel model best fit the data as compared to single level model.
    VL  - 4
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Author Information
  • Department of Statistics, Arba Minch University, Arba Minch, Ethiopia

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