The age at which child bearing begins, influences the number of children a woman bears throughout her reproductive period in the absence of any active fertility control. This study employed both parametric and non-parametric survival analysis techniques, with a cohort of women within the reproductive age (15-49 years), to determine the statistical distribution of the age at first birth of a woman from her time of birth and identify the significant prognostic factors determining the timing of first birth of Ghanaian women. Using data from the Ghana Demographic and Health Survey (GDHS), the study fitted several parametric Accelerated Failure Time models, from which the best parametric distribution for age at first birth was selected. The results revealed that, the average age at first birth was about 20 years, with more than 87.4% of the women having giving birth before they attained 25 years of age. The age at first birth among the Ghanaian women was best modeled by the log-logistic model. By this model, the age at which a woman had her first birth was determined, at the 10% significance level, by her Age at first marriage, her Educational level, her Wealth Status and whether or not the women practiced family planning before their first birth.
Published in | American Journal of Theoretical and Applied Statistics (Volume 4, Issue 2) |
DOI | 10.11648/j.ajtas.20150402.11 |
Page(s) | 41-52 |
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. |
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Copyright © The Author(s), 2015. Published by Science Publishing Group |
Survival, First Birth, Accelerated Failure Time Models, Waiting Time, Age at First Birth
[1] | Abhiman D., (2006). Population Evolution Model and its Application for the Estimation of Stable Fertility Rate of Indian States: Demography India, 35(1): 95-110. |
[2] | Akaike, H., (1974). A New Look at the Statistical Model Identification. IEEE Translation on Automatic Control, AC-19:716-723. |
[3] | Amuedo-Dorantes, C. and Kimmel J., (2004), ‘USA: Can the Family Earnings Gap be Reduced by Postponing Maternity?’ In: Gustafsson, S. & A. Kalwij (eds.) Forthcoming. Education and Postponement of Maternity. |
[4] | Becker S, (2001). Population Growth: American Journal of Public Health, 91(7): 1139-1140. |
[5] | Blackburn, M. L., Bloom D.E. and Neumark D., (1993). Fertility Timing, Wages and Human Capital. Journal of Population Economics, 6: 1-30. |
[6] | Bloom, D. E. and Trussel J., (1984). What Are the Determinants of Delayed Childbearing and Permanent Childlessness in the United States? Demography, 21 (4): 591-609. |
[7] | Cigno, A. (1991). Economics of the Family. Oxford: Oxford University Press. |
[8] | Cigno, A. and Ermisch J., (1989). A Micro -Economic Analysis of the Timing of Births. European Economic Review, 33 (4): 737-60. |
[9] | Fisher, B., (1991). Affirming Social Value, Women without Children in Maines: D. R. Social organization and social process, essays in honour of Anselm Strauss. |
[10] | Gillespie R., (2001). Contextualising Voluntary Childlessness within a Postmodern Model of Reproduction: Implications For Health And Social Needs. Critical Social Policy, 21(2). |
[11] | Gustafsson, S. and Wetzels C., (2000). Optimal age at maternity in Germany, Great-Britain, the Netherlands and Sweden.’ In: Meulders, D. (ed.) Gender and the Labor Market. Econometric Evidence on Obstacles in Achieving Gender Equality. Applied Econometric Association Conference Series, London: Mac Millan. |
[12] | Gustafsson, S. S., (2001). Optimal Age at Motherhood: Theoretical and Empirical Considerations on Postponement of Maternity in Europe. Journal of Population Economics, 14: 225-247. |
[13] | Hagman M., (2001). The world in 2050,More crowded, urban and aged:Bulletin of the World Health organization, 79(5): 484. |
[14] | Kasarda, J. D., Billy J.O.G. and West K., (1986). Status Enhancement and Fertility, New York. |
[15] | Kohler H.P., BillariF. C. and Ortega J. A., (2002). The emergence of lowest-low fertility in Europe during the 1990s: Population and Development Review, 28 (4): 641-680. |
[16] | Kravdal, O., (1994). The Importance of Economic Activity, Economic Potential and Economic Resources for the Timing of First Births in Norway. Population Studies, 48 (2): 249-67. |
[17] | Lisle L., (1996). Without Child, New York: Routledge. |
[18] | Logubayom I. A., and Luguterah A., (2013). Survival Analysis of Time to First Birth after Marriage. Research on Humanities and Social Sciences, 3 (12): 2222-2863. |
[19] | MacInnes J., (2003). A Promising Relationship. Sociology and Demography. |
[20] | McAllister F. and Clarke L., (1998).Choosing Childlessness in London. Family Policy Studies Centre. |
[21] | Murphy M., (1992). Economic models of fertility in post-war Britain: A conceptual and statistical re-interpretation. Population Studies, 46 (2): 235-258. |
[22] | Murphy M., (1993).The contraceptive pill and women’s employment as factors of fertility change in Britain 1963-1980: A challenge to conventional view. Population Studies, 47 (2): 221-243. |
[23] | Peto R. and Peto, J., (1972). Asympotically Efficient Rank Invariant Procedure. Journal of Rural Statistical Society, Series A, 135: 185-207. |
[24] | Schwarz, G. E., (1978). Estimating the Dimension of a Model. Annals of Statistics, 6:461-464. |
[25] | Sobotka T., (2004). Postponement of Childbearing and Low Fertility in Europe: PhD thesis, University of Groningen, Dutch University Press, Amsterdam. |
APA Style
Logubayom Anuwoje Ida, Luguterah Albert. (2015). The Statistical Distribution and Determinants of Mother’s Age at First Birth. American Journal of Theoretical and Applied Statistics, 4(2), 41-52. https://doi.org/10.11648/j.ajtas.20150402.11
ACS Style
Logubayom Anuwoje Ida; Luguterah Albert. The Statistical Distribution and Determinants of Mother’s Age at First Birth. Am. J. Theor. Appl. Stat. 2015, 4(2), 41-52. doi: 10.11648/j.ajtas.20150402.11
AMA Style
Logubayom Anuwoje Ida, Luguterah Albert. The Statistical Distribution and Determinants of Mother’s Age at First Birth. Am J Theor Appl Stat. 2015;4(2):41-52. doi: 10.11648/j.ajtas.20150402.11
@article{10.11648/j.ajtas.20150402.11, author = {Logubayom Anuwoje Ida and Luguterah Albert}, title = {The Statistical Distribution and Determinants of Mother’s Age at First Birth}, journal = {American Journal of Theoretical and Applied Statistics}, volume = {4}, number = {2}, pages = {41-52}, doi = {10.11648/j.ajtas.20150402.11}, url = {https://doi.org/10.11648/j.ajtas.20150402.11}, eprint = {https://article.sciencepublishinggroup.com/pdf/10.11648.j.ajtas.20150402.11}, abstract = {The age at which child bearing begins, influences the number of children a woman bears throughout her reproductive period in the absence of any active fertility control. This study employed both parametric and non-parametric survival analysis techniques, with a cohort of women within the reproductive age (15-49 years), to determine the statistical distribution of the age at first birth of a woman from her time of birth and identify the significant prognostic factors determining the timing of first birth of Ghanaian women. Using data from the Ghana Demographic and Health Survey (GDHS), the study fitted several parametric Accelerated Failure Time models, from which the best parametric distribution for age at first birth was selected. The results revealed that, the average age at first birth was about 20 years, with more than 87.4% of the women having giving birth before they attained 25 years of age. The age at first birth among the Ghanaian women was best modeled by the log-logistic model. By this model, the age at which a woman had her first birth was determined, at the 10% significance level, by her Age at first marriage, her Educational level, her Wealth Status and whether or not the women practiced family planning before their first birth.}, year = {2015} }
TY - JOUR T1 - The Statistical Distribution and Determinants of Mother’s Age at First Birth AU - Logubayom Anuwoje Ida AU - Luguterah Albert Y1 - 2015/02/16 PY - 2015 N1 - https://doi.org/10.11648/j.ajtas.20150402.11 DO - 10.11648/j.ajtas.20150402.11 T2 - American Journal of Theoretical and Applied Statistics JF - American Journal of Theoretical and Applied Statistics JO - American Journal of Theoretical and Applied Statistics SP - 41 EP - 52 PB - Science Publishing Group SN - 2326-9006 UR - https://doi.org/10.11648/j.ajtas.20150402.11 AB - The age at which child bearing begins, influences the number of children a woman bears throughout her reproductive period in the absence of any active fertility control. This study employed both parametric and non-parametric survival analysis techniques, with a cohort of women within the reproductive age (15-49 years), to determine the statistical distribution of the age at first birth of a woman from her time of birth and identify the significant prognostic factors determining the timing of first birth of Ghanaian women. Using data from the Ghana Demographic and Health Survey (GDHS), the study fitted several parametric Accelerated Failure Time models, from which the best parametric distribution for age at first birth was selected. The results revealed that, the average age at first birth was about 20 years, with more than 87.4% of the women having giving birth before they attained 25 years of age. The age at first birth among the Ghanaian women was best modeled by the log-logistic model. By this model, the age at which a woman had her first birth was determined, at the 10% significance level, by her Age at first marriage, her Educational level, her Wealth Status and whether or not the women practiced family planning before their first birth. VL - 4 IS - 2 ER -