Application of Survival Analysis in Studies of Human Ontogeny

Magdalena Kosińska, Anita Szwed

Department of Human Biological Development, Institute of Anthropology, Faculty of Biology, Adam Mickiewicz University, Poznań, Poland.

DOI: 10.4236/am.2014.511162                

Abstract

The main goal of this work is to demonstrate the suitability of survival analysis for ontogenetic studies. The research material includes retrospective data of the age of the occurrence of ontogenetic events such as birth (N = 487), menarche (N = 2016) and menopause (N = 3597). In order to study the time of occurrence of ontogenetic events and to indicate the impact of environmental factors the survival analysis was applied. First, the percentiles of functions established for studied events were calculated. Next, the Kaplan-Meier survival curves were derived. In the last step theinfluence of environmental factors was established and the comparison of groups determined based on the chosen factors was performed. The delivery time shows that 14% of infants were bornpreterm. The risk of preterm delivery increases with the severity of factors disrupting pregnancy (from none to coexisting maternal and fetal risk factors) (; p < 0.001). In the case of menarche percentile positions indicate that the menarche occurs between the 12thand the 14thyear of life as the period in which most girls exceed the puberty threshold. The Cox’s proportional hazard model indicates that the time of menarche occurrence is significantly depended (; p < 0.001) on the place of the mother’s residence and number of children in the family (respectively p < 0.03 and p < 0.001). The time interval established for 50% occurrence of this experience was designated between the 49^th and the 52^nd years of life. The time of menopause occurrence is significantly depended on both of considered factors: the educational level and smoking cigarettes (, p < 0.001). Survival analysis is suitable for studies of the distribution in time of developmental events. It can be used to indicate the factors which significantly influence the course of development by modifying the duration of developmental stages.

Keywords

Ontogenetic Events, Birth, Menarche, Menopause, Kaplan-Meier Method, Cox’s Proportional Hazard Model

Conflicts of Interest

The authors declare no conflicts of interest.

References

[1]	Bogin, B. (1988) Patterns of Human Growth. Cambridge University Press, Cambridge.
[2]	Szwed, A. and Kosińska, M. (2012) Biological Maturity at Birth, the Course of the Subsequent Ontogenetic Stages and Age at Menarche. HOMO-Journal of Comparative Human Biology, 63, 292-300. http://dx.doi.org/10.1016/j.jchb.2012.01.003
[3]	James-Todd, T., Tehranifar, P., Rich-Edwards, J., Titievsky, L. and Terry, M.B. (2010) The Impact of Socioeconomic Status across Early Life on Age at Menarche among a Racially Diverse Population of Girls. Annals of Epidemiology, 20, 836-842. http://dx.doi.org/10.1016/j.annepidem.2010.08.006
[4]	INSERM Collective Expertise Centre (2007) INSERM Collective Expert Reports Paris, Institut national de la sante et de la recherche 2000. Growth and Puberty Secular Trends, Environmental and Genetic Factors. http://www.ncbi.nlm.nih.gov/books/NBK10786
[5]	Latinen, J., Power, Ch. and J?rvelin, M.-R. (2001) Family Social Class, Maternal Body Mass Index, Childhood Body Mass Index, and Age at Menarche as Predictors of Adult Obesity. American Journal of Clinical Nutrition, 74, 287-294.
[6]	Kramer, M.S., Wilkins, R., Gouletf, L., Séguinf, L., Lydonc, J., Kahnd, S.R., McNamarae, H., Dassaf, C., Dahhoua, M., Masseh, A., Minere, L., Asselinh, G., Gauthierf, H., Ghanemf, A., Benjamine, A. and Platta, R.W. (2009) Investigating Socio-Economic Disparities in Preterm Birth: Evidence for Selective Study Participation and Selection Bias. Paediatric and Perinatal Epidemiology, 23, 301-309. http://dx.doi.org/10.1111/j.1365-3016.2009.01042.x
[7]	?aska-Mierzejewska, T. and Olszewska, E. (2004) The Maturation Rate of Girls Living in Rich and Poor Rural Regions of Poland before and after the Transformation of 1989. HOMO-Journal of Comparative Human Biology, 55, 129-142. http://dx.doi.org/10.1016/j.jchb.2003.07.001
[8]	Brambilla, D.J. and McKinlay, S.M. (1989) A Prospective Study of Factors Affecting Age at Menopause. Journal of Clinical Epidemiology, 2, 1031-1039. http://dx.doi.org/10.1016/0895-4356(89)90044-9
[9]	Lumley, J. (1993) The Epidemiology of Preterm Birth. Bailliere Clinical Obstetrics and Gynaecology, 7, 477-498. http://dx.doi.org/10.1016/S0950-3552(05)80445-6
[10]	Lumley, J. (2003) Defining the Problem: The Epidemiology of Preterm Birth. BJOG, 110, 3-7. http://dx.doi.org/10.1046/j.1471-0528.2003.00011.x
[11]	Pawlińska-Chmara, R. and Szwed, A. (2007) Cigarette Smoking and Age at Natural Menopause of Women in Poland. Internet Journal of Biological Anthropology, 2.
[12]	Kleinbaum, D.G. Survival Analysis. A Self-Learning Text. Spinger-Verlag, New York.
[13]	Xie, J., Brayne, C. and Matthews, F.E. (2008) Survival Times in People with Dementia: Analysis from Population Based Cohort Study with 14 Year Follow-Up. BMJ, 336, 258-262. http://dx.doi.org/10.1136/bmj.39433.616678.25
[14]	Salles, G.F., Bloch, K.V. and Cardoso, C.R.L. (2004) Mortality and Predictors of Mortality in a Cohort of Brazilian Type 2 Diabetic Patients. Diabetes Care, 27, 1299-1305. http://dx.doi.org/10.2337/diacare.27.6.1299
[15]	Kosiński, Z. and Ksit, P. (2006) Comparative Reproductive Biology of Middle Spotted Woodpeckers and Great Spotted Woodpeckers in a Riverine Forest. Bird Study, 53, 237-246.
[16]	Szwed, A., John, A., Czapla, Z. and Kosińska, M. (2013) Influence of Socioeconomic Factors on Age at Menarche of Polish Girls. Anthropologischer Anzeiger, 70, 455-470. http://dx.doi.org/10.1127/0003-5548/2013/0338
[17]	Kosińska, M. (2006) Two Methods for Estimating Age of Newborns in Catch-Up Growth Studies. Early Human Development, 82, 575-582. http://dx.doi.org/10.1016/j.earlhumdev.2005.12.004