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Application of Survival Analysis in Studies of Human Ontogeny

Application of Survival Analysis in Studies of Human Ontogeny
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摘要 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 49th and the 52nd 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. 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 49th and the 52nd 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.
出处 《Applied Mathematics》 2014年第11期1697-1704,共8页 应用数学(英文)
关键词 ONTOGENETIC Events BIRTH MENARCHE MENOPAUSE Kaplan-Meier Method Cox’s Proportional HAZARD Model Ontogenetic Events Birth Menarche Menopause Kaplan-Meier Method Cox’s Proportional Hazard Model
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