Researchers studying interventions to prevent subsequent teenage pregnancies, short inter- pregnancy intervals, or unintended pregnancies need statistical techniques that will allow them to make maximum use of the information available on those in the experimental and control groups, as well as provide insights into the reasons for the success or failure of the program. The usual way of analyzing such data is to take an arbitrary period, such as two years, and determine how many women became pregnant in that period and then determine the characteristics of those who did or did not become pregnant in that period. This method does not take full advantage of all the data that may be available. It eliminates any information about the women who: (1) are not yet two years past their previous pregnancy termination; (2) are more than two years past their previous termination; and (3) have been lost to follow-up. In the 1970s, life table analysis was used by Currie, Jekel, and Klerman (AJPH 1972) and Menken and Sheps (1973) to determine the impact of a program for teenage mothers. But since that time survival analyses has been developed for studying the occurrence and timing of events. The authors have used Cox’s regression model and other survival models to study the effect of interventions for preventing subsequent pregnancies in teenage and high-risk populations. The usefulness of such models will be illustrated using data from randomized studies.
Learning Objectives: As a result of reading this poster, the reader will: -understand the use of survival analysis in demographic studies; and - be aware of how this method has been applied in studies of teenage pregnancy and high-risk maternal populations
Keywords: Family Planning, Biostatistics
Presenting author's disclosure statement:
Organization/institution whose products or services will be discussed: None
I do not have any significant financial interest/arrangement or affiliation with any organization/institution whose products or services are being discussed in this session.