Mikolajczyk, R. T., & Stanford, J. B. (2006). Measuring fecundity with standardised estimates of expected pregnancies. Paediatric and Perinatal Epidemiology, 20 Suppl 1(s1), 43-50. https://doi.org/10.1111/j.1365-3016.2006.00770.x
Mikolajczyk RT, Stanford JB. Measuring fecundity with standardised estimates of expected pregnancies. Paediatr Perinat Epidemiol. 2006;20 Suppl 1(s1):43-50. doi:10.1111/j.1365-3016.2006.00770.x
Mikolajczyk, Rafael T., and Joseph B. Stanford. "Measuring fecundity with standardised estimates of expected pregnancies." Paediatric and Perinatal Epidemiology, vol. 20 Suppl 1, no. s1, 2006, pp. 43-50.
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Fecundity can be compared across studies using expected pregnancies
Expected pregnancies allow fecundity to be compared between groups using cycle length and days of intercourse. This 2006 methods paper by Mikolajczyk and Stanford tests the approach on 1681 menstrual cycles from couples with apparently normal fertility who charted with the Creighton Model FertilityCare System. After adjustment, a woman's age had virtually no effect on fecundity in this sample.
Key Findings
Estimates of the daily chance of pregnancy, referenced to the last day of the menstrual cycle, were remarkably similar across data sets built on different ovulation markers.
Expected pregnancies from the Creighton-derived estimates (set A) slightly underestimated observed pregnancies, while estimates combining European Fecundability Study fecundities with Creighton timing (set C) approximated them closely.
The younger group, split at the median age of 25 years, showed higher fecundity that frequency and timing of intercourse completely explained. After adjustment, age had virtually no effect in this sample.
Women who had given birth had intercourse less often in the fecund interval and conceived less often, yet observed pregnancies exceeded expected pregnancies roughly twofold, indicating higher baseline fecundity.
Interpretation
The paper develops a statistical method and demonstrates it on real data. Researchers calculate expected pregnancies from cycle length and days of intercourse, then compare them with observed pregnancies. The ratio adjusts for how often and when couples have intercourse, a potential confounder in fertility studies. The demonstration couples had apparently normal fertility and were free of medications or conditions known to affect it. The authors note that the method works for couple-level or cycle-level exposures sorted into categories, and they suggest further validation in other data sets.
RRM Context
Cycle charting is a core tool of restorative reproductive medicine. The Creighton Model FertilityCare System charts in this paper supplied the peak day of mucus, the days of intercourse and the pregnancies. The method does not necessarily need hormone tests, so charts kept with fertility awareness-based methods can serve as a data source for comparing fecundity between groups.
Our editorial summary of this paper, not the article's abstract.
Abstract
Approaches to measuring fecundity include the assessment of time to pregnancy and day-specific probabilities of conception (daily fecundities) indexed to a day of ovulation. In this paper, we develop an additional approach of calculating expected pregnancies based on daily fecundities indexed to the last day of the menstrual cycle. Expected pregnancies can thus be calculated while controlling for frequency and timing of coitus. Comparing observed pregnancies with expected pregnancies allows for a standardised comparison of fecundity between studies or groups within studies, and can be used to assess the effects of categorical covariates on the woman or couple level, and also on the cycle level. This can be accomplished in a minimal data set that does not necessarily require hormonal measurement or the explicit identification of ovulation. We demonstrate this approach by examining the effects of age and parity on fecundity in a data set from women monitoring their fertility cycles with the Creighton Model FertilityCare System.
Research Methods › Measurement and Statistics › Statistical Methods · Fertility Awareness › Methods › Creighton Model · Longevity and Reproductive Aging › Age and Fertility › Female Age and Fecundability
Rafael T Mikolajczyk, Joseph B Stanford
R Mikolajczyk, Joe Stanford, Joey Stanford, J Stanford
PMID 17061973 17061973 DOI 10.1111/j.1365-3016.2006.00770.x 10.1111/j.1365-3016.2006.00770.x Mikolajczyk et al. 2006, Mikolajczyk 2006
