Cookies on this website

We use cookies to ensure that we give you the best experience on our website. If you click 'Accept all cookies' we'll assume that you are happy to receive all cookies and you won't see this message again. If you click 'Reject all non-essential cookies' only necessary cookies providing core functionality such as security, network management, and accessibility will be enabled. Click 'Find out more' for information on how to change your cookie settings.

One method of assessing biologic fertility is to measure time to pregnancy (TTP). Accidental pregnancies do not generate a valid TTP value and lead to nonrandom missing data if couples experiencing accidental pregnancies are more fertile than the general population. If factors affecting the rate of accidental pregnancies, such as availability of effective contraception and induced abortion, vary over time, then the result may be protection bias in the estimates of fertility time trends. Six European data sets were analyzed to investigate whether evidence of protection bias exists in TTP studies of fertility trends in Europe over the past 50 years. Couples experiencing accidental pregnancies tended to be more fertile than the general population. However, trends in accidental pregnancy rates were inconsistent across countries and were insufficient to produce substantial bias in fertility trends in simulated data. Where protection bias is suspected, the authors demonstrate use of 2 multiple imputation methods to generate realizations for the missing TTP values for accidental pregnancies. Simulation studies show that both methods successfully reduce or eliminate protection bias. The authors also demonstrate that standard sensitivity analyses for dealing with accidental pregnancies provide an upper bound on the extent of any bias.

Original publication




Journal article


Am J Epidemiol

Publication Date





285 - 293


Adult, Bias, Europe, Female, Fertility, Forecasting, Humans, Infertility, Male, Models, Statistical, Pregnancy, Pregnancy Rate, Pregnancy, Unplanned, Risk Assessment, Time Factors