Background: Biomonitoring data of persistent organic pollutants (POPs) in breast milk are increasingly collected and available for quantitative analysis of levels and time trends. A common approach is to apply log-linear regression to calculate doubling and halving times of the POP concentrations based on the temporal trend observed in breast milk. However, there are different, sometimes conflicting interpretations of these doubling and halving times. Objectives: We provide a mechanistic understanding of doubling and halving times where possible. Five recommendations are proposed for dealing with POP concentration trends in breast milk during three distinct periods (pre-ban, transition, post-ban period). Discussion: Using temporal trends of BDE-47 and PCB-153 in breast milk data, we show which information can be gained from the time-trend data. To this end, we analyzed time trends of hypothetical POPs for different periods with time-variant exposure and different intrinsic elimination half-lives, using a dynamic population-based pharmacokinetic model. Different pieces of information can be extracted from time-trend data from different periods. The analysis of trends of shortlived POPs is rather straightforward and facilitates extraction of the intrinsic elimination half-lives from the breast milk data. However, trends of slowly eliminated POPs only provide indications for the exposure time trend. Conclusions: Time-trend data of rapidly eliminated POPs provide information on exposure time trends and elimination half-lives. Temporal trends of slowly eliminated POPs are more complicated to interpret, and the extraction of exposure time trends and elimination half-lives require data sets covering several decades.