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Men have a very high lifetime risk of developing prostate cancer, and so there is a pressing need to understand factors that influence this risk. One factor of interest is whether cycling increases of decreases prostate cancer lifetime risk. Two large observational studies of cyclists noted very low rates of prostate cancer amongst cyclists relative to the general population - neither however drew causal conclusions about risk based on this observational prevalence data alone. Here we explore if and how we can use such data to update our beliefs about whether cycling increases or decreases prostate cancer risk - we use probabilistic methods to quantify belief in risk given the observational data available. We examine whether there is a dose-response relationship, how we can make inferences about risks, and the impact upon selection bias upon these inferences. A simple analysis leads us to believe that cycling decreases risk, but we show how this is mistaken unless selection bias can be ruled out. If cyclists who develop prostate cancer are less likely to respond to these surveys, we may be mislead into believing that cycling decreases risk even if it actually increases risk. Overall we explore precisely why it is hard to draw conclusions about risk factors based upon observational prevalence data.