The 'obesity paradox' may not be a paradox at all

You're a researcher seeking to understand the effect of exposure X on outcome Y in disease group Z. Hundreds, if not thousands, of articles have been published reporting a harmful effect of X on Y in the general population. Large public health programs are in place to prevent X from occurring in an effort to minimize the risk of Y. To answer this question, you use data from a large cohort study of individuals with disease Z. You analyze the data using standard techniques. While reading the output from your statistical software, you notice a surprising finding. Both the point estimate and 95% confidence intervals indicate a protective effect of X (RR < 1.0). You check and re-check your analysis. At this point you are faced with two options: (A) you think to yourself, 'oh no, I must have done something wrong along the way to cause this unexpected finding or there must be some bias I have overlooked, I'd better go look seriously at what could be causing this unexpected and contradictory result' or option (B) label the result a 'paradox' and write up the manuscript for publication in an academic journal.