Recent studies have suggested that weight changes may be related to disease risk independent of weight status. A critical step in testing this assertion is the measurement of weight change and so-called 'weight cycling.' However intuitive the concept of weight cycling may appear, research in this area is hampered by complex methodological issues. This article discusses various measures of nominal weight cycling, including the standard deviation, coefficient of variation, regression techniques, and cycles. A cycle is a sequence of a gain followed by a loss or vice versa. The various measures are compared in seven hypothetical cases created to illustrate their strengths and weaknesses. Superior performance of the cycles measure over the coefficient of variation, number of fluctuations, and simple regression methods is argued. The linkage of the cycles measure with the statistical theory of runs also provides a basis for testing the significance of weight fluctuations or other variables that may cycle, such as blood lipids, etc. The cycles measure and runs test provide a viable definition for identifying weight cycling and a tool for evaluating the critical amount of weight gained and/or lost in relationship to risk.