In Japan, Specific medical examination is conducted for national health insurance subscribers of 40 to 74 years old to prevent lifestyle-related diseases. However, problems remain in effective utilization of these examination results. In this research, we classify health condition types using SOM, one of clustering method, from the Specific health examination results of Izumi City, Osaka Prefecture. We also examined how these types change. As a result of SOM, health conditions were divided into 20 nodes, and it was found that these nodes are characterized by blood pressure, blood glucose level and so on respectively. We divide these nodes into three patterns: healthy, boundary and metabolic. The metabolic pattern was found to have higher medical expenses and medical treatment rates than healthy pattern. In addition, it was found that each pattern transits via the boundary pattern during the 6 years, i.e. data collection term. Furthermore, the medical cost has been on an upward trend at any node, however we can confirmed the node which has transition to a node with a low medical expenses, and in these node, increase in medical expenses are suppressed. Our future work is how to reduce medical expenses by human intervention such as health classroom.