Objective To establish a statistical diagnostic method to identify patients with Minamata disease (MD)considering factors of aging and sex, we analyzed the neurological findings in MDpatients, inhabitants in a methylmercury polluted (MP) area, and inhabitants in a non-MP area. Materials and MethodsWecomparedthe neurological findings in MDpatients and inhabitants aged more than 40 years in the non-MParea. Based on the different frequencies of the neurological signs in the two groups, we devised

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... he following formula to calculate the predicting index for MD:predicting index = l/(l+e x)xl00 (The value ofx was calculated using the regression coefficients of each neurological finding obtained from logistic analysis. The index 100 indicated MD, and 0, non-MD). Results Using this method, we found that 100% of male and 98% of female patients with MD(95 cases) gave predicting indices higher than 95. Five percent of the aged inhabitants in the MP area (598 inhabitants) and 0.2% of those in the non-MP area (558 inhabitants) gave predicting indices of 50 or higher. Conclusion Our statistical diagnostic method for MD was useful in distinguishing MDpatients from healthy elders based on their neurological findings.