Analysis of regional differences in the amount of hypnotic and anxiolytic prescriptions in Japan using nationwide claims data

Background: In Japan, there has been no investigation of regional differences in the number or amount of prescriptions of anxiolytics or hypnotics. Attributes related to the high amount of prescriptions for these drugs are unknown. We investigated recent trends and regional differences in the amount of prescriptions of hypnotics and anxiolytics in Japan and identified factors associated with these regional differences. Methods: The National Database of Health Insurance Claims and Specific Health Checkups of Japan (NDB) Open data from 2015 to 2018 were used. We calculated diazepam-equivalent doses (mg) for each drug and the total amount of prescriptions per capita for hypnotics and anxiolytics by sex and age. In addition, we calculated the standardized claim ratio (SCR) of the amount of prescriptions by prefecture. We investigated factors associated with regional differences in the SCRs of hypnotics and anxiolytics using the prefectures’ medical, socioeconomic, and physical characteristics by an ecological study using a linear mixed-effects model. Results: The amount of prescriptions of hypnotics and anxiolytics, specifically, the amount of prescriptions of benzodiazepine receptor agonists (BZRAs), decreased in many of the adult age groups from 2015 to 2018. The regression analysis revealed that the number of medical clinics per capita, the number of public assistance recipients per capita, the proportion of persons whose HbA1c ≥ 6.5%, and the proportion of persons whose BMI ≥25 kg/m² were positively and significantly associated with the SCR of hypnosis. In contrast, the number of public assistance recipients per capita and the proportion of persons whose BMI ≥25 kg/m² were positively and significantly associated with the SCR of anxiolytics. Conclusions: Factors associated with prescription amount of hypnotics and anxiolytics were revealed in this study, and a further study is needed for investigating causal relationships between the prescriptions amount and the associated factors using individual data.