Journal of diabetes investigation · 2025
The Beck Depression Inventory-II scores of adults with type 1 diabetes in Japan: Analysis using the Juntendo-Aso Type 1 Diabetes (JAT-1) Cohort.
СтатьяНазвание и аннотация: Перевод пока не подготовлен
Обработка статьи · этапы, ошибки и управление
Загрузка состояния…
Ошибки и ограничения
История · было → стало
Состояние обновляется каждые 5 секунд, пока блок открыт. Процент показывается только там, где известен объём работы. Пауза останавливает продолжение этапа; текущий запрос к источнику может завершиться.
Ikeda Fuki, Sato Junko, Nakajima Kenichi, Koshibu Mami, Sato Ayako, Aso Katsumi, Nishida Yuya, Watada Hirotaka
Аннотация
INTRODUCTION: Depressive tendencies associated with difficulty in the treatment of type 1 diabetes (T1D) could hinder appropriate intervention. Factors related to depressive tendencies in Japan remain unclear, though recent advances in medication may have affected them.
MATERIALS AND METHODS: Three hundred and fifty-two Japanese patients with T1D registered in the Juntendo-Aso Type 1 Diabetes (JAT-1) Cohort Study were divided into two groups based on depressive tendencies assessed with the Beck Depression Inventory-II score. We compared background characteristics of the patients between the groups and also analyzed additional clinical factors and quality of life scores.
RESULTS: The patients with a Beck Depression Inventory-II score ≧14 (35.5%) are classified as having depressive tendencies. Compared to the individuals without depressive characteristics, those with depressive tendencies had significantly higher proportions of females, welfare recipients, and shift workers; a higher proportion of individuals with microvascular complications; higher diastolic pressure; eating out or taking out food more frequently for dinner; lower protein intake; and higher scores in the total score of diabetes-related problem domains and Pittsburgh Sleep Quality Index. Multiple regression analysis revealed that diastolic blood pressure, welfare recipient status, total score of diabetes-related problem domains (PAID), and Pittsburgh Sleep Quality Index were significantly associated factors with BDI-II score, and the PAID score showed the strongest association.
CONCLUSIONS: This study revealed that diabetes-specific psychological burden, evaluated with the PAID score, is strongly associated with depressive tendencies. Routine use of the PAID could support the strategies to prevent depression in people with type 1 diabetes by identifying those at risk.
MATERIALS AND METHODS: Three hundred and fifty-two Japanese patients with T1D registered in the Juntendo-Aso Type 1 Diabetes (JAT-1) Cohort Study were divided into two groups based on depressive tendencies assessed with the Beck Depression Inventory-II score. We compared background characteristics of the patients between the groups and also analyzed additional clinical factors and quality of life scores.
RESULTS: The patients with a Beck Depression Inventory-II score ≧14 (35.5%) are classified as having depressive tendencies. Compared to the individuals without depressive characteristics, those with depressive tendencies had significantly higher proportions of females, welfare recipients, and shift workers; a higher proportion of individuals with microvascular complications; higher diastolic pressure; eating out or taking out food more frequently for dinner; lower protein intake; and higher scores in the total score of diabetes-related problem domains and Pittsburgh Sleep Quality Index. Multiple regression analysis revealed that diastolic blood pressure, welfare recipient status, total score of diabetes-related problem domains (PAID), and Pittsburgh Sleep Quality Index were significantly associated factors with BDI-II score, and the PAID score showed the strongest association.
CONCLUSIONS: This study revealed that diabetes-specific psychological burden, evaluated with the PAID score, is strongly associated with depressive tendencies. Routine use of the PAID could support the strategies to prevent depression in people with type 1 diabetes by identifying those at risk.