Journal of diabetes science and technology · 2021
Racial Disparities in Diabetes Technology Use and Outcomes in Type 1 Diabetes in a Safety-Net Hospital.
СтатьяПоддержка NIH: внешняя программаНазвание 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.
Fantasia Kathryn L, Wirunsawanya Kamonkiat, Lee Christopher, Rizo Ivania
Аннотация
BACKGROUND: Limited data exist regarding diabetes technology use among adults with type 1 diabetes (T1D) in urban racially/ethnically diverse safety-net hospitals. We examined racial/ethnic differences in the use of continuous glucose monitor (CGM) and continuous subcutaneous insulin infusion (CSII) in this setting.
METHODS: A retrospective review of 227 patients ≥ 18 years of age with T1D seen in an urban, safety-net endocrinology clinic during 2016-2017 was completed (mean age: 39; 80% English-speaking; 50% had public insurance). Diabetes technology use, defined as either CGM or CSII or both CGM and CSII, and clinical outcomes were examined by race/ethnicity.
RESULTS: Overall, 30% used CGM and 26% used CSII. After adjusting for age, language, insurance, and annual income, diabetes technology use in non-White patients was significantly lower than in White patients, predominantly lower in Black (aOR 0.25 [95% CI 0.11-0.56]) and patients identified as other race/ethnicity (aOR 0.30 [95% CI 0.11-0.77]). At the highest household income level (≥$75,000/y), Black and Hispanic individuals were significantly less likely than White individuals to use diabetes technology (P < .0007). Mean hemoglobin A1c (HbA1c) was lower in patients using any diabetes technology compared with patients using no technology (P < .0001). Use of CGM and CSII together was associated with the lowest HbA1c across all racial/ethnic groups.
CONCLUSIONS: Racial/ethnic disparities in diabetes technology use and glycemic control were observed even after adjusting for sociodemographic factors. Further research should explore barriers to accessing diabetes technology in non-White populations.
METHODS: A retrospective review of 227 patients ≥ 18 years of age with T1D seen in an urban, safety-net endocrinology clinic during 2016-2017 was completed (mean age: 39; 80% English-speaking; 50% had public insurance). Diabetes technology use, defined as either CGM or CSII or both CGM and CSII, and clinical outcomes were examined by race/ethnicity.
RESULTS: Overall, 30% used CGM and 26% used CSII. After adjusting for age, language, insurance, and annual income, diabetes technology use in non-White patients was significantly lower than in White patients, predominantly lower in Black (aOR 0.25 [95% CI 0.11-0.56]) and patients identified as other race/ethnicity (aOR 0.30 [95% CI 0.11-0.77]). At the highest household income level (≥$75,000/y), Black and Hispanic individuals were significantly less likely than White individuals to use diabetes technology (P < .0007). Mean hemoglobin A1c (HbA1c) was lower in patients using any diabetes technology compared with patients using no technology (P < .0001). Use of CGM and CSII together was associated with the lowest HbA1c across all racial/ethnic groups.
CONCLUSIONS: Racial/ethnic disparities in diabetes technology use and glycemic control were observed even after adjusting for sociodemographic factors. Further research should explore barriers to accessing diabetes technology in non-White populations.