دانلود مقاله مشکلات اقتصادی ناشی از کرونا و عوامل اجتماعی-اقتصادی
چکیده
مقدمه
روش ها
نتایج
بحث
منابع
Abstract
Introduction
Methods
Results
Discussion
References
چکیده
اهداف
سه هدف این مطالعه تعیین مشکلات اقتصادی همه‌گیری COVID-19، پیش‌بینی کننده های اجتماعی-اقتصادی آن‌ها و ارتباط آن‌ها با شاخص‌های مدیریت دیابت در سه شهر در یک کشور با درآمد متوسط بود.
مواد و روش ها
یک نظرسنجی مقطعی مبتنی بر جامعه از 309 فرد مبتلا به دیابت در رده سنی 34 تا 85 ساله در 10 جامعه در طی ژوئیه و آگوست 2020 انجام شد. نظرسنجی های رو در رو توسط پزشکان عمومی مجرب انجام شد. سختی اقتصادی با از دست دادن درآمد و "سمیت مالی" در طول همه گیری COVID-19 ارزیابی شد، جایی که سمیت مالی به عنوان تجربه مشکلات اقتصادی در دسترسی به منابع مدیریت دیابت تعریف شد. شاخص های مدیریت دیابت با استفاده از تناوب پایش گلوکز خون و هموگلوبین A1c (HbA1c) ارزیابی شد.
نتایج
از بین تمام پاسخ دهندگان، 38.5٪ از دست دادن درآمد را گزارش کرده اند و 15.5٪ در طول همه گیری مسمومیت مالی را تجربه کردند. افراد جوانتر و خود اشتغال ساکن مناطق حومه شهر بیشتر احتمال دارد که از دست دادن درآمد را تجربه کنند. به طور مشابه، سکونت در حومه شهر و درآمد کمتر خانوار با مسمومیت مالی همراه بود. بیماران مبتلا به سمیت مالی کمتر احتمال داشت HbA1c را در سه ماه گذشته کنترل کنند (OR = 0.20؛ 95% فاصله اطمینان (CI)، 0.07-0.48).
نتیجه
مدیریت دیابت همانطور که با نظارت دوره ای کمتر HbA1c نشان داده شده است با تجربه مسمومیت مالی مرتبط با COVID-19 همراه بود. یافته‌های ما گروه‌های آسیب‌پذیر را شناسایی کرد که نیاز به حمایت بیشتر برای مدیریت دیابت دارند.
توجه! این متن ترجمه ماشینی بوده و توسط مترجمین ای ترجمه، ترجمه نشده است.
Abstract
Aims
The three objectives of this study were to determine the economic hardships of COVID-19 pandemic, their socio-economic predictors, and their association with diabetes management indicators in three cities in a middle-income country.
Methods
A community-based cross-sectional survey of 309 people with diabetes aged 34–85 was carried out in 10 communities during July and August 2020. Face-to-face surveys were conducted by trained community physicians. Economic hardship was assessed by income loss and “financial toxicity” during the COVID-19 pandemic, where financial toxicity was defined as experiencing economic difficulties in accessing diabetes management resources. Indicators of diabetes management was assessed by blood glucose and Hemoglobin A1c (HbA1c) monitoring frequency.
Results
Among all respondents, 38.5% reported having income loss, and 15.5% experiencing financial toxicity during the pandemic. Younger and self-employed people living suburban areas were more likely to experience income loss. Similarly, suburban area residency and lower household income were associated with financial toxicity. Patients with financial toxicity were less likely to monitor HbA1c in the past three months (OR = 0.20; 95% CI, 0.07–0.48).
Conclusion
Diabetes management as indicated by less frequent HbA1c monitoring was associated with experiencing COVID-19 related financial toxicity. Our findings identified vulnerable groups in need of additional support for diabetes management.
Introduction
The COVID-19 pandemic caused by SARS-CoV-2 coronavirus [[1]] has engendered substantial challenges against the economies and healthcare systems around the globe. To this end, national governments and organizations have adopted novel economic and clinical policies and guidelines in their attempts to address emergent issues caused by the pandemic and its sequela [[2], [3], [4], [5]]. While the pandemic's direct impacts on the economy and the healthcare systems of nations have been extensively studied [[6], [7]], its effects on particular patient populations also deserve research attention. Hence, the pandemic's economic effects on patients with diabetes ought to be studied since a strong clinical relationship between type 2 diabetes mellitus and COVID-19 has been previously discovered and the pandemic is likely to have considerable impacts on self-management of diabetes in such populations.
Results and analyses
Among a total of 328 people with diabetes (all eligible individuals) who were approached via phone for their willingness to participate in the cross-sectional survey, sixteen were excluded: one had died, seven were lost to follow-up, and eight refused to participate, with the response rate of the ICoDe survey being 95.1%. Three others were also excluded due to the lack of confirmed diagnosis of diabetes. The remaining 309 eligible patients were included in the analysis. The sample selection process is shown in Figure 1.