埃塞俄比亚东谢瓦地区糖尿病患者抑郁患病率及相关因素:贝叶斯方法。

Q1 Psychology
Depression Research and Treatment Pub Date : 2020-10-21 eCollection Date: 2020-01-01 DOI:10.1155/2020/4071575
Biruk Shalmeno Tusa, Mekuriaw Alemayehu, Adisu Birhanu Weldesenbet, Sewnet Adem Kebede, Getachew Asfaw Dagne
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引用次数: 7

摘要

背景:抑郁症是糖尿病(DM)患者中最紧迫的公共卫生问题之一,也是最普遍的合并症。抑郁症可能影响生活方式的决定和执行任务的能力,这些都是糖尿病的危险因素。为了减少发展中国家糖尿病患者中抑郁症的影响,识别和评估糖尿病患者中抑郁症的相关危险因素,从而设计有效的管理技术至关重要。与此相一致,本研究应用贝叶斯框架,汇集了先验信息和当前数据,以寻找与糖尿病患者抑郁相关的因素。方法:2019年3 - 4月在安道玛医院和医学院(AHMC)进行了一项以医院为基础的横断面研究。数据输入Epi-data 3.1,然后导出到R软件3.4.4。采用马尔可夫链蒙特卡罗(MCMC)算法拟合贝叶斯逻辑回归模型。计算模型参数的估计值,包括校正优势比(AOR)和95%可信区间(CI)。结果:共有359例成人糖尿病患者纳入分析。糖尿病患者抑郁患病率为9.22% (95% CI: 6.4% ~ 12.7%)。空腹血糖升高(AOR = -1.012;HPD CI:(1.0020, 1.025)),有糖尿病并发症(AOR = 0.1876;HPD CI:(0.0214, 0.671))、住院史(AOR = 0.2865;HPD CI:(0.0711, 0.7318)),低药物依从性(AOR = 29.29;HPD CI:(3.383, 92.26)),同时使用胰岛素和口服降糖药(AOR = 24.46;糖尿病患者HPD CI(15.20, 49.37)与抑郁呈显著强相关。结论:埃塞俄比亚Adama医院集水区糖尿病患者抑郁患病率很低。较高的空腹血糖水平、糖尿病并发症、住院史、低药物依从性以及同时服用胰岛素和口服抗糖尿病药物是糖尿病患者抑郁患病率的强预测因子。综上所述,结合抑郁症的筛查和治疗,糖尿病并发症的早期发现和管理,以及提高药物依从性的咨询是降低抑郁症对糖尿病患者影响的有效途径。
本文章由计算机程序翻译,如有差异,请以英文原文为准。

Prevalence of Depression and Associated Factors among Diabetes Patients in East Shewa, Ethiopia: Bayesian Approach.

Prevalence of Depression and Associated Factors among Diabetes Patients in East Shewa, Ethiopia: Bayesian Approach.

Prevalence of Depression and Associated Factors among Diabetes Patients in East Shewa, Ethiopia: Bayesian Approach.

Prevalence of Depression and Associated Factors among Diabetes Patients in East Shewa, Ethiopia: Bayesian Approach.

Background: Depression is one of the most pressing public health problems and also highly prevalent comorbid condition among diabetes mellitus (DM) patients. Depression may impact lifestyle decisions and ability to poorly perform tasks which are risk factors for DM. For reducing the impact of depression among DM patients in developing countries, it is crucial to identify and assess associated risk factors of depression among DM patients, thereby designing effective management techniques. In line with this, the current study applies the Bayesian framework, which pools prior information and current data, to find factors associated with depression among DM patients.

Methods: A hospital-based cross-sectional study was conducted at Adama Hospital and Medical College (AHMC) from March to April 2019. Data was entered into the Epi-data 3.1 then exported to the R software 3.4.4. Bayesian logistic regression models were fitted to the data using the Markov chain Monte Carlo (MCMC) algorithm. Estimates of model parameters including adjusted odds ratio (AOR) with 95% credible intervals (CI) were calculated.

Results: A total of 359 adults with DM were included in the analysis. The prevalence of depression among diabetic patients was 9.22% (95% CI: 6.4% to 12.7%). Higher fasting blood sugar level (AOR = -1.012; HPD CI: (1.0020, 1.025)), having diabetic complication (AOR = 0.1876; HPD CI: (0.0214, 0.671)), history of hospital admission (AOR = 0.2865; HPD CI: (0.0711, 0.7318)), low medication adherence (AOR = 29.29; HPD CI: (3.383, 92.26)), and taking both insulin and oral antidiabetic medication (AOR = 24.46; HPD CI: (15.20, 49.37) were significantly and strongly associated with depression among DM patients.

Conclusions: Prevalence of depression among diabetes patients in the catchment area of Adama Hospital, Ethiopia, was found to be very low. Higher fasting blood sugar level, diabetic complication, history of hospital admission, low medication adherence, and taking both insulin and oral antidiabetic medication were found to be strong predictors of prevalence of depression among DM patients. Based on the findings, we recommend that integrating screening and treating of depression, early detection and management of diabetic complication, and giving counseling to improve medication adherence is an effective approach for lowering the impact of depression on DM patients.

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来源期刊
Depression Research and Treatment
Depression Research and Treatment Psychology-Clinical Psychology
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