TIME TO DEVELOP DIABETIC NEUROPATHY AND ITS PREDICTORS AMONG TYPE 2 DIABETES MELLITUS PATIENTS TAKING CARE IN HOSPITALS OF WOLAITA ZONE SOUTHERN ETHIOPIA RETROSPECTIVE FOLLOW UP STUDY.

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dc.contributor.author BINIAM CHERU LALE
dc.date.accessioned 2024-06-10T10:15:01Z
dc.date.available 2024-06-10T10:15:01Z
dc.date.issued 2023-10
dc.identifier.uri http://hdl.handle.net/123456789/2009
dc.description TIME TO DEVELOP DIABETIC NEUROPATHY AND ITS PREDICTORS AMONG TYPE 2 DIABETES MELLITUS PATIENTS TAKING CARE IN HOSPITALS OF WOLAITA ZONE SOUTHERN ETHIOPIA RETROSPECTIVE FOLLOW UP STUDY. en_US
dc.description.abstract Introduction: Diabetic neuropathy effects inevitably result in a decrease in quality of life and significant financial burden on both patients and society. Despite the significant number of patients suffering from the negative effects of diabetic neuropathy in Ethiopia, evidence on the time to diabetic neuropathy and its predictors is lacking. As a result, the current study sought to offer information on the time to diabetic neuropathy and its predictors in diagnosed type 2 diabetes patients taking care in hospitals of Wolaita zone, Southern Ethiopia, 2023 Objective: To determine the time to develop diabetic neuropathy and its predictors among diagnosed type 2 diabetes patients taking care in hospitals of Wolaita zone, Southern Ethiopia, 2023 Methods: Retrospective follow up study was conducted among 525 type 2 diabetes mellitus patients who enrolled at Wolaita Sodo University Comprehensive Specialized Hospital and Dubo St Marry Catholic primary hospital, Southern Ethiopia from January 1, 2009 to December 31, 2018. Simple random sampling technique was used to select study participants. Extracted data was exported to Microsoft excel from kobo tool then imported to and analyzed by Stata version 14. Bivariate and Multivariable Cox proportional hazard regression analysis was done. The assumption of Cox proportional hazard was checked using scheonfeld residuals test and graphical methods. Goodness of model fitness was checked by using Cox Snell residual. Adjusted hazard ratio with 95% confidence interval and P-values was used to identify statistically significant predictors. Result: The incidence rate of diabetic neuropathy was 2.88 per one hundred person years. After adjusted for covariates the significant predictors for diabetic neuropathy were age (95% CI=1.01, 1.07), being female (95% CI=1.36, 3.12), dwelling in urban (95% CI=1.01, 2.69), oral hypoglycemic agent users (95% CI= 1.75, 5.95), having hypertension (95% CI=1.22, 4.57), and having diabetic retinopathy (95% CI=1.26, 4.29). Conclusions and recommendations: The incidence rate of diabetic neuropathy was relatively high. Age, female, urban, oral hypoglycemic agent, diabetic retinopathy, and hypertension were positively associated with diabetic neuropathy. To reduce the incidence of diabetic neuropathy special care should be given for those with other diabetic complication. en_US
dc.description.sponsorship AMU en_US
dc.language.iso en en_US
dc.subject Diabetic neuropathy, incidence, predictors, type 2 diabetes mellitus en_US
dc.title TIME TO DEVELOP DIABETIC NEUROPATHY AND ITS PREDICTORS AMONG TYPE 2 DIABETES MELLITUS PATIENTS TAKING CARE IN HOSPITALS OF WOLAITA ZONE SOUTHERN ETHIOPIA RETROSPECTIVE FOLLOW UP STUDY. en_US
dc.type Thesis en_US


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