Self-Care Practice and Associated Factors Among People Living with Type 2 Diabetes in Addis Ababa, Ethiopia: A Facility-Based Cross-Sectional Study

ObjectivesThis study aimed to determine the prevalence of anaemia among patients with type 2 diabetes mellitus (T2DM) and chronic kidney disease (CKD) at primary care settings and its associated factors.Design, setting and participantsThis cross-sectional study involved 808 adult patients with T2DM and CKD who were recruited via systematic sampling from 20 public primary care clinics in Peninsular Malaysia. Their sociodemographic, clinical and biomedical profiles were collected through interviews, examination of medical records and blood testing.ResultsThe prevalence of anaemia was 31.7% (256/808). The anaemia was mainly mild (61.5%) and normocytic normochromic (58.7%). About 88.7% of the patients with anaemia were not known to have anaemia prior to the study. Among 36 patients with documented history of anaemia, 80.6% were still anaemic, and only a half received iron therapy. Multivariate regression analysis showed that women (adjusted odd ratio (AOR): 1.57, 95% CI: 1.12 to 2.21, p=0.009) and those with older age (AOR: 1.04, 95% CI: 1.01 to 1.06, p<0.001), CKD stage 3a (AOR: 2.47; 95% CI: 1.25 to 4.87, p=0.009), CKD stage 3b (AOR: 4.36; 95% CI: 2.14 to 8.85, p<0.001), CKD stage 4 (AOR: 10.12; 95% CI: 4.36 to 23.47, p<0.001), CKD stage 5 (AOR: 10.80; 95% CI: 3.32 to 35.11, p<0.001) and foot complication (AOR 3.12, 95% CI: 1.51 to 6.46, p=0.002) were more likely to have anaemia. Having higher body mass index (AOR 0.95, 95% CI: 0.92 to 0.99, p=0.012) and higher diastolic blood pressure (AOR 0.97, 95% CI: 0.95 to 0.99, p<0.001) were associated with lower odds to have anaemia.ConclusionAnaemia among patients with T2DM and CKD in primary care was common, and the majority was unrecognised. Inadequate treatment of anaemia was also prevalent. Therefore, screening of anaemia should be incorporated into the routine assessment of diabetic complications particularly for those with significant associated factors. It is hoped that such strategy could lead to early treatment and hence improve their overall care.Trial registration numberNMRR-15-660-24324.

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Self-Care Adherence And Barriers To Good Glycaemic Control In Nepalese Type 2 Diabetes Mellitus Patients: A Hospital-Based Cross-Sectional Study

Journal of Multidisciplinary Healthcare ◽

10.2147/jmdh.s216842 ◽

2019 ◽

Vol Volume 12 ◽

pp. 817-826 ◽

Cited By ~ 2

Author(s):

Sushant Pokhrel ◽

Sneha Shrestha ◽

Alaska Timilsina ◽

Manisha Sapkota ◽

Mahendra Prasad Bhatt ◽

...

Keyword(s):

Diabetes Mellitus ◽

Type 2 Diabetes ◽

Type 2 Diabetes Mellitus ◽

Glycaemic Control ◽

Self Care ◽

Cross Sectional Study ◽

Sectional Study ◽

Cross Sectional ◽

Good Glycaemic Control

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Magnitude of metabolic syndrome and its associated factors among patients with type 2 diabetes mellitus in Ayder Comprehensive Specialized Hospital, Tigray, Ethiopia: a cross sectional study

BMC Research Notes ◽

10.1186/s13104-019-4609-1 ◽

2019 ◽

Vol 12 (1) ◽

Cited By ~ 6

Author(s):

Gebreamlak Gebremedhn Gebremeskel ◽

Kalayou Kidanu Berhe ◽

Desta Siyoum Belay ◽

Berihu Hailu Kidanu ◽

Assefa Iyasu Negash ◽

...

Keyword(s):

Diabetes Mellitus ◽

Type 2 Diabetes ◽

Metabolic Syndrome ◽

Associated Factors ◽

Cross Sectional Study ◽

Overweight And Obesity ◽

Sectional Study ◽

Cross Sectional ◽

Specialized Hospital

Abstract Objective The objective of this study was to assess magnitude of metabolic syndrome and its associated factors among type 2 diabetes mellitus patients in Ayder Comprehensive Specialized Hospital. A hospital based cross sectional study design was used. Binary logistic regression model was used. Result A total of 419 respondents (208 males and 211 females) were enrolled; the mean age was 56.39 (SD 10.18), 51.1% of the respondents had metabolic syndrome according to international diabetes federation. Sex and age were statistically associated with metabolic syndrome with [AOR (95% CI) 1.93 (1.057, 3.533) and 1.04 (1.012, 1.072)] respectively. Regular physical exercise, overweight and obesity were statistically associated with metabolic syndrome with [AOR (95% CI) 1.84 (1.002, 3.362), 2.68 (1.518, 4.747) and 3.55 (1.254, 10.074)] respectively. To conclude, Magnitude of metabolic syndrome was high. The associated factors for metabolic syndrome are physical inactivity, inadequate intake of fruits, family history, overweight, and obesity.

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Rate of glycemic control and associated factors among type two diabetes mellitus patients in Ethiopia: A cross sectional study

PLoS ONE ◽

10.1371/journal.pone.0251506 ◽

2021 ◽

Vol 16 (5) ◽

pp. e0251506

Author(s):

Shambel Nigussie ◽

Nigussie Birhan ◽

Firehiwot Amare ◽

Getnet Mengistu ◽

Fuad Adem ◽

...

Keyword(s):

Diabetes Mellitus ◽

Type 2 Diabetes ◽

Glycemic Control ◽

Associated Factors ◽

Cross Sectional Study ◽

Poor Glycemic Control ◽

Diabetic Patients ◽

Sectional Study ◽

Cross Sectional

Objective To assess the rate of glycemic control and associated factors among type 2 diabetes mellitus patients at Dilchora Referral Hospital, Dire Dawa, Eastern Ethiopia. Methods A cross-sectional study was conducted from 13 May to 16 August 2019. Type 2 diabetic patients on follow up at Dilchora Referral Hospital who fulfilled the inclusion criteria of the study were included. Systematic random sampling was used to select study participants. Data was collected by a face-to-face interview and review of medical records. The primary outcome was the level of blood glucose during three consecutive visits. Poor glycemic control was defined as a blood sugar level of more than 154 mg/dL based on the average of measurements from three consecutive visits. Multivariate logistic regression analysis was used to identify determinants of glycemic control. Result A total of 394 participants responded to the interview and were included in the final analysis. The overall prevalence of poor glycemic control was 45.2% (95%CI: 40.6%-50.0%). Patients who were on oral anti-diabetic drug plus insulin had more than two times greater chance of poor glycemic control than patients on oral anti-diabetic drug alone: 2.177(95%CI:1.10–4.29). The odds of poor glycemic control in patients who did not understand the pharmacist’s instructions was two times higher than patients with good understanding of instructions 1.86(95%CI: 1.10–3.13). Patients who had poor level of practice were found to have poor glycemic control: 1.69(95% CI: 1.13–2.55). Conclusion The overall prevalence of poor glycemic control was high among type 2 diabetes patients. Oral anti-diabetic drugs in combination with insulin, lack of understanding of pharmacist’s advice, and poor practice of diabetic patients were significant factors of poor glycemic control. Pharmacists should reassure the understanding of patients before discharge during counseling. Optimization of the dose of antidiabetic medications and combination of oral hypoglycemic agents should be considered.

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