Diabetic peripheral neuropathy among adult type 2 diabetes patients in Adama, Ethiopia: health facility-based study.
Yohannes Mekuria NegussieNardos Tilahun BekelePublished in: Scientific reports (2024)
Diabetic peripheral neuropathy is the most prominent microvascular complication of diabetes mellitus and the leading cause of ulceration, amputation, and extended hospitalization. Evidence regarding the magnitude and factors associated with diabetic peripheral neuropathy is not well documented in Ethiopia, particularly in the study area. A facility-based cross-sectional study was conducted among 293 adult type 2 diabetic patients who were on treatment and follow-up from May to June 31, 2023. To select participants in the study, a systematic random sampling method was utilized. Data were collected using semi-structured questionnaires and medical record reviews. The Michigan Neuropathy Screening Instrument (MNSI) was employed to assess diabetic peripheral neuropathy. To model the association between diabetic peripheral neuropathy and independent variables, binary logistic regression model was used. An adjusted odds ratio with a 95% confidence interval was used to estimate the association and statistical significance was proclaimed at a p-value < 0.05. The magnitude of diabetic peripheral neuropathy was 14.3% (95% CI 10.4-18.0). It was 13.4% (95% CI 8.4-19.1) among males and 15.4% (95% CI 10.1-22.2) among females. Age above 60 years (AOR = 5.06, 95% CI 1.60-15.96), being rural resident (AOR = 2.41; 95% CI 1.15-5.06), duration of diabetes above 5 years (AOR = 2.48, 95% CI 1.16-5.27) and having comorbid hypertension (AOR = 2.56, 95% CI 1.24-5.28) were independently associated with diabetic peripheral neuropathy. One in seven adult type 2 diabetes patients in the study area had diabetic peripheral neuropathy. Factors such as age, place of residence, duration of diabetes, and comorbid hypertension showed positive associations with diabetic peripheral neuropathy. Thus, it is imperative to give special consideration to diabetic patients who are elderly, living in rural areas, experiencing a prolonged duration of diabetes, or dealing with comorbid hypertension.
Keyphrases
- type diabetes
- glycemic control
- wound healing
- cardiovascular disease
- blood pressure
- healthcare
- insulin resistance
- end stage renal disease
- ejection fraction
- newly diagnosed
- mental health
- public health
- chronic kidney disease
- prognostic factors
- randomized controlled trial
- systematic review
- machine learning
- adipose tissue
- patient safety
- skeletal muscle
- artificial intelligence
- patient reported
- climate change
- deep learning
- middle aged