Prevalence and determinants of metabolic syndrome among type2 diabetic patients using different diagnosis criteria in ethiopia: systematic review and meta-analysis.

Background: Metabolic syndrome has become a major public health problem worldwide and is attributable to the spread of different non-communicable diseases such as type 2 diabetes mellitus, coronary artery diseases, stroke, and permanent or temporary disabilities. It is not a single disease entity but encompasses different risk factors. However, there were inconsistencies among previously conducted primary studies, hence this systematic review and meta-analysis aimed to determine the pooled prevalence and determinants of metabolic syndrome among type2 diabetes patients in Ethiopia.

Method: First-hand studies about the metabolic syndrome among adult type 2 diabetic patients in Ethiopia were searched through known and international databases (PubMed, Scopus, Web of Science, and Cochran Library) and search engines (Google and Google Scholar). Data was extracted using a standard data extraction checklist developed according to Joanna Briggs Institute (JBI). The I statistics are used to identify heterogeneity across studies. Funnel plot asymmetry and Egger's tests were used to check for publication bias. A random effect model was used to estimate the pooled prevalence of the metabolic syndrome among non-insulin-dependent patients in Ethiopia. The STATA version 11 software employed for statistical analysis was conducted using STATA version 11 software.

Result: The overall pooled prevalence of metabolic syndrome among type2 diabetic patients in was 54.56% [95%CI (43.73, 65.38), I = 97.0%, P = 0.001] using NCEP-ATP III, 48.32% [95%CI (42.1, 54.44), I = 97.0%, P = 0.001] IDF diagnosis criteria, 47.0[95%CI(27.01-66.99)], I = 97.5%, p = 0.001 using WHO and 59.37%(95%CI(47.21-71.52), I = 91.2%, p = 0.001 using harmonized diagnosis criteria respectively. This meta-analysis identified several significant predictors of metabolic syndrome among type 2 diabetes patients in Ethiopia. The odds of having metabolic syndrome was reduced for females (Adjusted Odds Ratio [AOR] = 0.55, 95% CI: 0.35-0.87) compared to males. However, the odds of metabolic syndrome increased with alcohol intake (AOR = 1.44, 95% CI: 1.03-2.01), the odds of living in urban areas(AOR = 2.12, 95% CI: 1.55-2.88), and the odds of having a diabetes duration of six or more years since diagnosis (AOR = 2.94, 95% CI: 1.17-7.41) were significant predictors.

Conclusion: The pooled prevalence was considerably high among type 2 diabetic patients in Ethiopia. The pooled prevalence of metabolic syndrome varies as per the diagnosis criteria used with the highest observed in harmonized diagnosis criteria. Being female, being rural residency, alcohol intake, and duration of diabetes since diagnosis were significant predictors of metabolic syndrome among type 2 diabetic patients in Ethiopia.