Study Selection
As shown in Fig. 1, a preliminary search of online databases using a combination of MeSH and free text words retrieved a total of 1418 potential articles, and an additional 3 articles were found through manual citation searching. After removing duplicates, 928 articles remained, which were then screened based on their titles and abstracts, resulting in the elimination of a further 872 articles that were irrelevant to the research question. Among the 56 articles that underwent full-text review, ultimately 30 articles met the inclusion criteria and were included in this review.
Characteristics of Included Studies.
A characteristic summary of thirty articles included in this study involving 8879 individuals is illustrated in Table 3. All were of cross-sectional study design conducted in six sub-Saharan African countries namely Cameroon, Ethiopia, Ghana, Nigeria, Zambia and South Africa as demonstrated in Fig. 2. In these studies, the prevalence of MetS was estimated based on the IDF and/or NCEP-ATP III 2004 criteria. Among the articles, eleven studies reported the prevalence of MetS based on both NCEP-ATP III 2004 and IDF criteria [32, 38, 53, 39, 40, 43–45, 48, 49, 51], fourteen studies reported based solely on NCEP-ATP III 2004 criteria [25, 26, 42, 46, 50, 52, 28–31, 33, 35, 36, 41] and five studies reported based on IDF criteria alone [24, 27, 34, 37, 47]. Additionally, nine studies reported the prevalence of MetS subcomponents based on NCEP-ATP III 2004 criteria [25, 26, 31, 35, 40–44] and six studies based on IDF criteria [24, 27, 40, 43, 44, 47].
Table 3
Characteristics of the included studies that evaluated the prevalence of MetS among T2DM in sub-Saharan population
Author[Year] | Country | Study design | Sampling method | Survey Period | Sample size | Sex | Mean age | Diagnostic criteria | Overall prevalence (NCEP/ATP-III) (IDF) |
Kalk et al. [24] 2008 | South Africa | Cross-sectional study | Convenience sampling | 1994–2002 | 500 | Both | 48.3 ± 8.7 | IDF | - | 69.0% |
Titty et al. [25] 2008 | Ghana | Cross-sectional study | Convenience sampling | January 2006 to May 2007 | 456 | Both | 55.8 ± 12.3 | NCEP-ATP III | 55.9% | - |
Titty et al. [26] 2009 | Ghana | Cross-sectional study | Unspecified | June 2006 to May 2007 | 300 | Both | 57.8 ± 11.3 | NCEP-ATP III | 60.3% | - |
Puepet et al. [27] 2009 | Nigeria | Cross-sectional study | Convenience sampling | January 2006 to December 2008 | 634 | Both | 54.2 ± 9.1 | IDF | - | 63.6% |
Unadike et al. [28] 2009 | Nigeria | Cross-sectional study | Unspecified | January to August 2008 | 240 | Both | 50.8 ± 11 | NCEP-ATP III | 62.5% | - |
Chanda et al. [29] 2010 | Zambia | Cross-sectional study | Unspecified | Unspecified | 400 | Both | 59.3 ± 11.13 | NCEP-ATP III | 73.0% | - |
Titty et al. [30] 2010 | Ghana | Cross-sectional study | Convenience sampling | September 2006 to August 2007 | 240 | Both | 47.2 ± 12.3 | NCEP-ATP-III | 43.3% | - |
Ogbera et al. [31] 2011 | Nigeria | Cross-sectional study | Unspecified | Unspecified | 201 | Female | 62.4 ± 7.7 | NCEP-ATP III | 69.0% | - |
Kangne et al. [32] 2012 | Cameroon | Cross-sectional study | Convenience sampling | 2006–2008 | 308 | Both | 55.8 ± 10.5 | NCEP-ATP III, IDF | 60.4% | 71.7% |
Osuji et al. [33] 2012 | Nigeria | Cross-sectional study | Unspecified | Unspecified | 93 | Both | 55.27 ± 12.55 | NCEP-ATP III | 66.7% | - |
Mogre et al. [34] 2014 | Ghana | Cross- sectional study | Convenience sampling | Unspecified | 200 | Both | 56.2 ± 12.13 | IDF | - | 24.0% |
Ejiofor et al. [36] 2015 | Nigeria | Cross-sectional study | Simple random sampling | March to September 2006 | 366 | Both | Unspecified | NCEP-ATP III | 67.8% | - |
Nsiah et al. [35] 2015 | Ghana | Cross-sectional study | Unspecified | February to April 2013 | 150 | Both | 51.3 ± 0.97 | NCEP-ATP III | 58.0% | - |
Abban et al. [38] 2017 | Ghana | Cross-sectional study | Convenience sampling | March to April 2015 | 103 | Both | 56.24 ± 9.77 | NCEP-ATP III, IDF | 59.09% | 75.0% |
Amidu et al. [39] 2017 | Ghana | Cross-sectional study | Convenience sampling | November 2010-March 2011 | 274 | Male | 59.9 ± 11.3 | NCEP-ATP III, IDF | 65.3% | 43.1% |
Onyenekwu et al. [37] 2017 | Nigeria | Cross-sectional study | Systematic sampling | Unspecified | 108 | Both | Unspecified | IDF | - | 97.2% |
Osei-Yeboah et al. [40] 2017 | Ghana | Cross-sectional study | Convenience sampling | February to April 2016 | 162 | Both | 56.4 ± 10.6 | NCEP-ATP III, IDF | 43.8% | 69.1% |
Woyesa et al. [41] 2017 | Ethiopia | Cross-sectional study | Simple random sampling | February to May 2017 | 314 | Both | 49.8 ± 9.8 | NCEP-ATP III | 70.1% | - |
Tadewos et al. [42] 2017 | Ethiopia | Cross-sectional study | Systematic random sampling | March to November 2014 | 270 | Both | 48.8 ± 11.9 | NCEP-ATP III | 45.9% | - |
Biadgo et al. [43] 2018 | Ethiopia | Cross-sectional study | Unspecified | June to July 2015 | 159 | Both | 49.8 ± 8.7 | NCEP-ATP III, IDF | 66.7% | 53.5% |
Birarra et al. [44] 2018 | Ethiopia | Cross-sectional study | Systematic random sampling | March to May 2017 | 256 | Both | Unspecified | NCEP-ATP III, IDF | 70.3% | 57.0% |
Obirikorang et al. [45] 2018 | Ghana | Cross-sectional study | Non-probability convenience sampling | Unspecified | 384 | Both | 56.4 ± 13.1 | NCEP-ATP III, IDF | 77.1% | 76.3% |
Agyemang-Yeboah et al. [46] 2019 | Ghana | Cross-sectional study | Simple random sampling | Unspecified | 405 | Both | 58.5 ± 9.9 | NCEP-ATP III | 90.6% | - |
Gebremeskel et al. [47] 2019 | Ethiopia | Cross-sectional study | Simple random sampling | February to June 2018 | 419 | Both | 56.39 ± 10.18 | IDF | - | 51.1% |
Wube et al. [48] 2019 | Ethiopia | Cross-sectional | Simple random sampling | February to May 2017 | 314 | Both | 49.8 ± 9.8 | NCEP-ATP III, IDF | 70.1% | 52.9% |
Zerga et al. [49] 2020 | Ethiopia | Cross-sectional study | Simple random sampling | February to March 2017 | 330 | Both | Unspecified | NCEP-ATP III, IDF | 59.4% | 50.3% |
Anto et al. [50] 2022 | Ghana | Cross-sectional study | Convenience sampling | March to June 2021 | 241 | Both | Unspecified | NCEP-ATP III | 42.7% | - |
Gebreyesus et al. [51] 2022 | Ethiopia | Cross-sectional study | Systematic sampling | September to November 2019 | 421 | Both | 58.2 ± 11 | NCEP-ATP III, IDF | 67.9% | 57.0% |
Gemeda et al. [52] 2022 | Ethiopia | Cross-sectional study | Simple random sampling | September 2020 to August 2021 | 394 | Both | Unspecified | NCEP-ATP III | 68.3% | - |
Charkos et al. [53] 2023 | Ethiopia | Cross-sectional study | Systematic random sampling | September to October 2022 | 237 | Both | Unspecified | NCEP-ATP III, IDF | 41.3% | 41.8% |
IDF: International Diabetes Federation; NCEP-ATP-III: National Cholesterol Education Program–Adult Treatment Panel I |
Burden of Metabolic syndrome Using NCEP-ATP III 2004 and IDF Criteria.
The weighted pooled prevalence of MetS among T2DM individuals in sub-Saharan Africa using NCEP-ATP III 2004 criteria is 63.1% (95% CI: 57.9–68.1), with significant heterogeneity I2 = 94% and Cochran Q-statistic p < 0.01 as graphically depicted in Fig. 3. While using IDF criteria yielded a pooled prevalence of 60.8% (95% CI: 50.7–70.0), with an I2 of 95% and Cochran Q-statistic p < 0.01 as shown in Fig. 4. The random-effects model was assumed due to the considerable heterogeneity observed across the included studies in the meta-analysis.
Prevalence of the Metabolic Syndrome Components.
In the current systematic review, the prevalence of the individual components of MetS other than hyperglycemia among the sub-Saharan Africa T2DM population was reported in ten studies based on NCEP-ATP III 2004 criteria, and six studies reported based on IDF criteria. The overall pooled prevalence of metabolic syndrome component by NCEP-ATP III 2004 criteria was as follows: central obesity 55.9% [95% CI: 47.6, 64.2], low HDL-c 43.3% [95% CI: 33.5, 53.2], hypertriglyceridemia 48.0% [95% CI: 35.2, 60.7] and hypertension 54.8% [95% CI: 43.2, 66.4]. These values are summarized in Table 4.
Whereas the overall pooled prevalence of MetS component by IDF criteria was as follows: central obesity 61.6% [95% CI: 47.9, 75.3], low HDL-c 49.9% [95% CI: 37.3, 62.6], hypertriglyceridemia 49.2% [95% CI: 34.1, 64.4] and hypertension 56.1% [95% CI: 46.7, 65.4] as summarized in Table 5.
Table 4
Pooled prevalence of metabolic syndrome component based on NCEP-ATP III 2004
| Prevalence of metabolic syndrome component |
Author [Year] | Sample | Central Obesity | Low-HDL-c | High-TG | Hypertension |
Titty et al. [25] 2008 | 456 | 43.6 | 47.4 | 37.5 | 46.9 |
Titty et al. [26] 2009 | 300 | 69.6 | 58.5 | 56.4 | 69.6 |
Unadike et al. [28] 2009 | 240 | 74.4 | 17.3 | 48.0 | 86.7 |
Ogbera et al. [31] 2011 | 201 | 75.0 | 59.0 | 19.0 | 64.0 |
Nsiah et al. [35] 2015 | 150 | 48.6 | 41.3 | 32.7 | 60.0 |
Osei-Yeboah et al. [40] 2017 | 162 | 48.2 | 23.5 | 16.7 | 66.7 |
Woyesa et al. [41] 2017 | 314 | 61.3 | 39.2 | 70.4 | 28.0 |
Tadewos et al. [42] 2017 | 270 | 40.7 | 47.0 | 68.1 | 28.1 |
Birarra et al. [44] 2018 | 256 | 53.5 | 67.2 | 68.8 | 43.4 |
Biadgo et al. [43] 2018 | 159 | 43.4 | 32.7 | 62.3 | 55.4 |
Pooled prevalence [95% CI] | 55.9 [47.6, 64.2] | 43.3 [33.5, 53.2] | 48.0 [35.2, 60.7] | 54.8 [43.2, 66.4] |
CI: Confidence Interval; HDL-c: High density lipoprotein cholesterol; TG: Triglyceride; NCEP-ATP III: National Cholesterol Education Program–Adult Treatment Panel III.
Table 5
Pooled prevalence of metabolic syndrome component based on IDF criteria
| Prevalence of metabolic syndrome component |
Author [Year] | Sample | Central Obesity | Low-HDL-c | High-TG | Hypertension |
Birarra et al. [44] 2018 | 256 | 61.7 | 66.8 | 67.6 | 43.0 |
Biadgo et al. [43] 2018 | 159 | 61.0 | 32.7 | 62.3 | 55.4 |
Osei-Yeboah et al. [40] 2017 | 162 | 30.8 | 47.5 | 16.7 | 66.7 |
Kalk et al. [24] 2008 | 500 | 75.2 | 47.6 | 42.0 | 67.0 |
Puepet et al. [27] 2009 | 634 | 80.0 | 70.0 | 62.9 | 63.1 |
Gebremeskel et al. [47] 2019 | 419 | 59.7 | 34.4 | 45.1 | 41.3 |
Pooled Prevalence [95% CI] | 61.6 [47.9, 75.3] | 49.9 [37.3, 62.6] | 49.2 [34.1, 64.4] | 56.1 [46.7, 65.4] |
CI: Confidence Interval; HDL-c: High density lipoprotein cholesterol; TG: Triglyceride ; IDF: International Diabetes Federation.
Subgroup and sensitivity analysis
Subgroup analyses were conducted based on gender, country, sample size, and mean age. According to the NCEP-ATP III 2004, a total of 17 studies reported prevalence based on gender, revealing that the pooled prevalence of MetS among females in SSA was significantly higher compared to males (73.5% vs. 50.5%). Meanwhile, the results of subgroup analysis based on sample size showed the highest prevalence in studies with ≥ 250 subjects compared to those with < 250 subjects (67.0% vs. 55.2%), as depicted in supplementary table 2. Furthermore, subgroup analysis based on IDF criteria, as shown in supplementary table 3, revealed a higher pooled prevalence among females (71.6%) compared to males (44.5%) among the 11 studies that reported prevalence based on gender. Among the 12 reports that specified participant mean age, the pooled prevalence was comparable across the two categories of mean age: <50 years and ≥ 50 years. Additionally, sensitivity analyses were conducted using the leave-one-out approach to evaluate the influence of individual studies on the overall estimate of MetS, based on the NCEP-ATP III 2004 and IDF criteria. The results indicated no substantial evidence for the influence of any single study on the overall pooled prevalence of MetS among individuals with T2DM in SSA (Figs. 5 and 6). To further explore the observed heterogeneity in the study, we conducted a meta-regression to account for this. The analysis revealed that gender had a significant influence on the overall effect sizes in both NCEP-ATP III 2004 and IDF (p < 0.0001, 0.0007 respectively) and studies with a sample size ≥ 250 for NCEP-ATP III 2004 there was a significant influence observed at p value 0.0106.