Osteoprotegerin is not a determinant of metabolic syndrome in sub-Saharan Africans after age adjustment

Prevalence of the metabolic syndrome in African populations: A systematic review and meta-analysis

BACKGROUND

The metabolic syndrome (MS) is a leading cause of death worldwide. Several studies have found MS to be prevalent in various African regions. However, no specific estimates of MS prevalence in African populations exist. The aim of this study was to estimate the overall prevalence of MS in the African populations.

METHODS

A systematic review was conducted in PubMed, Web of Science, Africa Index Medicus, and African Journal Online Scopus to find studies published up to the 15th of August 2022. Pooled prevalence was calculated based on six diagnostic methods. The pooled prevalence of MS was estimated using a random-effects model. Our risk of bias analysis was based on the Hoy et al. tool. A Heterogeneity (I2) assessment was performed, as well as an Egger test for publication bias. PROSPERO number CRD42021275176 was assigned to this study.

RESULTS

In total, 297 studies corresponding to 345 prevalence data from 29 African countries and involving 156 464 participants were included. The overall prevalence of MS in Africa was 32.4% (95% CI: 30.2-34.7) with significant heterogeneity (I2 = 98.9%; P<0.001). We obtained prevalence rates of 44.8% (95% CI: 24.8-65.7), 39.7% (95% CI: 31.7-48.1), 33.1% (95% CI: 28.5-37.8), 31.6% (95% CI: 27.8-35.6) and 29.3% (95% CI: 25.7-33) using the WHO, revised NCEP-ATP III, JIS, NCEP/ATP III and IDF definition criteria, respectively. The prevalence of MS was significantly higher in adults >18 years with 33.1% (95%CI: 30.8-35.5) compared to children <18 years with 13.3% (95%CI: 7.3-20.6) (P<0.001). MS prevalence was significantly higher in females with 36.9% (95%CI: 33.2-40.7) compared to males with 26.7% (95%CI: 23.1-30.5) (P<0.001). The prevalence of MS was highest among Type 2 diabetes patients with 66.9% (95%CI: 60.3-73.1), followed by patients with coronary artery disease with 55.2% (95%CI: 50.8-59.6) and cardiovascular diseases with 48.3% (95%CI: 33.5-63.3) (P<0.001). With 33.6% (95% CI: 28.3-39.1), the southern African region was the most affected, followed by upper-middle income economies with 35% (95% CI: 29.5-40.6).

CONCLUSION

This study, regardless of the definition used, reveals a high prevalence of MS in Africa, confirming the ongoing epidemiological transition in African countries. Early prevention and treatment strategies are urgently needed to reverse this trend.

Biomarkers of Metabolic Syndrome: Biochemical Background and Clinical Significance

Biomarkers of the metabolic syndrome are divided into four subgroups. Although dividing them in groups has some limitations, it can be used to draw some conclusions. In a first part, the dyslipidemias and markers of oxidative stress are discussed, while inflammatory markers and cardiometabolic biomarkers are reviewed in a second part. For most of them, the biochemical background and clinical significance are discussed, although here also a well-cut separation cannot always be made. Altered levels cannot always be claimed as the cause, risk, or consequence of the syndrome. Several factors are interrelated to each other and act in a concerted, antagonistic, synergistic, or modulating way. Most important conclusions are summarized at the end of every reviewed subgroup. Genetic biomarkers or influences of various food components on concentration levels are not included in this review article.

Osteoprotegerin in relation to insulin resistance and blood lipids in sub-Saharan African women with and without abdominal obesity

BACKGROUND

Osteoprotegerin (OPG), a soluble member of the tumor necrosis factor receptor superfamily that inhibits bone resorption, has been suggested as a potential marker of cardiovascular risk. This study aimed to assess the relationship between insulin resistance, lipid profile and OPG levels in obese and non-obese sub-Saharan African women.

METHODS

Sixty obese (44) and non-obese (16) volunteer women aged 18 to 40 years were recruited in this cross-sectional study. Their clinical (age, height, weight, waist circumference, systolic and diastolic blood pressures) and biochemical parameters (fasting blood glucose, total cholesterol, high density lipoprotein-cholesterol (HDL-C)) were measured using standard methods. Insulin levels were measured using an electrochemiluminescence immunoassay, while OPG levels were measured using the ELISA technique. Low density lipoprotein-cholesterol (LDL-C), body mass index (BMI) and Homeostasis Model Assessment of Insulin Resistance (HOMA-IR) were calculated using standard methods. Abdominal obesity was defined as a waist circumference ≥ 80 cm.

RESULTS

OPG levels were higher in obese than in normal subjects, though the difference was not significant (p = 0.9). BMI, waist circumference, percent body fat and systolic blood pressure were significantly higher in obese than in non-obese subjects (p < 0.05). In these subjects, only age significantly correlated with OPG levels (r = 0.831, p = 0.003), while none of the anthropometric nor metabolic parameter did, even after adjustment for age. In obese subjects, OPG levels fairly correlated with HDL-C (r = 0.298, p = 0.058), and significantly correlated with HOMA-IR (r = -0.438, p = 0.018). After adjustment for age, OPG levels remained negatively correlated to HOMA-IR (r = -0.516, p = 0.020) and LDL-C (r = -0.535, p = 0.015) and positively correlated to HDL-C (r = 0.615, p = 0.004). In multiple linear regression analysis, age was a main determinant of OPG levels in non-obese (β = 0.647, p = 0.006) and obese (β = 0.356, p = 0.044) women. HDL-C was also associated to OPG levels in obese women (β = 0.535, p = 0.009).

CONCLUSION

The positive correlation of OPG with HDL-C and HOMA-IR, and its negative correlation with LDL-C suggest that it may be a marker of insulin sensitivity/resistance and atherogenic risk in obese African women.