Dyslipidemia is a state that occurs due to abnormalities in the plasma lipids. These include increased plasma total cholesterol (TC), increased low-density lipoprotein cholesterol (LDL-C), increased triglycerides (TGs), and reduced high-density lipoprotein cholesterol (HDL-C) levels. It presents either as an elevation of one of the lipids or high levels of a combination of the lipids (1, 2). The exact mechanism of dyslipidemia is not fully understood but is most likely multifactorial with genetic variations being shown to account for about 43–83% of the variability of plasma lipoprotein levels in a normal healthy population (3, 4). Dyslipidemia is an autosomal dominant disorder caused by mutations in the low-density lipoprotein receptor (LDLR) gene. As a result of defective cell-surface LDLR, clearance of LDL-C from plasma is reduced leading to the increased plasma levels of LDL-C and TC (5). Individuals with dyslipidemia have a 2-fold higher risk of developing cardiovascular diseases (CVDs) than those with normal lipid levels (6).

Both LDL-C and HDL-C regulate the amount of cholesterol in the body. An imbalance between the two can increase the risk of myocardial infarction and stroke (7). The increased levels of LDL-C aggravate the development of atherosclerosis, which is documented as the main risk factor for stroke, peripheral vascular, and ischemic heart disease (IHD) (8). However, HDL-C helps to remove cholesterol from the body, which decreases the risk of atherosclerotic CVD (6).

Though the burden of disease in Africa has been dominated by infectious diseases, countries in this region are undergoing a continuous demographic change leading to the increasing frequency of non-communicable diseases (NCDs) (9). Substantial changes in the health of the population marked by the rising burden of CVDs are set to overtake infectious diseases as the leading cause of death by 2030. This epidemiological shift is mainly driven by unhealthy lifestyles due to rapid urbanization and modernization. Recently, infectious agents are considered more frequently as causes of diseases that have been thought previously to be of non-infectious etiology, such as coronary heart disease. Additionally, lipopolysaccharide (LPS) affects the circulating macrophages and increases the production of free radicals. Free radicals are known to oxidize LDL-C and transform macrophages into foam cells, which are known to be crucial in the pathogenesis of atherosclerosis (10).

Dyslipidemia is responsible for more than half of the global IHD and more than 4 million deaths annually (11). It remains a common public health problem as abnormal serum lipid profile has been steadily increasing due to economic growth, urbanization, and unhealthy lifestyles (12). In Africa, the prevalence of dyslipidemia ranges from 5.2 (13) to 89.9% (14). The presentation of an abnormal lipid profile is common in individuals with central obesity, anti-retroviral therapy (ART), metabolic syndrome, insulin resistance, and type 2 diabetes mellitus (DM) (15). The duration of HIV treatment, advanced age, sex, low CD4 counts, smoking, alcohol consumption, depression (12, 15, 16), and a diet high in saturated fat, sedentary lifestyle, and obesogenic (17) are the major risk factors of dyslipidemia.

The prevalence of CVD is mainly result of risk factors, mostly hypertension (HTN), diabetes, and obesity (9). Dyslipidemia is also more common among patients with coexisting cardiovascular risk factors, such as HTN, diabetes, or HIV (10). A systematic review conducted in the Gambia on CVD risk factors revealed the prevalence of insufficient fruit and vegetable consumption, inadequate physical activity, and alcohol consumption was 77.8, 14.6, and 2.3%, respectively (18).

Most (80%) of the lipid disorders are associated with diet and lifestyle (17). The dietary habits of populations in low-to-middle-income countries (LMICs) have rapidly shifted to less-healthy diets (19). These consist of processed foods, away-from-home food intake, and increased use of edible oils and sugar-sweetened beverages (20).

In recent decades, the global pattern of unhealthy diets driving the occurrence of metabolic disorders and NCDs has become more important in LMICs because of the double burden of diseases in such countries that jointly constitute major causes of morbidity and mortality (21). In many African countries, surveillance and research on NCDs are still lacking (22). However, in the last decades, the number of NCDs-related deaths in the region have grown dramatically (9). This review will allow researchers to assess the disease burden of dyslipidemia in Africa where data are often scarce and populations are understudied. Assessing the prevalence of dyslipidemia can also aid researchers in predicting the future disease development of conditions contingent on dyslipidemia, such as CVD. Accurate data on dyslipidemia prevalence and risk factors can serve to inform health professionals, policy makers, and the public to manage and plan. However, different previous studies conducted on risk factors of dyslipidemia showed conflicting results. Understanding the context-specific factors associated with dyslipidemia and its potential implications are critical to designing effective interventions for the prevention and treatment of metabolic and cardiovascular effects of dyslipidemia.

Dyslipidemia has emerged as an important cardiovascular risk factor in African countries (17). It is characterized by LDL-C increment, TG elevation, and HDL-C decrement or combined. The LDLR positioned on chromosome 19p13.2 plays a significant role in lipoprotein metabolism by mediating the uptake of cholesterol through the binding and subsequent cellular uptake of apolipoprotein-E and B- constituting lipoproteins. Mutations have been detected in different domains of the LDLR which have a distinct effect on LDLR structure and function. ATP-binding cassette A1 (ABCA1) plays a critical role in the reverse cholesterol transport system. Mutation in ABCA1, that encodes this protein, along with genes responsible for their transcription regulation, can lead to abnormality in the metabolism of lipids (48). Apolipoprotein A5 (APOA5) has been shown to be a key regulator of plasma TGs and there are several single nucleotide polymorphisms (SNPs) associated with the APOA5 gene (49). Future research should address the lack of LDL-C oxidation data generated by existing studies.

The prevalence of dyslipidemia in this review is higher than the finding of the study conducted among the hormonal contraceptive users from April to June 2014 at three health centers and one hospital in Harar town, Eastern Ethiopia (34.8%) (8). However, the present finding is lower than the findings of the study in Jimma, Southwestern Ethiopia (68.1%) (34), and South Africa (67.3%) (50). The finding of this review was also lower than the finding of a study done in Kembata, Southern Ethiopia (65.5%) (35), and Mekelle city, Northern Ethiopia (66.7%) (17). The higher prevalence of dyslipidemia might be attributed to the rapid urbanization, improved socioeconomic status, a change in the power of work, inadequate physical activity, and alteration in dietary habits.

The present study showed that the raised FBG was positively associated with dyslipidemia, which agrees with many previous studies (8, 51, 52). This might be because DM can cause a range of derangements in oxidation or reduction in lipid metabolism, which could in turn be responsible for the accumulation of lipid particles (34). We also revealed that the raised BP level was an independent predictor of dyslipidemia, which is consistent with the study conducted in Germany (52); but, the findings of this review disagree with the findings of the study reported in Iraq (53). This variation might be due to differences in the underlying disease, socio-demographic factors, genetic predisposition, dietary factors, and inadequate physical activity, which results in a higher incidence of metabolic abnormalities.

In the current review, BMI was found to have a positive association with dyslipidemia, which is consistent with many previous studies (16, 51, 54, 55). This finding is also similar to studies conducted in Ethiopia (44), Uganda (56), and Tanzania (57). However, previous works have doubted the reliability of BMI as an indicator of obesity (58, 59). Moreover, in young healthy adults, BMI and other surrogate indices of fatness, such as waist-to-height ratio and body adiposity index provide a poor prognosis of fat mass (60, 61). The observed association in other studies can be supported by the occurrence of ART associated lipodystrophy, which may be accompanied by the loss of peripheral subcutaneous fat (62). The other differences may be because the current review was conducted on participants with underlying different types of disease while other studies conducted only on patients with HIV and DM.

In our review, abdominal obesity or WC ≥ 94 cm was significantly associated with dyslipidemia, which agrees with other studies (34, 63). So far, anthropometric measurements, such as BMI, have been the most widely used instrument to measure general obesity. However, BMI does not account for the variation in body fat distribution and abdominal fat (64, 65). Excess of intra-abdominal fat causes a greater risk of morbidity than the overall fat accumulation (66). Thus, WC has been by far the best indicator of both intra-abdominal and total fat (67). Generally, altered anthropometric (68) and adipose tissue size have been associated with dyslipidemia in persons with and without HIV (69, 70). We found that the prevalence of dyslipidemia was almost equally determined by both BMI and WC. This might be due to a high chance of increasing concentrations of different lipid particles with increased BMI. Therefore, the combination of different anthropometric measurements should be used to evaluate the health condition of the patient or population.

Similar to the current review, studies conducted in South Africa (71), Cameroon (72) showed that being the female gender was not associated with a higher probability of presenting with dyslipidemia. In contrast to our review, the findings of a study done in Tanzania showed that being the female gender was an independent predictor of dyslipidemia (57). The discrepancy is more likely due to gender-related exercise, habits, and biological differences between men and women (27). Moreover, this study also found that lower odds of dyslipidemia were found among participants who have attained a lower level of education when compared with those who attended college and above. This is in agreement with other studies (41, 73). In contrast, other studies found contradicting results (74, 75). This may be due to differences in lifestyle.

In this study, sex, increased BMI, increased BP, and sedentary lifestyles were significantly associated with the increased risk of dyslipidemia. As all are modifiable risk factors except sex, it is essential to deliver behavioral interventions on the identified risk factors. Dietary modification is one of the most important lifestyle changes that have been shown to significantly decrease the risk of CVD. The CVD burden is reduced by optimum diet through the replacement of unprocessed meat with low saturated fat, animal proteins, and plant proteins (76). The recommended Dietary Reference Intake (DRI) daily allowance in men aged 19–50 years is 38 g/day and women aged 19–50 years is 25 g/days, and for men aged >51 is 31 g/day and women aged >51 is 21 g/day. The recommendation for children aged 1–3 is 19 g/day and aged 4–8 is 25 g/day. For boys, aged 9–13, the DRI recommendations are 31 g/day and 38 g/days for aged 14–18. For girls aged 9–18, the DRI recommendations are 26 g/day (77). Individuals are also recommended to intake fruit and vegetables at least 5 servings per day, perform moderate activity for more than 150 min/week, do vigorous physical activity for at least 75 min/ week, reduce salt and sugar intake to prevent dyslipidemia (2).

The limitations of this systematic review with meta-analysis include some studies did not have enough predictor variables to adequately determine the degree of its prediction, However, attempts were made to include all other potential variables that occurred across the identified database. Another limitation of this study was that we did not identify the association between diet and dyslipidemia because we could not retrieve data from original articles. To overcome such problems, important discussions were made concerning the quantity and quality of daily intake. It might also lack continental representativeness since no information was found from northern regions of the African continent. But, the demographic characteristics of the population in the North African region were almost similar to the rest of the other regions.

This review exposed that dyslipidemia is relatively high among study participants. The prevalence of dyslipidemia was the highest among the category of studies conducted on a group of communicable diseases and the general population. On the other hand, the lowest prevalence of dyslipidemia was reported among studies conducted on a group of infectious diseases. In addition, the highest prevalence of dyslipidemia was found among studies from East Africa and Southern Africa. The independent predictors of dyslipidemia were BMI >25.0 kg/m², raised FBG, raised BP, and WC > 94 cm. In addition, sex, medication adherence, educational status, FBG, BP, BMI, WC, marital status, and sedentary life were strongly associated with dyslipidemia. There should also be a pressing public health measure to prevent, identify, and treat dyslipidemia with a special emphasis on obese, diabetic, and hypertensive patients. Future researchers were recommended to address the association between diet and dyslipidemia.

The original contributions presented in the study are included in the article/Supplementary Material, further inquiries can be directed to the corresponding author/s.

MO and GA were involved in the selection of study, data extraction, quality assessment, statistical analysis, results interpretation, and writing the initial and final drafts of the manuscript. GAA, BW, TT, NAw, NAy, YH, and BJ were involved in data extraction, quality assessment, statistical analysis, and writing drafts of the manuscript. All authors read and approved the final manuscript, contributed to the article, and approved the submitted version.

The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.

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