BackgroundIn Nigeria, reports on the prevalence of modifiable cardiovascular disease (CVD) risk factors are scarce. In addition, socio-economic status (SES), an important component of the socioeconomic gradient in CVD and its risk factors has not been clearly elucidated. This study sought to assess the prevalence of CVD risk factors and how the difference in prevalence and accessibility to CVD risk screening across income levels and educational backgrounds contributes to disease diagnosis in rural and urban Nigerian adults.MethodsA cross sectional study was carried out on a sociocultural ethnic group of persons living in rural and urban settings. All participants were aged ≥ 18 years. The WHO STEPS questionnaire was used to document the demographics, history of previous medical check-up or screening, anthropometric and biochemical measurements of the participants. Average income level and educational status were indicators used to assess the impact of SES. Multivariate analyses were performed to assess any difference between the geographical locations and SES indicators, and prevalence of CVD risk factors and access to CVD risk screening.ResultsThe 422 participants (149 males and 273 females) had mean age (± standard deviation) of 38.3 ± 20.5 and 42.9 ± 20.7 years, respectively. Only total cholesterol (p = 0.001), triglyceride (p = 0.005), high density lipoprotein cholesterol (HDL) (p < 0.0001), body mass index (BMI) (p = 0.03) and average income rate (p = 0.01) showed significant difference between gender groups. Overall prevalence of prediabetes (4.9%), diabetes (5.4%), hypertension (35.7%), low HDL (17.8%), hypertriglyceridemia (23.2%), hypercholesterolemia (38.1%) and central obesity of 52.2% was recorded. Except between total cholesterol (p = 0.042) and HDL (p = 0.017), other CVD risk factors did not show a statistical significance across income levels. Participants with ‘university and postgraduate education’ had higher access to blood pressure and blood glucose screening compared to other educational groups; and this showed a statistical significance.ConclusionThis study has shown that a significant number of modifiable CVD risk factors exist in the rural and urban migrants of an adult Nigerian population. While income level did not affect the CVD risk factor prevalence, it did affect accessibility to CVD risk screening. There is a need for access to diagnosis of modifiable risk factors at all levels of society.

The study aims to develop a screening protocol for the risk of future cardiovascular disease and diabetes mellitus in people with prediabetes and undiagnosed diabetes; and to establish a framework for early identification and intervention of prediabetes including strategies for holistic management and monitoring of progression. The first phase is to identify prediabetes and undiagnosed diabetes in volunteers who are ≥18-years-old for 5 years. Point-of-care testing and questionnaire will be used to screen for prediabetes and cardiovascular disease. We anticipate screening more than 2000 individuals of both genders by the end of first phase. The second and third phases which shall run for 5-10 years will be longitudinal study involving participants identified in the first phase as having prediabetes without dyslipidaemia, or clinically established cardiovascular disease. The second phase shall focus on preventive management of risk of progress to diabetes with explicit diagnosis of cardiovascular disease. Oxidative stress measurements will be performed cum evaluation of the use of antioxidants, exercise, and nutrition. The third phase will include probing the development of diabetes and cardiovascular disease. Binomial logistic regression would be performed to generate and propose a model chart for the assessment of cardiovascular disease risk in prediabetes.

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Of the 211 subjects, mean age was 51.3±17.3 years. Average risk of developing CVD in the next 10 years was 3.7±5.3%. Prevalence of low, moderate and high risk of developing CVD among study participants was 86.3% (95% CI 82.0-91.3%), 11.8% (95% CI 6.9-16.1%) and 1.9% (95% CI 0.0-3.8%), respectively. Prevalence of MetS was 26.7% (95% CI 21.0-33.3%). There was poor agreement between MetS and the CVD risk scores (kappa=0.209, p=0.001) CONCLUSIONS: The results showed that complementary use of MetS and CVD risk score is imperative, as there is indication of risk in individuals without MetS. Also a large proportion of the study population requires lifestyle intervention. These findings provide the evidence necessary to tailor public health interventions in this population, especially towards younger age groups.