Association between metabolic syndrome and 10-year risk of developing cardiovascular disease in a Nigerian population.

BACKGROUND: Prevalence of metabolic syndrome (MetS) and consequential cardiovascular disease (CVD) events are on the increase in Nigeria. The study aimed to identify the prevalence of 10-year CVD risk in a Nigerian population and assess its relationship with different indices of MetS. METHOD: A cross-sectional study was carried out on apparently healthy persons aged 18 years of age or older. Ten-year risk was calculated using the ATPIII/Framingham criteria. Subjects with risk score <10% were considered as having low risk, 10-20% moderate risk and >20% at high risk of developing CVD in 10 years. MetS was defined based on the Joint Scientific Statement on Harmonizing the MetS. RESULT: 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.

Maximum accuracy obesity indices for screening metabolic syndrome in Nigeria: A consolidated analysis of four cross-sectional studies.

BACKGROUND: In sub-Saharan Africa, there is no precise use of metabolic syndrome (MetS) definitions and risk factors screening indices in many clinical and public health services. Methods proposed and used in Western populations are adopted without validation within the local settings. The aim of the study is to assess obesity indices and cut-off values that maximise screening of MetS and risk factors in the Nigerian population. METHOD: A consolidated analysis of 2809 samples from four population-based cross-sectional study of apparently healthy persons≥18 years was carried out. Optimal waist circumference (WC) and waist-to-height ratio (WHtR) cut points for diagnosing MetS and risk factors were determined using Optimal Data Analysis (ODA) model. The stability of the predictions of the models was also assessed. RESULTS: Overall mean values of BMI, WC and WHtR were 24.8±6.0kgm(-2), 84.0±11.3cm and 0.52±0.1 respectively. Optimal WC cut-off for discriminating MetS and diabetes was 83cm in females and 85cm in males, and 82cm in females and 89cm in males, respectively. WC was stable in discriminating diabetes than did WHtR and BMI, while WHtR showed better stability in predicting MetS than WC and BMI. CONCLUSION: The study shows that the optimal WC that maximises classification accuracy of MetS differs from that currently used for sub-Saharan ethnicity. The proposed global WHtR of 0.50 may misclassify MetS, diabetes and hypertension. Finally, the WC is a better predictor of diabetes, while WHtR is a better predictor of MetS in this sample population.

Association of physical activity with metabolic syndrome in a predominantly rural Nigerian population.

AIMS: Physical activity is an essential determinant of health. However, there is dearth of evidence regarding prevalence of physical activity in developing countries, especially its association with metabolic syndrome risk factors. This study assessed the association of physical activity with metabolic syndrome in a Nigerian population. MATERIALS AND METHODS: A cross-sectional study was carried out on apparently healthy persons who are ≥ 18 years old. The World Health Organisation (WHO) Global Physical Activity Questionnaire (GPAQ) was used to collect five domains of physical activity. Participants were classified as physically active or inactive based on meeting the cut-off value of 600 MET-min/week. Metabolic syndrome was diagnosed using the Joint Scientific Statement on Harmonizing the Metabolic Syndrome criteria. RESULTS: Overall prevalence of physically active individuals was 50.1% (CI: 45.6-54.7%). Physical inactivity is significantly more in females (p<0.01) and among participants >40 years old (p<0.0001). Whereas individuals with metabolic syndrome appeared more likely to be physically active (OR=1.48, CI: 0.71-3.09); physical inactivity showed to exist more among participants who were living in urban area (OR=6.61, CI: 3.40-12.85, p<0.001). Participants with prediabetes (OR=1.69, CI: 0.62-4.61) and diabetes (OR=1.91, CI: 0.65-5.63) were more likely to be physically inactive as compared to other metabolic syndrome risk factors. CONCLUSION: The high prevalence of physical inactivity in this study population is a clear indication that concerted efforts to improve physical activity may be required. However, it seems that metabolic syndrome is not improved by being physically active. This suggests that interventions directed at physical activity alone may not produce optimal efficacy in this study population.