Background:Leptin is a hormone produced directly from adipocytes and has been associated with type 2 diabetes mellitus (T2DM) which is characterized by insulin resistance (IR). Due to the increasing prevalence of obesity in sub-Saharan Africa, serum leptin can be explored as a predictive risk factor for T2DM. Therefore, the aim of this study was to determine the relationship between serum leptin and IR among obese women.Methods:This was a cross-sectional study of obese, adult Nigerian females. Participants with body mass index (BMI) ≥30 kg/m2 and nondiabetic were recruited as subjects. Fasting serum leptin, insulin, and plasma glucose were determined. IR was calculated using the formula: Homeostatic model assessment-IR (HOMA-IR) = (glucose × insulin)/22.5. Statistical analyses were performed using SPSS and P < 0.05 was considered to be significant.Results:Eighty obese females with mean ± standard deviation BMI 39.1 ± 7.2 kg/m2 and serum leptin level 48.4 ± 24.4 ng/ml participated in study. Prevalence of hyperleptinemia was 92.5% (confidence interval: 87.3–97.7%). The relationship between leptin and HOMA-IR among the subjects was: BMI 30–34.9 kg/m2: n = 27, r = 0.18, P = 0.42; BMI 35–39.9 kg/m2: n = 24, r = 0.36, P = 0.11; BMI ≥ 40 kg/m2: n = 29, r = 0.52, P = 0.004*; and after controlling for BMI (n = 29, r = 0.46, P = 0.014*). Multiple linear regression showed that leptin did not predict for IR (P = 0.837).Conclusion:Serum leptin levels were positively correlated with IR, which was significant among the Class III (morbid) obesity class. However, leptin was not a predictive factor for IR in obese Nigerian women.

IntroductionCardiovascular risk factors are prevalent in HIV-positive patients which places them at increased risk for cardiovascular disease (CVD). We aimed to determine the risk factors and risk assessment for CVD in HIV-positive patients with and without antiretroviral therapy.MethodsThis was a cross-sectional study of HIV-positive patients attending the Lagos University Teaching Hospital, Nigeria. Anthropometric and blood pressure measurements were performed; fasting lipid profile, plasma glucose, homocysteine and hsCRP were determined, as well as prevalences and risk assessments. Statistical tests were used to compare the groups and p-value <0.05 was considered to be significant.Results283 subjects were recruited for this study (100 HIV-positive treatment-naive, 100 HIV-positive treated and 83 HIV negative controls). Compared to the controls, mean (sd) values were significantly higher among HIV-treated subjects: waist circumference = 88.7 (10.4), p = 0.035; systolic bp= 124.9 (20.7), p = 0.014; glucose= 5.54 (1.7), p = 0.015; triglyceride= 2.0 (1.2), p < 0.001; homocysteine= 10.9 (8.9-16.2), p = 0.0003; while hsCRP= 2.9 (1.4-11.6), p = 0.002 and HDL-C = 0.9 (0.4), p = < 0.0001 were higher among the HIV-naïve subjects. Likewise, higher prevalences of the risk factors were noted among the HIV-treated subjects except low HDL-C (p < 0.001) and hsCRP (p = 0.03) which were higher in the HIV-naïve group. Risk assessment using ratios showed high risk for CVD especially in the HIV-naïve group. The median range for Framingham risk assessment was 1.0 - 7.5%.ConclusionRisk factors and risk assessment for CVD are increased in HIV-positive patients with and without antiretroviral therapy. Routine evaluation and risk assessment for CVD irrespective of therapy status is necessary to prevent future cardiovascular events.

BACKGROUND:Low-density lipoprotein cholesterol (LDLC) is a modifiable risk factor for atherosclerotic cardiovascular disease, therefore needs to be assessed and monitored. Direct homogeneous assays and various formulas exist to determine LDLC. We aimed to compare the directly measured LDL (dLDLC) with ten formulas for estimating LDLC.MATERIALS AND METHODS:This was a 2-year retrospective study of fasting lipid profile results obtained from HIV-positive patients attending an outpatient clinic at the University of Nigeria Teaching Hospital, Enugu, Nigeria, using homogeneous direct assays. Estimated LDLC was determined using ten formulas. Pearson's correlation, Bland–Altman plots, and linear regression were performed. Statistical significance was P < 0.05.RESULTS:Three thousand four hundred and eighty-two lipid results with mean ± standard deviation (SD) dLDLC of 2.1 ± 1.1 mmol/L were included in this study. There was a strong, positive correlation between Friedewald's LDLC and dLDLC n = 3412, r = 0.84, P < 0.001, but linear regression demonstrated a proportional bias P = 0.005. Ahmadi's equation showed the worst correlation n = 3482, r = 0.35, P < 0.001, but when applied to samples with triglyceride (TG) <1.13 mmol/L (100 mg/dl), the correlation showed a strong, positive relationship n = 1395, r = 0.80, P < 0.001, and no proportional bias P = 0.86. Teerankanchana's equation was the only formula that showed no difference between its LDLC and dLDLC (n = 3482, P = 0.056). It also demonstrated strong, positive correlation (n = 3482, r = 0.84, P < 0.001) and had a mean difference ± SD of −0.68 ± 0.63.CONCLUSION:Teerankanchana's formula showed good correlation and minimal bias with dLDLC at all TG levels. Moreover, linear regression showed no difference in the two. It seems to be the most suitable formula for estimating LDLC in our HIV-positive population.

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