The difference between modern lifestyle in urban areas and the traditional way of life in rural areas may affect the population's health in developing countries proportionally. In this study, we sought to describe and compare the metabolic (fasting blood sugar and lipid profile) profile in an urban and rural sample of a Cameroonian population, and study the association to anthropometric risk factors of obesity. 332 urban and 120 rural men and women originating from the Sanaga Maritime Department and living in the Littoral Region in Cameroon voluntarily participated in this study. In all participants, measurement of height, weight, waist circumference, hip circumference, blood pressure systolic (SBP) and blood pressure diastolic (DBP), resting heart rate (RHR), blood glucose and lipids was carried out using standard methods. Total body fat (BF%) was measured using bio-impedancemetry. Body mass index (BMI) and waist to hip ratio (WHR) were calculated. Low Density Lipoprotein-cholesterol (LDL-c) concentrations were calculated using the Friedwald formula. World Health Organization criteria were used to define high and low levels of blood pressure, metabolic and anthropometric factors. The highest blood pressure values were found in rural men. Concerning resting heart rate, only the youngest women's age group showed a significant difference between urban and rural areas (79 ± 14 bpm vs 88 ± 12 bpm, p = 0.04) respectively. As opposed to the general tendency in our population, blood glucose was higher in rural men and women compared to their urban counterparts in the older age group (6.00 ± 2.56 mmol/L vs 5.72 ± 2.72 mmol/L, p = 0.030; 5.77 ± 3.72 vs 5.08 ± 0.60, p = 0,887 respectively). Triglycerides (TG) were significantly higher in urban than rural men (1.23 ± 0.39 mmol/L vs 1.17 ± 0.64 mmol/L, p = 0.017). High Density Lipoprotein-cholesterol (HDL-c) levels were higher in rural compared to urban men (2.60 ± 0.10 35mmol/L vs 1.97 ± 1.14 mmol/L, p<0.001 respectively). However, total Cholesterol (TC) and LDL-c were significantly higher in urban than in rural men (p<0.001 and p = 0.005) and women (p<0.001 respectively. Diabetes' rate in this population was 6.6%. This rate was higher in the rural (8.3%) than in the urban area (6.0%). Age and RHR were significantly higher in diabetic women than in non-diabetics (p = 0.007; p = 0.032 respectively). In a multiple regression, age was an independent predictor of SBP, DBP and RHR in the entire population. Age predicted blood glucose in rural women only. BMI, WC and BF% were independent predictors of RHR in rural population, especially in men. WC and BF% predicted DBP in rural men only. Anthropometric parameters did not predict the lipid profile. Lipid profile was less atherogenic in rural than in urban area. The rural population was older than the urban one. Blood pressure and blood glucose were positively associated to age in men and women respectively; this could explain the higher prevalence of diabetes in rural than in urban area. The association of these metabolic variables to obesity indices is more frequent and important in urban than in rural area.
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