Surpoids et obésité dans la population au-dessus de 20 ans en milieu urbain bamakois (Mali)

Introduction: il est question dans notre travail d'étudier le SP et l'OB et les facteurs associés dans la population âgée de 20 ans ou plus. Méthodes: notre échantillon a été obtenu à partir d'une enquête sur les pathologies cardiovasculaires dans le District de Bamako et impliquant 2199 sujets de 5-104 ans, en sélectionnant tous les sujets âgés d'au moins 20 ans (1162). Pour chaque sujet, l'IMC, rapport taille / hanche et le tour de taille ont été déterminées. Les données ont été analysées avec SPSS 12. Résultats: l'âge moyen était de 36,86 années, 61,4% étaient des femmes, 49,7% dans le secteur informel et 38,0% avaient réalisé l'enseignement primaire. Facteurs de risque cardiovasculaires étaient l'inactivité physique (72,4%), le tabagisme (12,2%) et hypertension (26,7%). La prévalence de l'obésité était de 8,8 et 14,7% respectivement sur la base de l'indice de masse et le tour de taille. Conclusion: le SP et l'OB sont à prendre en compte dans les mesures de politique sanitaire que dans la pratique quotidienne des professionnels de santé, il est peut-être plus utile d'utiliser plusieurs paramètres pour être à même de bien stratifier nos patients par rapport à leur risque

Hypertension and Associated Factors in Rural and Urban Areas Mali: Data from the STEP 2013 Survey

Background. Our study aims to estimate hypertension (HTN) prevalence and its predictors in rural and urban area. Methods. We conducted a cross-sectional population-based study involving subjects aged 15 to 65 years. Collected data (sociodemographic, blood pressure, weight, height, and blood glucose) were analyzed using SPSS version 20. A logistic regression was conducted to look for factors associated with HTN. Results. Mean was 47 years. High blood pressure (HBP) prevalence was 21.1 and 24.7%, respectively, in rural and urban setting. In rural area age group significantly predicted hypertension with age of 60 years having more-than-4-times risk of hypertension, whereas, in urban area age group, sex and body mass index were predictors with OR: HTN raising from 2.06 [1.24–3.43] for 30–44 years old to 7.25 [4.00–13.13] for 60 years and more using <30 years as reference. Female sex was protective with OR of 0.45 [0.29–0.71] and using normal weight as reference OR for overweight was 1.54 [1.04–2.27] and 2.67 [1.64–4.36] for obesity. Conclusion. Hypertension prevalence is high and associated factors were age group in rural area and age group, female sex, and body mass index in urban area

Differences in the Cardiovascular Risk Assessment in Cardiology Outpatients in Mali: Comparison between Framingham Body Mass Index-Based Tool and Low-Information World Health Organization Chart

Objective. This study aimed to compare 2 laborless tools, namely, the body mass index-based Framingham (bmi-Frm) and low-information WHO- (li-WHO-) based risk scores, and assess their agreement in outpatients in a cardiology department. Methodology. Data stem from a cross-sectional previous study performed from May to September 2016 in the Cardiology Department of University Hospital Gabriel Touré (UH-GT) in Bamako. All patients aged 40 and more were included in the study allowing the assessment of bmi-Frm and li-WHO prediction charts. The cardiovascular risk (CVR) was evaluated using a calculator prepared by D‘Agostino et al. for the bmi-Frm and the li-WHO chart for the Afro-D region of the WHO. The risk score for both ranged from <10 to ≥40. The data were entered in an ACCESS 2010 database, then processed by MS Excel 2010, and finally analysed using IBM SPSS Statistics 20. Continuous variables were presented as means and standard deviations, and categorical variables were presented as frequencies with percentages. P<0.05 was considered the statistical significance level. After sample description, the risk score was assessed using bmi-Frm and li-WHO prediction tools. Finally, a kappa test was performed to check for the interreliability of both methods. For weighted kappa, coefficients were given all five classes of risk groups in 0, 25 steps from 1 for total concordance to 0 for total discordance. Results. This study involved 793 outpatients, 63.7% being female, 35.1% of them younger than 50 years, 57.9% with no formal education, and 67.7% with no medical insurance. Means for age, body mass index (BMI), and systolic blood pressure (SBP) were, respectively, 53.81 ± 16.729 years, 25.29 ± 06.151 kg/m2, and 139.49 ± 27.110 mm Hg. Using the li-WHO prediction chart gives a much higher proportion of low-risk patients compared to bmi-Frm (83.6 vs. 37.7). Sociodemographic characteristics such as education or income level were not different in risk score neither for the bmi-Frm nor for the li-WHO risk score. The percentage of agreement between both tools was 40.4%, and agreement (kappa of 0.1 and weighted kappa of 0.2) was found to be slight. Conclusion. Using the bmi-Frm and li-WHO tool gives a similar risk estimation in younger female patients. Older patients must be evaluated using high-information tools with cholesterol, e.g., versions of the Framingham risk equation or WHO using cholesterol. These must be confirmed in further studies and compared to data from prospective studie