Báo cáo sinh học: Fuzzy obesity index (MAFOI) for obesity evaluation and bariatric surgery indication

Tuyển tập báo cáo các nghiên cứu khoa học quốc tế ngành hóa học dành cho các bạn yêu hóa học tham khảo đề tài: Fuzzy obesity index (MAFOI) for obesity evaluation and bariatric surgery indication
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Báo cáo sinh học: "Fuzzy obesity index (MAFOI) for obesity evaluation and bariatric surgery indication"Miyahira et al. Journal of Translational Medicine 2011, 9:134http://www.translational-medicine.com/content/9/1/134 RESEARCH Open AccessFuzzy obesity index (MAFOI) for obesityevaluation and bariatric surgery indicationSusana Abe Miyahira1,2,3*, João Luiz Moreira Coutinho de Azevedo1 and Ernesto Araújo1,2,3 Abstract Background: The Miyahira-Araujo Fuzzy Obesity Index (MAFOI) for being used as an alternative in bariatric surgery indication (BSI) is validated in this paper. The search for a more accurate method to evaluate obesity and to indicate a better treatment is important in the world health context. Body mass index (BMI) is considered the main criteria for obesity treatment and BSI. Nevertheless, the fat excess related to the percentage of Body Fat (%BF) is actually the principal harmful factor in obesity disease that is usually neglected. The aim of this research is to validate a previous fuzzy mechanism by associating BMI with %BF that yields the Miyahira-Araujo Fuzzy Obesity Index (MAFOI) for obesity evaluation, classification, analysis, treatment, as well for better indication of surgical treatment. Methods: Seventy-two patients were evaluated for both BMI and %BF. The BMI and %BF classes are aggregated yielding a new index (MAFOI). The input linguistic variables are the BMI and %BF, and the output linguistic variable is employed an obesity classification with entirely new types of obesity in the fuzzy context, being used for BSI, as well. Results: There is gradual and smooth obesity classification and BSI criteria when using the Miyahira-Araujo Fuzzy Obesity Index (MAFOI), mainly if compared to BMI or %BF alone for dealing with obesity assessment, analysis, and treatment. Conclusion: The resulting fuzzy decision support system (MAFOI) becomes a feasible alternative for obesity classification and bariatric surgery indication.Background use as a leading cause of death, where obesity contri-The clinical conditions that are characterized as over- butes directly to the severity of the comorbities [12-15].weight (pre-obesity) and obesity are currently a universal Therefore, a great clinical interest exists for evaluatingepidemic of critical proportions. Efforts have been made overweight and obese patients to determine the risksto minimize this public health problem, but the preva- inherent with these conditions, to prescribe and controllence of obesity is still growing in both developed and conservative treatments, and to indicate when surgicaldeveloping countries [1-6]. treatment is needed. In the last 30 years, only the over- An excess of fat tissue (obesity) has been shown to be weight and obesity rating system, which uses the bodyharmful for multiple organs and systems through trom- mass index (BMI), has been internationally recognizedbogenic, atherogenic, oncogenic, hemodynamic, and [16] (Table 1).neuro-humoral mechanisms [7-11]. Recently, obesity BMI is a mechanism to measure weight excess exten-and related diseases (comorbidities), including diabetes sively used in a myriad of epidemiologic studies, and ismellitus, hypertension, coronary artery disease, cancer, incorporated with clinical practice because of its simpli-sleep apnea, and osteoartrosis, have replaced tobacco city [17]. However, it does not properly evaluate the body fat (BF) proportion because it fails to distinguish lean muscle mass from body fat [18]. The BF measure- ment has more value than global body mass measure-* Correspondence: susana_miyahira@uol.com.br1 Universidade Federal de São Paulo (UNIFESP), Brazil. R. Botucatu 740 - São ments since the harmful factor in obesity is thePaulo, SP, CEP 04023-900, Brazil accumulation of fat in the body, and lean muscle massFull list of author information is available at the end of the article ...