Fuzzy Obesity Index for obesity treatment and surgical indication

A Fuzzy Obesity Index for being used as an alternative in obesity treatment and bariatric surgery indication (BSI) is presented in this paper. Obesity is nowadays understood as universal epidemy and became an important source of death and co-morbidities. The search for a more accurate method to evaluate obesity and to indicate a better treatment is important in the world health context. In this paper the Body Mass Index (BMI) is first modified and treated as fuzzy sets. BMI is characterized by its capacity of weight excess and considered the main criteria for obesity treatment and BSI. Nevertheless, the fat excess related to the Body Fat (BF) is actually the principal harmful factor in obesity disease, that is usually neglected. Due to that this paper also presents a new fuzzy mechanism for evaluating obesity by associating BMI with Body Fat (BF) that yields a fuzzy obesity index for obesity evaluation and treatment and allows to build up a Fuzzy Decision Support System (FDSS) for BSI. Different values of BMI and BF (in terms of %BF) used for validating the proposed method classify individuals in distinct categories with degrees of compatibility more realistic than those accomplished by Boolean classification, as usually occur. The proposed method may assume an important whole in medicine as an index for obesity evaluation and surgery treatment by using the advantages of BMI and BF in synergy.

[1]  A. Halpern,et al.  [Effects of growth hormone on anthropometric and metabolic parameters in android obesity]. , 2006, Arquivos brasileiros de endocrinologia e metabologia.

[2]  T. Cole,et al.  A simplified approach to analysing bio-electrical impedance data in epidemiological surveys , 2007, International Journal of Obesity.

[3]  C. Tseng.  Body composition as a risk factor for coronary artery disease in Chinese type 2 diabetic patients in Taiwan. , 2003, Circulation journal : official journal of the Japanese Circulation Society.

[4]  Pere Caminal,et al.  Cerebral State Index during Propofol Anesthesia: A Comparison with the Bispectral Index and the A-Line ARX Index , 2006, Anesthesiology.

[5]  Richard Ricciardi,et al.  Use of bioelectrical impedance analysis in the evaluation, treatment, and prevention of overweight and obesity , 2007, Journal of the American Academy of Nurse Practitioners.

[6]  G. Kolata.  Obesity declared a disease. , 1985, Science.

[7]  F. Katch,et al.  Muscular development and lean body weight in body builders and weight lifters. , 1980, Medicine and science in sports and exercise.

[8]  T Bouillon,et al.  Model-based control of mechanical ventilation: design and clinical validation. , 2004, British journal of anaesthesia.

[9]  T. Fukunaga,et al.  Characteristics of Body Composition and Muscle Strength in College Sumo Wrestlers , 1997, International journal of sports medicine.

[10]  JM Jakicic,et al.  Bioelectrical impedance analysis to assess body composition in obese adult women: The effect of ethnicity , 1998, International Journal of Obesity.

[11]  M. Kawai,et al.  Body mass index (weight/height2) or percentage body fat by bioelectrical impedance analysis: which variable better reflects serum lipid profile? , 1999, International Journal of Obesity.

[12]  D. Mohan,et al.  Validation of body fat measurement by skinfolds and two bioelectric impedance methods with DEXA--the Chennai Urban Rural Epidemiology Study [CURES-3]. , 2004, The Journal of the Association of Physicians of India.

[13]  R. Singh,et al.  Body fat percent by bioelectrical impedance analysis and risk of coronary artery disease among urban men with low rates of obesity: the Indian paradox. , 1999, Journal of the American College of Nutrition.

[14]  J A Hodgdon,et al.  Lean body mass estimation by bioelectrical impedance analysis: a four-site cross-validation study. , 1988, The American journal of clinical nutrition.

[15]  J. Manson,et al.  A prospective study of weight change and health-related quality of life in women. , 1999, JAMA.

[16]  W. Gulliver,et al.  Comparison of multifrequency bioelectrical impedance analysis with dual-energy X-ray absorptiometry for assessment of percentage body fat in a large, healthy population. , 2005, The American journal of clinical nutrition.

[17]  C. Pichard,et al.  Body mass index compared to dual-energy x-ray absorptiometry: evidence for a spectrum bias. , 1997, Journal of clinical epidemiology.

[18]  N. Wake,et al.  Effect of Lateral Positioning on Upper Airway Size and Morphology in Sedated Children , 2005, Anesthesiology.

[19]  S. Hunt,et al.  The relationship between body mass index and per cent body fat in the severely obese , 2007, Diabetes, obesity & metabolism.

[20]  E. York-Crowe,et al.  Comparison of Body Composition Methods in Obese African‐American Women , 2006, Obesity.

[21]  H C Lukaski,et al.  Validation of tetrapolar bioelectrical impedance method to assess human body composition. , 1986, Journal of applied physiology.

[22]  Y Schutz,et al.  Fat-free mass index and fat mass index percentiles in Caucasians aged 18–98 y , 2002, International Journal of Obesity.

[23]  Donna Spiegelman,et al.  Comparison of Bioelectrical Impedance and BMI in Predicting Obesity‐Related Medical Conditions , 2006, Obesity.

[24]  W. James,et al.  New understanding in obesity research , 1999, Proceedings of the Nutrition Society.

[25]  Jernej Virant,et al.  Fuzzy Logic Alternative for Analysis in the Biomedical Sciences , 1999, Comput. Biomed. Res..

[26]  Hierarchical differences in body composition of professional Sumo wrestlers. , 1999, Annals of human biology.

[27]  J. Swan.  Adiposity , 1960 .

[28]  E. York-Crowe,et al.  Percent body fat measured by BIA and DEXA in obese, African-American adolescent girls , 2005, International Journal of Obesity.

[29]  M. C. Mancini,et al.  Efeito do hormônio de crescimento sobre parâmetros antropométricos e metabólicos na obesidade andróide , 2006 .

[30]  A. Luke,et al.  Validity of Hand‐to‐Foot Measurement of Bioimpedance: Standing Compared with Lying Position , 2006, Obesity.

[31]  V. Reyna,et al.  A web exercise in evidence-based medicine using cognitive theory , 2001, Journal of General Internal Medicine.

[32]  R. Roubenoff.  Applications of bioelectrical impedance analysis for body composition to epidemiologic studies. , 1996, The American journal of clinical nutrition.

[33]  J K Udupa,et al.  Computer-assisted quantitation of enhancing lesions in multiple sclerosis: correlation with clinical classification. , 1997, AJNR. American journal of neuroradiology.

[34]  Maysam F. Abbod,et al.  Survey of utilisation of fuzzy technology in Medicine and Healthcare , 2001, Fuzzy Sets Syst..

[35]  N. Ortega,et al.  Fuzzy linguistic model for evaluating the risk of neonatal death. , 2002, Revista de saude publica.

[36]  Ian R Pateyjohns,et al.  Comparison of Three Bioelectrical Impedance Methods with DXA in Overweight and Obese Men , 2006, Obesity.

[37]  V. Heyward,et al.  Applied Body Composition Assessment , 1996 .

[38]  R. Poulton,et al.  Adiposity, asthma, and airway inflammation. , 2007, The Journal of allergy and clinical immunology.

[39]  Juan J. Nieto,et al.  Fuzzy Logic in Medicine and Bioinformatics , 2006, Journal of biomedicine & biotechnology.

[40]  E. Feskens,et al.  Underweight and overweight in relation to mortality among men aged 40-59 and 50-69 years: the Seven Countries Study. , 2000, American journal of epidemiology.

[41]  M. Thun,et al.  Body-mass index and mortality in a prospective cohort of U.S. adults. , 1999, The New England journal of medicine.

[42]  R. Trio,et al.  Impedance vector distribution by body mass index and conventional bioelectrical impedance analysis in obese women. , 2003, Nutrition, metabolism, and cardiovascular diseases : NMCD.

[43]  F. Katsukawa,et al.  Unusual left ventricular dilatation without functional or biochemical impairment in normotensive extremely overweight Japanese professional sumo wrestlers. , 2003, The American journal of cardiology.