Differences among Diabetic &      Non-Diabetic persons, concerning       Body Fat Distribution assessed                   ...
E. Kapantais, E. Papadimitriou,                    K. Vendiadi, E. Manglara,                   K. Kofotzouli, M. Marangos ...
Background:       It is well established that excess body fat around the abdomen is      related to several metabolic dis...
Aim:        To assess the Conicity Index values             in a group of NIDDM, aged 50-65             years, as compare...
SUBJECTS & METHODS:       Subjects: Age: 50 - 65 years.                   86 Controls (53 males - 33 females) &          ...
RESULTS:               Males : 1.316 ± 0.081                         M ± SD              Females : 1.252 ± 0.112          ...
Mean BMI values.                                                          * p =0.025            30                        ...
Mean Conicity Index & WHR values               WHR         CONICITY INDEX                    * p=0.002                  ...
Conicity Index values,                   in Males and Females, NIDDM and Controls.                            MALES       ...
Correlation between Conicity Index & WHR                                  in Males and Females.                         r=...
Correlation between Conicity Index and WHR                       in Females with NIDDM & Controls.                        ...
Correlation between Conicity Index and WHR                         in Males with NIDDM & Controls.                        ...
CONCLUSIONS:                 In persons aged 50-65 years:               Women with NIDDM present                 similar ...
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1995 6th eco 3

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1995 6th eco 3

  1. 1. Differences among Diabetic & Non-Diabetic persons, concerning Body Fat Distribution assessed by CONICITY INDEX.6th European Congress on Obesity 1995
  2. 2. E. Kapantais, E. Papadimitriou, K. Vendiadi, E. Manglara, K. Kofotzouli, M. Marangos and N. Katsilambros. 1st Dpt. Propaedeutic Medicine Athens’ University Medical School “Laikon” General Hospital Athens - GREECE6th European Congress on Obesity 1995
  3. 3. Background:  It is well established that excess body fat around the abdomen is related to several metabolic disorders and mainly to type-2 Diabetes Mellitus (NIDDM).  The most accurate technique for assessing abdominal fat mass, Axial Computerized Tomography (ACT), is costly and time-consuming.  Anthropometry could be a valid alternative to ACT for the evaluatin of fat distribution. However, current anthropometric indicators of obesity have several limitations.  CONICITY INDEX implies that abdominal obesity is modelled as the progression of a body from cylindrical shape toward the shape of 2 cones with a common base at the waist level. This geometric approach expressed with the formula: CONICITY INDEX = abdominal girth 0.109(weight/height)½  With this new index, the abdominal girths of persons of the same height and weight are referred to the same standard value for comparison.6th European Congress on Obesity 1995
  4. 4. Aim:  To assess the Conicity Index values in a group of NIDDM, aged 50-65 years, as compared to Controls.  To study the correlation between CONICITY INDEX and WHR in NIDDM and Controls.6th European Congress on Obesity 1995
  5. 5. SUBJECTS & METHODS:  Subjects: Age: 50 - 65 years. 86 Controls (53 males - 33 females) & 64 Type-2 Diabetics (33 males - 31 females).  Measurements: Weight, Height, Abdominal Girth, Waist circumference, Hip circumference.  Calculation: 1) BMI= Weight / Height2 2) WHR= Waist circumference / Hip circumference 3) CONICITY INDEX= Abdominal Girth 0.109* (Weight / Height)½6th European Congress on Obesity 1995
  6. 6. RESULTS: Males : 1.316 ± 0.081 M ± SD Females : 1.252 ± 0.112 F M Males and Females CONICITY INDEX mean values.6th European Congress on Obesity 1995
  7. 7. Mean BMI values. * p =0.025 30 * 29 29.39 28 28.25 28.3 27 26 26.66 25 24 MALES FEMALES NIDDM1 Controls ### °×Ó·›Î˜: ¢È·‚ËÙÈ΀˜ - 4M¿ÚÙ×Ú˜ AÓ‰ Ú˜: ¢È·‚ËÙÈÎÔ› 2 - M¿ÚÙ×Ú˜ ## NIDDM 3 Controls6th European Congress on Obesity 1995
  8. 8. Mean Conicity Index & WHR values  WHR  CONICITY INDEX * p=0.002 * § p=0.001 § § MALES: FEMALES: NIDDM # Controls NIDDM # Controls6th European Congress on Obesity 1995
  9. 9. Conicity Index values, in Males and Females, NIDDM and Controls. MALES FEMALES 1.6 1.5 * 1.5 * 1.4 1.4 1.3 1.3 1.2 1.2 * * * 1.1 1.1 * 1.0 1.0 0 1 0 1 Controls # NIDDM Controls # NIDDM6th European Congress on Obesity 1995
  10. 10. Correlation between Conicity Index & WHR in Males and Females. r=0.78, p=0.000 r=0.74, p=0.000 1.2 1.1 1.1 1.0 W W H 1.0 H 0.9 R 0.9 R 0.8 0.8 0.7 0.7 1.0 1.1 1.2 1.3 1.4 1.5 1.6 1.0 1.1 1.2 1.3 1.4 1.5 Conicity Index Conicity Index MALES FEMALES6th European Congress on Obesity 1995
  11. 11. Correlation between Conicity Index and WHR in Females with NIDDM & Controls. r=0.58, p=0.001 r=0.80, p=0.000 1.0 1.1 1.0 0.9 W W H H 0.9 R 0.8 R 0.8 0.7 0.7 1.0 1.1 1.2 1.3 1.4 1.5 1.0 1.1 1.2 1.3 1.4 1.5 Conicity Index Conicity Index Controls NIDDM6th European Congress on Obesity 1995
  12. 12. Correlation between Conicity Index and WHR in Males with NIDDM & Controls. r=0.87, p=0.000 r=0.66, p=0.000 1.2 1.1 1.1 W 1.0 W 1.0 H H R 0.9 R 0.9 0.8 0.7 0.8 1.0 1.1 1.2 1.3 1.4 1.5 1.6 1.0 1.1 1.2 1.3 1.4 1.5 Conicity Index Conicity Index Controls NIDDM6th European Congress on Obesity 1995
  13. 13. CONCLUSIONS: In persons aged 50-65 years:  Women with NIDDM present similar Body Fat Distribution, as men with NIDDM.  Conicity Index is closely related to WHR.6th European Congress on Obesity 1995

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