Background: The objective of the present study was to compare the relationship of anthropometric and physiometric characteristics using principal component factor analysis among three groups of type 2 diabetic subject...Background: The objective of the present study was to compare the relationship of anthropometric and physiometric characteristics using principal component factor analysis among three groups of type 2 diabetic subjects such as males, pre and postmenopausal females in North Indian Punjabi population. Method: A total of 349 type 2 diabetic subjects (males 157;females 192;88 pre and 104 postmenopausal) were ascertained for the present study. Different anthropometric and physiometric measurements were taken. Principal component factor analysis (PCFA) was applied to identify the components which are more close to type 2 diabetes among the three groups. Results: PCFA revealed five uncorrelated components which explained 79% of the total variance among diabetic males and six unrelated components which explained 78% of the total variance among pre and postmenopausal females. The important two factors could be identified as central obesity (factor 1) and blood pressure (factor 2) among these three groups. Conclusion: Higher clustering of obesity and blood pressures were found in diabetic males as com pared to pre and postmenopausal diabetic females in North Indian Punjabi population whereas, waist to hip ratio (WHR) has maximum loading in postmenopausal females as compared to others.展开更多
文摘Background: The objective of the present study was to compare the relationship of anthropometric and physiometric characteristics using principal component factor analysis among three groups of type 2 diabetic subjects such as males, pre and postmenopausal females in North Indian Punjabi population. Method: A total of 349 type 2 diabetic subjects (males 157;females 192;88 pre and 104 postmenopausal) were ascertained for the present study. Different anthropometric and physiometric measurements were taken. Principal component factor analysis (PCFA) was applied to identify the components which are more close to type 2 diabetes among the three groups. Results: PCFA revealed five uncorrelated components which explained 79% of the total variance among diabetic males and six unrelated components which explained 78% of the total variance among pre and postmenopausal females. The important two factors could be identified as central obesity (factor 1) and blood pressure (factor 2) among these three groups. Conclusion: Higher clustering of obesity and blood pressures were found in diabetic males as com pared to pre and postmenopausal diabetic females in North Indian Punjabi population whereas, waist to hip ratio (WHR) has maximum loading in postmenopausal females as compared to others.
