Abstract
The objective of this paper is to analyze the relation of blood pressure values and the dimensions and different muscle and fat rates in healthy young women’s arms by means of data mining techniques. Methodology: 341 women from 18 to 29 years old were appraised in Divinópolis, Brazil and data on anthropometric measurements and Blood Pressure was collected and developed in multiple linear regression models using data mining techniques. Results: the average was 105,55 mmHg for systolic blood pressure (SBP) and 64,56 mmHg for diastolic blood pressure (DBP). The right arm’s SBP was higher when compared to the left arm (106,22 × 104,89) and DBP in the right arm was lower than it was in the left arm (63,94 × 65,19). The values of arm’s length (AL), triceps skinfold (TS) and arm’s muscle circumference (MC) correlates to SBP and DBP. The variables AL e MC can be considered forecasts of the increase of PAS and PAD’s values. Higher levels of MC Values with TS higher than 21,05 was a relevant factor in SBP’s increase. Conclusion: there are suggestions as to the dimensions and different fat and muscle rates being correlated with BP indirect measurement values: AL overestimates both SBP and DBP. TS and MC show distinct correlations between SBP and DBP according to specific intervals. Due to sex-related differences in the body composition of arms, can it be a measurement bias?
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de Oliveira Souza, P., de Oliveira, J.M.P., Januário, L.H. (2019). Indirect Measurement of Blood Pressure and Arm’s Body Composition in Women: Identification of Rules and Patterns Using Statistics and Data Mining. In: Rocha, Á., Adeli, H., Reis, L., Costanzo, S. (eds) New Knowledge in Information Systems and Technologies. WorldCIST'19 2019. Advances in Intelligent Systems and Computing, vol 932. Springer, Cham. https://doi.org/10.1007/978-3-030-16187-3_7
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