Arya Bhatta Journal of Mathematics and Informatics
  • Year: 2021
  • Volume: 13
  • Issue: 2

Evaluation of breast self-examination and clinical breast examination among rural female population in Tamilnadu: A pilot study

  • Author:
  • N. Paranjothi1, G. Manimannan2, A. Poongothai3, A. Poompavai3, R. Lakshmi Priya4
  • Total Page Count: 6
  • Page Number: 259 to 264

1Department of Statistics, Annamalai University, Chidambaram, Tamil Nadu

2Department of Statistics, Apollo Arts Arts and Science College, Chennai, Tamil Nadu

3Department of Statistics, Annamalai University, Chidambaram, Tamil Nadu

4Department of Statistics, Dr. Ambedkar Govt. Arts College, Vysarpadu, Chennai, Tamil Nadu

*E-mail: manimannang@gmail.com

Online Published on 28 December, 2021.

Abstract

This research paper attempts a cross-sectional descriptive study conducted on Female rural population at Karpaka Vinayagar Institute of Medical Science and Research Center, Chengalpet, Tamilnadu, India, among female population regarding their awareness of Breast Self-Examination (BSE) and Clinical Breast Examination (CBE). In the recent days, breast cancer is play vital disease for women and men also. In this connection, the primary sources of samples were collected from voluntary basis. Secrecy and privacy of the responses was assured. The questionnaire consists of threesections: socio-economic parameters, BSE and CBE. All the questions are closed ended and the total samplesize is 200. Initially, the descriptive statistics were described in the form of frequency tables and percentages. Principal Component Analysis, k-mean cluster and Multiple Discriminant analysis used to identify the structure, pattern and Cross Validation of BSE and CBE.Principal Component Analysis (PCA) is used for data reduction or variable reduction and this method extracted 9 factors with 70.95%, the nine factor regression scores are statistically significant except 3 factor regression score. The k-mean cluster identified three meaningful clusters and cross validate with the help of Multiple Discriminant Analysis. The extracted factors are named as Knowledge of BSE 1, Initial Stage of BSE, use of BSE, tool for BSE, practice of BSE, Benefits of BSE, Mammography and CBE, Knowledge of BSE 2, without awareness of CBE and BSE. The k-means cluster analysis achieved three clusters with 88, 71 and 43 respondents based on the centroids of their cluster. The clusters are assessed by high awareness in second cluster, moderate awareness in third cluster and low awareness in first cluster respectively. Finally, three cluster cross validation using Multiple Discriminant Analysis (MDA) accounts to 96.5% of original grouped cases correctly classified in first iteration itself

Keywords

Descriptive Statistics, CBE, BSE, PCA, K-mean Clustering, Multiple Discriminant Analysis