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Research Paper | Oncology Science | India | Volume 5 Issue 11, November 2016 | Popularity: 7.2 / 10

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Effect of Various Variables of Demographic and Life Style on Menopausal Women by Neural Network

Meenakshi Gahlot, Bharti Prakash

Abstract: Epidemiological factor play an important role in identifying the factors responsible for menopausal cancer. Demographic and life style tools are helpful in reducing cancer burden. Present study if focused on impact of demographic and life style on incidence of breast, cervical and uterine cancer with focus on menopausal women ageing 21-70 and above. Methods It is an epidemiological study in Ajmer municipal area with retrospective recorded data on breast, cervical and uterine cancer. Participants of current study were registered and diagnosed with breast, cervical and uterine cancer in different hospital of Ajmer municipal area between January 2010-Dec.2014. Women aged 21-70 and above with invasive cervical, uterine and breast cancer diagnosed in different major hospitals of Ajmer municipal area. Impact of demographic and life style on menopausal factor was analyzed by neural network technique. Results There is evidence that demographic and life style factors were associated with menopausal cancer. The significance value revealed that the role of cause of menopause, age of last period, physical activity/day, family member suffering from cancer, type of cancer family member suffering with, hormone therapy for menopause, BMI and other variables were significant at confidence interval of 0.05 level. Conclusions To significantly reduce the breast, uterine and cervical cancer mortality and different life style factor should be sturdily intensified to improve long term effectiveness. Quality assessment of life style should be done via early indicators. New cancer life style guidelines should be introduce in Ajmer municipal area and some of them should be gradually incorporated into society practice.

Keywords: Cancer risk, menopausal women, Life style, Neural network

Edition: Volume 5 Issue 11, November 2016

Pages: 651 - 653

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