Editorial
Volume 5 Issue 8 - 2020
Role of Body Mass Index on Insulin and Glucose for Breast Cancer Women
1Department of Physiology, Calcutta Medical College and Hospital, Kolkata, West Bengal, India
2Department of Statistics, The University of Burdwan, Burdwan, West Bengal, India
*Corresponding Author:Rabindra Nath Das, Department of Statistics, The University of Burdwan, Burdwan, West Bengal, India.
Received: July 03, 2020; Published: July 06, 2020
Body mass index (BMI = Weight(kg)/Height(m2)) is frequently treated as an important risk factor for many diseases. Generally, BMI < 25 kg/m2 is recommended as standard, otherwise it is treated as obesity. BMI is a composite measure, and it is used as the predictor of many diseases [1-3]. Practically, it is used as a measure of an individual index of fatness.
References
- Williams CL., et al. “Cardiovascular health in childhood: A statement for health professionals from the Committee on Atherosclerosis, Hypertension, and Obesity in the Young (AHOY) of the Council on Cardiovascular Disease in the Young, American Heart Association”. Circulation 106.1 (2002): 143-160.
- US Dept Health and Human Services. “The Surgeon General’s Call to Action to Prevent and Decrease Overweight and Obesity”. Rockville, MD: US Department of Health and Human Services, Public Health Service, Office of the Surgeon General (2001).
- National Institutes of Health. “Clinical guidelines on the identification, evaluation, and treatment of overweight and obesity in adults - the evidence report”. Obesity Research 6.2 (1998): 51-209S.
- Gunter MJ., et al. “Breast Cancer Risk in Metabolically Healthy but Overweight Postmenopausal Women”. Cancer Research 75.2 (2015): 270-274.
- Key TJ., et al. “Body mass index, serum sex hormones, and breast cancer risk in postmenopausal women”. Journal of the National Cancer Institute 95.16 (2003): 1218-1226.
- Crisóstomo J., et al. “Hyperresistinemia and metabolic dysregulation: a risky crosstalk in obese breast cancer”. Endocrine 53.2 (2016): 433-442.
- Patrício M., et al. “Using Resistin, glucose, age and BMI to predict the presence of breast cancer”. BMC Cancer 18.1 (2018): 18-29.
- Lee Y., et al. “Generalized Linear Models with Random Effects (Unified Analysis via H-likelihood) (second edition)”. Chapman and Hall, London (2017).
- Das RN and Lee Y. “Log-normal versus gamma models for analyzing data from quality-improvement experiments”. Quality Engineering 21.1 (2009): 79-87.
- Lesperance ML and Park S. “GLMs for the analysis of robust designs with dynamic characteristics”. Journal of Quality Technology 35.3 (2003): 253-263.
- Das RN., et al. “Relationship of body mass index with diabetes and breast cancer biomarkers”. Journal of Diabetes Management 9.1 (2019): 163-168.
- Kim J., et al. “Inter-relationship between diabetes and breast cancer biomarkers”. Oncology Radiotherapy 13.3 (2019): 82-89.
- Das RN. “Diabetes and obesity determinants based on blood serum”. Endocrinology and Diabetes Research 2.2 (2016): 1-6.
Citation: Ishita Saha and Rabindra Nath Das. “Role of Body Mass Index on Insulin and Glucose for Breast Cancer Women”. EC Endocrinology and Metabolic Research 5.8 (2020): 01-05.
Copyright: © 2020 Ishita Saha and Rabindra Nath Das. This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
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