Korean J Health Promot KJHP Korean Journal of Health Promotion 2234-2141 2093-5676 Korean Society for Health Promotion and Disease Prevention 10.15384/kjhp.2017.17.1.1 Original Article Associations between Breast Density on Mammography and Lifestyle Related Disease Hwang Dae Yeon Kim Yu Lee Hwang Bong Woon Kim Kwang Hyun Lym Ji Young Department of Family Medicine, Busan Medical Center, Busan, Korea. Corresponding author: Yu Lee Kim, MD, MS. Department of Family Medicine, Busan Medical Center, 359 World cup-daero, Yeonje-gu, Busan 47527, Korea. Tel: +82-51-607-2179, Fax: +82-51-507-3001, 07721052@hanmail.net 03 2017 31 03 2017 17 1 1 8 24 10 2016 09 02 2017 Copyright © 2017 Korean Society for Health Promotion and Disease Prevention 2017 This is an open-access article distributed under the terms of the Creative Commons Attribution Non-Commercial License (http://creativecommons.org/licenses/by-nc/3.0/) which permits unrestricted non-commercial use, distribution, and reproduction in any medium, provided the original work is properly cited. Background

Dense breast reduced the sensitivity of mammography in breast cancer screening and known as an independent risk factor of breast cancer. The relationship between breast density and age, body mass index has studied. However, there are few studies on the relationship between breast density and lifestyle related disease. In this study, we investigated the relationship between mammographic breast density and lifestyle related disease.

 Methods

Retrospective cross sectional research was carried out from people who visited a single health screening center in Busan from January 2015 to December 2015. We investigated age, past history of the subjects and measured their height, weight, blood pressure and waist circumference. The biochemical test was carried out using their blood. All patients underwent mammography. The breast density on mammography determined by the basis of American College of Radiology Breast Imaging Reporting and Data System (ACR BI-RADS) breast composition and 996 people was recruited.

 Results

In the distribution of breast density, 16.3% of women (n=160) had dense breast. Age (under 49), body mass index (BMI) (underweight) were positively correlated with the BI-RADS composition category 3, 4 but the number of lifestyle related disease were negatively correlated (age ρ=0.17, BMI ρ=0.39, the number of lifestyle related disease ρ=-0.21). The odds ratio (OR) of dense breast increased with decreasing lifestyle related disease severity (OR=3.06, 95% confidence interval: 1.13-8.22, P=0.027).

 Conclusions

This study showed that the number of lifestyle related disease was negatively correlated with mammographic density. The OR of dense breast increased with decreasing lifestyle related disease severity. Therefore, primary physicians should consider negative correlation between breast density and lifestyle related disease in breast cancer screening.

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Abbreviation: ACR BI-RADS, American College of Radiology Breast Imaging Reporting and Data System.

 The general characteristics of study population

Abbreviations: BMI, body mass index; LDL-C, low-density lipoprotein cholesterol; HDL-C, high-density lipoprotein cholesterol; BI-RADS, Breast Imaging Reporting and Data System.

Values are presented as number (%).

Analyzed by frequency analysis.

 A comparison between BI-RADS 1, 2 and BI-RADS 3, 4

Abbreviations: BI-RADS, Breast Imaging Reporting and Data System; SD, standard deviation; BMI, body mass index; LDL-C, low-density lipoprotein cholesterol; HDL-C, high-density lipoprotein cholesterol.

aCalculated by Student's t-test.

bCalculated by Chi-square test.

 Correlation between BI-RADS categories and lifestyle related disease

Abbreviations: BI-RADS, Breast Imaging Reporting and Data System; BMI, body mass index.

Calculated by Spearman correlation analysis.

aCorrelation coefficient.

 Odds ratio for breast density in lifestyle related disease severity

Abbreviations: OR, odds ratio; CI, confidence interval; BI-RADS, Breast Imaging Reporting and Data System.

Calculated by logistic regression analysis.

aAdjusted for age, body mass index.