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Associations between Breast Density on Mammography and Lifestyle Related Disease


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Associations between Breast Density on Mammography and Lifestyle Related Disease

Article information

Korean J Health Promot. 2017;17(1):1-8
Publication date (electronic) : 2017 March 31
doi : https://doi.org/10.15384/kjhp.2017.17.1.1
Dae Yeon Hwang, Yu Lee Kim, Bong Woon Hwang, Kwang Hyun Kim, Ji Young Lym
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
Received 2016 October 24; Accepted 2017 February 09.

Abstract

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.

Keywords: Mammography; Breast density; Life Style Induced Illness; Breast cancer

References

1. National cancer center. Breast cancer screening guideline [Internet] Goyang: National cancer information center; 2015. Accessed Oct 1, 2016. Available from: http://www.cancer.go.kr/ebook/146/webview/index.html.
2. McPherson K, Steel CM, Dixon JM. ABC of breast disease. Breast cancer-epidemiology, risk factors, and genetics. BMJ 2000;321(7261):624–628.
3. Boyd NF, Lockwood GA, Byng JW, Tritcher DL, Yaffe MJ. Mammographic densities and breast cancer risk. Cancer Epidemiol Biomarkers Prev 1998;7(12):1133–1144.
4. American College of Radiology. ACR BI-RADS® atlas: Breast imaging reporting and data system 5th editionth ed. Reston: American College of Radiology; 2013.
5. Carney PA, Kasales CJ, Tosteson AN, Weiss JE, Goodrich ME, Poplack SP, et al. Likelihood of additional work-up among women undergoing routine screening mammography: the impact of age, breast density, and hormone therapy use. Prev Med 2004;39(1):48–55.
6. Sellers TA, Vachon CM, Pankratz VS, Janney CA, Fredericksen Z, Brandt KR, et al. Association of childhood and adolescent anthropometric factors, physical activity, and diet with adult mammographic breast density. Am J Epidemiol 2007;166(4):456–464.
7. Jeon JH, Kang JH, Kim Y, Lee HY, Choi KS, Jun JK, et al. Reproductive and hormonal factors associated with fatty or dense breast patterns among Korean women. Cancer Res Treat 2011;43(1):42–48.
8. Jun JK, Kim MJ, Choi KS, Suh M, Jung KW. Development of a sampling strategy and sample size calculation to estimate the distribution of mammographic breast density in Korean women. Asian Pac J Cancer Prev 2012;13(9):4661–4664.
9. Kim SH, Kim MH, Oh KK. Analysis and comparison of breast density according to age on mammogram between Korean and Western women. J Korean Radiol Soc 2000;42(6):1009–1014.
10. Goh E, Shin KW, Seo YY, Ko JA, Park MS, Cho B, et al. Breast density in mammography according to body mass index(BMI) in Korean women. Korean J Health Promot Dis Prev 2008;8(4):281–286.
11. Jung JS, Kim JS, Park YM, Lee K, Park TJ. The relationship between body mass index and mammographic density in Korean women. J Korean Acad Fam Med 2008;29(11):831–837.
12. Cho JJ, Song HJ, Koh EY, Song YM, Han BK, Yun YS, et al. Mammographic breast density and risk factors of breast cancer in Korean women using multicenter study. J Korean Acad Fam Med 2006;27(1):33–41.
13. Lee S, Park HS, Kim SM, Kwon HS, Kim DY, Kim DJ, et al. Cut-off points of waist circumference for defining abdominal obesity in the Korean population. Korean J Obes 2006;15(1):1–9.
14. Basevi V, Di Mario S, Morciano C, Nonino F, Magrini N. Comment on: American diabetes association. Standards of medical care in diabetes--2011. Diabetes Care 2011;34(Suppl. 1):S11-S61. Diabetes Care 2011;34(5):e53. author relpy e54.
15. Korean Society of Lipidology and Atherosclerosis. Dyslipidemia treatment guideline. 3rd edition [Internet] Seoul: Korean Society of Lipidology and Atherosclerosis; 2015. Accessed Oct 1, 2016. Available from: http://www.lipid.or.kr/bbs/skin/default/download.php?code=care&number=1100.
16. Kang JK. Concept of lifestyle-related disease. Korean J Med 2003;65(1):121–125.
17. Humphrey LL, Helfand M, Chan BK, Woolf SH. Breast cancer screening: a summary of the evidence for the U.S. preventive services task force. Ann Intern Med 2002;137(5 Part 1):347–360.
18. Grove JS, Goodman MJ, Gilbert FI Jr, Mi MP. Factors associated with mammographic pattern. Br J Radiol 1985;58(685):21–25.
19. Carney PA, Miglioretti DL, Yankaskas BC, Kerlikowske K, Rosenberg R, Rutter CM, et al. Individual and combined effects of age, breast density, and hormone replacement therapy use on the accuracy of screening mammography. Ann Intern Med 2003;138(3):168–175.
20. Banks E, Reeves G, Beral V, Bull D, Crossley B, Simmonds M, et al. Influence of personal characteristics of individual women on sensitivity and specificity of mammography in the million women study: cohort study. BMJ 2004;329(7464):477.
21. Bhang SY, Lee HJ, Kang JH, Yu BY. Associations between metabolic syndrome and three-dimensional breast density using digital mammography. Korean J Health Promot 2015;15(4):168–174.
22. Conroy SM, Butler LM, Harvey D, Gold EB, Sternfeld B, Greendale GA, et al. Metabolic syndrome and mammographic density: the study of women's health across the nation. Int J Cancer 2011;129(7):1699–1707.
23. Boyd NF, Lockwood GA, Byng JW, Little LE, Yaffe MJ, Tritchler DL. The relationship of anthropometric measures to radiological features of the breast in premenopausal women. Br J Cancer 1998;78(9):1233–1238.
24. Sung J, Song YM, Stone J, Lee K, Kim SY. Association of body size measurements and mammographic density in Korean women: the healthy twin study. Cancer Epidemiol Biomarkers Prev 2010;19(6):1523–1531.
25. Sung J, Song YM, Stone J, Lee K, Kim SY. High-density lipoprotein cholesterol, obesity, and mammographic density in Korean women: the healthy twin study. J Epidemiol 2011;21(1):52–60.
26. Meyer MR, Barton M. Estrogens and coronary artery disease: new clinical perspectives. Adv Pharmacol 2016;77:307–360.
27. Chlebowski RT, Anderson GL, Gass M, Lane DS, Aragaki AK, Kuller LH, et al. Estrogen plus progestin and breast cancer incidence and mortality in postmenopausal women. JAMA 2010;304(15):1684–1692.
28. Han M. Metabolic syndrome emerging from menopause. J Korean Soc Menopause 2011;17(3):127–135.

Article information Continued

Copyright © 2017 Korean Society for Health Promotion and Disease Prevention

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.

Table 1

Breast composition categories according to ACR BI-RADS

Table 1

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

Table 2

The general characteristics of study population

Table 2

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.

Table 3

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

Table 3

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.

Table 4

Correlation between BI-RADS categories and lifestyle related disease

Table 4

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

Calculated by Spearman correlation analysis.

aCorrelation coefficient.

Table 5

Odds ratio for breast density in lifestyle related disease severity

Table 5

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.