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Association between body mass index and incidence of breast cancer in premenopausal women: a Japanese nationwide database study

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Abstract

Purpose

The association between body mass index (BMI) and the incidence of premenopausal breast cancer in the Asian population remains unclear. We investigated this association using data from a Japanese nationwide administrative database.

Methods

We retrospectively identified 785,703 females aged < 45 years with available health checkup data on BMI from January 2005 and April 2020 from a Japanese nationwide database. Cox proportional hazards model was used to estimate hazard ratios for breast cancer (total breast cancer, breast cancer with hormonal drug and trastuzumab administration, and breast cancer by age ≤ 45 years) associated with BMI recorded at the first health checkup. We conducted restricted cubic spline analysis without BMI categorization to investigate potential nonlinear associations with adjustment for backgrounds such as smoking and alcohol consumption.

Results

Overall, the median BMI was 20.5 (interquartile range [IQR], 18.9–22.7) kg/m2, and the median age was 37 (IQR, 29–41) years. Breast cancer occurred in 5597 participants (0.71%) at a median age of 44 (IQR, 42–46) years during a median follow-up of 1034 (IQR, 634–1779) days. A BMI of ≥ 22.0 kg/m2 was significantly associated with lower incidences of total breast cancer, breast cancer with hormonal drug administration, and breast cancer by age ≤ 45 years, whereas no significant associations were observed for breast cancer with trastuzumab administration.

Conclusion

This study, which used a Japanese nationwide database, demonstrated that BMI was inversely associated with premenopausal breast cancer development in Japanese women, similar to that observed in Western women.

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Data availability

The data from the JMDC Claims Database are available for anyone who would purchase it from JMDC Inc. (JMDC Inc.; Tokyo, Japan; https://www.jmdc.co.jp/en/index), which is a healthcare venture company in Tokyo, Japan.

Abbreviations

BMI:

Body mass index

CI:

Confidence interval

HR:

Hormone receptor

HER2:

Human epidermal growth factor receptor 2

RCS:

Restricted cubic spline

References

  1. Torre LA, Islami F, Siegel RL et al (2017) Global cancer in women: burden and trends. Cancer Epidemiol Biomark Prev 26:444–457. https://doi.org/10.1158/1055-9965.EPI-16-0858

    Article  Google Scholar 

  2. Premenopausal Breast Cancer Collaborative Group, Schoemaker MJ, Nichols HB et al (2018) Association of body mass index and age with subsequent breast cancer risk in premenopausal women. JAMA Oncol 4:e181771. https://doi.org/10.1001/jamaoncol.2018.1771

    Article  Google Scholar 

  3. Wada K, Nagata C, Tamakoshi A et al (2014) Body mass index and breast cancer risk in Japan: a pooled analysis of eight population-based cohort studies. Ann Oncol 25:519–524. https://doi.org/10.1093/annonc/mdt542

    Article  CAS  PubMed  Google Scholar 

  4. Suzuki S, Kojima M, Tokudome S et al (2013) Obesity/weight gain and breast cancer risk: findings from the Japan collaborative cohort study for the evaluation of cancer risk. J Epidemiol 23:139–145. https://doi.org/10.2188/jea.JE20120102

    Article  PubMed  Google Scholar 

  5. Suzuki R, Iwasaki M, Inoue M et al (2011) Body weight at age 20 years, subsequent weight change and breast cancer risk defined by estrogen and progesterone receptor status—the Japan public health center-based prospective study. Int J Cancer 129:1214–1224. https://doi.org/10.1002/ijc.25744

    Article  CAS  PubMed  Google Scholar 

  6. Renehan AG, Tyson M, Egger M et al (2008) Body-mass index and incidence of cancer: a systematic review and meta-analysis of prospective observational studies. Lancet 371:569–578. https://doi.org/10.1016/S0140-6736(08)60269-X

    Article  PubMed  Google Scholar 

  7. Amadou A, Ferrari P, Muwonge R et al (2013) Overweight, obesity and risk of premenopausal breast cancer according to ethnicity: a systematic review and dose–response meta-analysis. Obes Rev 14:665–678. https://doi.org/10.1111/obr.12028

    Article  CAS  PubMed  Google Scholar 

  8. Lee KR, Hwang IC, Han KD et al (2018) Waist circumference and risk of breast cancer in Korean women: a nationwide cohort study. Int J Cancer 142:1554–1559. https://doi.org/10.1002/ijc.31180

    Article  CAS  PubMed  Google Scholar 

  9. Hu YH, Nagata C, Shimizu H et al (1997) Association of body mass index, physical activity, and reproductive histories with breast cancer: a case-control study in Gifu, Japan. Breast Cancer Res Treat 43:65–72. https://doi.org/10.1023/A:1005745824388

    Article  CAS  PubMed  Google Scholar 

  10. Nitta J, Nojima M, Ohnishi H et al (2016) Weight gain and alcohol drinking associations with breast cancer risk in Japanese postmenopausal women—results from the Japan Collaborative Cohort (JACC) study. Asian Pac J Cancer Prev 17:1437–1443. https://doi.org/10.7314/APJCP.2016.17.3.1437

    Article  PubMed  Google Scholar 

  11. Taira N, Arai M, Ikeda M, et al (2016) The Japanese Breast Cancer Society clinical practice guidelines for epidemiology and prevention of breast cancer, 2015 edn. Breast Cancer 23, p 343–356. https://doi.org/10.1007/s12282-016-0673-8

  12. Chen MJ, Wu WY, Yen AM et al (2016) Body mass index and breast cancer: analysis of a nation-wide population-based prospective cohort study on 1 393 985 Taiwanese women. Int J Obes (Lond) 40:524–530. https://doi.org/10.1038/ijo.2015.205

    Article  Google Scholar 

  13. Greenland S (1995) Avoiding power loss associated with categorization and ordinal scores in dose–response and trend analysis. Epidemiology 6:450–454. https://doi.org/10.1097/00001648-199507000-00025

    Article  CAS  PubMed  Google Scholar 

  14. Greenland S (1995) Dose–response and trend analysis in epidemiology: alternatives to categorical analysis. Epidemiology 6:356–365. https://doi.org/10.1097/00001648-199507000-00005

    Article  CAS  PubMed  Google Scholar 

  15. Li H, Qian F, Zuo Y et al (2022) U-shaped relationship of high-density lipoprotein cholesterol and incidence of total, ischemic and hemorrhagic stroke: a prospective cohort study. Stroke. https://doi.org/10.1161/STROKEAHA.121.034393

    Article  PubMed  Google Scholar 

  16. Gershengorn HB, Pilcher DV, Litton E et al (2022) Association of patient-to-intensivist ratio with hospital mortality in Australia and New Zealand. Intensive Care Med 48:179–189. https://doi.org/10.1007/s00134-021-06575-z

    Article  PubMed  Google Scholar 

  17. Heiden BT, Eaton DB Jr, Chang SH et al (2021) Assessment of duration of smoking cessation prior to surgical treatment of non-small cell lung cancer. Ann Surg. https://doi.org/10.1097/SLA.0000000000005312

    Article  PubMed  Google Scholar 

  18. Kimura S, Sato T, Ikeda S et al (2010) Development of a database of health insurance claims: standardization of disease classifications and anonymous record linkage. J Epidemiol 20:413–419. https://doi.org/10.2188/jea.JE20090066

    Article  PubMed  PubMed Central  Google Scholar 

  19. Sato D, Goto T, Uda K et al (2021) Impact of national guidelines for antimicrobial stewardship to reduce antibiotic use in upper respiratory tract infection and gastroenteritis. Infect Control Hosp Epidemiol 42:280–286. https://doi.org/10.1017/ice.2020.427

    Article  PubMed  Google Scholar 

  20. Michihata N, Shigemi D, Sasabuchi Y et al (2019) Safety and effectiveness of Japanese herbal Kampo medicines for treatment of hyperemesis gravidarum. Int J Gynaecol Obstet 145:182–186. https://doi.org/10.1002/ijgo.12781

    Article  PubMed  Google Scholar 

  21. Amagai Y, Ishikawa S, Gotoh T et al (2006) Age at menopause and mortality in Japan: the Jichi Medical School Cohort study. J Epidemiol 16:161–166. https://doi.org/10.2188/jea.16.161

    Article  PubMed  PubMed Central  Google Scholar 

  22. Lee JS, Hayashi K, Mishra G et al (2013) Independent association between age at natural menopause and hypercholesterolemia, hypertension, and diabetes mellitus: Japan nurses’ health study. J Atheroscler Thromb 20:161–169. https://doi.org/10.5551/jat.14746

    Article  PubMed  Google Scholar 

  23. Zhu D, Chung HF, Dobson AJ et al (2019) Age at natural menopause and risk of incident cardiovascular disease: a pooled analysis of individual patient data. Lancet Public Health 4:e553–e564. https://doi.org/10.1016/S2468-2667(19)30155-0

    Article  PubMed  PubMed Central  Google Scholar 

  24. Tsumura K, Hayashi T, Suematsu C et al (1999) Daily alcohol consumption and the risk of type 2 diabetes in Japanese men: the Osaka Health Survey. Diabetes Care 22:1432–1437. https://doi.org/10.2337/diacare.22.9.1432

    Article  CAS  PubMed  Google Scholar 

  25. Watanabe M, Barzi F, Neal B et al (2002) Alcohol consumption and the risk of diabetes by body mass index levels in a cohort of 5,636 Japanese. Diabetes Res Clin Pract 57:191–197. https://doi.org/10.1016/s0168-8227(02)00083-9

    Article  PubMed  Google Scholar 

  26. Kawate N, Kayaba K, Hara M et al (2017) Body mass index and stroke incidence in Japanese community residents: The Jichi Medical School (JMS) Cohort Study. J Epidemiol 27:325–330. https://doi.org/10.1016/j.je.2016.08.007

    Article  PubMed  PubMed Central  Google Scholar 

  27. Kanazawa M, Yoshiike N, Osaka T et al (2005) Criteria and classification of obesity in Japan and Asia-Oceania. World Rev Nutr Diet 94:1–12. https://doi.org/10.1159/000088200

    Article  PubMed  Google Scholar 

  28. Shiozawa M, Kaneko H, Itoh H et al (2021) Association of body mass index with ischemic and hemorrhagic stroke. Nutrients 13:2343. https://doi.org/10.3390/nu13072343

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  29. Konishi T, Fujiogi M, Michihata N et al (2022) Impact of body mass index on short-term outcomes after differentiated thyroid cancer surgery: a nationwide inpatient database study in Japan. Eur Thyroid J 11:e2210081. https://doi.org/10.1530/ETJ-21-0081

    Article  Google Scholar 

  30. Konishi T, Fujiogi M, Michihata N et al (2020) Impact of body mass index on outcomes after breast cancer surgery: Nationwide inpatient database study in Japan. Clin Breast Cancer 20:e663–e674. https://doi.org/10.1016/j.clbc.2020.05.002

    Article  PubMed  Google Scholar 

  31. Mizukoshi MM, Hossian SZ, Poulos A (2020) Comparative analysis of breast cancer incidence rates between Australia and Japan: screening target implications. Asian Pac J Cancer Prev 21:2123–2129. https://doi.org/10.31557/APJCP.2020.21.7.2123

    Article  PubMed  PubMed Central  Google Scholar 

  32. Lin CH, Yap YS, Lee KH et al (2019) Contrasting epidemiology and clinicopathology of female breast cancer in Asians vs the US population. J Natl Cancer Inst 111:1298–1306. https://doi.org/10.1093/jnci/djz090

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  33. Konishi T, Fujiogi M, Michihata N et al (2021) Comparison of short-term surgical outcomes between men and women with breast cancer: a retrospective study using nationwide inpatient data in Japan. Breast Cancer Res Treat 186:731–739. https://doi.org/10.1007/s10549-020-06069-4

    Article  PubMed  Google Scholar 

  34. Hayashi N, Kumamaru H, Isozumi U et al (2020) Annual report of the Japanese Breast Cancer Registry for 2017. Breast Cancer 27:803–809. https://doi.org/10.1007/s12282-020-01139-3

    Article  PubMed  Google Scholar 

  35. OECD Overweight or obese population (indicator). https://www.oecd-ilibrary.org/social-issues-migration-health/overweight-or-obese-population/indicator/english_86583552-en

  36. Modi ND, Tan JQE, Rowland A et al (2021) The obesity paradox in early and advanced HER2 positive breast cancer: pooled analysis of clinical trial data. NPJ Breast Cancer 7:30. https://doi.org/10.1038/s41523-021-00241-9

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  37. Tworoger SS, Eliassen AH, Missmer SA et al (2006) Birthweight and body size throughout life in relation to sex hormones and prolactin concentrations in premenopausal women. Cancer Epidemiol Biomark Prev 15:2494–2501. https://doi.org/10.1158/1055-9965.EPI-06-0671

    Article  CAS  Google Scholar 

  38. Endogenous Hormones and Breast Cancer Collaborative Group, Key TJ, Appleby PN et al (2013) Sex hormones and breast cancer risk in premenopausal women: collaborative reanalysis of seven prospective studies. Lancet Oncol 14:1009–1019. https://doi.org/10.1016/S1470-2045(13)70301-2.Sex

    Article  PubMed Central  Google Scholar 

  39. Eliassen AH, Missmer SA, Tworoger SS et al (2006) Endogenous steroid hormone concentrations and risk of breast cancer among premenopausal women. J Natl Cancer Inst 98:1406–1415. https://doi.org/10.1093/jnci/djj376

    Article  CAS  PubMed  Google Scholar 

  40. Walker K, Bratton DJ, Frost C (2011) Premenopausal endogenous oestrogen levels and breast cancer risk: A meta-analysis. Br J Cancer 105:1451–1457. https://doi.org/10.1038/bjc.2011.358

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  41. Fortner RT, Eliassen AH, Spiegelman D et al (2013) Premenopausal endogenous steroid hormones and breast cancer risk: Results from the Nurses’ Health Study II. Breast Cancer Res 15:R19. https://doi.org/10.1186/bcr3394

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  42. Kaaks R, Tikk K, Sookthai D et al (2014) Premenopausal serum sex hormone levels in relation to breast cancer risk, overall and by hormone receptor status—results from the EPIC cohort. Int J Cancer 134:1947–1957. https://doi.org/10.1002/ijc.28528

    Article  CAS  PubMed  Google Scholar 

  43. Schernhammer ES, Sperati F, Razavi P et al (2013) Endogenous sex steroids in premenopausal women and risk of breast cancer: The ORDET cohort. Breast Cancer Res 15:R46. https://doi.org/10.1186/bcr3438

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  44. Dowsett M, Folkerd E (2015) Reduced progesterone levels explain the reduced risk of breast cancer in obese premenopausal women: a new hypothesis. Breast Cancer Res Treat 149:1–4. https://doi.org/10.1007/s10549-014-3211-4

    Article  CAS  PubMed  Google Scholar 

  45. Key TJ, Pike MC (1988) The role of oestrogens and progestagens in the epidemiology and prevention of breast cancer. Eur J Cancer Clin Oncol 24:29–43. https://doi.org/10.1016/0277-5379(88)90173-3

    Article  CAS  PubMed  Google Scholar 

  46. García-Estévez L, Cortés J, Pérez S et al (2021) Obesity and breast cancer: a paradoxical and controversial relationship influenced by menopausal status. Front Oncol 11:705911. https://doi.org/10.3389/fonc.2021.705911

    Article  PubMed  PubMed Central  Google Scholar 

  47. Oh H, Boeke CE, Tamimi RM et al (2015) The interaction between early-life body size and physical activity on risk of breast cancer. Int J Cancer 137:571–581. https://doi.org/10.1002/ijc.29272

    Article  CAS  PubMed  Google Scholar 

  48. Hirose K, Tajima K, Hamajima N et al (1999) Comparative case-referent study of risk factors among hormone-related female cancers in Japan. Jpn J Cancer Res 90:255–261. https://doi.org/10.1111/j.1349-7006.1999.tb00741.x

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  49. Kawai M, Minami Y, Kuriyama S et al (2010) Reproductive factors, exogenous female hormone use and breast cancer risk in Japanese: the Miyagi Cohort Study. Cancer Causes Control 21:135–145. https://doi.org/10.1007/s10552-009-9443-7

    Article  PubMed  Google Scholar 

  50. Collaborative Group on Hormonal Factors in Breast Cancer (2002) Breast cancer and breastfeeding: Collaborative reanalysis of individual data from 47 epidemiological studies in 30 countries, including 50302 women with breast cancer and 96973 women without the disease. Lancet 360:187–195. https://doi.org/10.1016/S0140-6736(02)09454-0

    Article  Google Scholar 

  51. Schisterman EF, Cole SR, Platt RW (2009) Overadjustment bias and unnecessary adjustment in epidemiologic studies. Epidemiology 20:488–495. https://doi.org/10.1097/EDE.0b013e3181a819a1

    Article  PubMed  PubMed Central  Google Scholar 

  52. Tung HT, Tsukuma H, Tanaka H et al (1999) Risk factors for breast cancer in Japan, with special attention to anthropometric measurements and reproductive history. Jpn J Clin Oncol 29:137–146. https://doi.org/10.1093/jjco/29.3.137

    Article  CAS  PubMed  Google Scholar 

  53. Pharoah PDP, Day NE, Duffy S et al (1997) Family history and the risk of breast cancer: A systematic review and meta-analysis. Int J Cancer 71:800–809. https://doi.org/10.1002/(sici)1097-0215(19970529)71:5%3c800::aid-ijc18%3e3.0.co;2-b

    Article  CAS  PubMed  Google Scholar 

  54. Nelson HD, Zakher B, Cantor A et al (2012) Risk factors for breast cancer for women aged 40 to 49 years: a systematic review and meta-analysis. Ann Intern Med 156:635–648. https://doi.org/10.7326/0003-4819-156-9-201205010-00006

    Article  PubMed  PubMed Central  Google Scholar 

  55. Chlebowski RT, Anderson GL, Gass M et al (2010) Estrogen plus progestin and breast cancer incidence and mortality in postmenopausal women. JAMA 304:1684–1692. https://doi.org/10.1001/jama.2010.1500

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  56. Saeki T, Sano M, Komoike Y et al (2008) No increase of breast cancer incidence in Japanese women who received hormone replacement therapy: Overview of a case-control study of breast cancer risk in Japan. Int J Clin Oncol 13:8–11. https://doi.org/10.1007/s10147-007-0728-0

    Article  PubMed  Google Scholar 

  57. Konishi T, Fujiogi M, Michihata N et al (2021) Association between body mass index and localization of breast cancer: results from a nationwide inpatient database in Japan. Breast Cancer Res Treat 185:175–182. https://doi.org/10.1007/s10549-020-05934-6

    Article  PubMed  Google Scholar 

  58. Park Y, Peterson LL, Colditz GA (2018) The plausibility of obesity paradox in cancer-point. Cancer Res 78:1898–1903. https://doi.org/10.1158/0008-5472.CAN-17-3043

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  59. Thrift AP, Natarajan Y, Liu Y, El-Serag HB (2019) Statin use after diagnosis of hepatocellular carcinoma is associated with decreased mortality. Clin Gastroenterol Hepatol 17:2117-2125.e3. https://doi.org/10.1016/j.cgh.2018.12.046

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  60. Rhee CM, Alexander EK, Bhan I, Brunelli SM (2013) Hypothyroidism and mortality among dialysis patients. Clin J Am Soc Nephrol 8:593–601. https://doi.org/10.2215/CJN.06920712

    Article  CAS  PubMed  Google Scholar 

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Funding

This work was supported by grants from the Ministry of Health, Labour and Welfare, Japan (21AA2007 and 20AA2005) and the Ministry of Education, Culture, Sports, Science and Technology, Japan (20H03907).

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Contributions

All authors contributed to the study conception and design. Material preparation, data collection and analysis were performed by TK, NM, MF, and HM. The first draft of the manuscript was written by TK and all authors commented on previous versions of the manuscript. All authors read and approved the final manuscript.

Corresponding author

Correspondence to Takaaki Konishi.

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The authors have no relevant financial or non-financial interests to disclose.

Ethical approval

This is an observational study. This study was approved by the Institutional Review Board of The University of Tokyo [approval number: 10862-(1)].

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The need for informed consent was waived owing to the retrospective nature of the study and the anonymity of the patient database.

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Konishi, T., Fujiogi, M., Michihata, N. et al. Association between body mass index and incidence of breast cancer in premenopausal women: a Japanese nationwide database study. Breast Cancer Res Treat 194, 315–325 (2022). https://doi.org/10.1007/s10549-022-06638-9

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