A possible dual effect of cigarette smoking on the risk of postmenopausal breast cancer.
Piet A van den BrandtPublished in: European journal of epidemiology (2017)
Smoking seems modestly associated with breast cancer, but the potential dual effect of smoking (with opposing properties: carcinogenic vs anti-estrogenic) is understudied. The relationship between smoking before and after menopause and risk of postmenopausal breast cancer was investigated in the Netherlands Cohort Study (NLCS). In the NLCS, 62,573 women aged 55-69 years provided information on smoking, dietary and other lifestyle habits in 1986. Follow-up for cancer incidence until 2007 (20.3 years) consisted of record linkages with the Netherlands Cancer Registry and the Dutch Pathology Registry PALGA. Multivariate case-cohort analyses were based on 2526 incident breast cancer cases and 1816 subcohort members with complete data on smoking. When smoking during pre- and postmenopausal periods was mutually adjusted for, breast cancer risk was significantly positively associated with premenopausal smoking pack-years, but inversely associated with postmenopausal smoking pack-years, both in a dose-dependent manner. In continuous analyses, the hazard ratios (95% CI) were 1.35 (1.10-1.65), and 0.47 (0.28-0.80) per increment of 20 premenopausal, and postmenopausal pack-years, respectively. The interaction between pre- and postmenopausal pack-years in relation to breast cancer risk was significant (P < 0.001). This study highlights the importance of distinguishing and adjusting for smoking in different life periods, and suggests dual effects of smoking on postmenopausal breast cancer risk.
Keyphrases
- breast cancer risk
- smoking cessation
- cardiovascular disease
- healthcare
- bone mineral density
- postmenopausal women
- metabolic syndrome
- mass spectrometry
- risk assessment
- risk factors
- adipose tissue
- type diabetes
- body composition
- social media
- skeletal muscle
- physical activity
- high resolution
- artificial intelligence
- insulin resistance
- deep learning
- young adults
- estrogen receptor
- high speed