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Lifestyle Patterns and Survival Following Breast Cancer in the Carolina Breast Cancer Study

Parada, Humberto Jr.a; Sun, Xuezhengb; Tse, Chiu-Kitb; Olshan, Andrew F.b; Troester, Melissa A.b

doi: 10.1097/EDE.0000000000000933

Background: Few studies have examined the impact of lifestyle patterns on survival following breast cancer. We aimed to identify distinct lifestyle patterns based on five behavior/dietary exposures among a population-based sample of women diagnosed with breast cancer and to examine their association with subsequent survival.

Methods: In the Carolina Breast Cancer Study Phases I/II, we interviewed 1,808 women 20–74 years of age following diagnosis of invasive breast cancer. We determined vital status using the National Death Index (717 deaths, 427 from breast cancer; median follow-up 13.56 years). We assessed lifestyle patterns using a latent class analysis based on five behavioral and dietary exposures: current versus never/former smokers; low versus high vegetable and fruit intake; high and low/moderate, versus no alcohol consumption; and no and low/moderate, versus high regular physical activity. We used Cox regression to estimate covariate-adjusted hazard ratios (HRs) and 95% confidence intervals (CIs) for all-cause mortality, and cause-specific and subdistribution HRs for breast cancer–specific mortality within 5 years and 13 years postdiagnosis conditional on 5-year survival.

Results: We identified three distinct lifestyle patterns: healthy behavior and diet (n = 916); healthy behavior and unhealthy diet (n = 624); and unhealthy behavior and diet (n = 268). The unhealthy (vs. healthy) behavior and diet pattern was associated with a 13-year conditional all-cause mortality HR of 1.4 (95% CI = 1.1, 1.9) and with 13-year conditional breast cancer–specific and subdistribution HRs of 1.2 (95% CI = 0.79, 1.9) and 1.2 (95% CI = 0.77, 1.8), respectively.

Conclusions: Behavioral and dietary patterns can be used to identify lifestyle patterns that influence survival patterns following breast cancer diagnosis.

From the aDivision of Epidemiology & Biostatistics, School of Public Health, San Diego State University, San Diego, CA

bDepartment of Epidemiology, University of North Carolina at Chapel Hill, Chapel Hill, NC.

Submitted March 14, 2018; accepted September 27, 2018.

This research was funded in part by the University Cancer Research Fund of North Carolina and the National Cancer Institute Specialized Program of Research Excellence (SPORE) in Breast Cancer (NIH/NCI P50-CA58223) and by a grant from the National Institute of Environmental Health Sciences (T32 ES007018).

The authors report no conflicts of interest.

The data and computer code for replicating these results would require a collaboration with the senior author, a formal data use agreement, and institutional review board approval from the participating institutions.

Compliance with Ethical Standards.

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Correspondence: Humberto Parada Jr., Division of Epidemiology & Biostatistics, School of Public Health, San Diego State University, 5500 Campanile Drive, Hardy Tower Room 168, San Diego, CA 92182. E-mail:

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