Objectives Shift work, such as alternating day and nights, causes chronobiologic disruptions which may cause an increase in hypertension risk. However, the relative contributions of the components of shift work - such as shift type (eg, night work) and rotations (ie, switching of shift times; day to night) - on this association are not clear. To address this question, we constructed novel definitions of night work and rotational work and assessed their associations with risk of incident hypertension. Methods A cohort of 2151 workers at eight aluminum manufacturing facilities previously studied for cardiovascular disease was followed from 2003 through 2013 for incident hypertension, as defined by ICD-9 insurance claims codes. Detailed time-registry data was used to classify each worker’s history of rotational and night work. The associations between recent rotational work and night work in the last 12 months and incident hypertension were estimated using adjusted Cox proportional hazards models. Results Elevated hazard ratios (HR) were observed for all levels of recent night work (>0–5, >5–50, >50–95, >95–100%) compared with non-night workers, and among all levels of rotational work (<1, 1–10, >10–20, >20–30, and >30%) compared with those working <1% rotational work. In models for considering the combination of night and rotational work, workers with mostly night work and frequent rotations (≥50% night and ≥10% rotation) had the highest risk of hypertension compared to non-night workers [HR 4.00, 95% confidence interval (CI )1.69–9.52]. Conclusions Our results suggest recent night and rotational work may both be associated with higher rates of incident hypertension.
Introduction Breast cancer, the leading cancer diagnosis among American women, is positively associated with postmenopausal obesity and little or no recreational physical activity (RPA). However, the underlying mechanisms of these associations remain unresolved. Aberrant changes in DNA methylation may represent an early event in carcinogenesis, but few studies have investigated associations between obesity/RPA and gene methylation, particularly in postmenopausal breast tumors where these lifestyle factors are most relevant. Methods We used case-case unconditional logistic regression to estimate odds ratios (ORs) and 95% confidence intervals (CI) for the associations between body mass index (BMI=weight [kg]/height [m2]) in the year prior to diagnosis, or RPA (average hours/week), and methylation status (methylated vs. unmethylated) of 13 breast cancer-related genes in 532 postmenopausal breast tumor samples from the Long Island Breast Cancer Study Project. We also explored whether the association between BMI/RPA and estrogen/progesterone-receptor status (ER+PR+ vs. all others) was differential with respect to gene methylation status. Methylation-specific PCR and the MethyLight assay were used to assess gene methylation. Results BMI 25-29.9kg/m2, and perhaps BMI≥30kg/m2, was associated with methylated HIN1 in breast tumor tissue. Cases with BMI≥30kg/m2 were more likely to have ER+PR+ breast tumors in the presence of unmethylated ESR1 (OR=2.63, 95% CI 1.32-5.25) and women with high RPA were more likely to have ER+PR+ breast tumors with methylated GSTP1 (OR=2.33, 95% CI 0.79-6.84). Discussion While biologically plausible, our findings that BMI is associated with methylated HIN1 and BMI/RPA are associated with ER+PR+ breast tumors in the presence of unmethylated ESR1 and methylated GSTP1, respectively, warrant further investigation. Future studies would benefit from enrolling greater numbers of postmenopausal women and examining a larger panel of breast cancer–related genes.
Background. Previous epidemiologic studies, including our own, have consistently linked long-term exposure to single-source polycyclic aromatic hydrocarbons (PAHs) to increased breast cancer incidence. It is unclear whether single sources, specific groups, or all PAH sources should be targeted for breast cancer risk reduction. This study considers the impact on breast cancer incidence from multiple PAH exposure sources in a single model, which better reflects exposure to these complex mixtures. Methods. In a population-based case-control study conducted on Long Island, New York (N=1,508 breast cancer cases/1,556 controls), a Bayesian hierarchical regression approach was used to estimate adjusted posterior means and credible intervals (CrI) for the adjusted odds ratios (ORs) for PAH exposure sources, considered singly and as groups: active smoking; residential environmental tobacco smoke (ETS); indoor and outdoor air pollution; and grilled/smoked meat intake. Results. Most women were exposed to PAHs from multiple sources. In a hierarchical model, breast cancer incidence was positively associated with ETS from a spouse (OR=1.20, 95%CrI=1.03, 1.42) and residential synthetic firelog burning (OR=1.30, 95%CrI=1.06, 1.60). Additionally, PAH exposure groups, including ingestion (OR=1.45, 95%CrI=1.16, 1.79), indoor stove/fireplace use (OR=1.30, 95%CrI=1.02, 1.62), and total indoor sources (active smoking, ETS from spouse, grilled/smoked meat intake, stove/fireplace use, OR=1.46, 95%CrI=1.03, 2.05), were associated with increased breast cancer incidence. Conclusions. Groups of PAH sources, especially those for ingestion and indoor sources, were associated with a 30-50% increase in breast cancer incidence. PAH exposure is ubiquitous and a potentially modifiable breast cancer risk factor. Citation Format: White AJ, Bradshaw PT, Herring AH, Teitelbaum SL, Beyea J, Stellman SD, Steck SE, Mordukhovich I, Eng SM, Engel LS, Conway K, Hatch M, Neugut AI, Santella RM, Gammon MD. Exposure to multiple sources of polycyclic aromatic hydrocarbon and breast cancer incidence. [abstract]. In: Proceedings of the Thirty-Eighth Annual CTRC-AACR San Antonio Breast Cancer Symposium: 2015 Dec 8-12; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2016;76(4 Suppl):Abstract nr P6-09-08.
Significance. Weight gain after breast cancer diagnosis is common and has been linked to poor prognosis. Studies of the etiology and longitudinal pattern of post-diagnosis weight gain are limited, yet are critical to developing effective prevention strategies to enhance ***survival.. Approach. We investigated the longitudinal pattern and determinants of post-diagnosis weight gain among 1,436 breast cancer survivors. The population-based cohort included women newly diagnosed with a first primary in situ or invasive breast cancer. Subjects were interviewed within 6 months of diagnosis and again 5 years later to ascertain factors related to survival, including self-reported anthropometric measures. We employed: adjusted random effects linear regression to identify factors related to weight change during the follow-up; multiple imputation to account for missing data; and Wald tests to test for significance of interactions with follow-up time. Results. Average weight gain was 0.74 kilograms (kg) during the first year after diagnosis and 2.39 kg at the follow-up interview. The strongest predictors of post-diagnosis gain were body size characteristics before diagnosis, which varied with time since diagnosis. Compared to women with body mass index (BMI, kg/m2) 18.5−24.9 1 year before diagnosis, those with greater BMI were more likely to gain weight during the first year after diagnosis [difference in mean yearly increase: BMI 25.0−29.9 vs. 18.5−24.9 (95% confidence interval): 1.93 kg/year (0.50, 3.37); BMI >=30.0 vs. 18.5−24.9: 0.47 kg/year (0.24, 0.71)] and after the first year [5.17 kg/year (3.68, 6.66) and 0.93 kg/year (0.58, 1.28), respectively], with the effect greater during the first year (p-interaction: <0.001). A pre-diagnosis weight gain of more than 10% since age 20 was also associated with post-diagnosis weight gain [during year 1, difference in mean yearly increase compared to maintenance within 3% age 20 weight: 2.32 kg/year (0.59, 4.05); after year 1: 0.53 kg/year (0.17, 0.89)] with the effect again stronger during the first year (p-interaction: 0.02). Modest associations, which varied only slightly with time, included: increases in post-diagnosis weight gain with chemotherapy, tumor characteristics indicative of poor prognosis, and a previous diagnosis of hypertension, blood clots, or diabetes; and decreases with increasing recreational physical activity and a history of myocardial infarction. Conclusions. Greater pre-diagnosis BMI and pre-diagnosis adult weight gain are strongly related to post-diagnosis weight gain among breast cancer survivors. The rate of post-diagnosis weight gain appears to be faster during the first year than after, suggesting that interventions to prevent post-diagnosis weight gain may be most important during the first year after diagnosis, especially among women who with BMI >= 25.0 1 year prior to diagnosis. Citation Information: Cancer Res 2011;71(24 Suppl):Abstract nr P4-12-03.
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