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1.  Post-diagnosis dietary factors and survival after invasive breast cancer 
Little is known about the effects of diet after breast cancer diagnosis on survival. We prospectively examined the relation between post-diagnosis dietary factors and breast cancer and all-cause survival in women with a history of invasive breast cancer diagnosed between 1987 and 1999 (at ages 20–79 years). Diet after breast cancer diagnosis was measured using a 126-item food frequency questionnaire. Among 4,441 women without a history of breast cancer recurrence prior to completing the questionnaire, 137 subsequently died from breast cancer within 7 years of enrollment. Hazard ratios (HR) and 95% confidence intervals (CI) were estimated for intake of macronutrients as well as selected micronutrients and food groups from Cox proportional hazards regression models. After adjustment for factors at diagnosis (age, state of residence, menopausal status, smoking, breast cancer stage, alcohol, history of hormone replacement therapy), interval between diagnosis and diet assessment, and at follow-up (energy intake, breast cancer treatment, body mass index, and physical activity), women in the highest compared to lowest quintile of intake of saturated fat and trans fat had a significantly higher risk of dying from any cause (HR = 1.41, 95% CI = 1.06 to 1.87, P-trend = 0.03) for saturated fat; (HR = 1.78, 95% CI = 1.35 to 2.32, P-trend = 0.01) for trans fat intake. Associations were similar, though did not achieve statistical significance, for breast cancer survival. This study suggests that lower intake of saturated and trans fat in the post-diagnosis diet is associated with improved survival after breast cancer diagnosis.
PMCID: PMC3201727  PMID: 21197569
breast cancer; survival; post-diagnosis diet
2.  The Survey of the Health of Wisconsin (SHOW), a novel infrastructure for population health research: rationale and methods 
BMC Public Health  2010;10:785.
Evidence-based public health requires the existence of reliable information systems for priority setting and evaluation of interventions. Existing data systems in the United States are either too crude (e.g., vital statistics), rely on administrative data (e.g., Medicare) or, because of their national scope (e.g., NHANES), lack the discriminatory power to assess specific needs and to evaluate community health activities at the state and local level. This manuscript describes the rationale and methods of the Survey of the Health of Wisconsin (SHOW), a novel infrastructure for population health research.
The program consists of a series of independent annual surveys gathering health-related data on representative samples of state residents and communities. Two-stage cluster sampling is used to select households and recruit approximately 800-1,000 adult participants (21-74 years old) each year. Recruitment and initial interviews are done at the household; additional interviews and physical exams are conducted at permanent or mobile examination centers. Individual survey data include physical, mental, and oral health history, health literacy, demographics, behavioral, lifestyle, occupational, and household characteristics as well as health care access and utilization. The physical exam includes blood pressure, anthropometry, bioimpedance, spirometry, urine collection and blood draws. Serum, plasma, and buffy coats (for DNA extraction) are stored in a biorepository for future studies. Every household is geocoded for linkage with existing contextual data including community level measures of the social and physical environment; local neighborhood characteristics are also recorded using an audit tool. Participants are re-contacted bi-annually by phone for health history updates.
SHOW generates data to assess health disparities across state communities as well as trends on prevalence of health outcomes and determinants. SHOW also serves as a platform for ancillary epidemiologic studies and for studies to evaluate the effect of community-specific interventions. It addresses key gaps in our current data resources and increases capacity for etiologic, applied and translational population health research. It is hoped that this program will serve as a model to better support evidence-based public health, facilitate intervention evaluation research, and ultimately help improve health throughout the state and nation.
PMCID: PMC3022857  PMID: 21182792
3.  Body mass index before and after breast cancer diagnosis: Associations with all-cause, breast cancer, and cardiovascular disease mortality 
Factors related to improving outcomes in breast cancer survivors are of increasing public health significance. We examined post-diagnosis weight change in relation to mortality risk in a cohort of breast cancer survivors.
We analyzed data from a cohort of 3,993 women aged 20−79 living in New Hampshire, Massachusetts or Wisconsin with invasive, nonmetastatic breast cancers diagnosed in 1988−1999 identified through state registries. Participants completed a structured telephone interview 1−2 years after diagnosis and returned a mailed follow-up questionnaire in 1998−2001 that addressed post-diagnosis weight and other factors. Vital status information was obtained from the National Death Index through December 2005. Hazard ratios (HR) and 95% confidence intervals (CI) were estimated from Cox proportional hazards models and adjusted for pre-diagnosis weight, age, stage, smoking, physical activity and other important covariates.
During an average 6.3 years of follow-up from the post-diagnosis questionnaire, we identified 421 total deaths, including 121 deaths from breast cancer and 95 deaths from cardiovascular disease. Increasing post-diagnosis weight gain and weight loss were each associated with greater all-cause mortality. Among women who gained weight after breast cancer diagnosis, each 5 kg gain was associated with a 12% increase in all-cause mortality (p=0.004), a 13% increase in breast cancer-specific mortality (p=0.01), and a 19% increase in cardiovascular disease mortality (p=0.04). Associations with breast cancer mortality were not modified by pre-diagnosis menopausal status, cigarette smoking, or body mass index.
These findings suggest that efforts to minimize weight gain after a breast cancer diagnosis may improve survival.
PMCID: PMC2715918  PMID: 19366908
Breast cancer; mortality; BMI; weight change; survival

Results 1-3 (3)