Walter C Willett

Stanford University, Palo Alto, California, United States

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Publications (305)2925.95 Total impact

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    ABSTRACT: The breast is particularly vulnerable to carcinogenic influences during adolescence due to rapid proliferation of mammary cells and lack of terminal differentiation. We investigated consumption of adolescent red meat and other protein sources in relation to breast cancer risk in the Nurses' Health Study II cohort.We followed prospectively 44,231 women aged 33-52 years who, in 1998, completed a detailed questionnaire about diet during adolescence. Relative risks (RR) and 95% confidence intervals (95%CI) were estimated using Cox proportional hazard regression.We documented 1132 breast cancer cases during 13-year follow-up. In multivariable Cox regression models with major breast cancer risk factors adjustment, greater consumption of adolescent total red meat was significantly associated with higher premenopausal breast cancer risk (highest vs lowest quintiles, RR, 1.42; 95%CI, 1.05-1.94; Ptrend=0.007), but not postmenopausal breast cancer. Adolescent poultry intake was associated with lower risk of breast cancer overall (RR, 0.75; 95%CI, 0.59-0.96; for each serving/day). Adolescent intakes of iron, heme iron, fish, eggs, legumes and nuts were not associated with breast cancer. Replacement of one serving/day of total red meat with one serving of combination of poultry, fish, legumes, and nuts was associated with a 16% lower risk of breast cancer overall (RR, 0.84; 95%CI, 0.74-0.96) and a 24% lower risk of premenopausal breast cancer (RR, 0.76; 95%CI, 0.64-0.92).Higher consumption of red meat during adolescence was associated with premenopausal breast cancer. Substituting other dietary protein sources for red meat in adolescent diet may decrease premenopausal breast cancer risk. © 2014 Wiley Periodicals, Inc.
    International Journal of Cancer 04/2015; 136(8). DOI:10.1002/ijc.29218 · 5.01 Impact Factor
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    ABSTRACT: Dietary guidelines recommend interchanging protein foods (e.g., chicken for red meat), but they may be exchanged for carbohydrate-rich foods varying in quality [glycemic load (GL)]. Whether such exchanges occur and how they influence long-term weight gain are not established. Our objective was to determine how changes in intake of protein foods, GL, and their interrelationship influence long-term weight gain. We investigated the association between 4-y changes in consumption of protein foods, GL, and their interaction with 4-y weight change over a 16- to 24-y follow-up, adjusted for other lifestyle changes (smoking, physical activity, television watching, sleep duration), body mass index, and all dietary factors simultaneously in 3 prospective US cohorts (Nurses' Health Study, Nurses' Health Study II, and Health Professionals Follow-Up Study) comprising 120,784 men and women free of chronic disease or obesity at baseline. Protein foods were not interchanged with each other (intercorrelations typically <|0.05|) but with carbohydrate (negative correlation as low as -0.39). Protein foods had different relations with long-term weight gain, with positive associations for meats, chicken with skin, and regular cheese (per increased serving/d, 0.13-1.17 kg; P = 0.02 to P < 0.001); no association for milk, legumes, peanuts, or eggs (P > 0.40 for each); and relative weight loss for yogurt, peanut butter, walnuts, other nuts, chicken without skin, low-fat cheese, and seafood (-0.14 to -0.71 kg; P = 0.01 to P < 0.001). Increases in GL were independently associated with a 0.42-kg greater weight gain per 50-unit increase (P < 0.001). Significant interactions (P-interaction < 0.05) between changes in protein foods and GL were identified; for example, increased cheese intake was associated with weight gain when GL increased, with weight stability when GL did not change, and with weight loss when exchanged for GL (i.e., decrease in GL). Protein foods were commonly interchanged with carbohydrate, and changes in protein foods and GL interacted to influence long-term weight gain. © 2015 American Society for Nutrition.
    American Journal of Clinical Nutrition 04/2015; DOI:10.3945/ajcn.114.100867 · 6.92 Impact Factor
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    ABSTRACT: We investigated quantity and quality of dietary carbohydrate as well as insulin load and insulin index during adolescence and also early adulthood in relation to risk of breast cancer in the Nurses' Health Study II. During 20 years of follow-up of 90,488 premenopausal women who completed a diet questionnaire in 1991, 2890 invasive breast cancer cases were documented. In 1998, 44,263 of these women also completed a questionnaire about their diet during high school; among these women we documented 1135 cases of breast cancer. Multivariable-adjusted Cox proportional hazards regression was used to model relative risks (RR) and 95% confidence intervals (95% CI) for breast cancer across categories of dietary carbohydrate, glycemic index (GI), glycemic load (GL), as well as insulin load and insulin index scores. Adolescent or early adult intakes of GI or GL were not associated with risk of breast cancer. Comparing women in the highest vs lowest quintile, the multivariable-adjusted RRs were 1.15 (0.95-1.38) for adolescent GI scores and 1.01 (0.90-1.14) for early adulthood GI scores. We also did not observe associations with insulin index and insulin load scores in adolescence or early adulthood and breast cancer risk. We found that diets high in GI, GL, insulin index and insulin load during adolescence or early adulthood were not associated with an increased risk of breast cancer in this cohort study. Diets with a high glucose or insulin response in adolescence or early adulthood were not significant predictors of breast cancer incidence. Copyright © 2015, American Association for Cancer Research.
    Cancer Epidemiology Biomarkers & Prevention 03/2015; DOI:10.1158/1055-9965.EPI-14-1401 · 4.32 Impact Factor
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    ABSTRACT: Obesity is well established as a cause of postmenopausal breast cancer incidence and mortality. In contrast, adiposity in early life reduces breast cancer incidence. However, whether short-term weight change influences breast cancer risk is not well known. We followed a cohort of 77,232 women from 1980 to 2006 (1,445,578 person-years), with routinely updated risk factor information, documenting 4196 incident cases of invasive breast cancer. ER and PR status were obtained from pathology reports and medical records yielding a total of 2033 ER+/PR+ tumors, 595 ER-/PR- tumors, 512 ER+/PR- tumors. The log incidence breast cancer model was used to assess the association of short-term weight gain (over past 4 years) while controlling for average BMI before and after menopause. Short-term weight change was significantly associated with breast cancer risk (RR 1.20; 95 % CI 1.09-1.33) for a 4-year weight gain of ≥15 lbs versus no change (≤5 lbs) (P_trend < 0.001). The association was stronger for premenopausal women (RR 1.38; 95 % CI 1.13-1.69) (P_trend = 0.004) than for postmenopausal women (RR 1.10; 95 % CI 0.97-1.25) (P_trend = 0.063). Short-term weight gain during premenopause had a stronger association for ER+/PR- (RR per 25 lb weight gain = 2.19; 95 % CI 1.33-3.61, P = 0.002) and ER-/PR- breast cancer (RR per 25 lb weight gain = 1.61; 95 % CI 1.09-2.38, P = 0.016) than for ER+/PR+ breast cancer (RR per 25 lb weight gain = 1.13; 95 % CI 0.89-1.43, P = 0.32). There are deleterious effects of short-term weight gain, particularly during pre-menopause, even after controlling for average BMI before and after menopause. The association was stronger for ER+/PR- and ER-/PR- than for ER+/PR+ breast cancer.
    Breast Cancer Research and Treatment 03/2015; DOI:10.1007/s10549-015-3344-0 · 4.20 Impact Factor
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    ABSTRACT: We pooled data from 5 large validation studies (1999-2009) of dietary self-report instruments that used recovery biomarkers as referents, to assess food frequency questionnaires (FFQs) and 24-hour recalls (24HRs). Here we report on total potassium and sodium intakes, their densities, and their ratio. Results were similar by sex but were heterogeneous across studies. For potassium, potassium density, sodium, sodium density, and sodium:potassium ratio, average correlation coefficients for the correlation of reported intake with true intake on the FFQs were 0.37, 0.47, 0.16, 0.32, and 0.49, respectively. For the same nutrients measured with a single 24HR, they were 0.47, 0.46, 0.32, 0.31, and 0.46, respectively, rising to 0.56, 0.53, 0.41, 0.38, and 0.60 for the average of three 24HRs. Average underreporting was 5%-6% with an FFQ and 0%-4% with a single 24HR for potassium but was 28%-39% and 4%-13%, respectively, for sodium. Higher body mass index was related to underreporting of sodium. Calibration equations for true intake that included personal characteristics provided improved prediction, except for sodium density. In summary, self-reports capture potassium intake quite well but sodium intake less well. Using densities improves the measurement of potassium and sodium on an FFQ. Sodium:potassium ratio is measured much better than sodium itself on both FFQs and 24HRs. Published by Oxford University Press on behalf of the Johns Hopkins Bloomberg School of Public Health 2015. This work is written by (a) US Government employee(s) and is in the public domain in the US.
    American journal of epidemiology 03/2015; DOI:10.1093/aje/kwu325 · 4.98 Impact Factor
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    ABSTRACT: The association between body fatness before adulthood and later risk of colorectal cancer remains unclear. We hypothesized that, independent of adult body fatness, early life body fatness would be associated with a higher risk of developing colorectal cancer. We assessed body fatness during childhood and adolescence using a validated 9-level somatotype and inquired body weight in young adulthood in the Nurses' Health Study and Health Professionals Follow-up Study. We used the Cox proportional hazard regression modeling to estimate relative risks [RR, 95% confidence intervals (CI)] adjusting for adult body mass index (BMI) and other known colorectal cancer risk factors. We identified 2,100 incident colorectal cancer cases (1,292 in women and 808 in men) during 22 years of follow-up. Among women, the RR (95% CI) for childhood body fatness of level 5 or higher versus level 1 was 1.28 (1.04-1.58; Ptrend = 0.08) and for adolescent body fatness, it was 1.27 (1.01-1.60; Ptrend = 0.23). The corresponding RRs for men were 1.04 (0.82-1.31; Ptrend = 0.48) and 0.98 (0.75-1.27; Ptrend = 0.20), respectively. Results were generally similar across anatomic subsites within the colorectum. In addition, the RRs comparing BMI categories ≥27.5 to <19 kg/m(2) were 1.44 (1.06-1.95, at age 18; Ptrend = 0.009) for women and 1.18 (0.84-1.65, at age 21; Ptrend = 0.57) for men. Increased body fatness in early life, independent of adult obesity, might be a risk factor for colorectal cancer in women, but we observed a weaker association in men. Our findings support the growing evidence that early life body fatness affects the risk of colorectal cancer many decades later. Cancer Epidemiol Biomarkers Prev; 24(4); 1-8. ©2015 AACR. ©2015 American Association for Cancer Research.
    Cancer Epidemiology Biomarkers & Prevention 03/2015; 24(4). DOI:10.1158/1055-9965.EPI-14-0909-T · 4.32 Impact Factor
  • Meir Stampfer, Walter Willett
    JAMA The Journal of the American Medical Association 03/2015; 313(13). DOI:10.1001/jama.2015.1961 · 30.39 Impact Factor
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    ABSTRACT: Food insecurity is associated with adverse mental health outcomes. Given that federal food assistance programs, such as the Supplemental Nutrition Assistance Program (SNAP), aim to alleviate food insecurity, there may be heterogeneity in the association between food insecurity and depression by SNAP participation status. With the use of data from the 2005-2010 NHANES, we examined the associations between household food security and depression and whether these differed by SNAP participation. The study population was restricted to 3518 adults with household incomes ≤130% of the federal poverty level. Food insecurity was assessed with the 18-item US Household Food Security Survey Module; a score of ≥3 was considered food insecure. Depression was assessed with the 9-item Patient Health Questionnaire and was defined as a score of ≥10. Multivariate logistic regression models examined the associations between food insecurity and depression, adjusting for sociodemographic and health characteristics. The overall prevalence of depression was 9.3%, ranging from 6.7% among SNAP nonparticipants to 12.8% among SNAP participants. For every depressive symptom, there was a dose-response relation, such that a higher prevalence was observed with worsening food insecurity. After multivariate adjustment, food insecurity was positively associated with depression (P-trend < 0.0001), but SNAP participation modified this relation (P-interaction = 0.03). Among low-income, eligible nonparticipants, very low food security was significantly associated with higher odds of depression (OR: 5.10; 95% CI: 3.09, 8.41). Among SNAP participants, very low food security was also associated with higher odds of depression but at a lower magnitude (OR: 2.21; 95% CI: 1.54, 3.17). The complex relation between food insecurity and mental health may vary on the basis of SNAP participation status. Programmatic efforts to address the risk of depression among their beneficiaries may positively affect the mental health of low-income adults. © 2015 American Society for Nutrition.
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    ABSTRACT: In a recent article in the American Journal of Epidemiology by Mendez et al. (Am J Epidemiol. 2011;173(4):448-458), the use of alternative approaches to the exclusion of implausible energy intakes led to significantly different cross-sectional associations between diet and body mass index (BMI), whereas the use of a simpler recommended criteria (<500 and >3,500 kcal/day) yielded no meaningful change. However, these findings might have been due to exclusions made based on weight, a primary determinant of BMI. Using data from 52,110 women in the Nurses' Health Study (1990), we reproduced the cross-sectional findings of Mendez et al. and compared the results from the recommended method with those from 2 weight-dependent alternative methods (the Goldberg method and predicted total energy expenditure method). The same 3 exclusion criteria were then used to examine dietary variables prospectively in relation to change in BMI, which is not a direct function of attained weight. We found similar associations using the 3 methods. In a separate cross-sectional analysis using biomarkers of dietary factors, we found similar correlations for intakes of fatty acids (n = 439) and carotenoids and retinol (n = 1,293) using the 3 methods for exclusions. These results do not support the general conclusion that use of exclusion criteria based on the alternative methods might confer an advantage over the recommended exclusion method. © The Author 2015. Published by Oxford University Press on behalf of the Johns Hopkins Bloomberg School of Public Health. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.
    American Journal of Epidemiology 02/2015; DOI:10.1093/aje/kwu308 · 4.98 Impact Factor
  • Jinnie J Rhee, Walter C Willett
    American Journal of Epidemiology 02/2015; DOI:10.1093/aje/kwu309 · 4.98 Impact Factor
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    ABSTRACT: To investigate the association between the Alternate Healthy Eating Index 2010 (AHEI-2010)-a measure of diet quality-and the risk of chronic obstructive pulmonary disease (COPD). Prospective cohort study. Participants in the Nurses' Health Study and the Health Professionals Follow-up Study, United States. 73 228 female nurses from 1984 to 2000 and 47 026 men from 1986 to 1998, who completed biennial questionnaires. The primary outcome was the self report of newly diagnosed COPD. Multivariable Cox proportional hazards models were adjusted for age, physical activity, body mass index, total energy intake, smoking, second hand tobacco exposure (only in the Nurses' Health Study), race/ethnicity, physician visits, US region, spouse's highest educational attainment (only in the Nurses' Health Study), and menopausal status (only in the Nurses' Health Study). Over the study period, 723 cases of newly diagnosed COPD occurred in women and 167 in men. In the pooled analysis, a significant negative association was seen between the risk of newly diagnosed COPD and fifths of the AHEI-2010: hazard ratios were 0.81 (95% confidence interval 0.51 to 1.29) for the second fifth, 0.98 (0.80 to 1.18) for the third fifth, 0.74 (0.59 to 0.92) for the fourth fifth, and 0.67 (0.53 to 0.85) for participants who ate the healthiest diet according to the AHEI-2010 (that is, were in the highest fifth), compared with those who ate the less healthy diet (participants in the lowest fifth). Similar findings were observed among ex-smokers and current smokers. A higher AHEI-2010 diet score (reflecting high intakes of whole grains, polyunsaturated fatty acids, nuts, and long chain omega-3 fats and low intakes of red/processed meats, refined grains, and sugar sweetened drinks) was associated with a lower risk of COPD in both women and men. These findings support the importance of a healthy diet in multi-interventional programs to prevent COPD. © Varraso et al 2015.
    BMJ Clinical Research 02/2015; 350(feb03 7):h286. DOI:10.1136/bmj.h286 · 14.09 Impact Factor
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    ABSTRACT: Despite mechanistic data that linked fish and omega-3 (n-3) PUFAs with lower risk of chronic obstructive pulmonary disease (COPD), epidemiologic data remain scarce. Fish and n-3 PUFAs are an important component of the prudent dietary pattern that is thought to be protective in the onset of COPD. We examined the role of fish and PUFA intakes on risk of developing COPD while taking into account the overall dietary pattern. We investigated the objective in 120,175 women and men from the Nurses' Health Study and Health Professionals Follow-Up Study. Over the study period (1984-2000), there were 889 cases of newly diagnosed COPD. Cumulative average intakes of fish, eicosapentaenoic acid, docosahexaenoic acid, n-3 PUFAs, n-6 PUFAs, and the n-3:n-6 ratio were calculated from repeated food-frequency questionnaires. Because fish is a food group included in the prudent pattern, we derived a new prudent pattern without the contribution from fish, and we termed this pattern the "modified prudent" pattern. We performed multivariable Cox proportional hazards models. Before the dietary pattern was taken into account, and with 14 factors controlled for, we showed that more-frequent fish intake (≥4 servings/wk) was inversely associated with risk of COPD [adjusted pooled HR for the highest intake compared with the lowest intake (<1 serving/wk): 0.71; 95% CI: 0.54, 0.94]. After additional adjustment for the dietary pattern (modified prudent and Western patterns), the association was NS (0.84; 95% CI: 0.63, 1.13). No significant associations were shown between PUFA intakes and risk of COPD. Although COPD-prevention efforts should continue to focus on smoking cessation, these prospective findings support the importance of promoting a healthy diet in multi-interventional programs to prevent COPD instead of focusing on changes in an isolated food or nutrient. © 2015 American Society for Nutrition.
    American Journal of Clinical Nutrition 02/2015; 101(2):354-61. DOI:10.3945/ajcn.114.094516 · 6.92 Impact Factor
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    ABSTRACT: Inflammation, and more generally, the immune response are thought to influence the development of prostate cancer. To determine components of the immune response that are potentially contributory, we prospectively evaluated the association of immune-mediated conditions, asthma and hayfever, with lethal prostate cancer risk in the Health Professionals Follow-Up Study. We included 47,880 men ages 40-75 years with no prior cancer diagnosis. On the baseline questionnaire in 1986 the men reported diagnoses of asthma and hayfever and year of onset. On follow-up questionnaires, they reported new asthma and prostate cancer diagnoses. We used Cox proportional hazards regression to estimate relative risks (RR). 9.2% reported ever having been diagnosed with asthma. 25.3% reported a hayfever diagnosis at baseline. During 995,176 person-years of follow-up by 2012, we confirmed 798 lethal prostate cancer cases (diagnosed with distant metastases, progressed to distant metastasis, or died of prostate cancer [N=625]). Ever having a diagnosis of asthma was inversely associated with risk of lethal (RR=0.71, 95% confidence interval [CI] 0.51-1.00) and fatal (RR=0.64, 95% CI 0.42-0.96) disease. Hayfever with onset in the distant past was possibly weakly positively associated with risk of lethal (RR=1.10, 95% CI 0.92-1.33) and fatal (RR=1.12, 95% CI 0.91-1.37) disease. Men who were ever diagnosed with asthma were less likely to develop lethal and fatal prostate cancer. Our findings may lead to testable hypotheses about specific immune profiles in the etiology of lethal prostate cancer. This article is protected by copyright. All rights reserved.
    International Journal of Cancer 02/2015; DOI:10.1002/ijc.29463 · 5.01 Impact Factor
  • Bernard Rosner, Sara Hendrickson, Walter Willett
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    ABSTRACT: Nutrient intake is often measured with substantial error both in commonly used surrogate instruments such as a food frequency questionnaire (FFQ) and in gold standard-type instruments such as a diet record (DR). If there is a correlated error between the FFQ and DR, then standard measurement error correction methods based on regression calibration can produce biased estimates of the regression coefficient (λ) of true intake on surrogate intake. However, if a biomarker exists and the error in the biomarker is independent of the error in the FFQ and DR, then the method of triads can be used to obtain unbiased estimates of λ, provided that there are replicate biomarker data on at least a subsample of validation study subjects. Because biomarker measurements are expensive, for a fixed budget, one can use a either design where a large number of subjects have one biomarker measure and only a small subsample is replicated or a design that has a smaller number of subjects and has most or all subjects validated. The purpose of this paper is to optimize the proportion of subjects with replicated biomarker measures, where optimization is with respect to minimizing the variance of . The methodology is illustrated using vitamin C intake data from the European Prospective Investigation into Cancer and Nutrition study where plasma vitamin C is the biomarker. In this example, the optimal validation study design is to have 21% of subjects with replicated biomarker measures. Copyright © 2014 John Wiley & Sons, Ltd.
    Statistics in Medicine 01/2015; 34(2). DOI:10.1002/sim.6327 · 2.04 Impact Factor
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    ABSTRACT: Is sugar-sweetened beverage (SSB) consumption associated with age at menarche? More frequent SSB consumption was associated with earlier menarche in a population of US girls. SSB consumption is associated with metabolic changes that could potentially impact menarcheal timing, but direct associations with age at menarche have yet to be investigated. The Growing up Today Study, a prospective cohort study of 16 875 children of Nurses' Health Study II participants residing in all 50 US states. This analysis followed 5583 girls, aged 9-14 years and premenarcheal at baseline, between 1996 and 2001. During 10 555 person-years of follow-up, 94% (n = 5227) of girls reported their age at menarche, and 3% (n = 159) remained premenarcheal in 2001; 4% (n = 197) of eligible girls were censored, primarily for missing age at menarche. Cumulative updated SSB consumption (composed of non-carbonated fruit drinks, sugar-sweetened soda and iced tea) was calculated using annual Youth/Adolescent Food Frequency Questionnaires from 1996 to 1998. Age at menarche was self-reported annually. The association between SSB consumption and age at menarche was assessed using Cox proportional hazards regression. More frequent SSB consumption predicted earlier menarche. At any given age between 9 and 18.5 years, premenarcheal girls who reported consuming >1.5 servings of SSBs per day were, on average, 24% more likely [95% confidence interval (CI): 13, 36%; P-trend: <0.001] to attain menarche in the next month relative to girls consuming ≤2 servings of SSBs weekly, adjusting for potential confounders including height, but not BMI (considered an intermediate). Correspondingly, girls consuming >1.5 SSBs daily had an estimated 2.7-month earlier menarche (95% CI: -4.1, -1.3 months) relative to those consuming ≤2 SSBs weekly. The frequency of non-carbonated fruit drink (P-trend: 0.03) and sugar-sweetened soda (P-trend: 0.001), but not iced tea (P-trend: 0.49), consumption also predicted earlier menarche. The effect of SSB consumption on age at menarche was observed in every tertile of baseline BMI. Diet soda and fruit juice consumption were not associated with age at menarche. Although we adjusted for a variety of suspected confounders, residual confounding is possible. We did not measure SSB consumption during early childhood, which may be an important window of exposure. More frequent SSB consumption may predict earlier menarche through mechanisms other than increased BMI. Our findings provide further support for public health efforts to reduce SSB consumption. The Growing up Today Study is supported by grant R03 CA 106238. J.L.C. was supported by the Breast Cancer Research Foundation; Training Grant T32ES007069 in Environmental Epidemiology from the National Institute of Environmental Health Sciences, National Institutes of Health; and Training Grant T32HD060454 in Reproductive, Perinatal and Pediatric Epidemiology from the National Institute of Child Health and Human Development, National Institutes of Health. A.L.F. is supported by the American Cancer Society, Research Scholar Grant in Cancer Control. K.B.M. was supported in part by the National Cancer Institute at the National Institutes of Health (Public Health Service grants R01CA158313 and R03CA170952). There are no conflicts of interest to declare. © The Author 2015. Published by Oxford University Press on behalf of the European Society of Human Reproduction and Embryology. All rights reserved. For Permissions, please email: journals.permissions@oup.com.
  • Diabetes Care 01/2015; 38(2):e13-e14. DOI:10.2337/dc14-2093 · 8.57 Impact Factor
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    ABSTRACT: The survival of breast cancer patients is largely influenced by tumor characteristics, such as TNM stage, tumor grade and hormone receptor status. However, there is growing evidence that inherited genetic variation might affect the disease prognosis and response to treatment. Several lines of evidence suggest that alleles influencing breast cancer risk might also be associated with breast cancer survival. We examined the associations between 35 breast cancer susceptibility loci and the disease over-all survival (OS) in 10,255 breast cancer patients from the National Cancer Institute Breast and Prostate Cancer Cohort Consortium (BPC3) of which 1,379 died, including 754 of breast cancer. We also conducted a meta-analysis of almost 35,000 patients and 5,000 deaths, combining results from BPC3 and the Breast Cancer Association Consortium (BCAC) and performed in silico analyses of SNPs with significant associations. In BPC3, the C allele of LSP1-rs3817198 was significantly associated with improved OS (HRper-allele =0.70; 95% CI: 0.58-0.85; Ptrend =2.84 × 10(-4) ; HRheterozygotes =0.71; 95% CI: 0.55-0.92; HRhomozygotes =0.48; 95% CI: 0.31-0.76; P2DF =1.45 × 10(-3) ). In silico, the C allele of LSP1-rs3817198 was predicted to increase expression of the tumor suppressor cyclin-dependent kinase inhibitor 1C (CDKN1C). In the meta-analysis, TNRC9-rs3803662 was significantly associated with increased death hazard (HRMETA =1.09; 95% CI: 1.04-1.15; Ptrend =6.6 × 10(-4) ; HRheterozygotes =0.96 95% CI: 0.90-1.03; HRhomozygotes = 1.21; 95% CI: 1.09-1.35; P2DF =1.25 × 10(-4) ). In conclusion, we show that there is little overlap between the breast cancer risk single nucleotide polymorphisms (SNPs) identified so far and the SNPs associated with breast cancer prognosis, with the possible exceptions of LSP1-rs3817198 and TNRC9-rs3803662. This article is protected by copyright. All rights reserved. © 2015 UICC.
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    ABSTRACT: To evaluate racial and ethnic differences in the association between a dietary diabetes risk reduction score and incidence of type 2 diabetes in U.S. white and minority women. We followed 156,030 non-Hispanic white (NHW), 2,026 Asian, 2,053 Hispanic, and 2,307 black women in the Nurses' Health Study (NHS) (1980-2008) and NHS II (1991-2009). A time-updated dietary diabetes risk reduction score (range 8-32) was created by adding points corresponding with each quartile of intake of eight dietary factors (1 = highest risk; 4 = lowest risk). A higher score indicates a healthier overall diet. We documented 10,922 incident type 2 diabetes cases in NHW, 157 in Asian, 193 in Hispanic, and 307 in black women. Multivariable-adjusted pooled hazard ratio across two cohorts for a 10th-90th percentile range difference in dietary diabetes risk reduction score was 0.49 (95% CI 0.46, 0.52) for NHW, 0.53 (0.31, 0.92) for Asian, 0.45 (0.29, 0.70) for Hispanic, 0.68 (0.47, 0.98) for black, and 0.58 (0.46, 0.74) for overall minority women (P for interaction between minority race/ethnicity and dietary score = 0.08). The absolute risk difference (cases per 1,000 person-years) for the same contrast in dietary score was -5.3 (-7.8, -2.7) for NHW, -7.2 (-22.9, 8.4) for Asian, -11.6 (-26.7, 3.5) for Hispanic, -6.8 (-19.5, 5.9) for black, and -8.0 (-15.6, -0.5) for overall minority women (P for interaction = 0.04). A higher dietary diabetes risk reduction score was inversely associated with risk of type 2 diabetes in all racial and ethnic groups, but the absolute risk difference was greater in minority women. © 2015 by the American Diabetes Association. Readers may use this article as long as the work is properly cited, the use is educational and not for profit, and the work is not altered.
    Diabetes Care 01/2015; DOI:10.2337/dc14-1986 · 8.57 Impact Factor
  • Ambika Satija, Edward Yu, Walter C Willett, Frank B Hu
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    ABSTRACT: Nutritional epidemiology has recently been criticized on several fronts, including the inability to measure diet accurately, and for its reliance on observational studies to address etiologic questions. In addition, several recent meta-analyses with serious methodologic flaws have arrived at erroneous or misleading conclusions, reigniting controversy over formerly settled debates. All of this has raised questions regarding the ability of nutritional epidemiologic studies to inform policy. These criticisms, to a large degree, stem from a misunderstanding of the methodologic issues of the field and the inappropriate use of the drug trial paradigm in nutrition research. The exposure of interest in nutritional epidemiology is human diet, which is a complex system of interacting components that cumulatively affect health. Consequently, nutritional epidemiology constantly faces a unique set of challenges and continually develops specific methodologies to address these. Misunderstanding these issues can lead to the nonconstructive and sometimes naive criticisms we see today. This article aims to clarify common misunderstandings of nutritional epidemiology, address challenges to the field, and discuss the utility of nutritional science in guiding policy by focusing on 5 broad questions commonly asked of the field. © 2015 American Society for Nutrition.
    Advances in Nutrition 01/2015; 6(1):5-18. DOI:10.3945/an.114.007492 · 3.20 Impact Factor
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    ABSTRACT: Experimental and epidemiologic data support a protective role for melatonin in breast cancer etiology, yet studies in premenopausal women are scarce. In a case-control study nested within the Nurses' Health Study II cohort, we measured the concentration of melatonin's major urinary metabolite, 6-sulfatoxymelatonin (aMT6s), in urine samples collected between 1996 and 1999 among 600 breast cancer cases and 786 matched controls. Cases were predominantly premenopausal women who were diagnosed with incident breast cancer after urine collection and before June 1, 2007. Using multivariable conditional logistic regression, we computed odds ratios and 95% confidence intervals. Melatonin levels were not significantly associated with total breast cancer risk (for the fourth (top) quartile (Q4) of aMT6s vs. the first (bottom) quartile (Q1), odds ratio (OR) = 0.91, 95% confidence interval (CI): 0.64, 1.28; Ptrend = 0.38) or risk of invasive or in situ breast cancer. Findings did not vary by body mass index, smoking status, menopausal status, or time between urine collection and diagnosis (all Pinteraction values ≥ 0.12). For example, the odds ratio for total breast cancer among women with ≤5 years between urine collection and diagnosis was 0.74 (Q4 vs. Q1; 95% CI: 0.45, 1.20; Ptrend = 0.09), and it was 1.20 (Q4 vs. Q1; 95% CI: 0.72, 1.98; Ptrend = 0.70) for women with >5 years. Our data do not support an overall association between urinary melatonin levels and breast cancer risk. © The Author 2015. Published by Oxford University Press on behalf of the Johns Hopkins Bloomberg School of Public Health. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.
    American Journal of Epidemiology 01/2015; 181(3). DOI:10.1093/aje/kwu261 · 4.98 Impact Factor

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2,925.95 Total Impact Points

Institutions

  • 2015
    • Stanford University
      • Division of Nephrology
      Palo Alto, California, United States
    • University of Massachusetts Amherst
      • Division of Biostatistics and Epidemiology
      Amherst Center, Massachusetts, United States
  • 2002–2015
    • Brigham and Women's Hospital
      • • Channing Division of Network Medicine
      • • Department of Medicine
      Boston, Massachusetts, United States
  • 1985–2015
    • Harvard University
      • Department of Nutrition
      Cambridge, Massachusetts, United States
  • 1983–2015
    • Harvard Medical School
      • • Department of Medicine
      • • Division of Nutrition
      Boston, Massachusetts, United States
  • 2014
    • Tufts University
      Бостон, Georgia, United States
    • Leiden University Medical Centre
      • Department of Clinical Epidemiology
      Leyden, South Holland, Netherlands
  • 2006–2014
    • Massachusetts Department of Public Health
      Boston, Massachusetts, United States
    • University of California, San Francisco
      • Division of General Internal Medicine
      San Francisco, CA, United States
    • University of California, Davis
      • Department of Molecular and Cellular Biology
      Davis, California, United States
    • Albert Einstein College of Medicine
      • Department of Epidemiology & Population Health
      New York City, NY, United States
    • University of North Carolina at Chapel Hill
      • Carolina Population Center
      Chapel Hill, NC, United States
  • 2010
    • Eunice Kennedy Shriver National Institute of Child Health and Human Development
      Роквилл, Maryland, United States
  • 1986–2003
    • Boston University
      • Department of Ophthalmology
      Boston, Massachusetts, United States
  • 1998
    • Centers for Disease Control and Prevention
      • Division of Nutrition, Physical Activity, and Obesity
      Druid Hills, GA, United States