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To assess the independent effect of waist circumference on mortality across the entire body mass index (BMI) range and to estimate the loss in life expectancy related to a higher waist circumference. We pooled data from 11 prospective cohort studies with 650,386 white adults aged 20 to 83 years and enrolled from January 1, 1986, through December 31, 2000. We used proportional hazards regression to estimate hazard ratios (HRs) and 95% CIs for the association of waist circumference with mortality. During a median follow-up of 9 years (maximum, 21 years), 78,268 participants died. After accounting for age, study, BMI, smoking status, alcohol consumption, and physical activity, a strong positive linear association of waist circumference with all-cause mortality was observed for men (HR, 1.52 for waist circumferences of ≥110 vs <90 cm; 95% CI, 1.45-1.59; HR, 1.07 per 5-cm increment in waist circumference; 95% CI, 1.06-1.08) and women (HR, 1.80 for waist circumferences of ≥95 vs <70 cm; 95% CI, 1.70-1.89; HR, 1.09 per 5-cm increment in waist circumference; 95% CI, 1.08-1.09). The estimated decrease in life expectancy for highest vs lowest waist circumference was approximately 3 years for men and approximately 5 years for women. The HR per 5-cm increment in waist circumference was similar for both sexes at all BMI levels from 20 to 50 kg/m2, but it was higher at younger ages, higher for longer follow-up, and lower among male current smokers. The associations were stronger for heart and respiratory disease mortality than for cancer. In white adults, higher waist circumference was positively associated with higher mortality at all levels of BMI from 20 to 50 kg/m2. Waist circumference should be assessed in combination with BMI, even for those in the normal BMI range, as part of risk assessment for obesity-related premature mortality.

INTRODUCTION Evidence is limited on the role of mid‐life Dietary Approaches to Stop Hypertension (DASH) diet in late‐life subjective cognitive complaints (SCCs). METHODS We included 5116 women (mean age in 1985–1991: 46 years) from the New York University Women's Health Study. SCCs were assessed from 2018 to 2020 (mean age: 79 years) by a 6‐item questionnaire. RESULTS Compared to women in the bottom quartile of the DASH scores, the odds ratio (OR) for having two or more SCCs was 0.83 (95% confidence interval: 0.70–0.99) for women in the top quartile of DASH scores at baseline (P for trend = 0.019). The association was similar with multiple imputation and inverse probability weighting to account for potential selection bias. The inverse association was stronger in women without a history of cancer (P for interaction = 0.003). DISCUSSION Greater adherence to the DASH diet in mid‐life was associated with lower prevalence of late‐life SCCs in women.

BackgroundWhile tobacco and alcohol are established risk factors for hepatocellular carcinoma (HCC), the most common type of primary liver cancer, it is unknown whether they also increase the risk of intrahepatic cholangiocarcinoma (ICC). Thus, we examined the association between tobacco and alcohol use by primary liver cancer type.MethodsThe Liver Cancer Pooling Project is a consortium of 14 US-based prospective cohort studies that includes data from 1,518,741 individuals (HCC n = 1423, ICC n = 410). Multivariable-adjusted hazards ratios (HRs) and 95% confidence intervals (CI) were estimated using proportional hazards regression.ResultsCurrent smokers at baseline had an increased risk of HCC (hazard ratio (HR) = 1.86, 95% confidence interval (CI): 1.57–2.20) and ICC (HR = 1.47, 95% CI: 1.07–2.02). Among individuals who quit smoking >30 years ago, HCC risk was almost equivalent to never smokers (HR = 1.09, 95% CI: 0.74–1.61). Compared to non-drinkers, heavy alcohol consumption was associated with an 87% increased HCC risk (HR≥7 drinks/day = 1.87, 95% CI: 1.41–2.47) and a 68% increased ICC risk (HR≥5 drinks/day = 1.68, 95% CI: 0.99–2.86). However, light-to-moderate alcohol consumption of <3 drinks/day appeared to be inversely associated with HCC risk (HR>0–<0.5 drinks/day = 0.77, 95% CI: 0.67–0.89; HR>0.5–<1 drinks/day = 0.57, 95% CI: 0.44–0.73; HR1–<3 drinks/day = 0.71, 95% CI: 0.58–0.87), but not ICC.ConclusionsThese findings suggest that, in this relatively healthy population, smoking cessation and light-to-moderate drinking may reduce the risk of HCC.

Background Midkine is a heparin-binding growth factor that is overexpressed in most human malignancies, including breast cancer. While elevated midkine levels have been associated with tumor progression and aging, its role as a predictive biomarker for breast cancer risk in healthy individuals remains unclear. We previously showed that higher midkine expression in estrogen receptor-positive (ER +) breast cancer in younger (< 55) women is associated with shorter disease-free survival. We investigated whether serum midkine levels in premenopausal women are associated with subsequent risk of ER + breast cancer. Methods We conducted a prospective, nested case–control study within the New York University Women’s Health Study (NYUWHS). Serum midkine levels were measured in baseline blood samples from 249 premenopausal women who developed ER + breast cancer more than 10 years after blood collection and 249 matched controls. Conditional logistic regression models were used to estimate odds ratios (ORs) and 95% confidence intervals (CIs) across quartiles and continuous midkine levels, adjusting for key breast cancer risk factors. Results Higher circulating midkine levels were associated with a marginally statistically significant lower risk of ER + breast cancer. Compared to the lowest quartile, women in the highest quartile had an OR of 0.55 (95% CI: 0.30–0.99; P for trend = 0.10). A doubling in midkine was associated with a 34% reduction in risk (OR = 0.66; 95% CI: 0.42–1.02). The inverse association was generally consistent across subgroups. Conclusion These findings suggest that higher baseline serum midkine levels in premenopausal women are associated with a reduced long-term risk of ER + breast cancer. This challenges prior assumptions about midkine’s uniformly pro-tumorigenic role and suggests it may be a context-dependent biomarker in breast cancer development.

Background Evidence suggests that the hormonal milieu of pregnancy is an important determinant of subsequent cancer and other chronic diseases in both the mother and the offspring. Many of the existing maternity and birth cohorts include specimens drawn only once during pregnancy. How well a single blood specimen collected during a pregnancy characterizes exposure to these hormones throughout gestation, and also in subsequent pregnancies, is not well understood. Methods We used serial serum samples from 71 pregnant women (25 primiparous, 25 multiparous, and 21 with two consecutive pregnancies) with natural, complication-free pregnancies and a healthy offspring at term who participated in a population-based screening trial for congenital infections in Finland between January 1st, 1988 and June 30, 1989 and provided a blood sample in each trimester. Results Hormone levels were more strongly correlated between consecutive trimesters of a pregnancy than between the 1st and 3rd trimester (e.g., estradiol, r T1 vs. T2  = 0.51 and r T2 vs. T3  = 0.60, p  < 0.01; r T1 vs. T3  = 0.32, p  < 0.05). Concentrations of sRANKL remained stable throughout gestation, whereas estradiol, estrone, progesterone, testosterone, prolactin, and osteoprotegerin increased throughout pregnancy. First trimester hormone concentrations explained less of the variation in the third trimester on their own than second trimester hormone levels (e.g. estradiol R 2 T1   =  16 % and R 2 T2  = 42 %). Addition of maternal (e.g., smoking) and/or child characteristics (e.g., sex) improved the accuracy of the 3rd trimester estimates for some of the hormones. Conclusions One hormone measurement in early pregnancy, in conjunction with maternal and fetal characteristics, permits estimation of 3rd trimester hormone concentrations. Therefore, single hormone measurements available from maternity cohorts are suitable to quantify hormone exposure during pregnancy. To our knowledge, we provide the first data on correlations between hormone concentrations both across trimesters of a single pregnancy, as well as between two subsequent pregnancies.

Background Sub-cohort sampling designs such as a case-cohort study play a key role in studying biomarker-disease associations due to their cost effectiveness. Time-to-event outcome is often the focus in cohort studies, and the research goal is to assess the association between the event risk and risk factors. In this paper, we propose a novel goodness-of-fit two-phase sampling design for time-to-event outcomes when some covariates (e.g., biomarkers) can only be measured on a subgroup of study subjects. Methods Assuming that an external model, which can be the well-established risk models such as the Gail model for breast cancer, Gleason score for prostate cancer, and Framingham risk models for heart diseases, or built from preliminary data, is available to relate the outcome and complete covariates, we propose to oversample subjects with worse goodness-of-fit (GOF) based on an external survival model and time-to-event. With the cases and controls sampled using the GOF two-phase design, the inverse sampling probability weighting method is used to estimate the log hazard ratio of both incomplete and complete covariates. We conducted extensive simulations to evaluate the efficiency gain of our proposed GOF two-phase sampling designs over case-cohort study designs. Results Through extensive simulations based on a dataset from the New York University Women’s Health Study, we showed that the proposed GOF two-phase sampling designs were unbiased and generally had higher efficiency compared to the standard case-cohort study designs. Conclusion In cohort studies with rare outcomes, an important design question is how to select informative subjects to reduce sampling costs while maintaining statistical efficiency. Our proposed goodness-of-fit two-phase design provides efficient alternatives to standard case-cohort designs for assessing the association between time-to-event outcome and risk factors. This method is conveniently implemented in standard software.

Pooled data from 19 prospective studies showed that after adjustments for age, physical activity, alcohol consumption, education, and marital status, both overweight and obesity were associated with increased mortality, which was lowest with a BMI between 20 and 25. Two thirds of the adult population in the United States and at least half the populations of many other developed countries are currently overweight or obese. 1 , 2 Although it is well established that obese people — defined as having a body-mass index (BMI) (the weight in kilograms divided by the square of the height in meters) of 30.0 or more — have increased death rates from heart disease, stroke, and many specific cancers, 3 the strength of the relationship between a high BMI and all-cause mortality remains uncertain, as does the optimal BMI with respect to mortality. Some studies suggest that . . .

Mean residual life (MRL) is the remaining life expectancy of a subject who has survived to a certain time point and can be used as an alternative to hazard function for characterizing the distribution of a time-to-event variable. Inference and application of MRL models have primarily focused on full-cohort studies. In practice, case-cohort and nested case-control designs have been commonly used within large cohorts that have long follow-up and study rare diseases, particularly when studying costly molecular biomarkers. They enable prospective inference as the full-cohort design with significant cost-saving benefits. In this paper, we study the modeling and inference of a family of generalized MRL models under case-cohort and nested case-control designs. Built upon the idea of inverse selection probability, the weighted estimating equations are constructed to estimate regression parameters and baseline MRL function. Asymptotic properties of the proposed estimators are established and finite-sample performance is evaluated by extensive numerical simulations. An application to the New York University Women’s Health Study is presented to illustrate the proposed models and demonstrate a model diagnostic method to guide practical implementation.

Background It is accepted that a woman's lifetime risk of developing breast cancer after menopause is reduced by early full term pregnancy and multiparity. This phenomenon is thought to be associated with the development and differentiation of the breast during pregnancy. Methods In order to understand the underlying molecular mechanisms of pregnancy induced breast cancer protection, we profiled and compared the transcriptomes of normal breast tissue biopsies from 71 parous (P) and 42 nulliparous (NP) healthy postmenopausal women using Affymetrix Human Genome U133 Plus 2.0 arrays. To validate the results, we performed real time PCR and immunohistochemistry. Results We identified 305 differentially expressed probesets (208 distinct genes). Of these, 267 probesets were up- and 38 down-regulated in parous breast samples; bioinformatics analysis using gene ontology enrichment revealed that up-regulated genes in the parous breast represented biological processes involving differentiation and development, anchoring of epithelial cells to the basement membrane, hemidesmosome and cell-substrate junction assembly, mRNA and RNA metabolic processes and RNA splicing machinery. The down-regulated genes represented biological processes that comprised cell proliferation, regulation of IGF-like growth factor receptor signaling, somatic stem cell maintenance, muscle cell differentiation and apoptosis. Conclusions This study suggests that the differentiation of the breast imprints a genomic signature that is centered in the mRNA processing reactome. These findings indicate that pregnancy may induce a safeguard mechanism at post-transcriptional level that maintains the fidelity of the transcriptional process.

Background/ObjectivesFolates found in natural foods are thought to protect against cancer. However, folic acid (FA), a synthetic form of folate used in supplements and fortified foods, may increase breast cancer risk if present in unmetabolized form (UMFA) in the circulation. This study examined the associations of serum UMFA and 5-methyltetrahydrofolate (5-mTHF), the predominant form of circulating folate, with breast cancer risk.Subjects/MethodsWe conducted a nested case-control study in a prospective cohort. In total, 553 cases of invasive breast cancer, diagnosed before mandatory FA fortification of grain in the US in 1998, were individually-matched to 1059 controls. Serum UMFA and 5-mTHF were measured using liquid chromatography-tandem mass spectrometry in stored serum samples, and 5-mTHF was corrected for storage degradation.ResultsSerum UMFA was not associated with breast cancer risk: the percentage of women with detectable levels of UMFA was similar in cases and controls (18% and 20%, respectively; p = 0.46). Two tag-SNPs in the promoter region of the FA-metabolizing gene were also not associated with risk. There was a marginally significant inverse association of 5-mTHFcorrected with breast cancer risk (odds ratio for the highest vs. lowest quintile = 0.69, 95% CI = 0.49 to 0.97; ptrend = 0.08).ConclusionsCirculating UMFA was not associated with breast cancer risk. These results apply to countries without mandatory FA food fortification. Studies are needed in countries with mandatory fortification, where levels of UMFA are much higher than in our study.